This cross-channel marketing piece is the first installment of our “Connected Marketing Stack” playbook.
In The 7 Habits of Highly Effective People, Stephen Covey popularized what’s become known as the Eisenhower Matrix. It’s comprised of four quadrants based on relative Urgency and Importance.
Marketers can generally agree that integrating data is important, as it will unlock higher quality insights and analytics, and create better brand experiences. Yet, some see it as a second-quadrant priority, that is to say, Important but not Urgent.
Here’s four reasons why connected marketing data — and the modern, API-led infrastructure that’s needed to support cross-channel marketing efforts — can’t wait any longer, and is worthy of first-quadrant attention:
The marketing stack is only getting more fragmented
According to a recent Gartner survey (Gartner subscription required) the average large company had 22 cross-channel marketing technology platforms/tools in their stack, and 8 more in the process of being deployed. The Big Five (Google, Adobe, Salesforce, Oracle & IBM) diversified marketing technology providers account for only about a third of all these deployments, according to Gartner’s research; while that’s a lot of data, it’s certainly not all of it.
What’s more, one of the key findings of the latest Digital Marketing Hub Magic Quadrant research was this: of all the end users surveyed, “88% reported integrations with at least one hub product other than the one by which they were referred.” Meaning that no matter which of the Big Five cross-channel marketing providers you may work with, large companies still need to have a multi-vendor data integration strategy if they want to create a single customer view.
Mobile and TV apps have created lots of new requirements
The widespread penetration of mobile and OTT apps on platforms like iOS, tvOS, Android, and Roku have put new demands on customer data infrastructure. These include:
- New types of data. There are now entirely new categories of data that don’t fit naturally into the “who, what, where” paradigm of the web era. For example, mobile has introduced push tokens, eWallets, device telemetry and geospatial information, to name a few of the new types not easily handled by legacy data warehouses. At the same time, apps utilize new types of identifiers, making web-era proxies (like web browser cookies) less relevant than ever.
- The need for speed. Because many apps fulfill in-the-moment needs, it’s no longer sufficient to sync data daily, as was the norm for DMPs during the web era. For example, you may need to send users notifications based on certain behaviors or contextual cues, such as when they are in or near a particular store. That moment does not last long, so marketers need to be able to respond faster than ever.
- New data collection challenges. App data collection generally happens point-to-point by writing software code on a per app and per OS basis. Without a proper data infrastructure, you essentially need a separate SDK for each and every tool in your marketing stack. That’s a lot of code that skilled developers need to write, maintain and release; and a lot to ask of your end users, having them constantly download updates on their ends. Even worse, companies are sending some of their most sensitive and critical data (including a user’s device ID and location) to multiple endpoints with little governance, which is only asking for trouble. Modern data infrastructure will address a lot of these challenges and more.
The rate of change is accelerating
Technology change and new innovations have always been a factor in marketing, but the rate of change is accelerating. As Scott Brinker has noted, the number of new platforms and tools being adopted is only increasing over the next few years with continued capital investment and an explosion of innovations around VR, AR, IoT, and conversational interfaces (to name a few).
Flexible, API-led infrastructure would allow them to change tools and try out new capabilities quickly, without consuming lengthy engineering cycles each time.
Consumers are demanding more, and accepting of less
Finally, and perhaps more important, to enable the type of seamless, device-hopping experience that users now expect, marketers need a modern data infrastructure capable of delivering them.
A Wunderman study notes how 87% of people now compare their experiences with a brand — any brand — against the likes of Netflix, Uber, and Amazon. At the most basic levels, these users expect instant load times and personalized functionality, and without the right data foundations, it’s very easy to end up with a tangled web of integrations that slow down the experience, crash the apps, and precludes the ability to do any meaningful level of personalization, especially across devices.
Furthermore, Forrester notes how in the “age of the customer” marketers’ scope of responsibility now extends way beyond media channels, and even beyond digital ones, to everywhere a consumer can experience a brand. This trend has created increased interest in hybrid sales/marketing, product/marketing, and marketing/support data flows (with mobile often serving as the experience hub across all of these, even the offline one). Cross-channel marketing will never be able to see this level of connectivity come to fruition in marketers’ lifetimes without building the proper IT foundations to support it.
When it comes to breaking down their data silos, marketers need to act quickly and decisively. The problem’s not getting any easier and it can’t wait.
David Spitz is CMO of mParticle. Follow him on Twitter (@david_spitz). Ready to get started? Check out the next installment in the series: Mastering the Marketing Data Fundamentals.