Today, we stand at a crossroads in digital transformation and innovation, and many business leaders may be asking themselves “what’s next?” when it comes to key technological investment in the near future. The demand for meaningful business insights has shaped the technological landscape for decades, driving innovation in collecting more data, the systems to store and process it, and then the skills and methods to transform it into meaningful information, for the actionable insights that drive business outcomes.
The next stage in this evolution is the “Relevance Transformation,” based on creating individualized interactions at every touchpoint throughout a digital experience. Individualization has become a driving force behind digital innovation across every industry, and business executives should be considering how best to harness the opportunities this will create to fuel business growth. Central to this demand for an individual experience is being relevant.
Bridging the Gaps to Bring Data Together
Right now businesses are collecting exponentially-growing volumes of signals about the interactions people have with them digitally: what customers are clicking on when landing on a web site, how long they visit a particular product page on an e-store, which external websites they visited en route, and what they ended up doing — converting to a customer, abandoning a cart, or nothing at all… However, many organizations are struggling to leverage this signal data to its full potential.
As businesses have expanded the variety of touchpoints with which they can engage customers, they have created a proliferation of systems across the customer-facing experience, each of which is locking up interaction data in their own silo. This core problem means that while these organizations may have terabytes of signal data accumulating, the value of that data is not being realized because the sum total of each person’s interactions is not being unified to present a meaningful digital footprint, or profile, of each customer, each prospect, or each employee.
Business leaders’ challenge is to bring all this signal data together in a synergistic, unified way, and put it to work, to convert prospects, delight customers and empower employees, ultimately, to affect the bottom line. At the same time, companies need to be able to deliver the most appropriate content to each individual, at those points of interaction. Content like product information, customer review, user-generated videos and more. Individual tailoring of content based on the sum total of interactions, in real-time, at scale, requires a helping hand from the CIO.
The AI Solution: Relevance Transformation
Business leaders are beginning to realize their need for unified systems that can process signals about every interaction for every individual and generate meaningful results in real time. In the past two years, searches for “Artificial Intelligence” have increased sharply, demonstrating the growing interest in using AI — specifically Machine Learning — to sift through volumes of data to extract actionable business insights. If Artificial Intelligence is the answer to the question of what type of technology is driving innovation today, then relevance transformation is the answer to the how. Unifying signal data across every interaction to enable a more complete view of individual customer behaviors, and to compare it with those of all customers, is key to unlocking the true potential of a business’s data.
Another element of relevance transformation is automating the process to do it at scale, at a lower cost, and delivering a unique experience to each person. Scalable cloud-based computing power on demand has enabled businesses to automatically create and manage millions of individual profiles based on specific signals from each user. That same compute power applied to machine learning models, enables recommendations to be tailored precisely to each user. This ensures he or she receives the most relevant content at every touchpoint in a transaction, across multiple systems. The more an individual uses the system the more signals the AI can incorporate into personalization. This works both on an individual level and in the aggregate; the more people use the system the more data available for Machine Learning to work on, making it better at recognizing and delivering accurately on a particular pattern, even for new users.
To remain competitive, business executives need to take a critical look at their operations and evaluate how much relevant signal data is simply falling through the cracks. Every non-relevant digital transaction translates to a lost potential opportunity, and a nudge towards a competitor. On the other hand, what would your business look like in a world where every customer had customized, relevant content instantly recommended whenever they engaged with you? How could customer experiences be improved by implementing relevance-driven insight engines? The answers to these questions will determine the laggards and the leaders in the next wave of innovation and digital transformation.
Businesses are realizing that the defining feature of whether their communications will be effective or not comes down to relevance: how well organizations can orchestrate the customer experience across a variety of different systems, yet deliver individualized, seamless experiences at every touchpoint in a digital transaction in a way that is relevant for every person, at every interaction point. Effective deployment of AI unifies those customer interactions to ensure effortless, personalized experiences on an individual level. Investment in this technology now demonstrably impacts a business’s user experiences, customer retention, conversion, and bottom line, and will determine the winners or losers in tomorrow’s insight-driven business landscape.