We've been talking about Adaptive Intelligence (AI) for a while now. As a refresher, AI is is the real-time, multidirectional sharing of data to derive contextually appropriate, authoritative knowledge that helps maximize business value.
Increasingly in inquiries, workshops, FLB sessions, and advisories, we hear from our customer insights (CI) clients that developing the capabilities required for adaptive intelligence would actually help them solve a lot of other problems, too. For example:
A systematic data innovation approach encourages knowledge sharing throughout the organization, reduces data acquisition redundancies, and brings energy and creativity to the CI practice.
A good handle on data origin kickstarts your marketing organization's big data process by providing a well-audited foundation to build upon.
Better data governance and data controls improve your privacy and security practices by ensuring cross-functional adoption of the same set of standards and processes.
Better data structure puts more data in the hands of analysts and decision-makers, in the moment and within the systems of need (eg, campaign management tools, content management systems, customer service portals, and more).
More data interoperability enables channel-agnostic customer recognition, and the ability to ingest novel forms of data -- like preference, wearables data, and many more -- that can vastly improve your ability to deliver great customer experiences.
As digital marketers, we know the importance of tracking, measuring, understanding, and meeting customers’ expectations at their preferred interaction points. We have convinced our budget masters of digital intelligence’s importance to the business as a whole and our spend on digital measurement and marketing technologies continues to increase—exciting vendors and enticing new ones to continually improve products.
But despite this increased investment in technologies, the same stubborn problem remains: different teams are working with siloed data sets while failing to understand and delight the customer across a variety of digital touch points. Why? Because while technology has provided the pieces for digital marketing, these pieces have not come together to deliver completed suites. Achieving this suite goal requires more than just an investment in technology; it requires a considerable effort and a strategy supported by executives that:
Recognizes the multi-channel digital customer experiences firms wish to project using customer insights
Realigns teams and processes to for better cross functional cooperation
Builds skills set and focuses more investment in staff and partnership
Consumers don’t trust your ads. In fact, fewer than one out of four US online consumers trust offline ads, and the numbers are even worse for digital. It’s time for a new approach to marketing, based on deep customer insights derived from a contextual, self-perpetuating, interaction cycle. Each interaction with your brand teaches you what a customer is trying to accomplish at that moment. You must build a mechanism that allows you to act on that insight, deliver utility in the moment of need, and propel the customer to the next best interaction. We call this mechanism a contextual marketing engine, and our latest research – The Power Of Customer Context – shows you how to build it, and why you need to start now.
We unveiled this new research last week at Forrester’s Forum for Marketing Leaders to an on-site audience of more than 900, and we'll do it again in a few weeks across the pond at our London Forum. What are the key takeaways?