The Mobile Startup Guide to MarTech: What to Track and Put in Your Stack

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.