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Nupur Bhade Vilas on October 20th 2021

Meet Twilio Engage: the first growth automation platform designed for the digital era.

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Jes Kirkwood on December 1st 2021

GitHub's VP, Growth Thibault Imbert reveals how the company's growth team drives results in an exclusive interview.

Geoffrey Keating on November 23rd 2021

All I want for Christmas is a customer data platform that makes it through the holidays.

Not your average wish-list headliner, except among infrastructure teams dealing with peak requests that are at least five times greater than the average load.

An outage during any of the peak shopping season events —Thanksgiving, Black Friday, 11/11 in China, Christmas—can easily cost you your festive mood and your company hundreds of thousands to millions of dollars.

At least 48 prominent brands experienced technical problems on 2020's Black Friday. Luckily, you don't have to put your fate in the hands of Santa or anyone else to make your wish come true. You can turn the holidays—and other peaks—into business as usual with proper and timely preparation.

We've put together five peak-season best practices for your data infrastructure that get you ready for some peaceful time off while the business keeps humming along.

1. Know previous peaks and what's changed since

Start preparing by revisiting the data and lessons learned from last year's holidays or another peak event. While historical performance isn't a mirror of the future, it's a helpful starting point for your preparations.

When making your projections, consider industry data like the above chart for the eCommerce sector, which shows and predicts that overall online sales will keep increasing.

These are common characteristics of peak events you should expect to find in your historical data, according to the Google Cloud blog:

  • Traffic increases of 5 to 20 times (or even greater).

  • Higher conversion rates and a more considerable burden on back-end systems—like payment processing—than on the front end.

  • Rapidly increasing traffic in a short period as the event starts.

  • A trailing decline to normal levels that's much slower than the acceleration to the peak level.

Not every business runs into a peak over the holidays—another good reason to check your historical data before acting.

Looking at Segment's data, for example, on average across all our customers, we saw a decrease of 30% in traffic during Thanksgiving. But for those in online retail, we observed surges of up to 1,000% for several hours during peak time.

Once you've collected your historical data, you want to consider what major changes have happened since then. Ask yourself:

  • What systems have we rolled out or refactored significantly?

  • What major features or services have we launched?

  • What new sources of data have we plugged into our data stack?

  • What types of customers, partners, and other vendors have we added or changed?

Note any such changes, especially if you haven't tested them under significant amounts of load. You'll want to pay special attention to these in the subsequent steps of your preparation.

You'll also want to reach out to colleagues in other departments to get their projections for the upcoming peaks. Forecasts for sales revenue, inventory, and shipping, as well as marketing initiatives, will all give you insights into what kind of volume to plan for.

2. Check in with customers and partners

Most people and businesses make plans for the holiday season. Whether you work directly with consumers (B2C) or other businesses (B2B), reach out and learn their plans so you can further improve yours. Also, talk to partners you rely on—like us, Segment, or cloud providers like AWS or Google—so they can make the necessary preparations, too.

In a B2C business, you want to understand how consumer behavior might change compared to last year. Maybe a new type of device is more popular now or a different social media channel. Such changes can affect loads on different areas of your system or require you to collect new data events. You also want to check which product launches, special offers, and other marketing campaigns look like upcoming holiday hits. Short of coordinating research interviews directly with customers—never a bad idea—heading over to the folks in marketing, growth, or research should get you plenty of insights.

For a B2B-focused company, you want to understand what the businesses you serve are planning for their customers. Your customer should be running through a preparation exercise similar to what we're outlining here. Figure out where you can best support them in this process and the kind of numbers they're expecting, and agree on how you'll cooperate over the holidays.

Some of the B2B customers of Segment, all of which we proactively reach out to to support them during the peak seasons.

Make sure to talk to partners you rely on once you've collected this information from your customers. Albert Strasheim, VP, Segment core engineering, says the cloud isn't infinite. Your vendors face the same peak events as you do, and their other customers compete with you for the same cloud resources.

