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Jes Kirkwood on November 15th 2021

Shopify's VP, Growth Morgan Brown reveals how the company's growth team drives results in an exclusive interview.

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Mark Hansen on May 20th 2019

This is a guest post by one of our most inspiring customers, Mark Hansen, who is a co-founder of Upsolve and an early member of Segment’s Startup Program. He shares his story of turning his fledgling bankruptcy non-profit into a data-backed organization built to scale.

“I’m too broke to file for bankruptcy,” is a phrase that should never be said. Yet nearly 20 million Americans every year find themselves in this position. Our organization Upsolve is on a mission is to help low-income Americans in financial distress file Chapter 7 bankruptcy at no cost. We do this by combining the power of technology with attorneys. Up through March 2019, we’ve helped hundreds of families clear over $37,000,000 of debt. But there are 20 million more that could use our help.

In this article, I’ll share the story of our organization’s Y Combinator W19 experience and how we found a pathway to scale our nonprofit. With Segment’s advice early on, we went from running a few SQL queries a month to analyzing user behavior and reacting to it within the same day. As the solo designer and developer for Upsolve, I thought being data-driven was a luxury. I hope this shows you that no matter how small you are, it’s an absolute necessity.

I hope our story brings ideas and lessons to you as you carry on in your own journey!

I use the term radical in its original meaning—getting down to and understanding the root cause. It means facing a system that does not lend itself to your needs and devising means by which you change that system. That is easier said than done. But one of the things that has to be faced is, in the process of wanting to change that system, how much have we got to do to find out who we are, where we have come from and where we are going....

— Ella Baker

Bankruptcy: A social safety net out of reach

Upsolve is a tech nonprofit that helps low-income families file bankruptcy for free. Bankruptcy is a tool that is often sought out by businesses, but individuals can declare bankruptcy, too! Declaring bankruptcy is often the social safety net of last resort when other systems have failed, allowing individuals to completely clear away any debts that they have except student loans.

For decades, poverty in the United States has been associated with social stigmas. Unfortunately, the reasons why people find themselves in financial trouble are often outside their control. Falling into financial ruin can happen to anyone, no matter the age, demographic, or education. The most common reasons people turn to bankruptcy are because of job loss, medical emergencies, predatory loans, and divorce. Those who are unable to take advantage of bankruptcy are at a high risk of falling into the cycle of poverty, homelessness, and going hungry. It’s also been proven they will have a shorter life expectancy by several years.

Despite the critical benefits of bankruptcy, only 2% of people who could benefit from filing for bankruptcy actually make it through this process. That’s because people imagine bankruptcy requires a lawyer, which can cost more than $1,000. If you have $30 in your pocket, and you’re living out of your car, this is not an option. But when you’re served a letter saying you will be sued if you don’t pay your debts, filing on your own becomes the only option.

Doing this process by yourself is intimidating. The first challenge is figuring out whether Chapter 7 bankruptcy makes sense, which forms are relevant, and how to fill them out correctly. The second challenge is to find the money and a working debit card to pay for two required online courses. The third is printing out hundreds of pages of documents, which is another big cost and time sink and might require traveling to find a printer. Finally, you’re expected to find time during a work week to make a multi-hour drive to the closest court. If you don’t have a car, you must coordinate borrowing one or getting a ride from a friend or public transportation. If you have kids, you must coordinate having someone take care of them.

In other words, good luck and pray you didn’t make errors. If you do have errors, the three most likely things to occur are:

  1. Your case is dismissed and closed, meaning you wasted an incredible amount of time and several hundred dollars (which you likely borrowed).

  2. You’re asked to make corrections, dragging out the process several more weeks.

  3. You receive a discharge, but when listing assets you incorrectly assigned exemption laws so some of your assets are seized. 

Exemption laws are state by state guidelines for what assets can and cannot be taken. To give an example of the complexity: a person in Missouri trying to protect their wedding ring has to understand exemption law Mo. Rev. Stat. § 513.430 1.(2), exemption law Mo. Rev. Stat. § 513.430 1.(3), and possibly federal exemption law 11 U.S.C. § 522(d)(4), all of which have their own caveats and limits for protecting assets.

This has to be done with every asset a person owns from clothes, to cars, to retirement funds. Mislabel one and you can potentially lose it.

What might a different future look like?

If the bankruptcy code is made up of a bunch of rules, couldn’t software make this easier? Couldn’t software tell you if you’re a good fit? Couldn’t software just tell you what forms are relevant? Couldn’t software automatically get your course and court fees waived? Couldn’t software tell you about relevant updates so you didn’t have to check the mail?

Yes, it can! And that’s what we did to give people back their access to this important social safety net. Up through March 2019, we’ve cleared $37,000,000+ of debt for hundreds of families.

The path to this future wasn’t clear 

In December, we only had received $559 in donations from users who filed as a thank you, and the grant money in our bank accounts would only get us 9 more months down the line. We really didn’t want to see the headline: “Poverty fighting nonprofit shuts its doors.”

Additionally, to help every person who could benefit from Chapter 7 would cost millions ($5 fixed cost per case times the 20 million people in the United States who could benefit from filing for bankruptcy). No foundation could support that sort of cost in the long run.

As we grappled with how we could give 20 million families access to bankruptcy, we looked to a place where growth and scale was the absolute goal. Enter, Y Combinator. We took a leap of faith to put in our application, and before we knew it we sat in a room with the YC batch. The expectation:  A nonprofit should be as effective and ambitious as all the other organizations they took in.

YC’s challenge— Become sustainable

Y Combinator was a tough environment, not because we had to work harder, but because all our norms would be challenged. As much as we loved to create a better and better product to help people through bankruptcy, the financial self-sustainability of the organization needed attention. Our second week, the partners drove it home for us with a startling request:

Partners: Become break-even by demo day.

Us: But regulations don’t allow us to sell the service, our users have no money and deserve it for free, volume is so low …

Partners: Airbnb did it. Can you earn $500 by next group office hours?

Us: *Pause*…Yes

The phone call ended, and we just started firing off ideas. We knew we couldn’t finish enough cases by office hours to get more than $500 in donations.

Flying blind on the path to growth 

Before even considering revenue, we were focused on how we could do 10% more case filings each week. SEO-minded content was the strategy, but we couldn’t really tell how well or poorly we were doing. The only indicator we had was the number of accounts created. We didn't know how to setup and measure our goals, and we didn't know how many people were dropping off in the funnel or where! We needed to get these stats to know where to spend time improving the product if we wanted to have any chance meeting expectations for the next group office hours.

With all the other fires raging, measuring the flow of our product was getting the back burner. I had given teammates BI tools and SQL queries, but they were still uncomfortable with self-research. We had a volunteer try to centralize BI and logs by transitioning us to the ELK stack (ElasticSearch, Logstash, Kibana) but it was breaking down almost daily and they had disappeared.

I felt like I was floundering. It felt like we were all flying blind, and my increasingly crazy looking SQL queries were all that gave us insight into what was happening. When deciding which office hours we should go to the day of YC’s growth workshop, we clearly knew we needed guidance with our analytics.

“Stop doing that!”

As a nonprofit, we were trying to save every penny we could. With AWS credits out the wazoo and knowing that big tech companies ran ELK stacks, it seemed worthwhile to invest in the future proof solution. But it’s hard when you’re the only dev to evaluate when your time spent is far greater than some other alternative.

That Saturday, my team and I decided to attend the YC Growth Bootcamp. We were excited by a lot of the sessions, and I was especially amped to learn about analytics. Segment’s co-founder Ilya Volodarksy gave a presentation that helped us understand what was possible if we understood our customers, and how a certain set of tools and practices would continue to work if we scaled. I still remember the slide showing goal tracking and the behavior flows in Google Analytics and being amazed that was a feature. Afterwards, we were able to sign up for an analytics office hours session with Ilya, and dig deep into our stack. It was clear it was time to ditch the ELK stack.

A few hundred dollars on helpful tools could be the difference of a growing or failing business, and if we couldn’t pay for these tools, we had bigger problems. It made sense to go all in and invest for YC. Ilya gave us a set of recommendations we implemented that weekend, and we were off! My co-founders weren’t distracting me with complex questions I need to write custom SQL queries for, we finally had visibility into behavior of our users and parts of the funnel we were blind to, and we had peace of mind that the tools in place were all we’d need to get to the next level.

Ready to go!

Data/analytics stack before the bootcamp:

Only I can access: ELK Stack (broke every day), Google Analytics (Misconfigured), Postico (PSQL client)

Stack after the bootcamp

Teamwide access: Amplitude, ChartIO, CustomerIO, Fullstory, Google Analytics, Google Search Console, Segment

Stack we use today today:

Teamwide access: Amplitude, ChartIO, CustomerIO, Fullstory, Google Analytics, Google Search Console, Segment

12 Days, $500 Left — Business Model #1

The first and obvious way to earn $500 was improve our donation flow. For every person we helped, it cost us $5, so helping all 20 million would require $100,000,000. We had been asking users to donate after we’ve helped them file because we do not charge people for our service. This is called a “Donate What’s Fair” model.

The three levers we had for trying to move this 10X were to increase how many people filed bankruptcy, increase how much we asked for, and change where in our flow we asked for a donation.

With 12 days to make $500, we couldn’t get 10x people to the filing step. We finally had visibility into our product funnel and all drop off happened in the information collection phase, which was necessary and could only be marginally improved.

So we looked at how we could increase the amount given per user by changing the design in two ways: 1) ask for a donation when giving users paperwork, the moment our users experience the greatest value and 2) be more explicit about our costs helping people and show future impact. With these modifications, we were seeing above $5 in donation revenue per user. Here were two iterations.

V2 - Increase Visibility

V3 - Explain Where The Money Goes

We were amazed that this worked. We now broke even with every case we did, making it feasible for us in the long run to help millions of families! But with that small a margin, we had to do 360,000 cases in the next 9 months to survive and by this point we did 400. We still only had 9 months to live.

6 Days, $164 left — Business model #2

Up until this point we had received $136 in donations and another $200 from revenue experiments Rohan and Jonathan had done that in the end that cost more than they were worth. With 6 days left, things weren’t looking good.

In between meetings, writing code, going to events, etc. we had our metrics tab up.

We were marinating in the numbers over the days when Rohan had a realization that would change the trajectory of Upsolve forever. That orange line represented dozens of people who were coming to our service that we couldn’t help, and attorneys were spending a ton of money trying to acquire users on Google ads to just get users to their website. Would our high-income visitors to Upsolve prefer we put them in touch with an attorney? Would the attorneys be willing to pay for that introduction? With a few phone calls, spreadsheets, and experiments we realized both were a yes, and we partnered with Legal Zoom.

