The digital path to purchase for any potential customer can include a number of different twists and turns including ones leading to dead ends (i.e., no purchase or, just as bad, abandoned shopping carts). Understanding customers and their digital journey has become an important tool for marketers. “Customer journey maps have become a key asset in every marketer’s arsenal,” writes Jake Sorofman (@jakesorofman), a Research Vice President at Gartner, “but I’m here to tell you that, from a customer experience perspective, most of these maps are directions down a blind alley.”[1] He explains:
“With alarming frequency, I see examples of customer journey maps that codify buying stages, but say absolutely nothing about what the customer is trying to achieve. Against this model, marketers layer in programs and tactics to move prospects through a prescribed journey by the equivalent of brute force. Why? Because many marketers conflate customer needs with their own, creating journey maps that are impressively articulate expressions of their own sales and marketing goals, but utterly tone-deaf when it comes to the customer. A slightly better variant is when marketers at least make an effort to channel the customer need state, designing customer journey maps from the perspective of their best guess of customer needs. They may be shooting in the dark, but at least the intention is there. I guess that should count for something. This isn’t meant to be a scathing indictment. I recognize that making sense of the customer journey can feel like solving the riddle of the sphinx. How do you design a customer journey when the data is incomplete, the signals are weak and the patterns are unclear? This stuff is hardly easy. But too often, marketers give up before they’ve even started. They allow this absence of clarity to be overtaken by the presence of their own urgency. And, in doing so, they end up designing journeys, not from the outside-in to fulfill customers’ changing need state, but from the inside-out to fulfill their own commercial interests. Thus, the customer journey becomes the customer gauntlet.”
Marketers would do well to read that paragraph again. Sorofman’s suggestion that customer journeys can only be discovered through outside-in thinking comports with Lora Cecere’s belief that all supply chain thinking should be outside-in. Cecere (@lcecere), founder of Supply Chain Insights, writes, “I strongly believe leaders must build their supply chains with new building blocks. While traditional supply chain processes evolved from functional excellence definitions for source, make and deliver from the inside-out, to make the digital pivot and become more market-driven, companies need to define new supply chain processes outside-in.”[2] That includes marketing. Sorofman adds, “Discovery comes from listening and learning, which requires an open mind, an open heart, a genuine respect for customers and a desire to serve. This requires a certain degree of humility and patience. It also requires data. Discovering the customer journey begins with research and continues with an ongoing process of measurement and optimization. This is hardly a set-it-and-forget-it endeavor.” Unstated but understood is the fact that the data must be properly analyzed to discover the insights it contains. Because customer data can come from varied sources, both structured and unstructured, I believe cognitive computing capabilities are required to help understand customers and their digital path to purchase. Cognitive computing systems, which I define as a combination of artificial intelligence, advanced mathematics, and natural language processing, can collect, integrate, and analyze a variety of data and can include many more variables than has been previously possible.
Errol van Engelen (@bizzmaxx_eu), a business consultant, notes, “To me, the biggest obstacle is that many companies focus on ‘Big Data’ instead of ‘Smart Data,’ which I would argue is the information that can really transform your business. Data on its own isn’t dynamic. It isn’t smart. It’s static. It takes the right questions and the right insights to make it dynamic. You need to know what to expect of the information you have.”[3] As van Engelen points out, data isn’t smart. What makes it smart data is smart analytics (i.e., the kind of advanced analysis available in cognitive computing systems). Van Engelen continues:
“Marketing analytics is rapidly evolving past a single-channel and campaign view to encompass the entire customer engagement with the organization. Customer Journey analytics attempt to understand how individuals and customer segments interact across channels and over time. The practice is phased around the activities of gathering, connecting, visualizing and acting on data, often collected on an individual level.”
As more and more data becomes available, the need for artificial intelligence will also grow. Like Sorofman and Cecere, van Engelen sees an outside-in approach as necessary to really know and understand your customers. “The second common area of Customer Experience analysis,” he writes, “is ‘voice of the customer’ and refers to the tools and techniques used to gather information about customer opinions, attitudes and emotions. Voice of customer analytics differs from Customer Journey analytics and other forms of marketing analytics in their emphasis on mental states rather than behaviors — on customers’ thoughts, rather than their actions. Marketing organizations use this type of analysis for reputation management, competitive intelligence and managing products.” Voice of the customer analytics is difficult because mental states can be elusive. Social media is often the best source of data for this kind of analytics. Because social media is primarily text-based, natural language processing is essential to make sense of it. I call this semantic intelligence.
Most interaction with social media originates on a mobile platform (primarily smartphones). The staff at eMarketer notes that mobile technologies affect both the digital path to purchase and the behavior of potential customers. “As mobile usage becomes ubiquitous,’ the staff writes, “the path to purchase is becoming less defined. Shoppers are always connected, well-informed and often quick to convert both digitally and in-store. The traditional shopping phases still exist, but once smartphones are introduced, behavior shifts. … Overall, mobile is having a striking effect on shopping behavior in all settings, and it is no longer the sole province of out-and-about smartphone users or those buying inexpensive products or services in short windows of time. What consumers want is changing and retailers are having to keep up.”[4] The article stresses that customers are looking for “a seamless experience across mobile and desktop. … A subpar experience would be unwelcome during any phase of shopping.”
Sorofman concludes, “What’s important to remember is that customer journeys aren’t created; they’re discovered. When we try to create journeys, we fall into one of these two traps: we either hallucinate customer needs or throw away the customer experience playbook altogether and focus on the needs we know intimately: our own.” Cognitive computing systems can help with both discovery of the customer digital path to purchase and the customer experience.
Footnotes
[1] Jake Sorofman, “Customer Journeys Are Discovered, Not Created,” Gartner for Marketing Leaders, 5 May 2016.
[2] Lora Cecere, “Building Outside-In Processes,” Beet Fusion, 8 April 2016.
[3] Errol van Engelen, “Why You Need To Use Smart Data To Improve Customer Experience,” Datafloq, 27 March 2016.
[4] “Mobile is replacing desktop as the primary means of online access in the home,” eMarketer, 2 May 2014.