Reach out early to:

  • Check how your partners can support you. They might have documentation on handling peaks, template configurations for their products or services, and dedicated support teams to take on some of the preparation tasks.

  • Make reservations for the cloud resources you'll need. (More on this later under Create headroom and other buffers, as most but not all cloud resources can scale up automatically.)

  • Establish how and with whom you'll communicate leading up to and during the peak event.

Don't forget to check the existing service-level agreements (SLAs) you have in place with vendors and whether the agreed response times suffice.

3. Prepare with tests, game days, and system checks

You can only determine whether your team, partners, and infrastructure are peak-season-ready through tests and games that simulate actual events as closely as possible.

Since you can't measure, test, or prepare for the unknown, you first need to establish which metrics reflect system health and whether you're capturing such data for monitoring.

Image credit

If you had to pick just four such data points, you can't go wrong with Google's Four Golden Signals:

  • Latency: The time it takes a request—like asking a web page to load—to reach the system.

  • Traffic: The total demand on the system, usually measured in requests per second.

  • Errors: The rate of failing requests, either as an absolute number or a proportion of all requests.

  • Saturation: One or more metrics reflecting the utilization of critical system resources, say what percentage of memory the servers are using or the amount of database storage you have available.

You can complement technical health metrics like the ones above by monitoring critical business numbers such as revenue, website traffic, and orders placed. These indicators can also signal potential problems when they show irregularities.

With the numbers to monitor identified, you'll want to see how different aspects of your data infrastructure hold up under a large volume of simulated requests—load testing.

You want to test the entire customer journey—not just individual elements—under such pressure, so you'll see what the customer experience will be like. Make sure to try several load mixes, like mobile versus desktop, various transaction types, or traffic coming from different regions. These test variations can all reveal particular weaknesses in your system.

You'll also want to check whether spikes in traffic don't set off automated defensive mechanisms in your system that mistake the holiday surge for an attack or other security breach.

While load tests reveal how a system responds to peak traffic, game days show how your teams respond. You'll want to think through potential failures during the holidays and then stage those situations to see where your operational procedures or knowledge are insufficient. Depending on the stakes and your team's size, you might want to run several of these and even include outside vendors.

You could, for example, simulate that one of your primary methods of payment stops working because of an outage at your payment processor. Such a simulation will reveal which teams need to get involved—did anyone think of the added load on customer support such an outage will cause?—and whether you’ve established effective lines of communication with a third party like your payment processor.

4. Create headroom and other buffers

You'll want to create buffers in your system because your earlier plans and test results are estimates—reality can always turn out differently.

At Segment, we look at vital infrastructure components like Kafka, a data event streaming platform, and DynamoDB, a NoSQL database service, to ensure they have headroom—additional space above the peak traffic we expect.

You need to do such checks on all critical pieces of your tech stack. As much as possible, you want to create headroom and other buffers in your system through auto-scaling: the automatic expanding and shrinking of storage, memory, and other resources as traffic goes up or down.

You can configure many modern cloud services like AWS and Google for such auto-scaling. Yet, these processes might not keep up with rapid, five- to tenfold traffic increases. Under such circumstances, manual scaling might still be the most reliable solution. Discuss your plans and projections with your partners to determine which parts of your system can auto-scale and which elements need reservations and manual operation.

Amazon Kinesis is an advanced data product that helps customers analyze their video and data streams in real time. (Screenshot from the Kinesis explainer video.)

A typical issue we see with Segment customers is scaling Kinesis data, which provides real-time insights on video and data streams. It's not impossible to configure auto-scaling for Kinesis, but it's not straightforward either and often overlooked during peak season preparations.

A final, important buffer you want to create is a change freeze across your infrastructure leading up to and during peak events. Changes in one part of a system can trigger unexpected events elsewhere and render all of your preparations useless. At a minimum, such a change freeze should apply to releasing new or updated features. Typically, you want to extend it to the scope of marketing activities and third-party services integrated with or connected to your system.

