Choosing the Right Stack

by Eric Kim Solutions Architect @ Segment


Now that we’ve established the what and how of customer data collection, we can move on to the where.

So where will you send your data? It’s not an easy question to answer. At the time of this writing, there are nearly 7,000 marketing technology tools listed in the Marketing Technology Lumascape. Most of these tools are built to help you make sense of and act on your data.

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Needless to say, there’s a lot of noise. Identifying which companies are growing rapidly and which categories are ripe for disruption is no simple task. And with more and more marketing and data tools coming on the market each year, finding the right one can be overwhelming.

In this chapter, we’ll help you navigate this crazy world by breaking down how vendors compare. Let’s get started.

Start with business objectives

Finding the right tech stack for your use case starts with a bit of self-reflection. A helpful mental model to make tool selection more manageable is to group tools by use case or category. While Segment integrates with upwards of 300 tools, many help accomplish similar outcomes. To help simplify things, we like to group tools into categories such as: Analytics, Email Marketing, Advertising, Customer Support, Attribution, and Push Notifications.

You can also prioritize tool selection based on your current initiatives. For example, if you’re looking to convert more free trials into paid customers, perhaps you’ll want to look into a messaging automation tool to surface reasons to go paid. Or maybe you’re looking to get more insights about customers and Google Analytics is not cutting it? You could prioritize an advanced analytics tool.

We find it helpful to ask yourself a few preliminary questions like: What are my business objectives? Where do the majority of customers interact with my brand? What industries do we serve best? What’s the composition of my team (engineers, product, and marketing)?

The general idea is to map your business objectives to a class of tools first, then determine which specific vendor will be best for your specific use case. Below we’ve mapped out some groupings to help you do just that.

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Tools for understanding customers

Without question, the foundational class of tool to better understand your customers is Analytics.

Within this class alone, there are a wide variety of vendors that provide robust user analytics services—things like engagement tracking, funnel or cohort analysis, retention, and journey mapping. Some of the most widely used analytics tools include Google Analytics, Amplitude, Mixpanel, and Adobe Analytics.

A few tips for choosing analytics tools

Start with a list of must-have features If you’ve used analytics tools before, then you will probably have some sense of what features are must-haves, nice-to-haves, and features you never use. When searching, it can be helpful to create a matrix of features that you care about.

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Mobile vs. web

One thing to watch out for, is analytics vendors who started with web analytics and developed mobile SDKs as an afterthought. If you’re a mobilefirst company, then you’ll want to use an analytics tool that was built with mobile in mind. Tools like Mixpanel and Amplitude, for example, were built in the mobile era and support a multitude of mobile SDKs, in-app events, push messages, and more.

Look back to your tracking plan

In the last chapter, we outlined a path for creating a tracking plan. With this tracking plan in hand, you’ll be able to identify tools that can easily support your event tracking requirements. If you don’t have a tracking plan, it’s helpful to first think through questions you’ll need an analytics tool to answer—how are leads converting from one page (or screen) to the next? How do conversion rates compare week over week? Did this UX change impact revenue?

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Tools for communicating with customers

In addition to leveraging an analytics tool to better understand your customers, you’ll likely need a tool to efficiently communicate with them.

Email marketing

The primary method for communicating with customers has traditionally been over email, using an email marketing tool—sometimes referred to as an Email Service Provider (ESP). Although some claim that email is dead, email communications is still used by the vast majority of companies no matter what industry or size.

Recent changes in the ESP landscape have made choosing an email service provider (ESP) less straightforward than it used to be. Some of those trends include the following:

Larger vendors keep acquiring email tools. ExactTarget and Pardot were acquired by Salesforce. Marketo was acquired by Adobe. Oracle acquired Eloqua. And the list goes on and on.

Email tools are opting for less specialization to generate broader appeal. Email providers that were originally geared toward small and mid-sized businesses like Constant Contact and Campaign Monitor moved up-market in an attempt to meet the needs of enterprise companies. Similarly, ESPs that had been primarily transactional auto-response email providers, like Sendgrid, began adding more functionality as they matured.

Up-and-comers have entered and shaken up the market. Some new vendors in the space—many of whom were originally sales tools or mobile marketing platforms—are now trying to expand their offerings and market themselves as ESPs or marketing suite alternatives. These email tools include companies like Customer.io, Drip, Autopilot, and Iterable.