$500 and a path to long-term impact

At first, we just printed phone numbers from the screener to our Slack and gave folks a call to validate interest. Then we put a button that didn’t do anything just to see if people would click it and called up attorneys ourselves to match with people who clicked. Click rates were incredibly high with our warm and trusting copy, showing us there was some promise.

When we formalized an agreement with a third-party, they gave us a phone number which if users called, would lead to double the referral revenue for us. Making this CTA a “call 1-800...” and seeing it drop to a 2% conversion rate made us really internalize just how toxic phone numbers were to our community. So much so we removed the phone number question from our screener for qualified user sign ups.

After a few more iterations, we came to an onboarding flow that provided meaningful conversion. The conversion numbers showed us that all we needed was to 2-3x website traffic and we could become self-sustainable.

By the time of group office hours, we not only were able to meet a goal we thought was wild a week earlier, but we had a formula for becoming a self-sustaining non-profit. The partners and everyone in our group gave us an applause and were excited to see us to get self-sustainability.

What is this feeling?

This was becoming a weird transition moment. Up until this point, I had placed all my actions through the lens of making something people love. Now we are able to place our work with a surrounding formula that delivered on both revenue and impact. Was this what it feels like when you have “product market fit”? I guess so.

When data and charts were available constantly to everyone, I felt we started to act differently. With the driving goal so clear, we were able to operate more efficiently and autonomously. With this data washing over us so often, we also started to understand our users in non-obvious ways. 

But the biggest change in my mind was how we started to evaluate each others’ priorities against our own.  Now, we  judge how our priorities align with organizational goals. Second, we compare our own needs against others in a much clearer way. We all felt the pains of growth, but when we began to see a big uptick in sign-ups, we knew Tina was going to getting hit hard with reviews. We all could quickly identify and agree upon where our limited development time needed to be spent.

$500 cleared! All hands on deck for top of funnel!

With success hitting our $500 challenge, we looked outwards with our new formula in hand and a real challenge to ourselves to become financially self-sustaining by the end of YC. The feedback from the partners at this point was to move on to top of the funnel. The conversion rate was great and for the amount of work we were putting in, it didn’t seem like a 10x possibility was possible in conversions.

With SEO as the strategy, we want on a feature building spree.

We restructured our website to be locality based and improved internal linking.

Then we placed CTAs everywhere.

Then we boosted our page speed and more until we started to see diminishing returns to our programmatic and technical SEO efforts, and finally a bit of impact from an algorithmic change focused on financial information websites.

YC in Data

While words are great, nothing summarizes our work better than two charts.

It’s clear to see how we went from getting data in, to finding a business model, to improving conversions, and finally add in top of the funnel. The result was 60% self-sustainability by demo day of W19.

How we change

This experience felt like something Lewis and Clark would have gone through. In getting to the coast, they had to constantly evaluate where they were and how to go forward. You can only see so far, so you can only just choose the best path from where you are.

Segment was our version of Lewis & Clark’s celestial navigation tools. The ease of use and data it provided allowed us to evaluate our paths forward, helping us see where the 10x opportunity could lie. We weren’t optimizing our product, we were finding ways to push ourselves to meet the challenge of helping millions of families in America. 

Thank you!

Thank you for reading. Our journey has many peaks and valleys, but the past few months were a very special for us, and there were many people along the way that I want to note as being part of the journey:

Thank you to my Upsolve family that I’ve been honored to be a part of that learned, grew, and challenged itself: Jonathan, Holly, KT, Nicole, Rohan, and Tina.

Thank you to our YC family that helped us grow every week: Kevin, Michael, and Tim.

Thank you to the Segment family that gave us time and space and showed us what a great company looks like: Calvin, Courtney, Ilya, Kerianne, Leah, and Peter.

And finally, thank you to the Ohlone people and their descendants who lent us the land our industry has been able to build upon for decades and launch world changing ideas from.

If you or someone you know is in financial distress, send them to our website to learn if they should file for bankruptcy.

If you're excited about Upsolve's mission, we're looking for amazing engineers!

If you’re interested in using data to help you know where to focus during the overwhelming early stage, check out the Segment Startup Program and sign up for its bi-weekly "Analytics for Startups" office hours.

Ian Blair on May 13th 2019

This post is a guest submission by one of our customers at BuildFire for Segment’s Chain Letter blog series. The Chain Letter series profiles clever uses of Segment Connections partner tools that, when chained together, lead to some pretty advanced programmatic models, custom messaging strategies, and more. Thanks to BuildFire and Proof for sharing their story!

—Segment


From small businesses to Fortune 500 leaders, developing a mobile application is an arduous and often confusing decision for any company. Building and maintaining an app can be time-consuming, expensive, and requires a ton of ongoing maintenance. Plus, the world of app development is extremely competitive with thousands of agencies and independent developers competing for clients. That leads to a lot of noise around what can be reasonably produced within your budget and timeline.

My company, BuildFire, has carved out a niche in the space by creating a streamlined software platform to help our customers build beautiful apps quickly and affordably. Over the past 5 years, we’ve developed 10,000+ apps for over 10 million users across a variety of industries.

As the CEO and marketing leader of the business, I am tasked with acquiring these high-value customers in the most cost-effective way possible. We’ve had great success with our existing funnel, but we’re always looking for new ways to improve our signups and make the on-site experience more relevant for visitors.

Personalizing every customers’ experience

I frequently deploy A/B tests and other CRO experiments, but personalization at scale (while maintaining proper analytics and tracking) was never feasible since we lacked a dedicated engineer on our growth team. So we set out on a search for a personalization partner to help identify who our visitors are and improve their on-site session. After studying the market and seeing what solutions existed, we partnered as an Early Access customer of Proof Experiences to tackle personalization in our signup funnel.

We chose Proof Experiences in part because they were a new Segment integration. We use Segment to capture event data on our site, store enriched first-party data, and create a data infrastructure to cater to customers in every interaction they have with our brand. Using Segment has been critical to our growth strategy and allowed us the footing to launch many experiments, so finding a personalization partner that could directly integrate with Segment was a must-have for our team.

Proof Experiences is a B2B personalization tool that allows us to create audiences for different customer segments and then deploy custom website experiences for them. We use it to personalize headlines, swap out testimonials, autofill form fields, and much more. It easily hooks into our favorite A/B testing (Google Optimize) and analytics tools (Amplitude) through Segment. Experiences also includes the ease of use and point-and-click visual editing systems I’m used to using in other landing page and website builders.

The Proof Experiences visual editor allows you to click and edit live pages

Integrating Segment and Proof Experiences

Honestly, we were skeptical about the results we could get from personalization, but we wanted to give it a thorough shot. Proof Experiences allows us to collect data about our on-site visitors to use in audience creation. Then, we can enrich the contact with data from Clearbit or from our data in Segment. Finally, we can launch custom audiences for deploying personalized experiences quickly and with ease. We use their platform to bucket our visitors by industry (E-commerce, Education, Non-Profit, etc) and then we use that segmentation as a starting point to deliver more relevant content to our visitors. In the Experiences editor, we can visually swap out headlines, images, value props, CTAs, testimonials, and other on-page elements — without having to launch new landing pages.

Plus, we can conditionally hide live chat, add social proof to pages, and prefill forms from the Experiences platform. It’s powerful and it can all be done without having to get my engineering team involved—a huge factor in our decision to personalize in the first place.

And since Proof provides deep direct integration with Segment, setting up the connection was easy.  In Proof Experiences, you simply generate an API key and name it Segment.

Then, you head to the Proof Experiences Destination in the Segment catalog and enable it. You paste your API key into the configuration window and click Save.

And voila! You’re all set up to send data from Segment into Proof and have data flow from Proof into Segment.

Personalizing our signup flow to increase MQL’s by 46%

When we first started working with the Proof Experiences team, we looked through our funnel together and identified the metrics that we cared most about improving. Ultimately, as a growth team, we’re measured by the number of customers we acquire and the revenue those customers add to the business. For that reason, we decided to target an increased number of MQLs as it is a key leading metric to our revenue growth goals.

To increase MQLs, the Proof Experiences team recommended deploying several “playbooks” to improve the current performance of our signup flow.

BuildFire homepage

Our first major playbook focused around the inclusion of live updating social proof on our homepage and signup flow. By including in-line social proof under next-step CTAs, we were able to increase the percentage of visitors continuing onward to the next page. By mentioning the number of customers that signed up in the last month (8664 in the screenshots above and below), we were able to address a common customer objection and provide data to incentivize our visitors to continue to the next step.

The second playbook focused on using email addresses to autofill demographic and firmographic data in the signup flow. Before using Experiences, we collected emails in a form field on the last page of the signup flow. In order to personalize the rest of the signup flow, we moved the email field to the first step of the signup flow to allow Proof Experiences to call Clearbit’s API to find out a person's identify if the data wasn’t already stored in our Segment warehouse. If it was, we initiated an Identify call to pull in other fields to personalize the following 3 pages of our flow.

Finally, we’ve identified that we are much more likely to close a deal if we can quickly get a customer on the phone after they sign up. After successfully completing our signup flow, we push registrants to schedule a call with our Sales team. To humanize the messaging on this page and to increase the likelihood of a call, we used Proof Experiences to adjust a headline to match a visitor’s responses to earlier questions.

Rather than having a one size fits all headline, we used personalization to adjust it for each audience bucket. Since the visitor indicated they were interested in building an app for their business, the headline in the screenshot below adjusted to indicate the meeting is with a Corporate App consultant.

We’re an extremely data-driven company, and we watched our metrics closely as we launched this experiment with Proof. We A/B tested our initial personalization experiment, and we were able to conclude with 95% significance that using Proof Experiences and Segment in our signup flow increased our MQLs by 46%. We were blown away by these results.

Based on our data from this experiment, we are working to deploy even more ways to use the Segment and Proof Experiences integration to personalize our site. It’s been a great way to create a more human website for our visitors while improving our most important growth metrics.

Calvin French-Owen on April 24th 2019

There are thousands of analytics, email, and marketing tools out there waiting for you to try them.

It’s no secret, choosing between these thousands of tools is complex. It’s hard to assess which tools you’ll outgrow in the next two months versus the ones which will grow with you for years.

At Segment, we’ve now seen thousands of companies embark on this journey. From their earliest stages to reaching unicorn status, we’ve watched companies switch out their data stacks hundreds of thousands of times. 

We’d like to help you plan ahead. In this post we’ll share the trends we’ve seen over the last three years when it comes to switching tools. It’s our hope that this analysis gives you a window into what’s next and how to think about evaluating different vendors for your data stack. (You can also talk to a Segment team member if you want some pointers for building your stack)

The dataset and adoption graphs

In this article, we’ll dig into a Segment dataset that goes all the way back to mid-2016. It looks at all of our accounts, and includes day-by-day results for which destinations each workspace has enabled (quick caveat, it does not include sources or warehouse destinations).