5. Ensure focus and clarity during the peak event

When you've done all the preparations we've run through, a peak day can unfold much like a regular one. But some folks will have to work or be on call on days they'd rather be home, no matter how much prep work you put in, and they'd better know what to do in case something does go wrong.

You want to establish well in advance the exact responsibilities of each team and which individuals take on which shifts. Do such planning before the festive season starts and spread the burden of working on events such as Thanksgiving, Christmas, and perhaps New Year's evenly across team members.

Make sure to carefully review your standard on-call and incident procedures and see what changes you need to make for peak season by asking questions such as:

  • Are alerts set up for every critical metric you identified earlier?

  • To whom does the first alert go? Who is the fallback if that alert goes unanswered or unnoticed? What are the required response times for different types of alerts?

  • What's the first action someone should take for a specific alert? What happens when the initial procedure, template, or checklist doesn't solve the problem?

  • What does escalation look like? Under what circumstances and how can someone reach the engineering management team or even executives?

Don't just think about internal procedures and contacts when answering such questions. Consider which incidents need third-party involvement and include their contact persons and details in your plans. Segment's support team, for example, have coverage plans in place during holidays, and have team members standing by should a significant issue occur.

Most incidents are manageable if they get detected and handled anywhere between minutes and an hour or two. Albert Strasheim, VP, Segment core engineering, sees customers run into trouble when there's no automated alerting and noticing something is wrong takes more than a few hours.

You can avoid such problems by having virtual or in-office dashboards with your critical metrics and alerts displayed in real time. You might want to create a war room—physical or virtual—for larger operations, where people from all relevant teams work together synchronously and communication is instant.

Get next year's holiday gift ready now

That's the best part of the holiday season: you can be pretty sure the same events will be on the calendar again next year. All the effort you put in now increases the chances of your wishes coming through this holiday season and the one after.

Jes Kirkwood on November 22nd 2021

Zendesk's Director, Product Growth & Monetization Mona Nasiri reveals how the company's growth team drives results in an exclusive interview.

Geoffrey Keating on November 19th 2021

Tray.io uses Segment to calculate a user score that predicts retention. Here's how they built it.

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.

Guest author: Dan McGaw on November 1st 2021

I've watched thousands of startups build, grow, and optimize their tech stacks. Throughout the years, and while implementing Segment, teams have asked me the same questions time and time again.

  1. Which events should we track?

  2. What about metrics and customer data?

The answers are consequential; I've seen too many promising startups with great products fail due to fixable logistical issues and insufficient resources. That's why we’re collaborating with Segment’s Startup Program to give you this take on the tools, metrics, and user events crucial for success: this time for ecommerce companies.

The Added Value of a Solid Ecommerce Stack 

The nature of ecommerce necessitates a speedy tech stack to seamlessly collect user data, transmit it to the relevant destination, and respond to customer activity in real-time. The complete customer journey and closed reporting loop that will provide a stable framework from which you can scale your business.

As your business grows, you'll use your tech stack to further refine and optimize your practices, now armed with historical data that covers the full customer journey. From here, you'll find and grow the lifetime value of your customers, allowing you to optimize your customer acquisition for actual ROI and ROAS. You’ll also have what it takes to improve drop-off rates, or automate communication throughout the touchpoints.

Ultimately, you’ll be able to snowball the revenue.

Ecommerce Events to Track

So, which events are most relevant to ecommerce startups? 

You want to focus on the customer journey and cover its full range. Cover the various stages in the purchase flow. Pay attention to the following interactions:

  • Product Viewed: Occurs when a user visits a product page.

  • Product Added: Whenever a visitor adds a product to their shopping cart.

  • Checkout Started: Once a visitor adds a product and clicks the “checkout” button.

  • Checkout Step Completed: After a visitor adds a product, clicks the “checkout” button, enters their payment information, and moves onto the final stage of checkout..

