Analytics and the Digital Path to Purchase
Consumers are increasingly using the digital path to purchase as they shop for goods and services. That means, among other things, consumers are generating enormous amounts of data that can be used by marketers to understand purchasing behaviors. Analysts from the Boston Consulting Group (BCG) note, “Digital marketing presents a tremendous opportunity to engage consumers, but precious few companies have realized its full potential.” The BCG analysts admit lack of success doesn’t mean lack of effort. They admit companies are trying. “In the US, spending on digital advertising in 2017 is on track to surpass spending on television advertising. Globally, certain markets devote more than 40% of their media advertising budget to digital marketing, according to media company Magna. But supersizing the digital-marketing budget is not enough.”
Big Data and the Digital Path to Purchase
The digital path to purchase has numerous on-ramps and off-ramps. Chris Matty (@versiumceo), CEO and a co-founder of Versium, observes, “As consumers become more digitally connected, their buying journeys are becoming increasingly complex: The path to purchase is no longer a linear funnel; rather, it’s a circuitous journey that continues long after the transaction has been completed.” Consumers can use the on-ramps — desktop PCs, tablets, or smartphones — to search for products, compare prices, or respond to offers. Each of these activities generates data that can be mined for insights. Data — ginormous amounts of it — are generated every day by consumers; and, marketers need to know how best to use this data in order to better meet consumer demands. As Martin Kihn (@martykihn), a Research Vice President at Gartner, writes, “Big Data is a big reality.” He defines Big Data this way: “Big Data is data that is so big it won’t fit on a single machine. It has to be spread over many machines. And it can come from anywhere, so it might be in strange and exotic formats. And it’s coming fast. These ideas of size, road speed and formats are captured in the often-quoted concept of the ‘three V’s’: volume, velocity and variety.” He goes to explain the basics of Big Data and the ecosystem that supports it. If you want to learn more, I recommend following the link in the footnotes. BCG analysts note that Big Data is one of the three forces leading companies are capitalizing on to fundamentally change the way marketing can be done. Those forces are:
- Access to large quantities of real-time data to inform their campaigns
- Ability to engage in long-term, omnichannel relationships with consumers (as opposed to one-way, scattershot interactions)
- Flexibility to deploy multiple concepts and gather real-time feedback from customers
Matty asserts you can combine those forces into what he calls the consumer lifecycle. He explains, “Today’s consumers have more touch points with more brands than ever before; and so, to capture and retain their business, marketers must have a deep understanding of consumers and their intentions at every stage of the customer lifecycle.” Marketers can only gain “a deep understanding of consumers and their intentions” by analyzing the data they generate.
Analytics and the Digital Path to Purchase
“Customers’ increased digital engagement with brands has also allowed organizations to amass more customer data,” Matty writes, “creating the opportunity to glean actionable customer insights through predictive analytics, a form of advanced analytics that uses both new and historical data to forecast future activity, behavior, and trends.” As President and CEO of a cognitive computing firm, you won’t be surprised to learn I predict cognitive computing platforms will eventually dominate marketing analytics. Cognitive computing platforms can gather, integrate, and analyze both structured and unstructured data — an absolute essential in today’s data-rich environment. Once marketers learn to appreciate all of the capabilities embedded in cognitive computing platforms, they’ll wonder how they ever got along without them. The fundamental capability, as Matty notes, is the ability to perform advanced analytics. He continues:
“Predictive analytics has become much more prominent over the past few years as organizations look to harness their data: Gartner estimates that by 2020 predictive and prescriptive analytics will attract 40% of enterprises’ net new investment in business intelligence (BI) and analytics. Today’s marketers should apply predictive analytics at every stage of the customer journey, from raising awareness, to educating prospects, to completing the transaction, to enhancing customer service and beyond. Doing so will help marketers anticipate their customers’ needs and desires at every moment, so that they personalize engagement with each customer.”
Another reason cognitive computing platforms will prove invaluable to marketers is they learn as they work. BCG analysts assert, “Consumer behavior is changing fast.” A cognitive computing platform is more likely to discover changing trends on the consumer digital path to purchase than its human counterparts. Although that may sound like I’m setting up a man versus machine scenario, I’m not. I’m a big believer in human/machine collaboration and marketing is a prime candidate for such collaboration. As Kihn notes, “Big Data is no substitute for Big Ideas.” BCG analysts underscore the importance of having big ideas by noting:
“Consumers are … more digitally savvy and increasingly impatient with traditional marketing techniques and intrusive or irrelevant content and messages. More than 25% of all smartphone users have installed ad blockers, according to eMarketer, and that figure is climbing rapidly. When selecting new products and services, consumers rely more than ever on advocacy from people they know and trust. Personal recommendations are now five times more trusted than brand marketing, according to the Word of Mouth Marketing Association. … Innovators have brought new advertising technologies into the marketplace, allowing for much more personalized and targeted advertising. New ad properties that allow for video insertion are rapidly replacing flat display ads. Specific ads can now be targeted at a particular audience or type of consumer. Data and analytics encourage test-and-learn experimentation and ad purchasing through automated platforms and auctions. All told, personalized advertising could constitute 80% of digital marketing budgets within three to five years (and will increasingly penetrate traditional media as well).”
Without the capabilities embedded in cognitive computing platforms, marketers are unlikely to achieve the type of personalization discussed above.
As the digital path to purchase increases in importance, digital marketing also increases in importance. BCG analysts note, “For decades, marketing has been organized around the slow world of TV and print ads, which requires lengthy creative processes, months of fine-tuning, and much uncertainty regarding market feedback. Modern marketing capitalizes on the inherent flexibility of digital to reduce time and expense and increase efficacy.” They add, “To fully benefit from [the advantages of digital marketing], most companies will require a fundamental reboot in their strategy, organization, and ways of working.” I suggest they invest in a good cognitive computing platform. Such a platform can help companies transform to meet the challenges of the digital age.
 Marc Schuuring, Diederik Vismans, Nicolas De Bellefonds, Steve Knox, Jody Visser, and Marty Smits, “The Digital Marketing Revolution Has Only Just Begun,” Boston Consulting Group, 10 May 2017.
 Chris Matty, “How to Use Predictive Analytics to Engage Customers Throughout Their Journey,” MarketingProfs, 28 July 2017.
 Martin Kihn, “What Marketers Should Know About Big Data,” Gartner for Marketers Blog, 27 October 2015.