We’ve chosen to graph this data with time as the x-axis. On the y-axis, we graph a line for each tool. The colors also indicate a rough categorization. Similar colors correspond to similar categories of tools. 

Without further ado, let’s dig in to the different ‘archetypes’ we’ve observed. They’re ordered from most to least common:

  1. The Bake-off

  2. The Graduation

  3. The Bulk Buy

  4. The Switch

  5. The Evolution

  6. The “Marie Kondo”

  7. The GDPR Worrier

  8. The Scientist

  9. The Early Adopter

  10. The New Hire


1. The Bake-off

What it is: The first trend we see is companies that use Segment to send the same data to a bunch of tools all at once. It’s sort of like ordering multiple pairs of sneakers, and returning everything but the ones you like. 

What it looks like:

Here you can see a user who initially started with six different tools (including a few which compete against one another). After two months of trialing, they picked the long-term tools they wanted to keep (ActiveCampaign, Customer.io, Mixpanel), and ditched the rest. 

2. The Graduation

What it is: While other companies compare tools all at once, these companies have a steady ‘graduation’ across tools—they start with a handful of use cases, and steadily shift those out over time. 

What it looks like: Graphs like these tend to look like a rhombus going up and to the right. As new tools come on the market, the old ones are replaced by newer, better fits.

These users add a few tools every month. As they discover new parts of their business to unlock, and new best-in-breed tools, they migrate their business to use the cutting edge.

We see some graduates fall more in the camp of continuing to add tools as they fit new use cases. 

In this case, the user started with just a single tool, but steadily expanded over time. Over a 1.5 year period, they moved from a single use case of Lucky Orange to over 12 different tools spread across analytics, messaging, advertising, and attribution use cases.

3. The Bulk Buy

What it is: To our surprise, not all users take the slow and steady path of the graduates. Sometimes we also see them make big stack decisions in bulk. Users don’t just enable tools one at a time. They often enable new destinations in groups of 3 to 5. Unlike the ‘bake-off’, we see users enabling tools across categories. 

What it looks like

In the above graph, you can see three of these distinct refreshes happen: March 2016, November 2016, and September 2017. In each case, the number of tools the customer was using expanded significantly, with a handful of tools being shut off.

Below, you can see examples of other bulk buys.

In each case, the use cases for each of these tools are different (they are color-coded by category). But their timing lines up consistently. 

4. The Switch

What it is: They don’t slowly graduate and they don’t make bulk decisions, these companies switch tools in quick succession when they first begin using Segment. Then, they settle into more of a routine set of tools which are only altered every 6 months. 

What it looks like:

This user had an initial 5-month period where they enabled 22 different destinations. They ended up sticking with just 10 of those for the long run after some initial experimentation.

You can also see by the grouping of like colors that this user was running a bit of a ‘bake-off’ as well. They start by trying three analytics tools, then move on to the advertising and error tracking use cases. 

5. The Evolution

What it is: In some cases, a company’s entire data stack will evolve. There is almost no commonality between the tools they started with, and where they are at now.  We find this happens especially often amongst our smallest customers. 

What it looks like: Here’s the growth curve for a 50-person e-commerce company. 

In this stack evolution, you can see that the user enabled nine tools in their first year of using Segment. Today, only three of them still remain in use (Woopra, ClientSuccess, and AutopilotHQ). 

Instead, they have switched out their entire stack by adding in another seven destinations. 

Here’s another stark example, this time from a small telco. 

The user started by doing a bake-off of popular analytics tools. Over the course of their evolution as a company, they’ve used 18 different tools. Today, they only use 4, and three of those are totally different than the starting set. 

Across our user base, we see more and more accounts that use a completely different stack than they started with. 

6. The “Marie Kondo”

What it is: In a handful of cases, we’ve seen areas where users wholesale swap their existing stack at a single point in time. Typically this is spurred by a new hire coming in, deciding that the existing tools aren’t working, and swapping them all out. 

What it looks like: The following graph comes from a quickly growing insurance startup of ~150 people. 

Here, you can see that in May 2017, almost all of the existing tools were replaced in favor of a different stack. 

While this isn’t the most common use case, the “Marie Kondo” uses Segment as a nice insurance policy. Instead of being locked in to a single vendor for years on end, users have the freedom to switch as their business (and maybe their preference) changes. 

7. The GDPR Worrier

What it is: Regulations are powerful business drivers. Last May, the new privacy regulation in Europe known as the GDPR (General Data Privacy Regulation) went into effect. It specified that companies had to give their users the right not only to request their data, but to be ‘forgotten’ and purged from tracking systems (and that includes their analytics tools).

If you think back to a year ago, this was the time that you probably received a bunch of terms of service updates. Companies were in a mad scramble to make themselves GDPR compliant, and that included the tools they were using. 

What it looks like: Here, we’ve included graphs which seem to be highly correlated with the May 25th date that the GDPR went into effect (the dashed vertical line).

In the month leading up to May 25, 2018, we see a significant number of users who instantly disable various tools that they might be using. These seem to be predominantly advertising tools + pixels, but there are a handful of other cases which seem to have users worried.

Fortunately, Segment helps our users cover this out of the box. We’ve built GDPR deletions in as a core feature of Segment, in addition to giving you the power to disable a tool with the flick of a switch.  

We felt good about having aligned ourselves with privacy-first efforts, but it was interesting to see the market agrees with our decision. 

8. The Scientist

What it is: Sometimes companies are interested in trying out a new category tool to meet their use case, but aren’t sure which one they should pick. So they decide to keep a lot of similar tools running concurrently to solve best-in-breed use cases instead of relying on one tool for everything. It’s sort of like the bake-off, but systematically moving into new categories of tools.

What it looks like:

Despite being relatively small (< 10 people, satellite imagery company), this company is able to punch above its weight class by being focused and thoughtful when it comes to adopting new tools. 

You can see here by the groupings of colors that this workspace moves from primarily an analytics use case to picking a set of advertising tools, and then further still to screen recording and heatmaps

The scientists systematically expand into new categories (the color-coded piece here) as they get more advanced and their business evolves. 

We see this sort of category adoption happening most often with advertising tools. Typically a marketing or growth hire will come onboard, and want to test out many different ad platforms to see which performs best. With Segment, they can do this in about 10-minutes, and wait for the results.

9. The Early Adopters

What it is: We’re constantly adding integrations through our newly launched Developer Center (we’ve added ~34 in the past 6 weeks), and we wanted to understand if companies on the ‘cutting edge’ of trying new data stack had anything in common. We found they are willing to use a lot of tools to solve their problems.

What it looks like: Here, you can find the curves for two of our users who were some of the first to enable ClearBrain, one of the new integrations made possible via our new Developer Center. The first is a B2B SaaS company of around ~100 employees. They show a consistent growth in terms of toolkit over the past three years. 

The second also added ClearBrain just after it was announced. This company is much larger, with just over 1,000 employees. They’ve had a similar growth trajectory over a three year period, adding an impressive 29 destinations for their customer data.

The thing that struck us about each of these two graphs is how similar they look. Even though one of these companies is 10x bigger than the other, with thousands of employees, both of these graphs show a steady adoption in toolkits. 

It’s hard to separate in this example what is correlation and what is causation. It seems intuitive that a fast growing company would more readily adopt new tools. There’s another angle that these companies actually grew more quickly because they were able to experiment and iterate rapidly. 

10. The New Hire

What it is: It is often the case that new tool adoption is hire driven. In some cases, it is very clear that the company is getting very serious about a particular use case and likely has hired someone to manage it.

What it looks like: We see a lot of curves that end up looking something like this:

This Segment user was relatively stagnant in their integration usage for years. They were happy with their stack of Sendwithus and Customer.io.

But in 2018, those needs shifted. We suspect that a new hire came onboard, specifically tasked with driving more growth for the business. When that happened, they immediately started leveraging a whole host of other tools.

Choosing your own buying strategy

Only you can determine what the right toolkit looks like for your business. However here are a few takeaways that you can use the next time you’re evaluating the next switch or turning on the latest tool.

1) The lower the cost to evaluate a vendor, the more switching happens

This is sort of the whole thesis for Segment in the first place, but it’s cool to see it actually play out in the data. As the cost to try new tools drops to zero, users do it more and more. It’s never been easier to evaluate a new vendor to understand how it works with your data, and not some pre-populated demo data. We see users evaluating vendors three to five at a time, and picking their favorite. 

2) The stacks you use today are not the stacks of tomorrow

Of the graphs we shared here, on average these companies have tried out 21.2 tools over the course of their lifetime, but are using 12.2 of those today. Though they might come in with an initial use case and toolkit, those change over a multi-year time period as the company grows and the market shifts. The signal here is clear: if you’re buying from a vendor, target the 1-2 year time horizon, but don’t necessarily expect it to last more than 18 months. Get help choosing durable tools for your stack here 👉

3) As your business grows, you want new types of tools

Different types of tools have different target audiences. Some are good for finding the initial product-market fit (analytics and live chat), while others target companies who are looking to scale their growth (advertising).

The following chart gives you an idea of how our customers add these tools over time. Across all of our users, we looked at the breakdown for which categories of integrations they were adding to their workspace as the first, second, and third integrations.

You can see here that most (over 60% of customers) start with an analytics use case. From there, they then expand to email, screen recording, and live chat tools, and then to more specialized use cases like advertising and raw data (which tend to be the majority after the 10-15th integration added). The Scientists are particularly good at evaluating one category at a time, and then picking the best tools for their business. 

4) New regulations force new behaviors

We see a surprisingly large impact of regulation in terms of the tools our users adopt. Today, it’s GDPR. But there’s also CCPA looming on the horizon. As governments become more and more privacy conscious, we expect the value companies to get from data control to go up dramatically. Critically, it’s worth evaluating any of these vendors to see how they will support new regulations. 

5) High growth companies tend to be early adopters

The most avid adopters of new tools tend to be the ones who are growing most actively. They are able to constantly experiment with new avenues for growth, and at the same time outsource anything non-core to various SaaS offerings. 

This is the biggest reason new partners are building on Segment today. High growth startups are constantly looking to get an edge on their competition, and using the best-in-class new tools is one of the best ways to do that.


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Arndt Voge on March 14th 2019

This post is a guest submission by one of our customers at Peerspace. It covers the story of how they were able to use Segment and one of our Connection partner tools to drive awesome results. Thanks to Peerspace for sharing their story!

—Segment

Peerspace is the leading online marketplace for meeting and event venues. Consumers and businesses alike book thousands of event and meeting spaces each month, all through the platform.

