Published on May 11, 2017/Last edited on May 11, 2017/5 min read
We’ve been talking a lot lately about marketing tech stacks—that is, collections of different kinds of software used to execute a given brand’s marketing strategy. But a marketing tech stack doesn’t work unless the different parts (from lifecycle engagement platforms like Appboy to data warehouses and UI/UX testing tools, and more) can communicate with each other. If your brand can’t transfer data between these different layers in real time, you can’t act effectively on the customer information you possess, and that means you can’t create the kinds of seamless, valuable experiences that support strong relationships with your users.
That’s where effective data management comes in.
Data flowing through a marketing technology stack
Think of it like this: Say you want to set up a triggered message that recommends upcoming local concerts whenever a customer travels to a new city. That requires first-party data from your app, a trigger set up through your lifecycle engagement platform, and targeted concert suggestions from your recommendation engine, just to name a few elements. Without proper data management and data export, that information doesn’t flow throughout your stack, doesn’t trigger your messaging (at least not in the way or at the time you wanted it to), doesn’t pull in personalized concert recommendations, and can lead to a missed opportunity—or, even worse, a poor user experience.
These days, it seems every company is looking for that single-customer view—the ability to understand the person behind all the screens. And hey! We don’t blame them. A single customer view makes it possible to interact with your customers in timely, contextual, and relevant ways. On the customer’s side, it makes for personalized messaging that actually enhances their experiences rather than interrupting them. For marketers and brands, it can mean more brand loyalty and more revenue as a result.
How do you get that single customer view? You assemble a collection of tools that can gather the information you need, and then you make sure those tools can tell each other what they find out—in other words, your stack components need to be able to transfer the data they collect throughout the stack for you to be able to act on it effectively. Data management saves the day.
There’s more to the single-customer view than pulling in data from their phone AND their computer. When we say single-customer view, it’s not just purchase history, app-use frequency or typical demographics and psychographics. Those can be great for segmentation, and are a huge part of the view, but a true single-customer view makes it possible to quite literally understand every unique experience that an individual user has with your brand. At this year’s LTR conference, Segment’s Raphael Parker used an anecdote to demonstrate:
You’re a shoe retailer, and you have a user who spent over $100 within the app on five consecutive Friday nights. Then, all of a sudden, they’re gone. So, what happened? Parker suggested, “If the goal is really just looking at what happened in the mobile app, then you’re going to get a missed impression.” He continued, ”If you’re able to then also say, ‘Oh, after their last purchase they sent in a customer support ticket’…and you can uncover that data too, then you have a much better understanding of what’s gone wrong.”
Whether it’s a situation like the one Parker outlines, or even a simple test to see which types of messaging yield higher long-term revenue, being able to understand and access data between your tools at any given time is a key component of an effective marketing strategy.
No two stacks are exactly alike. Every vertical and every brand has their own specific set of needs that should be reflected in their stack’s chosen tools. That said, it’s hard to put together your ideal stack right off the bat—and that’s okay. You may swap out some technology after a contract is up, you may add on new elements like data enrichment tools or deep linking tools, or a number of other changes. Iteration is central to modern marketing, and that goes double for assembling a best-in-class marketing tech stack.
When your data management and data export capabilities are top notch, you have so much more freedom to iterate. By ensuring that your new tools can communicate with the established ones and vice versa, the inevitable growing pains of trying something new are a lot smaller, and the process of building your ideal marketing tech stack can happen that much sooner.
In short, data management helps to collect, organize, and interpret your data so that the different parts of your stack can “talk” to each other more effectively. When you’re able to export that data in real time to these curated tools, you’ve got yourself a genuinely interoperable marketing tech stack.
It’s also worth noting that in the alternative scenario, where you don’t have the ability to manage your data between tools, you create data silos that have to be manually managed by your team members. That means more opportunities for human error, fewer opportunities for true, real-time messaging, and a whole lot more work. And while we’re all about the intersection of humanity and technology… there are some things best left to the computers to handle.
Data management tools are clearly a key component to the ideal marketing tech stack. Be sure to check out about Appboy’s newest product announcements like Currents (currently in beta), our high-volume data export tool that connects directly to other stack properties in real time, allowing you to send your Appboy data to your data warehouse, business intelligence tools, data management solutions, and other technologies—all in an instant.