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Nupur Bhade Vilas on October 20th 2021

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Diana Smith on January 9th 2015

Like many startups, we’re experimenting with traction channels to discover what will drive our next stage of growth. But before we could test user acquisition, we had to answer an important question.

How much should we spend on this stuff?

We didn’t want to waste cash on frivolous ads or channels that weren’t working. We needed a benchmark help understand what was a good buy, and what wasn’t.

Today, we’re sharing our process with you! Here is the step-by-step guide we’ve used to confidently calculate what we should spend on customer acquisition and the tools that have helped us along the way.

Ask Three Questions.

For a SaaS company, there are three main questions you need to answer before you create a budget for acquiring new customers.

1. How much do your paying customers spend throughout their lifecycle?

We’re talking lifetime value or LTV. RJMetrics has a nifty calculator for this, but here’s a quick and dirty formula.

Gross Margin is what’s left after you’ve paid for COGS, or the cost of goods sold, such as support and hosting expenses. Churn is the percent of people that leave, unsubscribe, or in other words stop paying for your service on a monthly basis.

2. What percentage of people that signup actually pay you?

Many SaaS companies offer a free trial or freemium plan, so not every signup becomes a paying customer. You’ll need to calculate your Signup-to-Paying Conversion Rate to know what you can pay for a signup.

3. What percentage of folks that visit your website sign up?

You can calculate this Signup Conversion Rate with a simple funnel. If you’re using landing pages in your ads, use the landing page conversion rate.

For an e-commerce company, you can merge the third and second steps because you’re not giving away anything for free! You’d just calculate Visited Site / Completed Purchase.

If some of your campaigns target in-between conversion events (like capturing lead information for a newsletter), then your two calculations might look like:

Of course for mobile apps, you’ll be looking at app installs to rather than website views.

Now that you’ve calculated your three inputs: lifetime value, signup to paying conversion rate, and signup rate, you can easily calculate how much to pay to acquire new customers and to get a click through to your website.

Cost Per Acquisition Formula.

There are two main metrics advertisers use to report their costs: Cost Per Acquisition (CPA), or the amount of media dollars you need to spend to get one sign up, and Cost Per Click (CPC), or how much you pay when someone clicks through an ad to your site. Let’s start with CPA. It’s a two part formula for those of us that offer freemium products.

1. How much can I spend to acquire a paid customer?

A third of LTV is on the higher end of what you’d want to spend for one paying customer, but it’s fine for when you’re experimenting with new channels. After all, you’ll still be making money if your customer acquisition costs are lower than your LTV. However, when you find a channel that works, you’ll want to optimize for a lower CPPC that’s closer to LTV / 5.

2. How much can I spend to acquire one signup?

If some of your signups are on a free plan or trial, this additional formula factors that into the cost to acquire a single signup.

One caveat – some companies have enterprise plans that are much more expensive than self-service plans. In this case, you might want to factor in conversions to enterprise when paying for a regular old signup.

Calculating Cost Per Click.

Often times, your advertising platforms will make you choose a maximum bid for a click, rather than letting you pay for actual signups. This is where your Signup Conversion Rate from question 3 comes into play, since it calculates the likelihood that someone who clicks through your ad will convert.

How much can I spend for one click to my website?

There you have it folks – a very good baseline for what you should be spending on customer acquisition. Check out this Google Spreadsheet to input your own numbers, and calculate your own costs!

Optimizing Per Channel.

While these formulas give you a guide for what to spend, analytics, event-tracking and attribution tools will help you optimize your acquisition budget.

For example, people who find you via Google Adwords might pay you more money overtime than people who come from Twitter. As an advanced marketer, you’re going to want to evaluate the LTV of signups from each channel, which will change what you can spend to acquire customers via that channel.

Just plug the channel LTV number into the equations above, and you’ll be good to go. Also, make sure you’re getting enough traffic to make these calculations significant. Here is a tool to calculate how much you need.

You can compare if the costs are too high and the LTV too low for a specific platform compared to your baseline and cut it from the budget. Or, if you find a bargain channel, you can pour on the cash.