We have over 10,000 listed spaces being used for activities ranging from corporate offsites, to film and photo production, to personal events, addressing a wide range of individual customer needs across all major US cities. Our web-centric focus has historically been on driving traffic and making product improvements that benefit our entire user base. However, as our traffic has grown, we have increasingly needed to address customer use cases in a personalized yet scalable way to maintain high conversion rates throughout the funnel.

Tailoring our message to our diverse set of guests and hosts has required creating a clean data layer to identify visitors, modify website experiences in real time, and instrument a measurement system to assess impact—all within the budget and scrappy means of a startup. We looked at a wide range of tools and ultimately chose Segment and Mutiny to tackle this problem.

We use Segment to capture all of our event and conversion data and digest it downstream for important pillars of our Growth strategy, such as analytics, paid acquisition bidding, A/B testing, and personalization.

In addition, we chose Mutiny to help us tackle personalization. We have deployed it to dynamically show personalized variations to visitors. Mutiny makes personalization easy out-of-the-box and has allowed us to test on top of our React-powered, single page application, which has proven challenging to do with traditional A/B testing tools.

Integrating Segment and Mutiny

Mutiny integrates firmographic, contextual, and behavioral data from a variety of sources to identify anonymous website traffic. We use that data to create audiences (such as startups vs. enterprise customers or corporate vs. personal use) and use their self-service editor to modify elements of our website or add additional ones for that audience (such as showing a logo bar to business visitors). Mutiny automatically handles hold-out A/B testing by showing some visitors the personalized content and some the original content in order to measure the change in conversion.

Mutiny has a one-click integration with Segment that’s enabled on Mutiny’s interface. As a Segment customer, we can connect our data to Mutiny to create audiences, personalize, and track conversion events. The consistency of the Segment schema has made the data actionable and easy to set up.

Connecting Segment within Mutiny

We use the data integration between the two platforms to do all of our conversion tracking for personalized experiences. Mutiny captures conversion events from Segment for real time reporting. In addition to pushing Mutiny test cell assignments automatically back into Segment, as can be seen in the Segment debugger feature below:

Segment debugger feature

All Segment data automatically streams into BigQuery as one of our Destinations, allowing our team to marry anonymous IDs through Identify events with downstream conversion data. This enables Peerspace to access complex testing reports through dashboards in Periscope or write their own SQL on top of the raw data.

The team loves how easily accessible and actionable the data is. Jason Wolf, who runs our Growth Analytics at Peerspace says:

“Segment has allowed us to effortlessly set up and maintain an invaluable flow of A/B testing data. Their integration with Mutiny is already paying huge dividends by enabling us to monitor our users' end-to-end experience, and we're only just starting to scratch the surface on building and tracking a personalized marketplace.”

Driving more user signups through personalization

Our team uses Mutiny powered with Segment data to modify and personalize Peerspace’s landing pages and homepage. For example, a business professional visiting the site from Atlanta is instantly assured that Peerspace offers the best venues in their region and that each venue can be equipped with A/V and other business equipment relevant to their specific segment.

Personalized version (right) includes location (1) and B2B specific modules (2 and 3)

We have seen personalization increase our user signups by up to 98%. That’s double the users without spending an additional dollar on user acquisition. Since we trust our data, we feel great about the results. We are expanding personalization from paid landing pages to our entire website, starting with the homepage.

We are excited to start pulling in a customer’s past transaction data into our landing pages as social proof for visitors from companies we have previously transacted with and to target repeat purchases. This is just the beginning!


About the author

Arndt Voges is the Head of Growth at Peerspace, the leading online marketplace for meeting and event venues. Prior to Peerspace, he ran Demand Generation at Magento (acquired by Adobe) and led various Growth Product teams at Ancestry.com. Arndt loves to build things and get his hands dirty, from implementing smaller A/B tests to working on cars. He recently took a sabbatical to fulfill his long-time dream to apprentice as a mechanic.

Calvin French-Owen on March 5th 2019

If you follow the MarTech ecosystem, you’re probably familiar with the MarTech 5000. This annual infographic shows all shades of growth tools, grouped by their use case. Every year the graphic grows denser. It now displays some 7,000+ companies, and the 2019 landscape hasn’t even been released yet! 

Marketing Technology Landscape 2018 ("Martech 5000")

While the graphic is interesting at an aggregate level and helps categorize the market, it doesn't show which companies are growing rapidly and which old categories are ripe for disruption.

We thought we could help.

Over the past seven years, we’ve helped thousands of companies collect data from their websites and mobile apps, and federate that data to over 250 different SaaS tools. We give them a code snippet, instructions for sending data to our API, and then we allow them to turn on different integrations with ‘the flip of a switch.’ 

By analyzing the data of how our user base enables these tools on the Segment customer data platform, we’ve been able to generate an in-depth view of how the SaaS market is evolving for analytics, marketing, and growth.

Today, we’d like to share these insights with you, comparing each tool along with its competitors, and highlighting who’s growing the fastest. We’ll include some light commentary, including where we see the highest potential, but for the most part, these graphs speak for themselves. 

We’re also doing our small part to help drive the growth of the 2019 category winners and beyond. This year, we’re opening up the Segment platform to partners, and our Developer Center is available in beta for you to start building integrations today. 

The categories

For some quick background, Segment helps businesses collect and manage their own data about who their users are and what they are doing. We then send this data to a variety of tools our customers choose to use. 

Marketing teams might use this data to power MailChimp, and product teams might use the same data to power Google Analytics or Amplitude. Each category we present solves a different problem or appeals to the different job functions in a business.

 We’ll cover the following categories:

Let’s dig in.

Understanding the graphs

Before you get started reviewing our category analysis, it’s important to understand what the graphs mean.

Here are a few helpful tips.

How information is presented:

  • Each graph represents how many Segment customers enabled a destination in a given quarter—meaning the graphs represent growth, rather than total number of users per tool.

  • Interpreting lines on the graph:

    • Upward line = tool is growing exponentially (colored and highlighted)

    • Flat line = tool is growing linearly

    • Downward line = tool is growing, but growth is slowing (grey lines)

  • Each graph highlights exponentially growing tools with colored lines. Other tools in the category are shown for scale in light grey lines.

  • Any graphs which start at zero indicate the tool was added to Segment within the past 3 years, and that you should discount the zeros.

Caveats:

  • These graphs do not account for customer value. A multi-billion dollar public company and a developer’s side project will each count as a single customer. As such, this analysis skews towards self-service tools.

  • This data is sourced from internal usage behavior.  This means we know the data is extremely high fidelity, but also that it generally skews towards users who know about Segment and are thinking critically about their data in the first place. We haven’t included tools that are not on our platform.

There’s a definite selection bias here, but we think it’s an incredibly interesting dataset to model pure account growth as we’ve seen it.


Analytics

The background: Analytics was one of the earliest categories we had at Segment. Of the six integrations we launched with, 50% of them fit into the category of ‘analytics.’

Today, there are three major players we’d like to highlight in the category, which doesn’t seem to be growing as actively as it once was.

Our data:

As you might expect, there is the clear dominance of Google Analytics, the big line at the top. It’s a free product, able to take in large amounts of data, and give you a pretty wide range of insights about where your web traffic is coming from. 

Notably, Google Analytics is also the first integration that our users tend to enable. We see about 60% of customers enabling Google Analytics before enabling another integration.

However, it seems that there is still room in this space to expand. Amplitude is growing at an astonishing rate, and Mixpanel continues to innovate as well. While Amplitude started out as the easy-to-install alternative to the first wave of behavioral analytics tools, namely Mixpanel, both companies continue to push the envelope on product development.

Both show climbing adoption and are iterating quickly as they expand the notion of what’s possible when it comes to behavioral analytics. The lively competition means it’s a great time to be a customer in the space, as providers push each other to innovate at a much faster pace.

The bottom line: Analytics as a category seems to be slowing its growth, but that doesn’t mean there isn’t room for innovation. Self-service tools targeting all types of companies—from startups to enterprise—continue to grow quickly. 

Fastest growing: Google Analytics, Amplitude

Raw Data

The background: Some raw data tools on Segment’s platform, like Webhooks and Zapier, enable even more tools we don’t support today. Others provide a means for companies to run their own custom data pipelines, like Amazon S3 and Kinesis

Our data:

Overall, we continue to see strong growth across the board in terms of adoption of these tools. 

As cloud tooling is making it easier and easier to run complex analysis on terabytes of data, we see more data pipelines consuming from Kinesis and PubSub to power custom ML pipelines. 

We also see strong adoption of Amazon S3. Customers putting data in S3 report it is a cost-effective, long-term place to store and run analysis on your data via EMR or Athena. Many of our customers even run event-based data pipelines based upon S3 events as part of a broader movement towards purely ‘serverless’ solutions.

Unlike projections that we’ve seen elsewhere, Google Cloud PubSub seems to be gaining more market share versus its competitors, though it still lags behind Kinesis. This adds additional insights as many outlets report that AWS owns 70% of the market.

The bottom line: Raw data tools are in. Segment’s easy collection, coupled with cheap storage and serverless workers means that there is a ton of growth in this space. Cloud providers continue to build more useful primitives for developers to plug into.

Fastest growing: Webhooks, Kinesis, Amazon S3, Google Cloud PubSub

Email

The background: Email is a crowded space mostly because there are so many different niche opportunities in this market. 

Marketing automation tools try to differentiate on any number of axes. Some target consumer businesses (Iterable); others target B2B (Marketo). Some focus mostly on advanced segmentation, others differentiate in terms of customizable drip campaigns.

Our data:

Regardless of the differences between competitors in this category, two things are clear:

  1. The category in aggregate continues to grow. (10 of these tools are growing exponentially).

  2. There is upheaval where existing players are being driven out.

Looking at the top line, we have Customer.io, an email tool targeting SMBs and mid-sized businesses. They are currently leading the space in terms of Segment installs per month, and appear to be growing linearly over the past 18 months.

Moving to the next three lines in these graphs, the big existing players from 2016 seem to have growth rates that are starting to flatten out. Instead, they are being replaced by upstarts who are growing actively.

In particular, Braze and Iterable stand out as new tools on the market who are actively gaining in terms of market share, while their larger competitors seem to be slowing.

The bottom line: Email as a whole continues to grow, with different tools finding their own niches. Most email tools are branching out beyond email to also offer push notifications and text message options. At least on the three-year timescale, email is an area that seems ripe for disruption. 

Fastest growing: Braze, Iterable, Customer.io

Advertising

The background: Advertising includes tools that are ad networks, DSPs, and programmatic tools. In the least sophisticated use case, businesses can use one of these tools to target a specific demographic (e.g. advertise to car owners in San Francisco). 

In more sophisticated approaches, many companies use tools like Facebook and Google to advertise to other users they don’t know about but share characteristics with their users (so-called “lookalike” audiences). This strategy is also known to offer strong performance by being the most targeted. 