  • Order Completed: Once a visitor completes entering all their information for purchase and reaches the thank you screen.

Top Ecommerce Metrics: How a Stack Helps Measure What Matters

As a part of transactional sites, e-commerce pages are focused on converting visitors into customers and first-time customers into repeat customers. The metrics most valuable to you will be those that uncover subtle shopping behavior, connecting your customer's average purchase spend with their repurchase rate, lifetime value, and finally, to your sales totals.

Visit to Order Rate

The percentage of visits that convert into orders. The metric helps you answer “What makes the customers purchase the first time?”

Average Order Value (AOV)

The averaged total value of every order placed on a store over a specified period. The metric helps you answer “What makes the customers spend more?” or “Which campaign leads to the highest purchases?”

Total Revenue & Orders 

Shows the revenue you've earned across all channels and orders placed. This is often the KPI for ecommerce marketing. The metric helps you answer “Which products are our 80-20?” or “What are the main movers of our top-line revenue?”.

Customer Lifetime Value (CVL)

The total value in dollars the customer will contribute over a lifetime. Lifetime is usually calculated between 12 and 24 months. The metric helps you answer “What is the real value of the customer we acquired?”

CLV takes reporting from immediate to real value. Lifetime value is often a lot higher than immediate value. Also, when one channel, campaign or product stands out in immediate value, it doesn’t necessarily stand out in lifetime value.

Repurchase Rate & Frequency

Another valuable metric that measures repeat purchases. Repurchase rate and frequency are calculated by dividing the number of customers who made at least two purchases in a given timeframe by the total customer count. 

One of your most actionable metrics in ecommerce is your repeat purchase rate. You can measure it with the help of your order completed event, and tying it to the customer whose journey you follow. Then you’ll build out a funnel to see what channels and products drive repeat purchases. So the metric will help answer “What makes our customers come back?”

Use Cases of Integrations for Ecommerce Growth

By combining the power and utility of different MarTech tools, you expand the capabilities of each. That’s how you use a stack to improve or scale ecommerce revenue. Let’s walk through examples.

Add Customer.io Email Events to Customer Journeys

Email events from platforms such as Customer.io often do not make it to user analytics or data warehouses. That’s a huge missed opportunity for personalization or touchpoint automation. Segment translates  event data from your email platform and passes it on to tools such as BigQuery and Amplitude.

You can then follow the full customer journey, optimize based on events such as Email Delivered / Opened / Clicked / Unsubscribe, or create complete reporting about your email flows.

Report on Javascript Data Sources

Javascript is the standard language for analytics. Along with the biggest tools such as Google Analytics or Tag Manager, and many others, you’ll see javascript in custom attribution models. The models often populate data that’s hard to integrate exactly because it is custom, and doesn’t always follow the formats required by your favorite reporting tools. This can make reporting much less insightful.

With Segment, you can translate your custom attribution data and taxonomy into a format that’s understood by a data warehouse such as BigQuery. From there, you can easily send it to a reporting tool such as Chartio or PopSQL. Think data such as page and identity tables, the common attribution data points. You’ll be on your way to a closed reporting loop, with accurate and complete ROAS insights.

Calculate the Full Customer Acquisition Cost

Just like with the above-mentioned ability to translate custom javascript to the rest of your MarTech stack, Segment plays the Rosettta Stone of APIs for your ad platforms. Segment will pull data from Facebook Ads, Google Ads, and other ad marketplaces, then push it into your BigQuery data warehouse. You’ll be able to get the full picture of how the different ads push the customers down the funnel, and you can also add data about interactions such as checkout events.

As a result, you’ll be able to send complete acquisition data into a reporting tool such as Chartio or PopSQL. There, you can, for example, build models for calculating key metrics such as CAC (Customer Acquisition Cost).

Power and Automate Custom Messaging

In MarTech stacks based on Segment, you can have the same tool receive or send data. Customer.io is an example. Above, we had an example of Customer.io sitting upstream, so it could send data for use in customer journey analytics. Here, Customer.io sits downstream, receiving data from a javascript source.

