Large volumes of old, multi-structured, incomplete data can ruin anyone’s CDP appetite
They sat across from me at the large, round breakfast table. It was just us three among the thousands preparing for their day of networking and learning at this tech giant’s summit. And they looked worried.
I have a confession to make. I regularly learn as much at martech conference breakfasts and lunches as I do visiting booths or in sessions. That’s because, in an informal visit over a meal, people tend to open up. I can listen to practitioners who are struggling – those in the trenches doing all they can to make martech investments pay off through achieving common business requirements such as unified customer views, optimized customer journeys, and personalized customer experiences.
My two breakfast mates this sunny morning managed the data team for one of the largest auto manufacturers in the world. They had embarked on a transformation with a state-of-the-art CDP solution two years before yet hadn’t overcome internal hurdles that kept them from going live, much less at the scale they envisioned . They hadn’t generated a single high-impact campaign based on data from the CDP that would resonate with their c-level executives.
When I asked why, they looked overwhelmed. They explained that just for their country alone, they had millions of customer records from decades of service and that their goal was to unify individual records, ensure they were up-to-date, enable recognition, and in the end, be able to drive acquisition and growth campaigns through personalized customer experiences across all touch points. That’s a tall order with the data in various silos, in dozens of disparate structures, and decades-old to boot.
Overwhelmed by a sea of data? Absolutely. But questioning the potential of the big CDP investment. Not at all. In fact, their faces lit up when they talked about all the potential they still believed existed in the platform. That’s when we refilled our coffees and pivoted to fulfilling the CDP promise.
I explained to them that the recipe for CDP data readiness is very straightforward, but to get the most out of it, they needed to start with the end goal – the customer journeys – and work their way back. They needed to:
- Start small and deliver results on a few use cases to show success and establish a quick pace. At the same time making space for bigger and more complex projects on the roadmap.
- Establish key performance indicators (KPIs) and requirements for each of their customer journeys, then catalog and prioritize them
- Identify the martech system integrations, map the workflows, and capture the gaps
- Document the required content types and available content or gaps
- Iterate the roadmap for getting to the required level of data availability
- Map the logical order of execution for journey deployment
- Determine if they have the required people and teams in place and, if not, document the skill gaps and timeline for filling them
- Socialize their plan by publishing a journey catalog, requirements, KPIs, and an executive summary to generate buy-in
- Partner with a trusted customer intelligence provider for cleansed, standardized data enhancement, optimized recognition, personalization, segmentation, and rich, closed-loop analytics to drive constant campaign improvement … always with an eye on data privacy and security in the regions where they operate.
Breakfast was over. The conference organizers were clearing the ballroom and herding us all upstairs for the keynote speech. I thanked my new friends and sent them off with, I trust, a bit of renewed hope and a plan. I’d given them the recipe. Without it, they’d be hard-pressed to get their CDP soufflé to rise, even after years of effort.
For more savory CDP data-readiness recipes, email us at [email protected]