Our data:

Perhaps unsurprisingly, we see DSPs and programmatic tools growing much less quickly. They form the downward sloping grey lines in the background.

Facebook and Google are clear leaders here, though the other social networks are still growing exponentially off a smaller customer base.

Interestingly, this chart effectively ranks the social networks by their ability to generate new ad accounts. Facebook and Adwords appear to be growing exponentially, while the other networks are still growing healthily, but more linearly. 

  1. Facebook

  2. Google Adwords

  3. LinkedIn

  4. Bing Ads

  5. Quora

  6. Pinterest

Our internal analysis confirms the results that Mary Meeker shared in her 2017 internet report

The bottom line: Advertising as a whole is a growing category. Google and Facebook continue to dominate, though Facebook is growing much more rapidly. The other social networks continue to grow exponentially off a smaller base. Other ad tools seem to be moving out.

Fastest growing: Facebook, Google Adwords, Linkedin, Quora, Bing, Pinterest

Mobile Attribution

The background: Mobile attribution tools attempt to… well… attribute the actions users take to the various channels where they came from. 

In most cases, these tools are trying to help mobile app developers understand how users install their apps. Unlike on the web, you don’t get a referrer field passed along from the browser as a UTM parameter, so you typically need some sort of other tool to analyze where the user came from (app store, an advertisement, a web page, etc).

Our data:

In terms of Mobile Attribution tools, we see two clear leaders by number of accounts: AppsFlyer and Branch Metrics, and also solid sustained growth from Adjust.

What’s most interesting about this whole category is that it seems to be continuing to grow very fast. Branch, AppsFlyer, and Adjust all are growing exponentially by number of accounts. 

It’s no wonder that this has been one of the most actively funded areas of SaaS in the past few years. Between just the top three players, over $350 million has been invested in mobile attribution. That said, it looks like we are starting to see more ‘breakaway’ winners from the mobile attribution category. 

The bottom line: Mobile attribution continues to be a growing category, with more funding being given to the winners. It seems mobile attribution is still a category that is receiving a lot more interest. 

Fastest growing: AppsFlyer, Adjust, Branch

Warehouses

The background: Warehouses are databases that empower our customers to use SQL to run very custom analysis that they might not get from an out-of-the-box tool.

We didn’t launch our warehouses offering until mid-2016, which is why the graphs don’t pick up until then.

Our data:

Of the cloud-hosted data warehouses, BigQuery seems to be growing most quickly.

One of the new entrants, Snowflake is also starting to accelerate its growth, though not yet at the levels of the earlier competitors. Snowflake tends to target more enterprise buyers, and therefore, benefits less from the self-service motion that Google and Amazon are able to achieve.

The bottom line: This entire market is still growing very actively. As companies become more data conscious and the infrastructure primitives get cheaper and more powerful, using the raw events is more and more appealing.

Fastest growing: BigQuery, Snowflake, AWS (really, all are growing)

CRMs

The background: CRMs present an interesting beast of a category. Salesforce has been the long, consistent leader in CRM, and is often seen as the defining brand for the category. 

Our data:

The first aspect that jumps out of our analysis is that Salesforce doesn’t dominate the CRM category in the way you might think. 

We have a number of theories for this. 

The leading theory is that Salesforce is a heavily customizable tool. Companies usually build custom workflows and schemas in Salesforce that reflect their use cases.

Segment has historically focused on fully “turnkey” integrations. Customers who want unique integration setups that fall outside of the defaults we set are more likely to use intermediary “glue” partners like Tray.io and Zapier to get their Segment data into Salesforce. Therefore, we see a subset of data biased towards the turnkey CRMs. 

Our other take is that HubSpot primarily targets SMB businesses, rather than more traditional enterprises. HubSpot continues to grow actively because it has a much larger and actively growing market when judged in terms of number of businesses, given that each business is much smaller in size. 

The bottom line: CRM as a category is growing slightly, with more accelerating growth curves from the players who target SMBs. 

Fastest growing: HubSpot

Live Chat

The background: Live Chat tools have been around since 2009. Olark, part of the YC S09 batch, pioneered the idea of talking directly with your users on your website. Since then, the category has become more crowded with new entrants. 

But the number of entrants stalled by 2014, when it seemed like the Live Chat category was relatively set.

Our data:

The Live Chat market changed drastically in 2016 when Drift, the fastest accelerating player, entered the market. 

It’s interesting to see Drift so quickly capture market share here, in what seemed to be a relatively stable market. In terms of go-to-market, Drift has done an incredible job showcasing end use cases for their customers.

The bottom line: Live Chat as a category is relatively stable in terms of growth, but Drift is proving that new entrants can still take market share. Having a clear set of ‘recipes’ for their users has helped accelerate their growth substantially.

Fastest growing: Drift

Performance Monitoring

The background: Performance monitoring and error reporting is a fairly unique category compared to the rest of the tools we support. It’s focused mostly on developer workflows rather than driving growth or retention. 

As a whole, we’ve seen the bulk of the players in this market stay relatively flat in terms of growth rate, with one exception that is growing rapidly: Sentry.

Our data:

Most of the Segment performance monitoring tools take advantage of the ability to collect various forms of crash and error data from a page.

Sentry takes this a step further. Sentry also sends data back into Segment, so not only can you see your analytics events as “breadcrumbs” in your error tools (as in the others) but you can see your customer errors and crashes along side the full customer journey from Segment! 

This superpower lets you actually measure to see how performance and responsiveness affect the overall customer experience.

The bottom line: Sentry is the clear leader in the performance monitoring space. Their top-notch product quality and clear surfacing of user events in the context of errors is likely driving their continued growth.

Fastest growing: Sentry

Referrals

The background: Referrals are a very new category for Segment. There’s only a handful of players, but the entire goal is to drive more users to your website by having your existing users refer them.

These tool help you create referral campaigns, provide mailing list infrastructure, and customize links for your users to share on social media.

Our data:

Of these tools, Friendbuy stands out as the new entrant who is seeing significant adoption. They’ve put a focus on direct-to-consumer retail and subscription companies (Dollar Shave Club, ClassPass, and Outdoor Voices) with remarkable results.

The bottom line: Companies are looking to offset the high cost to acquire customers (CAC) in favor of a selling motion that’s more viral and easier to scale. Referral tools are a natural fit to help here. Why only invest in ads when your users are already willing to tell their friends?

Fastest growing: Friendbuy

SMS and Push Notifications

The background: SMS and push notification tools help companies notify their users at the right time with the right message. While Apple and Google provide APIs to message users, this set of tools helps coordinate those pushes.

Our data:

Here, there are a bunch of players who are growing actively, but there are two that stand out in terms of trajectory: Braze and UserEngage

Braze has been growing actively and is working toward becoming the one of the most advanced push notification and SMS tool on the market. Braze allows you to model the full user journey and gives you extremely customize-able tools to create what they call a canvas.

UserEngage (now known as User.com), is a player who you might be less familiar with. They initially started out of Poland, raised 2.7 million as part of their Series A in late 2018, and have been growing quickly since then.

The bottom line: SMS and push notifications still seem like a growing market, but one that is rapidly starting to consolidate around a handful of winners. That said, it is not yet ‘set’, as we can see from recent growth of upstarts like UserEngage.

Fastest growing: Braze, UserEngage

Session Replay

The background: Session replay gives users the ability to follow along with various browser sessions, as if they were doing in-person user testing. 

It’s a helpful tool for understanding areas of your app that are hard to navigate, or what is stopping your users from completing your setup flows.

Our data:

This category has two companies, FullStory and Hotjar, showing strong market share growth that can be attributed to incredible product execution.

As can be seen from the graph, once these companies went live in the Segment catalog they were able to see significant adoption ramp very quickly. In fact, they were each able to create a sustained lead flow of customers using their product. 

This is another reason we’re incredibly excited about opening up our platform. Our Developer Center allows companies like Hotjar to build an integration right away, and start building a sustainable source of customers that find value in their product when combined with Segment data.

The bottom line: FullStory and Hotjar are breakouts in the space. It’s been hard for their competitors to compete with their growth velocity.

Fastest growing: FullStory, Hotjar

Emerging Trend 1: Customer Success is ripe for disruption

Interestingly, when we look at the Customer Success category in the catalog, we don’t nearly see the explosive exponential growth of integrations that we do elsewhere.

On the whole, we see the category continuing to flatline by number of enabled accounts, without a clear winner. 

This analysis puzzled us. 

If anything, it seems like customer success should be a growing category. Given the general explosion of SaaS businesses, the growth of direct-to-consumer, and big IPOs of B2B startups like NewRelic, Zendesk, Okta, and Twilio, we’d expect customer success to be a huge focus.

Instead, we think there’s a selection bias happening. Customers must be going somewhere to handle customer success tools, but it is possible that this is not reflected in the Segment catalog today.

Interestingly, of the 18 new integrations who have been added via the Developer Center, seven are focused on Customer Success: Vitally, Kustomer, Savio, ChurnZero, ScopeAI, Unwaffle, and UserBot.

Many of these tools are trying to leverage new advancements in ML/AI to better score users who might be likely to churn. As Segment is one of the best sources of the behavioral data required to make a good score, it seems only natural that we help power this next generation of tools. 

Emerging Trend 2: Beyond users to accounts

When Mixpanel launched in 2009, web analytics weren’t exactly a new market. Website owners had been using everything from Google Analytics to Hit Counters for years to understand their users.

But Mixpanel took it a step further. Instead of measuring pageviews alone (a proxy for value), Mixpanel sought to model the new types of behavior happening online with web apps. It differentiated itself by being the first product designed to track user events rather than pageviews. 

Today, nearly all tools have followed Mixpanel’s lead. Instead of tracking simple pageviews, they allow developers to send in all sorts of semantic events which are more closely tied to business-critical metrics. 

In our newest cohort of tools launched via our open platform, we’re seeing a similar paradigm shift emerging. This time, it’s focused entirely around B2B businesses who sell into separate ‘accounts.’

If you run a B2B business, you typically have to make a hard choice. You can track data on the individual user level, but then you may have a hard time combining it later (how do I understand what a 2,000 person organization is doing?). On the other hand, you can track the health and actions of overall ‘accounts’, but possibly miss data from individual users (what if you have one user who loves you but another who hates you?).

With this new class of tools, we’ve specifically seen a stronger focus towards tracking individual user actions, but combining those into the idea of an account. 

We even have a few examples below of companies that are leading the charge in this space.


Segment: The Next Generation

In closing, we’d like to highlight a few of the new tools which have been integrated using the Developer Center (now in beta for accepted partners).