Tools That Can Help.

A/B Testing.

To get the most bang from your marketing bucks, you’ll want to consider optimizing the conversion rates we discussed. OptimizelyLeanplum (for mobile), and Taplytics (also mobile) are some good A/B testing tools to improve your website and landing page copy, design, and conversions.

Marketing Automation.

Event-based email and push notification services like Customer.ioOutboundVero, and Kahuna can help you move users through the activation funnel with personalized, timely communication and increase your Signup-to-Paying conversion rate.

Attribution.

If you’re running a ton of campaigns, keeping track of conversions and spends can get tricky. Mobile App Tracking and Convertro help marketers make sense of their entire media budget and see which channels are performing best. Google Analytics also has solid attribution reporting.

Integration Platform.

Segment is the easiest way to capture the data you need to calculate customer acquisition costs, and then send your conversion events to all of these tools. If you integrate Segment into your app or website once, then you can flip a switch to integrate any of these services. Your time is money, and we’ll save it.

I hope you found these tips helpful! If you have any other suggestions, share them with @segment on Twitter!

Janessa Lantz on December 2nd 2014

Janessa Lantz from RJMetrics – a Segment SQL partner – shares marketing and product tips for engaging, retaining and learning from your best customers.

The best companies are already using customer lifetime value (LTV) to measure marketing ROI. LTV is a powerful metric for optimizing marketing spend, allowing marketers to look beyond the channels or campaigns delivering first-transactions to identify those that are bringing in high-value, repeat purchases.

But that’s not all you can do with LTV.

To get you started, here are a few product and marketing hacks that leverage your high value customers:

1. Identify and encourage high value behaviors

What are your top customers doing on your site and what could their behavior tell you about other potentially valuable customers? Put your event data to work to answer this question and you can uncover the “golden motions” driving your business. In RJMetrics, you can build lists of your top customers by spend, then analyze what your best customers are doing on your site with Segment SQL data to find this out.

Once you know high value behaviors, you can use engagement tools, like email marketing and push notifications, to encourage users who haven’t taken high value actions to do so. For example, a SaaS company might find that their best customers invite at least two other users from their organization. An e-commerce company might find that repeat purchasers share their new goods on social media within a day of ordering. You could set up automatic campaigns to reach out to people who haven’t taken these important actions and help them to make the most out of your product.

2. Treat your top customers like VIPs

In the average ecommerce store, the top one percent of customers spends 30-times more than the average customer. You should be treating these customers like VIPs. For example, you could identify top customers who were on your site recently. Once your list is ready, export it, upload it to your email service provider and reach out to your best customers with a highly-personalized, tailored offer.

If you’re looking to engage with your very best customers without filling up their inboxes, you could use Facebook retargeting in a similar way. Once you’ve uploaded your list to Facebook Custom Audiences, you can send custom ads and offers to your most engaged, highest value customers.

3. Evaluate how new features are performing

Cohort analysis – or evaluating how a similar group of users behave overtime – is a great way to measure how feature changes are impacting customer engagement. With LTV, you can take this analysis to the next level by segmenting high-value vs. low-value customers.

Did your best customers quickly adopt the new feature? Is it driving low-value customers into the high-value range? Answering these types of questions will help you define and tweak your product roadmap and evaluate if new features were worth it.


Hope you enjoyed these tips! To learn more about what else you can do with RJMetrics and Segment, click here or hit us up on Twitter @RJMetrics and @Segment.

Jake Peterson on November 23rd 2014

Your analytics are only as good as the data you’re tracking. And deciding what to track is the hardest part about making your data useful. It’s overwhelming to create a tracking plan from scratch, so this article will give you a head start.

After discussing with hundreds of customers, reviewing best practices across all our partners, and some good ol’ trial and error, we’ve revamped Segment’s own tracking plan. We’re sharing it with you today, so you can use it as a reference.

First things first.

You should keep a few things in mind as you start building your tracking plan.

  • It’s all about the funnel. How do people discover, start using, and pay for your product? What are the most important steps along the way? These are the crucial events you want to capture.