Segment can even send your JS data to multiple communication platforms at a time. So e.g. Customer.io for emails and Drift for chat and text messages. This way, all of your messaging can be both custom and automated based on events or custom user traits. User events like shopping cart abandonment, newsletters signups, and purchases can help segment the customers. You’ll be able to automatically trigger personalized email sends, push notifications, or SMS messages. Or you’ll be able to make your chat bot much more personal and useful.

Follow Product-level Activity

Amplitude is a popular analytics platform that's grown in popularity thanks to its depth, predictive and personalization capabilities, and automated optimization features. When enriched with clean, normalized data, users can optimize across the entire customer journey, improve user acquisition, uncover purchase behavior patterns, and connect product-level data with revenue.

However, imagine your user data is tied up in a JS source such as Google Analytics. So we’ll once again connect Segment and have it feed data into Amplitude. This links Order Completed, an event from Segment’s ecommerce spec, with the Product Purchased event in Amplitude. You could also do that for events such as Product Viewed, or Added to Cart. You’ll then be able to slice revenue data by product, product category, or SKU.

Your Visual Reference of Ecommerce Tool Integrations

The diagrams you see above come from our infographic with examples and explanations of ecommerce stacks integrated through Segment. Get your own pdf below for future use, so you can quickly scan it and remind yourself of ideas for your own stack.

Download your copy of the ecommerce stack infographic.

Join the Segment Startup Program, Build a Strong Stack, Grow Your Ecommerce Business

Segment's Startup Program is here to give early-stage startups the tools necessary to build stacks like this and thrive. Eligible startups get $25k in Segment credits for up to two years, which can be used for Segment’s Team Plan. Additionally, Segment is throwing in over $1 million in free marketing and analytics platforms like Amplitude and Amazon Web Services, on top of a number of heavy software discounts. You’ll even get access to level-up resources such as Segment’s Analytics Academy or Analytics office hours.

Eligible startups must have been incorporated less than two years ago and have raised no greater than $5 million in total funding.

Don’t wait any longer, go learn more about Segment’s one-of-a-kind Startup Program. And if you’d like a hand picking your tools along the way, feel free to use our WYSIWYG MarTech stack builder.

About the Author

Dan McGaw is the founder of McGaw.io, MarTech speaker, and co-founder of analytics tools such as UTM.io. He’s worked extensively with Segment implementations and led the creation of tools such as the Segment CSV importer.

Guest author: Dan McGaw on October 29th 2021

In my many years managing MarTech implementations, I receive two questions more than any other: 

1. Which user events are worth tracking?

2. Which marketing metrics should I collect?

The answer depends on a range of factors. First and foremost, your business model. Mobile marketers face a unique user base with a low tolerance for apps that don't meet high expectations for functionality and reliability. That's why we’re collaborating with Segment’s Startup Program to give you this take on the tools, metrics, and user events crucial for success.

The Added Value of a Solid Mobile Stack

I have a hard time imagining a successful app developer that reliably makes and scales quality apps without the feedback, performance improvements, and added functionality that tech stacks provide. Doing without means making do with guesswork. Maybe it will work, but maybe it won’t.

Mobile purchase cycles leave developers only a moment to hook users. That requires swift and prompt action to attract and retain users by intervening in crucial moments to improve their customer experience.

As a mobile app creator, you need your tech stack to capture a much wider array of user data, and respond to user activity and needs in a way that keeps them engaged, creates beneficial functionality, and fixes any technical stumbling blocks. 

Top User Events to Track

Which user events are most actionable in the analytics of mobile startups? Those that track the part of the journey from app install to first order.

  • Application Installed: Triggered after users first download your app or upon opening it via their home screen.

  • Install Attributed: Credits the right marketing channel for delivering new users.