We see these tools as the next generation of entrants into the customer data space. Almost all of them have existing Segment customers who have leveraged home-grown connectors to get integrated. 

Today, we’re excited that each of these integrations is in our official catalog. With every new tool built on our platform, our customers are finding new ways to use their data to improve their customer experiences. 

Kustomer

Kustomer is a customer success tool designed to help your support team quickly respond to customer issues with an unparalleled level of service.

Unlike other help desks or account scoring tools, Kustomer tries to bring the full view of the customer all into one place. They focus on combining ‘custom objects,’ things like orders and products, with user behavior and questions all in one single place. It’s sort of like a help desk on steroids.

For months, many of our users (like Glossier and StickerMule) have used both Segment and Kustomer to help treat their customers to world-class service. But each of these companies has had to build their own connection from scratch.

Today, that changes.  

"Now, users can instantly unlock a number of use cases leveraging their first-party data to proactively engage with their customers.” - Peter Johnson, VP of Product at Kustomer

Mutiny

Mutiny helps SaaS companies easily personalize their website content for each visitor.

Unlike traditional personalization solutions, Mutiny requires minimal data integration and engineering work to set up. They leverage aggregate learnings across B2B customers to help each customer launch the most impactful personalization experiences and get to results faster. 

Customers who use Mutiny and Segment can access near real-time data to inform personalized content. Website conversion events such as a visitor “booking a venue” are tracked by Segment and sent to Mutiny in real-time. 

To understand how powerful this is, we asked Peerspace, a Segment customer currently sending data to Mutiny:

“We use Segment to manage our data and Mutiny to give each of our website visitors a tailored experience that’s right for them. Website conversion events, such as when a visitor books a venue, is tracked by Segment and sent to Mutiny in real-time enabling us to see how each personalized experience is performing. We have seen up to 98% increase in conversion -- with the Segment Mutiny integration we can feel confident in the results.” - Arndt Voges, Head of Growth at Peerspace

Vitally

Vitally is a customer success platform that takes in all the data about your users to give you better onboarding and retention tooling. They were also one of the top integrations we saw users adding via Webhooks. 

In particular, Vitally specializes in high-growth companies. Vitally understands most customer success teams are undersized and need tools that help two CSMs seem like 200. 

They seamlessly organize all your customer data–Segment traits and events, conversations, subscriptions, and NPS scores–into 360° profiles. They then layer that data with automated workflows that help auto-detect and engage with customers in need. 

As you acquire more trials and customers, Vitally handles that scale seamlessly with powerful segmentation and analytics that help you continuously optimize every customer stage, from self-service trials to churn.

“At Gorgias, we help Shopify stores provide the best customer service, so it’s only natural that our own support should stand out. Segment + Vitally helps us do just that. Vitally enables us to analyze our customers’ interactions with our product, received via Segment, thus helping us identify and predict their needs through built-in indicators and success metrics. By pushing that over to Segment and propagating the enriched data to our entire marketing stack, we can be proactive in the way we serve our customers while improving our automation process.” - Axelle Heems, Growth Ops at Gorgias

Split

Split is a feature flagging and experimentation tool. It helps product and engineering teams to safely release new functionality while understanding the impact on customer experience.

Split helps you:

  • create different variations and feature flags for your users

  • group users into different variations depending on arbitrary rules

  • understand the impact of one variant against another

The superpower of Split is that it lets you combine data about your users with which variant they see. If you see a new feature performing badly, you can immediately find out and disable it, all in Split’s interface!

We asked one of our customers, Imperfect Produce, for a little more background on how they used the Segment <> Split connection. Here’s what they said:

“Sending Segment event data to Split, such as ‘added item to cart’, will help us to innovate faster than ever before. We already send a rich set of custom events to Segment for understanding user behavior. Having Split tie those measurements to feature flags and experiments gives us a powerfully-integrated system for finding out exactly what new features make our customers the happiest.” - Patti Chan, Director of Product at Imperfect Produce

ClearBrain

ClearBrain helps growth marketers create predictions and target their users based on intent. It’s not quite magic, but it’s close.

If you’re already using Segment, setting up ClearBrain is incredibly straightforward:

  • You send your Segment data to ClearBrain

  • You tell Clearbrain which actions and traits you want to predict (paying users, net promoters, etc.)

  • ClearBrain automatically groups those users into audiences using its AI/ML framework

With ClearBrain, you can predict any action or trait with a simple self-serve interface. This allows you to configure hundreds of predictive audiences by likelihood to convert, churn, purchase, or engage (or literally any event you’ve tracked in Segment) within minutes.

“Using Segment enabled us to get started on predictive analytics tools like ClearBrain a lot faster. With historical data replay, we can send years of Segment data to power predictive insights in ClearBrain and gain automated audience insights on the most important actions that lead to upgrade or churn.” - Kyle Gesuelli, Head of Growth at Frame.io

An open Segment platform

Needless to say, we’re incredibly excited to open the Segment platform to our technology partners and to start giving early access to our Developer Center beta. In the next few months, we are committing to:

More integrations on the Segment catalog

In one month, over 18 partners used our open platform to build a destination and 20 more are coming soon. If you’re a partner who wants to power your tool with rich customer data, now is the perfect time to request access to build on Segment

More partner discovery

As we expand our integration catalog, we want to make updates that help customers find what they’re looking for. That means helping partners get discovered when they solve customer problems, as well as making recommendations for what customers can integrate next.

More product innovation

By opening the Segment platform, we are helping new entrants, new categories, and established tools to better onboard customer data into their products. Not only does this mean our partners can get customers to value faster, it also means that they can focus on the product areas that can help them achieve ‘best in breed’ status.

If you’re interested in building on our platform and adding your product to the Segment catalog, you can start by requesting access to our Developer Center beta here

If you’re a customer who wants your vendors to add an integration with Segment, we’ve made it easy to share the reasons why they should build an integration.

Emre Sonmez on December 18th 2018

This post is a guest submission by one of our customers at Smartcar for Segment’s Chain Letter blog series. The Chain Letter series profiles clever uses of Segment Connections partner tools that, when chained together, lead to some pretty advanced programmatic models, custom messaging strategies, and more. Thanks to Smartcar for sharing their story!

—Segment

For an early-stage startup, getting new signups is always exciting — but how do you sort through that new user base and focus on the leads with the most potential?

This is something we struggled with during the early days at Smartcar. Our product, an API for cars, lives in a space that is just emerging. The concept of building a mobile app that reads data from cars (e.g. the odometer) without any hardware is difficult to communicate. Vehicle owners are connecting their car to a mobile app (e.g. a mileage-based car insurance app) for the very first time.

When we came out of stealth and launched the Smartcar dashboard a few months ago, we started observing different types of users. We quickly realized that we shouldn’t target every newly signed-up developer in the same way. Our team needed to know which users to reach out to, when, and about what.

With this objective in mind, we redesigned the dashboard in September using React and Redux and decided to integrate three user event tracking tools:

  • Segment to identify users and track events

  • Intercom to manage messaging campaigns based on these events

  • Mixpanel to track where users drop off when getting started on Smartcar

To integrate with Segment, we dispatched Redux actions that report events from the Smartcar dashboard. Here’s how we did it.

Defining our Redux action

Before we instrumented our React components, we defined a clear goal. We wanted to implement identify, page, and track calls to track how users interact with our dashboard, segment them into groups (e.g. “viewed support center”), and use this to inform how we communicate with them.

We also wanted to easily validate event parameters and test whether we called the correct Segment method.

To achieve our goal, we decided to use Redux actions and Redux Sagas. The Redux action reports the event to Segment. After the action is dispatched, the Redux Saga makes the actual API call to Segment.

Note: We use Redux Sagas to handle side effects in our React applications.

First, we defined a REPORT_TO_SEGMENT action. This action includes the type of call (identify, page, or track), a title ID (which we map to the event title), and any data that we want to pass into the event.

Code snippet of an example action

Reporting to Segment using a Redux Saga

We then added a Saga that listens for this action and executes the following steps:

  1. Validate that the type of call is either identify, page, or track.

  2. Validate that the title exists in a JSON file. To ensure consistency across event names, we map all title IDs to the actual titles in JSON files. Since lately, we could choose to do this through Segment Protocols instead.

  3. Make an API call to Segment.

  4. If any of the previous steps fail, report an error to Sentry.

Code snippet of Saga

Code snippet of reportToSegment function

Code snippet of validateEvent function

Dispatch an action from a React component

Now we can dispatch a REPORT_TO_SEGMENT event from any React component that is connected to the Redux store!

For example, if you create an account on Smartcar, we’ll provide resources to help you get started with our API. Those resources are located in the “resource card” section of our dashboard.

The demo app is one of the resources that we show users in the “resource card” section of our dashboard.

Whenever a user clicks on “Run our demo,” we dispatch a REPORT_TO_SEGMENT action in the ResourceCard component.

This action will run the Saga that we described above. It will then validate the event and make a track call to Segment.

Configure Intercom

Now, let’s say our business team wants to send a follow-up email to the users who clicked on “Run our demo.” To make this possible, we added Intercom as a Destination in Segment to send the data from the Smartcar dashboard.

By adding Intercom as a destination, we could configure an Intercom campaign that we send to all users who click on “Run our demo.”

Add Mixpanel to our destinations

Finally, we added Mixpanel as a destination in Segment. This way, our team can follow the first steps of our newest users. We can observe how these developers progress through the various steps of getting started with Smartcar. By tracking these events through Mixpanel, we can find out how new product features affect specific metrics (e.g. the number of users who create an account and then run our demo app).

This is how we used React, Redux, and Redux Sagas to integrate with Segment, Intercom, and Mixpanel. Using this stack, we have been able to segment our users and eliminate the amount of time our business team spent asking how and when to reach out to our users during the onboarding process. We can make sure that developers get up and running quickly with the Smartcar platform, and we can continuously make improvements to our developer journey. All this with a single integration and without the hassle of juggling different tools for engineering, marketing, and sales.


Smartcar enables developers to locate and unlock cars with an API.

Want to take their API for a spin? Check out their docs, get started with the Smartcar demo app, or shoot them an (mailto: support@smartcar.com)!

Kyle Gesuelli on October 31st 2018

This post is a guest submission by one of our customers at Frame.io for Segment’s Chain Letter blog series. The Chain Letter series profiles clever uses of Segment Connections partner tools that, when chained together, lead to some pretty advanced programmatic models, custom messaging strategies, and more. Thanks to Frame.io for sharing their story!

—Segment

Churn, it’s the secret killer of SaaS. Adding new customers and growing your top line means nothing if it’s all leaking out the bottom of your funnel in just a few short months.

