This sponsored post is produced by mParticle.
For many years now, advertising technology and marketing technology have been two sibling disciplines unable to communicate. The methods and tools for managing data for advertising technology (adtech) purposes have been quite separate from the methods and tools of doing similarly for marketing technology (martech) purposes.
In many cases, that separation was intentional and for good reason — for example, to address privacy concerns in a browser-centric world. However, as everything shifts to mobile, and adtech and martech collide, it’s now imperative that there be strong communication between the two. The question is, where does one start? Before answering that, let’s take a step back and look at how we got here.
Mobile makes everything personal
The impact of mobile on both ad- and mar-tech in the last few years can hardly be overstated. Cookies have been eradicated on many devices, and many of the most popular mobile apps now allow marketers to personalize messages based on user’s emails, anonymous ad IDs, and other more persistent identifiers.
Messages that once felt spooky on the web (wait, how did this random website know I was searching for that thing yesterday?!) are now seen as the respectful and hyper-efficient way of relating with people in a highly relationship-driven, time- and space- constrained environment (thank you, Facebook app, for helping me re-discover this product or app I was interested in without having to search!). It helps, too, that mobile devices are not commonly shared across multiple users, which wasn’t always the case with desktop browsers.
The net result is that, where CRM was once limited to execution channels like email and call centers, marketers can now apply their customer data in more ways than ever. There’s not only Facebook Custom Audiences, but also Twitter Tailored Audiences, Google’s Customer Match and many other services like them.
To take advantage of the opportunity, however, marketers now need to move away from a legacy mindset, which segregated advertising from CRM. They need to adopt an audience-centric approach, in which audience data gets managed holistically, irrespective of its delivery means.
Why unifying data is key to realizing mobile’s true potential
Let’s consider two scenarios where unifying data across martech and adtech is critically important.
First, take a classic CRM use case: delivering a retention message to a high-value customer who’s been showing signs they may have lost interest, or be about to churn. For most businesses these days, your highest value users are the ones most likely to have installed your app. The old way would have been to trigger an email offer but now you can do so much more. For example, you can now send a re-engagement offer on Twitter, say, based on the same sort of triggers that once instigated an email. The targeted mobile ad is particularly important if a user has installed your app but hasn’t been back to it in a while (something which can be specified in the segment criteria definition). You need a joined-up data platform in order to deliver the right message to your customers, be it through email or paid media, so that customers themselves can choose where they’d prefer to interact with you.
Second, consider the case of shopping cart abandonment. Let’s say you have an audience segment of “Users who abandoned a shopping cart worth greater than $100.” You want to reach members of the segment with a reminder message through multiple touch points that could include an email, a Facebook ad, and a mobile push notification, in that order, and all within no more than 48 hours of the cart abandonment. If your first-touch email is successful, then your Facebook ad will be a waste. If your second-touch Facebook ad is successful, then your mobile push notification will be a disjointed customer experience and may lead the user to disable future app notifications. Only a unified “madtech” data platform would be capable of removing people as they exit an audience segment, in real-time, to avoid wasting their time with irrelevant messages.
Enter the converged data platform
Marketing data platforms have come a long way but still have a long way to go. They need to converge on two levels. First, they need to unite insights surrounding what have conventionally been thought of as adtech and martech. Second, they need to converge into a complete solution, across measurement, planning and execution. One without the other is not enough.
Right now, no vendors do all of it equally well.
Most of the platforms that purport to be leading the way in unifying adtech and martech data do so only within a limited scope of use cases. They may focus exclusively on unifying measurement inputs and outputs. Or they may offer planning solutions, such as predictive modeling capabilities, but not the direct connections people need into their marketing and analytics tools of choice.
If you need to choose just one, it’s usually a good idea to start with a data platform that excels at execution. That means ensuring that the right connectors exist for your data to drive meaningful actions across all the various tools and tactics that matter for your business. These could include Google, the enterprise marketing clouds such as Salesforce, Oracle, and Adobe, and social platforms such as Facebook, Twitter, Snapchat, and Pinterest. Likely, it will also include one or more of the next generation mobile-first CRM solutions such as Appboy, LeanPlum, and Urban Airship.
Why start here? One reason is that unifying data for the purpose of planning and measurement is relatively easy compared to the challenge of creating global audience segments, sending them in an executable format into the full range of martech and adtech platforms, and keeping everything neatly in sync, in real-time.
The other is that execution is what allows you to reshape your customer experiences, and demonstrate an immediate ROI on your data platform investments, from day one. Past success with data in the web age is not an indicator of future results in the mobile era. Execution-oriented data platforms, which can drive actions across adtech and martech and produce quick and meaningful results, are the critical next step for advertisers and marketers alike in a madtech world.
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