Big Data and the Revolution in Marketing

Posted on the 06 March 2013 by Stephendeangelis @EnterraCEO

"Driving analytics against big-data is causing marketers to rethink what they do from the ground up," writes Kim Davis. In fact, Davis believes that big data is fomenting a revolution in marketing. ["Big-Data Drives a Marketing Revolution," Internet Evolution, 18 February 2013] Davis argues that "marketers, from the CMO down, need to change in order to deal with a 'highly instrumented, highly connected, highly intelligent world economy.'" He asserts that even in a sector roiled by revolution, there are three fundamental marketing principles that need to be kept in mind. They are:

  • Know your customer.
  • Know what to market, and how to market it.
  • Protect the brand promise.

Davis writes, "Essentially, these principles survive in a data-driven economy, but each is transformed by contact with analytics." That is especially true when it comes to getting to know your customer. Davis explains:

"Firstly, customers are no longer a faceless mass, the behavior of which can be more or less predicted and understood using classic market segmentation techniques. Online activity, not least over mobile channels, has made behavior so transparent that consumers emerge as individuals, demanding a specifically tailored commerce experience. Secondly, analytics allows us to systematize engagement across multiple channels -- from call centers to apps -- so as to maximize the value for the consumer at every point of contact. Thirdly, the benefits -- and risks -- of social media provide ample motivation for brand and culture to be authentically one. In other words, an organization's culture should be such that it's organically represented by all employees engaging with real and potential markets over social channels. Brand value can live or die in the global, social conversation. Predictive analytics can point the way to the next offer, the next action, and the next customer need, in a way that feels more like providing a service than marketing a product."

Targeted marketing all about providing "a specifically tailored commerce experience." In the era of big data, getting to know your customer requires good analysis. That's why Davis insists that buying the right "IT is no longer a cost, but a strategic investment." He concludes, "Marketers, armed with this view of customers as integrated individuals, are actually well armed to decide which customers they ultimately want. Beyond that ... they can begin to think about what they want their customers to become." Marketers know that the Pareto Principle is alive and well in the business sector (i.e., 80% of your sales come from 20% of your clients). Big data analytics can help adjust those percentages by helping identify potential high value customers.

Davis' colleague, Rich Luciano, insists, "Putting the customer in the driver's seat can actually provide a market advantage. ... It's good for the customer, too." ["Analytics: The Cornerstone for a Smarter Commerce Strategy," Internet Evolution, 5 December 2012] Luciano explains:

"The global conversation taking place on social media platforms, together with the ready access to those platforms afforded by the explosion in use of mobile devices, has transformed the relationship between business and consumer. In the first place, consumers are empowered by the extraordinary amount of product information available. Furthermore, in sharing and responding to this information, consumers are creating data packed with insights. When companies use business analytics tools to extract nuggets of usable information from this consumer data, it's the consumer who ultimately benefits through an improved commercial experience."

Luciano writes, "A good business analytics solution should place data directly in the hands of decision-makers." What he really means is that a good business analytics solution should place actionable insights (or intelligence) into the hands of decision-makers. Data and insights are not the same thing; but, Luciano knows that. He continues:

"One way this can be achieved is by integrating data from multiple sources and channeling clear, reliable information to accessible dashboards or reports. Arming employees with the information they need rewards businesses with increased revenues and reduced operating costs. Perhaps more importantly, it benefits customers by offering them the products their input has helped define, delivered in the way they prefer, and with after-sales service to which they best respond."

The key to targeted marketing, Luciano insists, is "getting a grip on the data." He concludes, "Business analytics is no longer something nice to have. It's the cornerstone of a strategy that will not only increase ... competitiveness, ... but improve the commerce experience for customers as well." In some circles, this is called "shopper marketing." According to Wikipedia, shopper marketing is "understanding how one's target consumers behave as shoppers, in different channels and formats, and leveraging this intelligence to the benefit of all stakeholders, defined as brands, consumers, retailers and shoppers." Hayden Sutherland believes that online and in-store consumer marketing efforts need to be more coordinated if shopper marketing is going to achieve good results. ["Multi-channel retail meets Shopper Marketing," Press 2.0, 20 February 2013] In order to achieve these results, Sutherland believes online and in-store marketing disciplines must come together to:

  • Understand the roles that in-store and online now have
  • Map the Paths to Purchase (both Digital to Store and Store to Digital)
  • Grow customer loyalty and retain existing customers

He concludes, "In short, multi-channel retail/eCommerce and shopper marketing now need to merge into a single area of specialisation ... Multi-channel shopper marketing." One store that has done well merging retail and eCommerce channels is Macy's. Its MOM initiative (My Macy's localization, Omnichannel, and MAGIC selling strategy) has resulted in more satisfied customers and increased sales. ["Macy's Loves MOM, And Consumers Do Too," by Walter Loeb, Forbes, 27 February 2013] Loeb briefly explains the MOM strategy:

"For more than three years the company has worked on specific localization – 'My Macy's – which focuses on having each store feature merchandise that is relevant to customers who live and shop in that area. ... The customer has responded enthusiastically to the My Macy’s strategy. The Omnichannel strategy allows for extraordinary service to customers. In addition to warehouse fulfillment of purchases from in-store, on-line or mail order customers, Macy’s now has 292 stores that participate in the fulfillment of orders – to insure that the customer receives better service as purchases are delivered quicker than ever before. By the end of the year management expects to have about 500 stores participating in this program. Magic selling is the third key initiative. Through new training tools, associates are taught how to be more engaged with the customers and how to be more empowered so that they can make decisions on the selling floor. It is an important step ensuring more caring and responsive customer service."

Nichole Kelly, President of Social Media Explorer and SME Digital, believes that shopper behavior no longer conforms to the sales funnel theory that hypothesizes "someone comes into the top of the funnel and sales fall out the bottom." ["The Death of the Sales Funnel as We Know It," Social Media Explorer, 19 February 2013] She continues:

"Is that true in today's world? Do we start at the top and make our way through to the end? Or do we start at the top, leave, jump levels, come back, leave again, come back at the beginning and at some point come back and buy? Are we following a linear purchase pattern or an erratic path of engagement that sometimes results in a purchase? I think the assumption that any large percentage of buyers follow a pre-determined path to a sale online is incorrect."

Kelly agrees with Sutherland that online and in-store activities need to come together to get a true picture of a consumer's path to conversion. "It is extremely difficult to track the true path to sale," she writes, "when there are only online components. Throw in offline components and you're toast. ... If we truly want to understand this erratic ride our buyers are taking us on we should be demanding that tools start to keep track of EVERY touch point, at least online. ... Progress before perfection should be your new motto. Start getting better data with what you have now, but we should always be working towards perfection." She concludes:

"At the end of the day there are 'core' points in every sales process that most buyers go through. They may fall in and out of the funnel at various stages, but we still can focus our efforts on optimizing the path from one stage to the next, understanding we are simply modeling a process not the reality of the buyer’s progress. But I think a new model is needed and it doesn’t look like a funnel. Rather it looks like an illustration of the interworking of a neural network. ... This could illustrate where we are leading the buyer and the various paths a buyer could take to get there. It shows that the path to purchase is no longer linear; it is a network of touch points, decision points, and opportunities that are either taken or declined by the buyer. If we could track this it seems reasonable to assume that certain paths and certain conversions would glow brighter as they are working more effectively than others. It could also show the black hole where potential buyers go and never return. Could we then optimize our efforts to put others down that path over less effective paths? Honestly, I don’t know. But I will tell you, if I can figure out how to model this with real data in a way that can be analyzed I’ll be the first to try. For now, I’ll continue to use a model that people recognize understanding the flaws it holds, while I try to build a new model for the future."

I believe Kelly is correct that a new sales model is coming and that it will look a lot more like a neural network than a linear path or funnel. The key to success in digital path to purchase will be making the right offer at the right time to a consumer who just happens to be in a shopping mood. Sometimes consumers are pursuing a specific item and sometimes, as Kelly writes, they "still make purchases and purchase inquiries on a whim." Targeted marketing needs to make the most of both opportunities.