At Frame.io, where I lead growth efforts, churn is always top of mind. For a little context before we jump in, Frame.io makes it really easy to upload large video files to the cloud, securely share those assets, manage multiple versions, gather timestamped feedback, and get approval  - all helping our customers deliver video up to 60% faster. Our clients range from video giants like Netflix and Turner on the high end, all the way to wedding videographers and small individual freelancers on the low end. While churn from larger customers like BuzzFeed and Vice who have hundreds of employees working on dozens of concurrent projects isn’t as much an issue for us, the story is very different in the long tail of the market.

For freelance editors and smaller 1-2 person production companies, projects are often inconsistent. Nobody wants to pay for a service they aren’t using, let alone during a period in which new revenue isn’t coming through the door. In fact, 60% of overall churn at Frame.io stems from the client’s project ending.

Fortunately, we see a 50% unbounded reactivation rate from this segment when they pick up their next project. So, the name of the game in combatting this particular type of churn is capturing revenue during that downtime.

Internally, we were averse to “optimizing” our cancellation flow. There are many companies who focus on creating barriers to canceling as a method of mitigating churn. Ever tried to quit the gym and they made you come back later because the manager was out that day? That’s one way to create a cancellation barrier, but this isn’t in our DNA. The real solution for these types of customers was creating a compelling use case for Frame.io between projects. Features in support of that idea could include low-cost archival storage, an embeddable video player, hosting for reels and portfolios, etc.

Like for many startups, bringing any of these ideas to life would be a big build, not an optimization. In fact, there hasn’t been a single time in my 6 years working in growth when I haven’t been strapped for engineering resources. It’s painful, but at the same time, it’s made me creative.

As a growth practitioner, I’ve been astounded over the past few years at how many interesting experiences we can craft with little to no engineering involvement. Using Segment helps us seamlessly collect, store, and transfer data, then chain together a variety of tools to personalize and enhance our customers’ experiences. Traditional email tools can enhance communications with push notifications and direct mail. Zapier connects APIs of disparate tools with a UI simple enough for a marketer. Drift lets you create chatbots, and parse the language of users’ responses to trigger an action. Clearbit helps you identify companies based on IP address. Optimizely lets you personalize your site experience, leveraging connections with Segment and Clearbit. The sky's the limit.

Frame.io’s churn mitigation workflow.

I decided to embark on an experiment to mitigate churn as fast as I could without much involvement from engineering - essentially crafting an experience where we send Drift critical account information via Segment at the time a user clicks to cancel, launch a chatbot via Drift, offer the user who wants to cancel a variety of solutions to prevent cancellation, and finally leverage Zapier to send instructions to the support team to handle the request to amend a subscription or cancel manually.

Sample .identify call from the churn mitigation workflow

Once this experiment proved out whether we could mitigate churn with a chained tool workflow, our plan was to either build a UI to replicate this experience, or keep the chatbot and send webhooks from Zapier to our API to handle the remediation with no human intervention.

Solutions for our customers who were cancelling because their project ended included transferring their account and billing to a colleague or client, pausing a subscription in-between projects for a lower monthly cost, or receiving a one-time discount for the next billing cycle to reduce the burden until more revenue came in the door. Below is what it looked like in practice.

Here’s a screenshot of how we use webhooks in Zapier to send the data back to Segment so it can be tracked and visualized/trended in Looker.

Frame.io uses webhooks in Zapier to send data back to Segment.

In the first month since launching this flow, we’ve saved 13% of potential churns. Although that doesn’t sound astronomical, the results for the business are tremendous.

Closing this leaky bucket even a little means the LTV of our average customer increases, allowing us to spend more to acquire new customers, of which I need fewer since I’m earning more from my existing paid base. Churn is one of the levers that can have the most significant impact on a business, and we’re happy when we make even a small dent.

Andrew Park on October 9th 2018

This post is a guest submission by one of our partners at Tray.io for Segment’s Chain Letter blog series. The Chain Letter series profiles clever uses of Segment Connections partner tools that, when chained together, lead to some pretty advanced programmatic models, custom messaging strategies, and more. Thanks to Tray.io for sharing DigitalOcean’s story!

—Segment

The marketing team at DigitalOcean knew it couldn’t usher in growth for its more than half a million global customers using traditional demand gen tactics. David Dorman, Director of Growth and  Demand Gen, and Andy Hattemer, Senior Growth Marketing Manager, needed a system that would deliver highly customized, context-heavy outbound and nurture messaging to individual users at different points in their customer journey. Creating and executing on an individualized messaging system at scale involved several hurdles. This is the story of how DigitalOcean evolved a reactive marketing approach, previously powered only with Salesforce and Marketo, into a highly personalized messaging strategy by layering in Tray.io, Clearbit, and Segment.  

A two-system state of the world

While DigitalOcean was using Salesforce for customer relationship management and Marketo as its way to integrate customer messaging into Salesforce, the growth marketing team quickly realized that these two solutions, while popular for certain marketing automation and CRM functions, weren’t going to scale without additional functionalities.

The marketing platforms lacked the customized multi-directional, multi-app syncs that DigitalOcean needed - the kind of syncs that would flow important customer data to and from Segment to both enrich user data in other applications, as well as to update Segment records afterward to ensure DigitalOcean’s campaigns were always properly targeted. The team also found itself up against Marketo’s low API call limits - typical for most marketing platforms, but a bottleneck for a team that needed to route huge amounts of mission-critical customer data. The solution was to enrich their customer data and craft messages that spoke to the distinct needs of each user while being able to deploy these messages multiple times per day, at scale.

Adding in a customer marketing data stream

As a Tray.io and Segment customer, DigitalOcean realized that it could use Tray.io’s General Automation Platform and Segment’s Personas product to develop Audiences to send to their downstream tools like Marketo to tailor campaigns for each user. DigitalOcean created a system that chained together:

  • Segment Connections and Personas to inform the messaging customization and enrichment process. Once the enrichment and customer profiling process was complete, DigitalOcean used Segment Connections to build email metadata to properly identify which users would be appropriate for which messaging

  • Clearbit to enrich each customer with full lead information, including name, email, and location

  • Salesforce to confirm DigitalOcean customers against their account records in the CRM

  • Tray.io to integrate all of DigitalOcean’s cloud-based services, creating a sophisticated automated workflow that would enrich leads with initial webhook data, Segment Personas data, and Clearbit, compare against Salesforce account info, and prep Segment email metadata

Step 1: Enrich Messaging, Add Personas, Enrich Lead Data

DigitalOcean built a complex workflow on the Tray Platform that automatically fired off multiple times per day according to a scheduled trigger. The first part of the workflow, once triggered, enriches the current messaging queue via webhook for its many messaging parameters (_including _Attributes_Timestamp, SenderID, MessageAttributes_City, MessageAttributes_PostalCode), then sends a GET webhook request to pull Segment Personas details from a records.segment.com URL.

Next, the workflow combined this persona information with enrichment from Clearbit using a Clearbit Output function for specific lead details (including Person_FullName, Person_Employment -Domain/Name/Title/Role/Seniority__, and Person_EmailProvider__, Geo - City/State/Country Person_Company_Metrics - NumEmployees/MarketCap/AmountRaised/AnnualRevenue) to give the clearest possible picture of the target customer.

By knowing where each company is headquartered, DigitalOcean could ensure its messaging would be sent in the appropriate language, and the most relevant users could join their local Meetups. By connecting Crunchbase data, the team could ensure it was presenting appropriate messaging based on their users’ company size (for instance, marketing messaging for a small-to-medium-sized business won’t resonate appropriately with an enterprise customer).

As a result of this series of steps, DigitalOcean’s team would ensure it had enriched profiles for each of its thousands of customers in its messaging queue, profiled with Segment Personas and enriched with Clearbit data as well as with employee size details sourced from Crunchbase to ensure it was sending messaging appropriate to specific job titles and company sizes. For instance, a specific marketing message might hit home with an Associate IT Manager at a small-to-midsize company; but that same message would be unlikely to resonate with a VP of Engineering at an enterprise firm.

Step 2: Tray Helpers, Confirm CRM Account Details, Email Metadata

Once the automated workflow in the Tray Platform had enriched and profiled the company’s customers, DigitalOcean then directed it to use a variety of customized Tray Platform helpers, such as running an API query at api.crunchbase.com to confirm whether a customer’s company with missing data had a Crunchbase listing, then loading in a new profile if that company’s Crunchbase profile had not yet been added:

The workflow then made a call to Salesforce to Lookup Salesforce ID Output for Accounts and Account ID to confirm whether the customer’s company was already listed in the CRM. Finally, the workflow made a Segment Email Metadata Output call to identify users matching the enriched profile to prepare the appropriate customized messaging stream for those users.

Hundreds of thousands of custom messages sent monthly

As a result of using Segment’s Personas functionality and its ability to interact with email metadata, DigitalOcean quickly scaled from traditional marketing automation to enrich and prepare custom messaging for some 50,000 contacts in its first week of deployment. DigitalOcean is now sending out personalized messages at scale to their prospects and customers with the right message at the right time. This gives DigitalOcean the speed, visibility, and costs savings to be proactive with their marketing across all customer touch points.

The Segment Growth Team on August 6th 2018

This is a continuation of a post on analytics tools. If you’re just tuning in, check out part 1 here.

Analytics tools profiles

Adobe Analytics

Adobe Analytics is a comprehensive analytics suite that provides multi-channel web and marketing analytics. Often described as robust and highly customizable, Adobe Analytics is typically used by mid-market and enterprise companies with many data sources and large datasets; it’s less appropriate for bootstrapped startups who only need to conduct basic analyses. Recently, Adobe has focused considerable effort on mapping the user journey and understanding different audiences—it allows more sophisticated segment-building than many other providers and uses machine learning to help identify new audience groups. Mid-market and enterprise companies who need more advanced tools to transform their data into actionable insights should definitely consider Adobe Analytics.

Some key features include:

  • The ability to collect and process data from virtually any channel—online and offline, email, video, search, display and more.

  • Advanced analytics that go beyond basic reporting to provide a complete view of the customer journey such as fallout, flow, and pathing analysis.

  • Highly customizable and AI-driven segment definitions.

  • Powerful data science processes that can predict a customer’s likelihood to convert and churn.

  • Algorithmic attribution to help companies understand the impact of each user interaction.

  • Intelligent alerts that are sent when significant trends or anomalous events occur (e.g., KPI data, product performance issues, usage trends, etc.).

  • Highly customizable reporting and dashboards.