  • Less is more. Track only the events you will use to make decisions, only the most essential pieces of information. Start with three. Seriously, three. Only add more later.

  • Get organized. Pick a convention for naming your events and properties. Your eyes, brain, and new team members will thank you later.

Core Lifecycle Events

Our customers hit three important lifecycle events as they find, implement, and pay for Segment. These lifecycle events are very similar across most SaaS companies. Here’s how we record them down as discrete events:

  • Signed Up

  • Sent Project Data

  • Started Subscription

Why?

In our own tracking plan template, (you can see it in a Google Sheet here), we have a column called “Why?”. In the “why” column we explain the purpose for tracking each event, which forces us to focus on what’s most important and leave out extraneous data that’s not critical to our business. We’d suggest you do the same! We actually borrowed this idea from you, our customers!

Protip. We’re sticklers for formatting and consistency over here, so any new person on the team can easily search for and add new events. We suggest naming all your events with past tense verbs and capitalized letters, ex: Signed Up__. Name properties in camelcase (lowercaseCapital form) for easy reading, ex: userLogin__.


Tracking Plan

Alright, let’s dig into why and how we track each of these events.

Signed Up

The Signed Up event is the key metric for Design to see how the site is converting and for Marketing to measure campaigns. It’s a user’s first baby step of commitment.

analytics.track('Signed Up', { userLogin: 'peter-gibbons', type: 'invite', organizationId: 'aef6d5f6e' });

We differentiate organic signups and invited signups, so we can understand organic website conversion separately from internal team sharing. To distinguish between organic and invited signups we use an event property called type. We also use automatically recorded UTM parameters to differentiate users that come through paid campaigns like Adwords.

Sent Project Data

This is it folks. This is the crux of whether or not people are using our product. Have they integrated? Are they sending data? How much? To which partner integrations? Via which methods? From which libraries and platforms? It all goes here.

analytics.track(userId, 'Sent Project Data', { // project projectId: 'bce5fad577', projectSlug: 'initech.com', projectCollaborators: 1,

// owner ownerId: 'aef6d5f6e', ownerType: 'organization', ownerOwners: 12,

// usage callsMonthly: 134811, callsWeekly: 22,

// methods methodIdentify: 14811, methodAlias: 1320, methodTrack: 2861, methodPage: 115819, methodScreen: 0, methodGroup: 0,

// libraries libraryIos: 13289, libraryAnalyticsjs: 121582,

// integrations integrations: 3, integrationKISSmetrics: true, integrationGoogleAnalytics: true, integrationCustomerio: true });

With this paramount event, we can measure which integrations and libraries are the most popular, bill folks according to their usage, understand how much data we’re processing, and measure our active users.

The tricky thing with this event is that it’s unique per project, but everything else is tracked per user. So we record a Sent Project Data event once a day, for each user, for every project they’re connected with that had data sent. For example, a user might be an owner or collaborator on 3 projects that sent data today, in which case we’ll send 3 Sent Project Data events, one for each of those projects.

This is a server-side event. Learn more about server vs. client side events here.

Started Subscription

We offer a 14 day free trial, so it’s important for us to capture when people actually start a plan and enter a credit card. This is the final step of the activation process.

This event should only be triggered when we immediately start billing them: credit card, plan, everything is set up. This is a server-side event as well.

analytics.track(userId, 'Started Subscription', { ownerId: 'aef6d5f6e', ownerType: 'organization', ownerLogin: 'initech', ownerEmail: 'peter@initech.com', planName: 'Startup', planId: 'startup-$79-1-month', });

Phew! That’s our three core funnel events. These are the most essential events to help us determine the health of our business.

If you’re just getting started, we recommend you check out our template for a basic tracking plan here. Like I said before, start with three core events.

If you’re an analytics wizard, read on. We’re a data company, so we couldn’t help but identify a few more events that help us make better decisions.

Getting Fancy

In addition to our core funnel, we’ve started tracking a few additional events to help us inspect user behavior around the edges of the core funnel.

  • Created Organization – Most of our revenue comes from organizations that use Segment, so it’s important for us to know when someone levels up from a personal account to an organization account.

