More RSG clients are considering the potential for a Customer Data Platform (CDP) in their marketing and engagement stacks, and I can understand why. If you're trying to engage customers and prospects across channels, while leveraging current and future innovations in artificial intelligence, CDP technology might make sense. Just keep these four take-aways in mind as you explore.
1. A CDP can become a key layer in your stack, but not a magic bullet
Marketers use CDPs to better understand, segment, and engage their customers and prospects. But what are you actually going to do with this information?
I know that many of you have very smart, dynamic engagement and management systems at the top of your stack, and you want to fuel them with better, more unified customer data. But have you thought through just how you'll customize experiences and messages for different segments? Do you have a content strategy around this and a team ready to build and manage all the content and experience variants?
2. You need forethought on data models, scope, and priorities
Significant planning, analysis and integration work is required to extract the full value of a CDP implementation. Tasks like developing a data strategy and gaining stakeholder buy-in, defining attributes, and establishing connectors to front end engagement systems. CDPs should simplify the data storage and integration environment, but they won't tell you what to store and where to integrate...
Scope becomes important here. At RSG, we evaluate vendors primarily based on the extent to which they address business use cases. And so our new CDP research assesses whether and how different players cover nine key scenarios.
Nine CDP Scenarios. Source: Real Story Group
3. The CDP marketplace is highly fragmented
You have about two dozen plausible choices here. So cast a wide net initially, focus on specific use cases, and mitigate against vendor/ecosystem immaturity.
If you're considering licensing a customer data platform, you can download a sample vendor evaluation (of IBM's UBX offering), to see how we critique these tools.
4. Try before you buy, even if it's labor lntensive
Employ an agile-oriented selection process featuring adaptive testing. Assemble an interdisciplinary team, including marketing, security, data analytics, and systems specialists. You definitely want to try before you buy. Test the tools, with:
- Real scenarios
- Real data
- Real people
- Real environments
This can be resource intensive but what’s the cost of a failed implementation?
RSG's hard-hitting vendor evaluations provide the real story about when a particular solution might match your needs, or more importantly, where it may fall short.