  • User Created: This middle-funnel event occurs after users install and once they register an account with your service. It identifies active users.

  • [Feature Used]: Triggered whenever users launch a feature of your choice. This can be cross-referenced with retention data to uncover the stickiest features. 

  • Order Completed: Tracks when users make in-app purchases and contribute to your revenue. 

Top Mobile Metrics—How a Stack Helps Measure What Matters

Tracking the key mobile events will generate actionable metrics for you. To spend your effort where it can make a difference in a predictable way, focus on the revenue metric. Then break it down to the steps that bring your users closer to revenue.

Revenue

Track revenue just the way you need—subscription-based or ecommerce. Slice it by DAU (daily average users) or MAU (monthly average users), or marketing channel. The Order Completed event is what connects the dots for you here.

Install to Signup Rate

The install-to-signup-rate metric, also called the activation rate, puts your app's onboarding process under a microscope. It helps you answer the question “How many of the users who install the app actually start using it, too?” The magic is done by relating the Application Installed and User Created events.

Your job is to find where and how users get confused or otherwise discouraged before registration. You may also want to look into which channel or campaign brought the engaged users.

Signup to Pay Rate

This metric picks up where our last metric left off, answering “How often do new users become paying customers?” It extrapolates the User Created and Order Completed events. By extension, it tells you about how well your user activation strategy is doing.

Compare across marketing channels to identify the most reliable channels for creating real-deal customers. Get granular and analyze cohorts based on their install date or app activity. Or calculate the average cost of converting a visitor to a paid user.

New, Retained & Churned Active Users

These metrics connect retention to user activity, and answer questions such as: “Which features make the users stick?” or “Which features make the users churn?” It does so by relating the Install Attributed and [Feature Used] events to data about DAU. 

Retention and revenue are two sides of the same coin. Get the data that’ll enable you to retain users better, and it’ll make a world of difference to the bottom line.

Use Cases of Integrations for Mobile Growth

The applications you choose for your stack are important, second only to the quality of integrations that hold your stack together. After all, a good stack gives you new tools and expanded capabilities to improve the customer experience.  That’s how you use a stack to improve revenue. Let’s walk through a few examples.

Add Email Events to Customer Journeys

Free the data that would otherwise be siloed in Braze or another messaging platform. You'll use Segment to help pass data about user activity that occurs off app—in email and text. 

Now, events like Email Delivered will flow down to your analytics platform, Amplitude, which can be combined with data from other marketing channels and app activity. The email events will also be sent to your data warehouse, BigQuery, for additional analysis and backup.

The combined data stream also helps you track the full customer journey. The full set of touch points you create with users—whether it’s to engage existing ones, or to convert new ones. This will help you improve and grow your email flows.

Use App Usage Data in Marketing Attribution

Tie in-app user engagement data with your marketing attribution. In the above example, you can do so by extracting the Install Attributed event, created by Appsflyer. Then you’ll translate it in Segment and pass it on to your attribution reports in Amplitude.

Your marketing reporting will level up, letting you compare user engagement across marketing channels or campaigns. You will also put yourself in the position to reveal differences in purchasing behavior and retention.

Load and Model Ad Spend

Get Facebook Ads and Google Ads data to play nice together. The ad spend numbers get piped through Segment, then flow into your visualization and modeling platforms such as Chartio or POPSQL. You can then model and optimize CAC (customer acquisition cost). The two ad platforms will get a fair comparison

As you’ll often want to do, you can also send the data to BigQuery, where it can be processed further.

Personalize and Automate Messaging

Make your messaging matter. So much so that it will be relevant to the user’s location and app usage.

In this use case, Radar collects location-specific events, and connects it with the user’s history. But the data is only valuable when integrated with a platform that acts on it. So you can use Segment to send the location data and user traits to Braze. As a result, your messaging with the users can be both personalized and automated. That’s custom messaging at its best.

You’ll enable interactions such as location-specific deals, geofencing, localized inventories, geotargeting, or store locators.

