In this Research NXT Interview, David Raab, the founder of the Customer Data Platform Institute, who is also a marketing technology expert, an independent consultant and author of many articles on marketing tech and analytics talks about how AI and CDP together can unlock the infinite possibilities for Marketers in the present era. He emphasizes how AI can empower marketers by aligning tech, data, and creativity to deliver personalized customer experience at scale. Additionally, at the end of our discussion, David shares his willingness to know how much AI marketers think they are using versus what they are using.
Key takeaways from this Research NXT interview:
- Role of CDP in an AI-enabled Marketing
- How AI is evolving to take up more specialized roles in marketing
- And, the edge marketers get with AI-powered marketing automation
Here are some extracts from the insightful conversation we had with David Raab
Research NXT: How have things transformed in the Martech space so far, and how is AI taking over now? And what kind of changes can we expect soon?
David: AI has undoubtedly had a significant impact on marketing and technology; however, I don’t think it has taken over. We see an evolution in AI from performing narrow tasks like predictive modelling to taking up more specialized applications that to need string together multiple tasks and take over more of a coordination and management role. AI in today’s context has evolved towards managing the entire customer journey and not just one instance at a time. AI-enabled marketing systems will eventually decide and orchestrate the whole customer communications process independently and in an optimized manner at scale. So we are seeing AI creep up the ladder of complexity and take over more complicated and coordinated tasks, much like human counterparts.
Research NXT: What is a real CDP and how does it complement an AI-enabled environment?
David: The point of the RealCDP program is to establish a universal standard for all systems that call themselves CDPs so that customers across the globe could have a defined set of expectations from them. Everyone has an intuitive understanding of what a CDP is; however, it’s not well articulated clearly, so all systems who call themselves CDP do not meet those expectations. The fundamental purpose of the Real CDP program is to help people make the CDP buying decision more confidently.
The actual requirement of a true CDP is that it should be able to intake data from all sources, store that data indefinitely, present the data in unified customer profiles, and it should also be able to share the data with all the systems. This is a basic set of requirements for CDP, which systems like a DMP or CRM don’t provide in one way or the other. A true CDP should have all these capabilities, even if it’s through an API or if it requires manual entry by the vendor or the user to expose the data to other systems. The reason these requirements should be in place is that people should get the CDP to do what they implemented the CDP to do.
Research NXT: What are the top AI in marketing use cases wherein CDP would contribute?
David: The most important thing with AI is the data it is trained on, and the core role of a CDP is to assemble all that data and make it available in a format that it is suitable for the application so that AI can work on it. Hence, any AI in marketing use cases would benefit from a CDP. In terms of specific use cases, we have seen predictive modelling and campaign designing most commonly . In terms of Chatbots, CDP is useful where customer data is used to benefit the call centre. Agents take the next best option recommendations powered by AI.
Research NXT: What should be the trigger for an organization starting to consider a CDP for themselves and how should they go about while evaluating a CDP?
David: CDP is ideally for an organization of considerable size. They are usually for mid-tier or enterprise companies where there is enough data and complexity and enough resources to take advantage of the CDP. In terms of industries, initially, it was primarily in retail and in online media where you have a lot of frequent small transactions per customer, where there are many recommendations to be made. In scenarios like this, it is easy to measure the value added by a CDP. More recently, we are seeing CDPs being used pretty much everywhere, like services, transportation, hospitality, and beginning to see it in education and telecom too. Another benefit of CDP, apart from the financial benefit, is enhanced CX through personalization at scale. And since every customer today has high expectations, CDP is useful across industries, across company size, and business models.
Research NXT: At what phase of an organization should they be starting to implement AI for marketing?
David: In my opinion, AI is productized, and simplified AI is already in use across organizations. I don’t think AI to be implemented needs an organization to reach a particular stage of maturity level. It doesn’t mean organizations need to create AI from scratch, as more of the strategic systems like CRM and Marketing Automation already have some AI embedded in them. I think everybody has access to AI, and they can take advantage of it without being very technically adept.
It doesn’t mean that marketers should blindly trust AI. They should check out what the AI is good at and how it should be applied appropriately so that the data they need is there, and could be reasonably used.
Research NXT: How was your recent experience in India while you collaborated with Netcore to host the CDP Workshop? What did you sense about the current progress of MarTech in India while you interacted with marketing leaders here?
David: I like India. India is a complicated space with a lot of smart and educated people. The challenge of doing business in India is very different from other places. A vast section of consumers in India has access to mobile connectivity irrespective of their economic background, and it’s fascinating. We do see great technologies in India; we see companies having a lot of different use cases. For example, one use case was that of a bank that had a hard time figuring out the financial status of its customers as the data was not readily available, unlike in the USA, where it’s pretty easy to access. So before anything else, customer data needs to be in place for technology to act upon it.
Research NXT: As a Marketer, what should there be in a checklist while evaluating or upgrading the systems to a CDP?
David: I think marketers need to understand their situation and create their checklist based on what use cases they care about. They will also need to identify what specific requirements they have from a CDP. Is it just the customer data, or do they also wish the CDP to do the analytics and also run the marketing campaigns. Some CDPs do that and some don’t. They will also need to choose which channels for outbound should the CDP support if they want the CDP to deliver pretty much what Netcore does. The choice depends on a high level on what scope of CDP functions the buyer wants in their particular situation. Realtime recommendation function is another function should be considered. If it’s needed, buyers need to understand how the CDP makes these recommendations.
Research NXT: And finally, what is the one question that you would like to ask Marketers across the world about AI?
David: There are many but what comes to my mind currently is to know: How many of the marketing systems that they use has AI capability built-in? I am curious to see the answers, and it would be great to compare it to reality. It would be interesting to see how much AI marketers think they are using versus what they are using.