Presented by mParticle
Elite professional athletes know the importance of mastering the fundamentals. Even the greatest football teams spend the majority of their time practicing blocking, tackling, and ball handling way before they start thinking about running trick plays.
Digital marketers, on the other hand, are notorious for their fondness for quick hacks, silver bullets, and shiny objects. One might argue that it’s been a useful evolutionary trait, as it encourages frequent testing and experimentation with all the latest platforms and tools.
But, when it comes to data infrastructure, they need to get a lot more disciplined. Remember, even Facebook changed their motto from “Move fast and break things” to “Move fast with stable infrastructure.” Digital marketers will never be able to move as quickly as they’d like without investing deliberately and methodically into building the proper data foundation.
The hierarchy of marketing data platform needs
When most people think about the digital marketing foundations they think about the central elements of what Gartner describes as “digital marketing hubs”. These would include companies such as Adobe, Oracle, and Salesforce, among others who bring together a combination of data infrastructure, analytics, and execution.
In addition to offering analytics and engagement applications, these systems, notes Gartner, promise to coordinate all the data within their “clouds” around four key pillars: (1) workflow and collaboration, (2) master audience profile management, (3) intelligent orchestration, and (4) unified measurement and optimization. Thus, these are commonly considered to be the foundational elements of the modern marketing stack.
What’s often overlooked, however, even as foundational infrastructure, is that these pillars presuppose two things: data connectivity and data control. Without them, everything else is dead on arrival.
The big hubs do offer data connectivity and control services, to the extent that the data captured relates to their product suites. And while that’s a lot of relevant data, it’s certainly not a complete approach. According to the most recent Magic Quadrant survey, 80 percent of hub customers surveyed report using multiple vendors rather than going “all in” with a single one.
What’s more, as others have noted, the number of new platforms and tools being adopted is only going to increase over the next several years with continued capital investment, an explosion of innovations around VR, AR, IoT, and conversational interfaces (to name a few), along with a growing demand for hybrid sales/marketing, product/marketing, and marketing/support initiatives.
Marketers who lack a unified, connected approach to data are like a sports team that hasn’t mastered the fundamentals. They may get lucky and score some quick points, but it’s not sustainable or repeatable. For marketers this comes in the form of:
- Disjointed customer experiences, particularly multi-screen ones
- ROI measurement challenges
- New initiatives being stalled as engineering cycles get consumed by “whack-a-mole” maintenance efforts
- Advanced analytics being thwarted as data scientists spend inordinate time trying to compile and combine data sets, rather than analyze them
- Predictive algorithms and AI that have little business value because they are not connected to execution
What good fundamentals look like
How do you ensure clean, connected data in a world where data is being generated on and off property and resides in multiple internal and external systems? It all starts with having a good API strategy.
The good news, for marketers, is most modern platforms and tools already offer APIs to consume and expose data. The bad news is that they do not all do it in the same way or equally well; essentially there are no standards. The reason is that they only care about the subset of data that’s relevant for powering their respective service. Based on these limitations, you can see why these disparate APIs are necessary components of the stack but not sufficient to providing the foundation for proper customer data infrastructure.
5 key attributes to master your connectivity layer
- Collectively exhaustive: Your connectivity layer should be “fit for purpose” for powering your entire stack, not just a component of it. Many digital marketing hubs built for CRM and web execution lack the means to collect the full spectrum of app data from mobile and connected devices, putting the onus on the organization to figure that part out. Conversely, many best-in-breed mobile solutions are deficient in other areas, such as data ingesting data from the mainstream marketing cloud providers and/or data warehouses. A good connectivity layer needs to support all the data types you require to power all the tools in your stack.
- Low maintenance: Your connectivity layer should eliminate, or at least minimize significantly, the overhead associated with maintaining third-party APIs. Because as APIs change, which they often do, you will need to update your systems, you want to ensure that those changes are a) well telegraphed and also b) don’t create any downstream challenges. This is particularly true of APIs that rely on mobile app SDKs since they will require an app store update pushed to all your end users’ devices. That’s why, whenever possible, you’ll want to opt for a single point of data collection and an abstracted approach to data connections.
- Open: Your connectivity layer should be partner and channel agnostic. It should be able to expose any and all data you need from it to everywhere you need that data to go. This also means that its API endpoints should be well documented so that developers can write to them should there be a need to add services that are not already configured.
- Flexible: Your connectivity layer should be able to “translate” in order to support all of the various schemas utilized by each of the endpoints across your marketing stack. For example, data may need to be mapped to meet a certain vendors’ fixed taxonomies or data models. Or, while some systems may accept a real-time stream, others may impose throttling limited such that you may need to batch data to them. Your data platform must be flexible enough to accommodate these requirements from all relevant “consuming” APIs.
- Secure: Your connectivity layers needs to be secure and reliable from end to end. This is not a trivial point, as data leakage is real. Data must be encrypted along the entire data journey, from when it’s collected to when it’s at rest to when it’s transmitted downstream. There should also be live monitoring capabilities to troubleshoot bugs before they become an issue, error alerting so problems don’t stay hidden for long, and the ability to “replay” backup data at any point, if necessary.
A connectivity layer with these 5 attributes is the modern marketer’s equivalent of blocking, tackling and ball handling. Once you’ve achieved a certain level you can you can start layering on other “skills” (like data cleansing, segmentation, identity resolution, analytics, personalization, AI) and trick plays.
Although even then, you should never stop practicing these fundamentals.
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