Your Visual Reference of Ecommerce Tool Integrations

The diagrams we're using in this post come from our infographic, which you can download below for future use.

Download your copy of the mobile stack infographic.

Join the Segment Startup Program, Build a Strong Stack, Grow Your Mobile Business

Our Startup Program is here to give early-stage startups the tools necessary to build stacks like this and thrive. Eligible startups get $25k in Segment credits for up to two years, using Segment’s Team Plan. Additionally, Segment is throwing in over $1 million in free marketing and analytics platforms like Amplitude and Amazon Web Services, on top of a number of heavy software discounts. You’ll even get access to level-up resources such as Segment’s Analytics Academy or Analytics office hours.

Eligible startups must have been incorporated less than two years ago and have raised no greater than $5 million in total funding.

Don’t wait any longer. Go learn more about Segment’s one-of-a-kind Startup Program. And if you’d like a hand picking your tools along the way, feel free to use our WYSIWYG MarTech stack builder.

Learn more about the Segment Startup Program.

About the Author

Dan McGaw is the founder of McGaw.io, MarTech speaker, and co-founder of analytics tools such as UTM.io. He’s worked extensively with Segment implementations and led the creation of tools such as the Segment CSV importer.

Guest author: Dan McGaw on October 28th 2021

As a growth hacker, MarTech founder and implementation consultant, I often get the following questions:

  • Which user events are worth tracking?

  • Which metrics should I use for decision making?

  • How should I build and use my stack to scale?

The answer is different for every business. But for B2C subscription-based business, they need a responsive stack that draws high volumes of prospects and reliably pulls them through their conversion funnels with as little drop-off as possible. 

That's why we’re collaborating with Segment’s Startup Program to give you this take on the tools, metrics, and user events crucial for success.

The Added Value of a Solid B2C Subscription Stack

Getting B2C marketing right means aligning your team members with their responsibility for the purchase cycle, helping them identify and fast-track high-value leads, and ensuring smooth transitions between funnel stages and business functions. 

I have a hard time imagining a B2C subscription company thriving without the responsive infrastructure, digestible user feedback,  event-based data, and added functionality a well-implemented stack brings.

Top B2C Events Your Stack Should Track 

Your stack’s toolset is only as good as its implementation. Also, a good stack gives you new tools and expanded capabilities to improve the customer experience. That’s how you use a stack to improve revenue. Let’s walk through a few examples of the user events that help you get there.

  • Lead Created: Unknown users trigger the Lead Created event by submitting their contact information (and usually other traits).

  • User Created: After leads or visitors create their first login, the User Created event occurs. This means the user has started using your application properly, and is closer to spending money in case that hasn’t happened yet.

  • [Feature Used]: This custom, product-based event can help you determine the relationship between key feature usage and long-term customer value, in addition to retention. Find ways to encourage repeat usage to optimize. Examples include Song Played, Lesson Completed, or Note Created.

  • Order Completed: Users have completed the customer journey by the time they reach Order Completed. This event is often used to track retention, revenue, and conversion rates from free to paid users.

Top B2C Metrics: How a Stack Helps Measure What Matters

Marketers in B2C subscription businesses need a broad view of the customer purchase cycle, with the ability to get granular and tinker with each conversion step. Use metrics to evaluate audiences and identify the best channels for high-volume conversion. 

Visitor-to-Signup Conversion Rate

This metric combines page views with the User Created event and helps users compare marketing channels to identify key audiences. Find a way to move this one a little, and you can see substantial gains in revenue. 

Trial Subscription Conversion Rate

Understand how frequently your visitors become users after sampling your services. By cross-referencing page views and the User Created event, you open up further examination of marketing channels and their varying ability to convert visitors.

New and Total Monthly Recurring Revenue (MRR)

Once users trigger Order Completed, they'll find themselves in this camp, where new and total revenue are tracked. Identify best-contributing channels and product features. Switch between MRR and ARR as you need.