Adobe Analytics is great for:

  • Objectives: Identify new audiences, increase conversion rates, enhance user experiences, drive customer lifetime value through repeat engagement, optimize digital marketing effectiveness, improve site performance

  • Role: Marketers, product managers, developers

  • Customer company size: Mid-market and enterprise (100 – 10,000+ employees)

  • Industries: e-commerce, marketing and advertising, media, travel, financial services, technology

Amplitude

Amplitude provides real-time, cross-platform analytics with an emphasis on helping product managers understand the user journey, identify the best and worst-performing features and improve retention rates. Product teams can create custom events and tailored segmentations based on the actions users have taken. This provides insight into the common paths taken by users, identifies drop-off points and features correlated with increased retention, and helps to predict new user retention rates. By leveraging these user segments, marketers can also create targeted campaigns and A/B test results to identify winning variations. Moreover, Amplitude’s intuitive design, eye-catching visualizations, and customizable dashboards help teams gain insights faster.

Some key features include:

  • Web and mobile analytics that provide a clear picture of product health, including engagement, funnels, cohort retention, revenue, custom formulas and flexible segmentation.

  • The ability to funnel audiences by custom events and actions like checkout completed, item added to cart or payment entered.

  • Intelligent alerts that are sent when significant trends or anomalous events occur (e.g., KPI data, product performance issues, usage trends, etc.).

  • Account-level analytics and CRM-integration for B2B companies to help each team focus on the set of customers that can create the highest ROI through product changes.

Amplitude is great for:

  • Objectives: Enhance user experiences, drive customer lifetime value through repeat engagement

  • Role: Product managers, marketers

  • Customer company size: Startup and mid-market (1 – 500 employees)

  • Industries: Technology (including B2B SaaS), media, e-commerce, financial services

Flurry

Flurry is a free Yahoo-owned mobile app analytics tool that is currently used by more than 1,000,000 apps. It monitors user events and usage trends to help product teams identify UI flow issues and enhance features to increase user retention. Designed to be easy-to-use and implement, Flurry is ideal for app companies who need fairly basic reporting with a little customization.

Some key features include:

Easy-to-implement, real-time mobile app analytics detailing user and session activity.

  • Funnel and user path analyses to compare conversion rates and other user actions across different dimensions such as age, device type or custom events.

  • Segmentation analyses based on standard attributes such as age, gender, location, acquisition channel and custom events.

  • The ability to track mobile in-app purchase revenue across iOS and Android and understand which products are driving revenue.

  • Real-time crash reporting that offers a clear description of the issue, which devices are impacted and when the issue was seen last.

  • Portfolio analytics that enable companies to manage their app portfolios, including data about overlap and cross-sell conversions.

  • Scheduled or behaviorally-triggered in-app notifications.

Flurry is great for:

  • Objectives: Enhance user experiences, drive customer lifetime value through repeat engagement and in-app purchases, improve app performance

  • Role: Product managers, mobile marketers, developers

  • Customer company size: Startup and mid-market (1 – 500 employees)

  • Industries: Technology, media, gaming

Google Analytics

Google Analytics is the most widely adopted web and mobile analytics provider. It takes a two-tiered approach, providing basic Google Analytics for free—targeted at small and medium-sized businesses—and Google Analytics 360, a paid offering for large enterprises. One of Google Analytics’ greatest differentiators is its integration with other Google services, such as Google Ads (formerly AdWords) and AdSense, which allows for a more holistic view of the user journey and improved targeting for paid media. For example, by linking Google Analytics and AdWords, companies can fill in gaps in their conversion tracking data and create remarketing lists based on Google Analytics data. With Google Analytics 360 comes higher data volume and more custom metrics, as well as an advanced, machine-learning upgrade to funnel reporting and attribution modeling. Larger companies that need significant customization and powerful reporting options, or those with substantial Google media spends, will want to consider Google Analytics 360.

Some key features include:

  • The ability to import interaction data from any internet-connected third-party system (e.g., CRM, desktop app, etc.) for Google Analytics 360.

  • Segmentation capabilities, funnel reporting and attribution modeling—basic for Google Analytics and sophisticated, AI-driven for Google Analytics 360.

  • Various tag management tools to streamline the configuration of complex tracking.

  • Seamless integrations across Google’s cloud offerings, including its digital advertising suite, machine learning libraries, and data warehousing solutions. (The latter only applies to Google Analytics 360.)

  • Customizable reporting and dashboards, as well as data access via mobile app, API, email notifications and more.

  • A recently released Analytics Intelligence feature for Google Analytics 360, which uses machine learning to return answers to users’ natural language queries (e.g., “Which channel had the highest goal conversion rate?”).

Google Analytics is great for:

  • Objectives: Increase conversion rates, enhance user experiences, drive customer lifetime value through repeat engagement, optimize digital marketing effectiveness

  • Role: Marketers and product managers

  • Customer company size: Startup and smaller mid-market for basic Google Analytics (1 – 500 employees); larger mid-market and enterprise for Google Analytics 360 (500 – 3,000+ employees)

  • Industries: Marketing and advertising, technology, media, commerce, travel

Heap

Heap enables companies to track first and build their funnels later by automatically capturing every user interaction on web, mobile and cloud services, not just the interactions that it’s pre-configured to track. This means that every department—from marketing to HR—can pull insights from Heap’s platform retroactively, without the intervention of a developer or analyst. This flexibility makes Heap ideal for companies with multiple departments who need user-friendly access to analytics, as well as those who don’t have the developer resources to support very rapid, data-driven decision-making.

Some key features include:

  • Automatic capture of every click, tap, swipe, form submission and more from a website or mobile app without the need to set up event tracking in advance.

  • Point-and-click web and mobile tag creation, allowing marketers to define custom events without coding.

  • Funnel analysis across different user segments, device types or attribution channels to identify friction points and improve conversion rates.

  • Complex segment definitions that combine user activity and user attributes (e.g., vertical, contract value and first touch attribution).

  • One-click integrations with third-party cloud apps (e.g., CRMs, marketing automation tools, payment processors, etc.) to enrich user-level and event data.

Heap is great for:

  • Objectives: Increase conversion rates, enhance user experiences, drive customer lifetime value through repeat engagement

  • Role: Marketers, product managers, salespeople

  • Customer company size: Startup and mid-market (20 – 1,000 employees)

  • Industries: e-commerce, technology, media, financial services

Kissmetrics

Kissmetrics is a web and mobile engagement platform that connects behavioral analytics with powerful email automation. It delivers simple yet valuable reporting of customer behavior across devices with precision segmentation and targeting options. A key differentiator for Kissmetrics is its inclusion of marketing automation tools such as behaviorally-triggered email campaigns, which can be sent to targeted user groups based on custom events or funnels. Kissmetrics provides excellent out-of-the-box reporting for small and medium data volumes and is a great option for companies who want to focus only on key metrics without being overwhelmed by data.

Some key features include:

  • Cross-platform behavior reports to help marketers identify and monitor custom audience growth segments, including up-sell and cross-sell opportunities.

  • Automated or manually-targeted emails based on completed custom actions, unique events or funnels. A/B testing for email campaigns is also supported.

  • Integration with third-party platforms like Shopify and Woo Commerce to import shopping history, segment customers, and follow them from their first visit to purchase and beyond—with no coding required.

  • Automated customer data reports, so marketers can review key metrics on active and churned populations.

Kissmetrics is great for:

  • Objectives: Increase conversion rates, drive customer lifetime value through repeat purchases

  • Role: Marketers

  • Customer company size: Startup and midmarket (1 – 1,000 employees)

  • Industries: e-commerce, marketing and advertising, media, travel

Mixpanel

Mixpanel provides web and in-app event analytics to help marketers improve conversion and retention rates. In addition to tracking user activity and funnels, Mixpanel identifies the user behaviors associated with higher engagement and retention and recommends actions to move the needle on these metrics. Additional marketing tools are included, such as the ability to A/B test campaigns and send in-app notifications to users based on specific actions they’ve taken. Mixpanel is relatively easy to implement and easy to use with an intuitive UI and polished reports.

Some key features include:

  • Sophisticated retention analyses that can answer questions like, “How many new mobile users from each of our mobile ad campaigns came back to use our product?”

  • Automatic segmentation to identify high and low-performing user groups, new audience targets, etc.

  • The ability to run A/B tests for specific user segments using an in-browser editor that can easily change the app’s UI—such as by removing features, changing colors, editing text, or uploading an image.

  • Predefined “Insight” questions that allow non-technical marketers to analyze data, discover how user engagement has changed, and pinpoint ways to optimize engagement.

  • Predictive analytics that identify users who are likely to perform an action based on past behavior, enabling more targeted and proactive marketing.

  • Intelligent alerts that are sent when significant trends or anomalous events occur (e.g., KPI data, product performance issues, usage trends, etc.).

Mixpanel is great for:

  • Objectives: Increase conversion rates, drive customer lifetime value through repeat engagement, optimize marketing campaigns

  • Role: Marketers, product managers, developers

  • Customer company size: Startup and mid-market (1 – 1,000 employees)

  • Industries: Technology, media, financial services

Woopra

Woopra is a real-time analytics platform that monitors how users behave across product, marketing, sales and support touchpoints. It’s designed to help answer questions ranging from, “Do users return after using our core product feature?” to “How does live chat impact conversions?” Woopra delivers both a high-level analysis of how different user groups move through the funnel, as well as detailed information on individual users’ journeys to assist customer success teams. Compared to other platforms, Woopra is intuitive and relatively easy to implement with dozens of one-click integrations.

Some key features include:

  • Cross-platform integration with CRM, mobile, email, marketing automation, social and support tools to provide a detailed picture of user interactions.

  • Customer journey analysis to reveal critical obstacles and opportunities at every point in the customer experience from marketing campaigns to product engagement.

  • The ability to create dynamic segments of users based on any combination of criteria—from opening an email, to signing up for a trial, to using a new product feature.

  • Trend reports to monitor product performance across multiple dimensions (e.g., location, subscription type, version, etc.) and to identify the features that drive long-term revenue.

  • Automated triggers to activate other engagement processes, such as updating the status of engaged leads in Salesforce or firing a Slack trigger to notify customer success when a user is ready to upgrade.

Woopra is great for:

  • Objectives: Increase conversion rates, enhance user experiences, drive customer lifetime value through repeat engagement, optimize marketing campaigns

  • Role: Marketers, product managers, customer success representatives

  • Customer company size: Startup and mid-market (1-1,000 employees)

  • Industries: e-commerce, technology, media, travel, financial services

Conclusion

Choosing an analytics provider can be a daunting task; there are dozens of options available with a wide range of features and sophistication levels. To start whittling down those options, consider your company’s size, data volume, and budget. Then make a list of your business’s most pressing questions and get input from the different teams who could benefit from enhanced customer analytics. If you already have some analytics in place, what answers aren’t you getting from them?

Instead of implementing each tool individually, you can use Segment to collect customer data with a single API. From there we automatically transform the data and send it out to any tools your team uses. Segment currently integrates with more than 200 tools—check out our full catalog or request a demo to learn more.

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