  • Invited User – When users invite more people to their organization, it’s a good indicator that they’re engaged and serious about using the product. This helps us measure growth within organizations.

  • Enabled Integration – Turning on an integration is a key engagement metric.

  • Disabled Integration – We also want to know which integrations people are turning off, experimentation with different tools is positive engagement.

  • Debugger Call Expanded – When we see that a certain customer has used the live event stream feature a number of times, we reach out to see if we can help them debug.

  • Created Ticket – How is our support doing? How many users contact support during or after the setup process? This event helps us measure our setup guide and documentation quality as well.

Identify and Page Calls

Using Segment track calls you can easily capture interactions people take on your site. But you really want to tie this information to two other pieces of the puzzle: who is taking the action and where they are when they do it. That’s where our identify and page methods come into play.

Take a look here to learn about all of our methods.

analytics.page('Docs', { section: 'API Reference', topic: 'Identify Method' });

Note: The Segment page method also collects the page title__, url__, path__, referrer__, search and campaign (UTM parameters) automatically.

analytics.identify(userId, { created: '2014-06-30T16:40:52.238Z', name: 'Kanye West', email: 'kanye@iamawesome.com', login: 'kanyew', type: 'user' });


If you want all of this in a handy Google Doc, we’ve got you covered.

And remember, if you have any tracking questions or thoughts on our plan, don’t hesitate to contact us.

Thanks!

Derek Steer on November 19th 2014

We welcome Derek Steer, CEO of Mode, to the Segment blog! Mode is a SQL integration partner and has created these open source queries so you can start learning ASAP. The best part? Their playbooks are tailor-made for the Segment SQL schema.

The Fast Track to Data Driven.

You’re planning ahead to 2015. “Be more data-driven” is on your company to-do list.

You want to give your team access to better information–and help them make more informed decisions. Questions like “how many invites did we see yesterday?” and “how are customers using the invite feature?” are popping up right and left. Maybe you’re hearing things like “what marketing channels lead to the highest lifetime value customers?” when six months ago this type of question sounded simpler, like “how many daily sign ups are we getting?”

It turns out a lot of these insights are hiding in the raw event data that your product is already generating, quietly in the background.

Thanks to Segment, you can track these analytics events and flip on Amazon Redshift to start digging into these questions.

As we started working with our own Segment data—and helping some customers beta testing the product—we found that many of us had similar questions about how people use our products.

To put all these questions in one place, we started writing SQL queries that could be tailored to anyone’s Segment data schema. These open source queries—we call them the Mode Playbook—can help you find Retention and User Behavior insights in your data from the moment you connect your database to Mode.

Find Insights Fast with Open Source SQL.

Let’s look at an imaginary messaging app as an example.

Your Product Managers are talking about how to increase sent messages but no one seems to have a specific understanding of what users do before they send a message. With the User Path report, you can help them visualize the paths the users take before sending a message.

This report, like every other Playbook report, uses a common table expression. Think of a common table expression like a temporary table that a subsequent query can reference. Modify the common table expression to reference your schema and run it. The next step is to share it with coworkers and start talking about what the data means for upcoming decisions.

The magic of this common table expression and the standardized Segment event stream is that this report will work whether you’re analyzing messages sent, photos shared, orders placed—anything. It can also work with mobile apps: Replace the pages table with the screens table, and the properties.title column with the name column.

If you’d like to use more explicit events other than page or screen views, you can combine Segment events together into a single table using the UNION function in Redshift. As long as the events table defined here has a user_id column, and event_name column, and an occurred_at column, the rest of the report just works.

You can also explore other aspects of retention and user behavior in the seven other Playbooks.

Sometimes Simple Queries Are Best.

You don’t always need a fancy interactive chart to answer someone’s question—and dashboards often lead to requests for underlying data. So, we advocate starting with simple queries that get to the heart of your questions. Let’s say the Product Manager in the example above is curious how message volume changed since a feature launch. It just takes a quick query to find out:

Create a simple line chart and share the report out with stakeholders. They’ll be able to refresh the results any time.