Monthly Churn

Retention is no different from revenue in the subscription model. With the help of a product analytics platform such as Amplitude and the Order Completed event, users can slice monthly revenue by overall retention, engagement, and feature usage to shed light on the levers that make your customer experience stickier. For early-stage startups, the retention may be even more important than revenue.

Use Cases of Integrations for B2C Growth

When you integrate numerous MarTech tools, you not only pool resources, you expand each tool’s functional capacity. Making good use of the ecosystem can help you scale B2C revenue. Below are examples for your inspiration.

Fuel and Automate Personalized Messaging

One of the best features Segment brings to stacks: allowing the same tool to send and receive data. Where other use cases such as the next one in this article see Customer.io sending event signals upstream to Segment, in this instance, we have a custom JavaScript (JS) data source pushing event and user traits to Customer.io.

And since Segment can send JS data to multiple communication platforms at once, we're delivering the same user data to Autopilot and Drift. With Drift, event data can trigger automated and personalized chat and text experiences (designed to qualify and convert users). Once it gets to Autopilot, it's combined with other customer data sources for personalized lead nurturing email campaigns (which are also automated).

Add Customer.io Email Events

By intervening in crucial (context-specific) moments in the customer journey, marketers can improve the customer experience—increasing engagement and avoiding churn.  However, event-based data from communications platforms like Customer.io are frequently disconnected from analytics platforms and marketing automations.

Segment connects event-based triggers from Customer.io with our product analytics platform Amplitude and our data warehouse BigQuery. Now events like Email Clicked can trigger any number of actions, like personalized purchase incentives or assigning users to various cohorts based on their demonstrated level of interest.

Report on JavaScript Data Sources

Custom attribution models use JS to send the data such as Page and Identity tables. But such custom data sources can be hard to sync with your reporting and data exploration tools such as Chartio.

With Segment, you can translate data and consolidate taxonomy, so they live alongside data from other sources in your warehouse and reporting tools. As a result, you can build accurate attribution and calculate your ROAS.

Load Ad Spend & Compare Ad Inventory Performance

Facebook Ads and Google Ads don't play well together, which means you have to be creative in your reporting if you want to show the full picture. Segment comes to the rescue once again. Both ad inventory sources can be loaded into BigQuery. There, you’ll combine the ad spend data with web activity data that’s also piped through Segment.

The infrastructure will unlock new analytics possibilities. You’ll be able to push the combined data into visualization and modeling platforms like Chartio or POPSQL, and build models on key metrics such as Customer Acquisition Cost (CAC).

Your Visual Reference of B2C Subscription Tool Integrations

The diagrams you see above come from our infographic with examples and explanations of B2C subscription stacks integrated through Segment. Get your own pdf below for future use, so you can quickly scan it and remind yourself of ideas for your own stack.

Download your copy of the ecommerce stack infographic.

Join the Segment Startup Program, Build a Strong Stack, Grow Your B2C Subscription Business

Segment's Startup Program is here to give early-stage startups the tools necessary to build stacks like this and thrive. Eligible startups get $25k in Segment credits for up to two years, which can be used for Segment’s Team Plan.

Additionally, Segment is throwing in over $1 million in free marketing and analytics platforms like Amplitude and Amazon Web Services, on top of a number of heavy software discounts. You’ll even get access to level-up resources such as Segment’s Analytics Academy or Analytics office hours.

Eligible startups must have been incorporated less than two years ago and have raised no greater than $5 million in total funding.

Don’t wait any longer. Learn more about Segment’s one-of-a-kind Startup Program. And if you’d like a hand picking your tools along the way, feel free to use our WYSIWYG MarTech stack builder.

About the Author

Dan McGaw is the founder of McGaw.io, MarTech speaker, and co-founder of analytics tools such as UTM.io. He’s worked extensively with Segment implementations and led the creation of tools such as the Segment CSV importer.

Jim Young on October 28th 2021

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