Mobile messaging

If you’re at a mobile-first company, there are many tools that provide you with ways to communicate with customers via SMS or push notifications. Braze, Iterable, and Kahuna are great examples of mobile analytics providers that also offer tools to communicate with your customers across mobile devices via SMS and push notification. It’s also worth noting that many email and mobile messaging tools are merging feature sets. Many companies such as Braze, Iterable, and Customer.io offer support for both email and mobile communications with customers.

Live chat and other messaging

Another way to communicate with users and customers is through a live chat or messaging app. Tools like Intercom and Drift allow go-to-market teams to start a conversation with their users or customers in real time through a live chat plugin that appears within an app or website.

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Tools for acquiring more customers

If a key channel for growth is paid acquisition, then you’ll most likely want to send user data to advertising platforms for use cases like retargeting nonconverted visitors, enhanced audience targeting, and suppressing existing customers.

To make your paid advertising efforts more effective, you can pass first-party user data into ad platforms like Google Ads, Facebook, Twitter, LinkedIn, and other niche platforms. Doing so will allow you to target audiences based on their stage in the buying cycle, familiarity with your brand, and user traits (e.g. industry, job title, geolocation).

You can also pass your first-party customer data into a variety of other nondirect advertising platforms. In Ad Tech, these are referred to as Demand Side Platforms, some of which are Criteo, MediaMath, AppNexus, and AdRoll.

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Tools for delivering a better customer experience

Another category of tools to consider is experience optimization, also commonly referred to as experimentation or A/B testing tools.

These tools offer powerful ways for product and marketing teams to test, learn, and deploy winning digital experiences to engage more users and drive more conversions. Most of these tools also take the custom development and measurement work out of setting up an experiment or personalizing the user experience by surfacing relevant content.

We also like to breakdown experience optimization tools into the following two categories–A/B testing and personalization.

A/B Testing

Optimizely, VWO (Visual Website Optimizer), Google Optimize, Apptimize, and Leanplum are all examples of prominent players in the A/B testing space. Like the analytics tool category, some of these tools were built for mobile-first companies and others for web. When making a selection, we suggest building a table similar to the analytics features matrix above.

Web and In-App Personalization

In addition to running experiments to improve conversion, you can also use tools to deliver a more personalized experience to users. Tools like Appcues, Optimizely, Webengage, and Leanplum allow you to dynamically modify the user experience on your website or app. Personalized experiences can be made via a number of dimensions such as user demographics, product usage, stage in customer lifecycle, etc.

Dig deeper to understand your customers

Data Warehousing is the last category of tools we’ll highlight here. It’s an important one, as a data warehouse is often the source of truth for data at many organizations. You can think of a data warehouse as a home for all of your data. Companies use a data warehouse to aggregate data from a number of different data sources so it’s easy to analyze.

With a data warehouse, you have ultimate flexibility for how you store and later query your data. It helps you answer those tough analytical questions that your board may be asking about that aren’t possible to do with your standard analytics tool.

Data warehouse considerations

You should consider a data warehouse if you want to do the following:

  • Centrally store all of your business-critical data
  • Analyze your web, mobile, CRM, and other applications together in a single place
  • Dive deeper than traditional analytics tools by querying raw data with SQL
  • Provide multiple people access to the same data set simultaneously

If you do decide a data warehouse is necessary for your team’s needs, there are a number of important factors to consider when making a selection:

  • Data types: what type of data you want your warehouse to store
  • Scale: the amount of data you plan to store
  • Performance: how quickly you need your data when you query it
  • Maintenance: how much engineering effort you’re willing and able to dedicate to your warehouse
  • Cost: how much you are willing to spend on your data warehouse
  • Community: how connected your warehouse is to other critical tools and services

Many of the factors listed will directly influence one another, and tradeoffs may be necessary. For example, opting for less scale may decrease performance but will typically be more cost-effective.

For more info about data warehouse selection and considerations, check out our in-depth guide here: How to choose the right data warehouse.

Hopefully, this framework gets the wheels spinning on where to begin with selecting the appropriate tools for your stack.

If you want to go even deeper, we’ve written a seven lesson course that goes into detail on the categories above and other tools for attribution, performance monitoring, and business intelligence. Get started with that course here: Choosing the Right Stack.

Finally, if you want to get a full list of all classes of tools available on Segment, check out our integration catalog here.

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