Polish Up Your SQL Skills. Your 2015 Self Will Thank You.

We developed the Playbook to get you and your company on the fast track to being more data-driven, inspiring deeper exploration of your data with SQL. It’s easy to get started with SQL, especially if you’re familiar with Excel. We created a free, interactive tutorial called SQL School, so you can dive right into learning SQL or brush up your skills.

We’re excited to help you find insights in your Segment SQL data. You can sign up for Segment SQL here and for Mode here.

To learn more about how we seamlessly integrate with Segment SQL and have helped customers like Munchery get up-and-running quickly, mosey on over to Mode.

Harry Glaser on November 17th 2014

We welcome Harry Glaser, CEO of our SQL partner Periscope, to the Segment blog! Harry’s talking cross-database joins on the heels of our Amazon Redshiftlaunch. If you want to analyze behavioral data across platforms, and Excel won’t cut it, here are some tips to level-up your analytics game.

All The King’s Databases

It began with the best of intentions: You launched your first web app for your customers, backed by a database full of transactional data to analyze. In time you added a read replica, and replaced Excel with an more-advanced visualization tool to go with it.

Now you’re launching your first mobile app. You want SQL access to the underlying data store, but building a server to receive pings is much too difficult. So you make great use of a fabulous event-tracking to SQL solution.

But now your data is in two places. What if you want to know whether your iOS users are big spenders? You’d need to slice monthly iOS users in your mobile app database by payment plan information in your web app database. Luckily, there is a solution: cross-database joins.

Cross-Database Joins

You need to connect your transactional, web, and mobile in one table. To start, Let’s count our iPhone MAUs (monthy active users), with Segment’s SQL schema as an example.

We’re counting a user as active in a given month if they’ve started a session in that month. This query gives us a graph like this:

Now, we just need to bring our payment plans into the chart. This is where the magic happens. We’ll join in the users table on our web database, and slice the query by users.payment_plan:

Note that we now need to fully qualify the tables in the FROM and JOIN clauses with their database names: segment and web_prod.

And our hard work pays off! Here we can see our iPhone MAUs sliced by payment plan:

How It Works

Cross-database joins, and in the case of Periscope – our query speeds, are enabled by our Postgres-based data cache. Each customer’s data is stored in the same database, with one schema per (database, schema) pair. This architecture allows us to run exactly the query you wrote, with some simple rewrites to make it valid.

Here’s the rewritten query:

In this example, your Segment database’s iphone_production schema is translated to the db_1234_iphone_production schema in Periscope’s data cache. And web_prod‘s (unspecified) public schema is translated to the db_1235_public schema. The rest of the query remains the same!

Start Exploring

We hope you enjoyed this lesson in cross-data base joins. If you have any thoughts or questions, reach out to us on Twitter @PeriscopeData or hit up friends@segment.com. We’d love to discuss.

We’re also offering a 30 day trial for Segment Redshift customers. To get started, swing on over to the Segment Redshift access page and then sign up for Periscope.

Diana Smith on September 5th 2014

Last week, we announced new support for popular ecommerce platforms including Goodsie, a stylish store builder with neat customers like Church of MerchThe Boomcase, and Strolby. We sat down with Jonathan Marcus, founder and CEO of Goodsie, and Jeremy Mora, founder and CEO of Church of Merch, to learn more about how merchants are using Segment on the Goodsie platform.

Segment: Let’s start with the basics. What is Goodsie?

Jonathan: Goodsie provides modern ecommerce software for small and medium size retailers. Our real-time design system is drag-and-drop, modular and can be easily customized by people of all skill levels. We enable anyone to build an Internet Retailer Top 500 level ecommerce presence without the technical overhead associated with other ecommerce platforms. We also have a multi-store white label ecommerce platform for companies like Church of Merch who host multiple stores for different customers.

Segment: And that brings us to Church of Merch. Could you tell us about your business?

Jeremy: We provide merchandise services (product production, fulfillment, ecommerce and tour support) to many of the world’s leading EDM artists like Dada Life, Zedd, Krewella and lots of other popular musicians such as Beck and Phoenix. We use Goodsie as a platform to build all of our stores.

