How to assemble a best in class tech stack

While choosing the right messaging platform is critical, how you integrate it into your business is a bigger indicator of your ability to drive innovation and impact. Last month at MAU, I moderated a panel that discussed the use of machine learning in messaging. Given the amount of interest in this topic, I thought I’d take the time to delve deeper into the topic by sharing some integrations that will empower your team to start running some truly innovative messaging campaigns.

First things first: if your goal is to prioritize broader CRM efforts over mobile messaging, then you’ll want to skip ahead and focus on integrating your data warehouse. However, if your goal is to build a robust mobile messaging campaign, one of the first things you’ll want to do is add the SDK to your website and mobile app(s). Not only will this enable you to send in-app, web and push notifications,  it will also allow you to create cohorts based on front-end user behavior and tie downstream engagement and performance to specific campaigns.

Unless your engineers love SDK integrations, I’d highly suggest utilizing a Customer Data Platform, or CDP. Once the CDP is implemented, it functions as the single SDK on the front-end, using its own backend to distribute data to other platforms that need it. For example, in this instance we’d directly integrate a CDP into our website and apps, then “activate” our messaging tool through that. Not only does this save your engineering team a lot of time and energy, but it also reduces your marketing team’s dependence, giving them more flexibility to implement the latest technology.

The right setup can take your marketing team’s ability to be data-driven to a whole new level, and it starts with your data warehouse. Connecting your messaging platform with your data warehouse will enable you to receive more precise transactional data in instances where you might lack visibility on the front-end, like actions that occur across channels—even those that take place offline. For example, let’s say you’re hoping to further engage your brick-and-mortar customers by sending them a confirmation email after they’ve made a purchase at a physical store. You wouldn’t want to trust front-end analytics with a task such as this, but the backend integration will get all this data in for a nice, timely message once the sale has gone through.

While your data warehouse should always be the ultimate source of truth, it probably isn’t intuitive enough for many members of your product or marketing teams to utilize—this is where third-party analytics tools come into play. By integrating your messaging platform with a product analytics tool, you’ll empower your marketing team to conduct the impact analysis themselves without having to rely upon a data scientist.