Segment: That’s awesome! We’ve got a lot of fans of those bands around here, so we’re amped y’all are using Segment. Jonathan, how does Segment work on the Goodsie platform?

Jonathan: Segment provides our customers with access to a vast array of the best-in-class third-party analytics and marketing services like Olark (live chat), Optimizely (A/B testing), Mixpanel (real-time analytics), and 100+ others. And, they do this without requiring any technical integration, which tightly aligns with our code-free product positioning.

Segment: That’s a good point! Our ecommerce plugins make Segment available to store owners with zero code for the first time. Jeremy, what are the benefits of code-free integration in your opinion?

Jeremy: We are currently using Segment to connect with CrazyEgg for heat-mapping and Olark for live chat. Soon, we would like to add Mixpanel for real-time analytics and Optimizely for A/B testing. Segment allows us to turn all of these services on instantly and without any technical work! Having on-demand, technical free access to all of these best-in-class services allows us to become more sophisticated with analytics, optimization and marketing, which translates into more sales and a smarter process for the musicians we work with.

Thanks again to Goodsie and Church of Merch for chatting with us! To learn more about our options for ecommerce, click here or sign up today.

Diana Smith on September 2nd 2014

Last week we announced new ecommerce plugins for online merchants to integrate analytics and marketing tools with zero code. Here’s a conversation with our platform partner at WooCommerce, Joel Bronkowski. He’s given us the inside scoop on WooCommerce, the Segment plugin, and why WooThemes follows the model build, measure, learn. Read on to learn more!

Segment: Tell us a little bit about WooCommerce.

Joel: WooCommerce is the world’s most popular ecommerce platform. Powered by WordPress and built by WooThemes, the goal of WooCommerce is to allow you to sell anything online - beautifully. You can integrate with payment processors, easily manage shipping methods and inventory, set up flexible tax rules, and view detailed store reports all from your WordPress dashboard.

Segment: What are a few of your favorite customer stores?

Joel: I’m glad you asked this! Trolling through WooCommerce sites and seeing all the amazing ways our platform is being used is one of my favorite things to do. Some of my favorites are Porter & YorkHatcherySanta Monica Pier and Pedego.

Segment: Why would these kinds of stores want to use Segment’s WooCommerce plugin?

Joel: Segment enables WooCommerce store owners to easily pick which customer data or triggers they want to track, all through an easy and automated process. Via the WooCommerce Segment extension by Extensionworks, customers are then able use Segment to send that data to advertising, analytics and email tools.

Segment: What can your customers do with the right analytics and marketing tools?

Joel: Within the ecommerce space understanding your customer behavior and audience is extremely key. Analytics and marketing tools can help merchants learn about their user base behavior and then take action based on that data. Let’s take WooThemes for an example.

The concept of build, measure and learn was somewhat new when I came to WooThemes, but it has since become an integral part of what we do. As much as possible we try to understand our customer needs and behavior, and then base business decisions on this information. Data drives most of our decisions at WooThemes, and in the instances where we take chances, we always try to learn from the data following any experiment.

Segment: The idea of build, measure, learn seems like a great strategy for WooThemes. In your personal role, do you use any metrics to measure your success?

Joel: My role is mainly focused on forming new relationships with companies we have a WooCommerce integration with or companies we are interested in working with. Sometimes it’s hard to measure the value of a relationship, but it always feels good to see new products hitting the market or to see a special offer go out to our customers. I’d like to think that a large part of my role is making WooCommerce and WooThemes look more attractive by working with only the best ecommerce and WordPress services. We are always looking to provide new valuable offerings and tools to our users. It’s always a huge win when we can create partnerships where the customer wins (by saving money), the service partner wins by acquiring new users, and we win by generating revenue.

Segment: Sounds like a winning trifacta. We’re glad we made the cut!

Thanks again to Joel from WooThemes and WooCommerce for taking the time to chat with us. To learn more about how to boost sales with ecommerce analytics, click here or sign up today.

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