Targeted Marketing in the Age of Cognitive Computing

Stephen DeAngelis

May 31, 2016

“The future of marketing,” writes Derek Newton (@DerekTNG), “is intensely personal — marketing targeted not just to you, but to where you are and about what you’re doing right this very moment.”[1] Targeted marketing has been around for a few years; however, technologies that power targeted marketing are getting more sophisticated all the time. Newton insists we are rapidly approaching the time when we will see personalized advertising all around us. He elaborates:

“The technology may not be quite ready to scan your eyes and instantly access your entire buying and commercial browsing history. But almost all the data about who you are, where you’ve been, what you’ve bought, what you’ve watched and who you chatted with is already stored somewhere. And that data is increasingly being connected to your smart phone — which ‘knows’ where you are right this second. It may still feel like science fiction but that data to device to you loop is already being deployed in customer service settings.”

Tony Blankemeyer (@tblanx), managing director of the Startups in Residence program for 84.51°, compares consumer use of connected technologies to “show and tell” exercises we all experienced in grade school. “If we look to today’s marketing environment,” he writes, “consumers are showing and telling each and every day. Digital has enabled marketing and technology groups to leverage customer data in order to understand desires and needs to deliver relevance in their lives.”[2] That’s really the point of targeted marketing — providing consumers with information and offers that are personally relevant. Done correctly, targeted marketing creates a win-win situation for everyone involved. Although data is abundant, making sense of that data and using it to provide relevant content and offers requires sophisticated software. A field of artificial intelligence called cognitive computing will likely take center stage in the marketing arena. Cognitive computing systems can provide insights so granular that Murali Nadarajah, Head of Big Data and Analytics for Xchanging calls it creating a “segment of one.”[3] Cognitive computing involves artificial intelligence (including machine learning), advanced mathematics, and natural language processing — and there are differences in the cognitive computing systems currently available. All analytics systems, however, must have data. Louis Columbus (@LouisColumbus) believes there are “hundreds of areas big data and analytics will revolutionize marketing and sales.”[4] He discusses ten uses of big data analytics making a difference today:

1. Differentiating pricing strategies at the customer-product level and optimizing pricing using big data are becoming more achievable. McKinsey found that 75% of a typical company’s revenue comes from its standard products and that 30% of the thousands of pricing decisions companies make every year fail to deliver the best price.” Whenever a large number of variables is involved, like those necessary to optimize pricing, cognitive computing systems outperform older systems and provide better insights.

2. Big data is revolutionizing how companies attain greater customer responsiveness and gain greater customer insights. A Forrester study found that 44% of B2C marketers are using big data and analytics to improve responsiveness to 36% are actively using analytics and data mining to gain greater insights to plan more relationship-driven strategies.” Providing insights is one of the things that cognitive computing systems do best.

3. Customer Analytics (48%), Operational Analytics (21%), Fraud and Compliance (12%) New Product & Service Innovation (10%) and Enterprise Data Warehouse Optimization (10%) are among the most popular big data use cases in sales and marketing. A recent study by DataMeer found customer analytics dominate big data use in sales and marketing departments, supporting the four key strategies of increasing customer acquisition, reducing customer churn, increasing revenue per customer and improving existing products.” Again, cognitive computing excels in all these areas.

4. Supported by Big Data and its affiliated technologies, it’s now possible to embed intelligence into contextual marketing. The marketing platform stack in many companies is growing fast based on evolving customer, sales, service and channel needs not met with existing systems today. As a result, many marketing stacks aren’t completely integrated at the data and process levels. Big data analytics provides the foundation for creating scalable Systems of Insight to help alleviate this problem.” Whenever you see the modifiers “smart” or “intelligent” associated with technology, you can be pretty sure that cognitive computing is involved.

5. Forrester found that big data analytics increases marketers’ ability to get beyond campaign execution and focus on how to make customer relationships more successful. By using big data analytics to define and guide customer development, marketers increase the potential of creating greater customer loyalty and improving customer lifetime.”

6. Optimizing selling strategies and go-to-market plans using geoanalytics are starting to happen in the biopharma industry. McKinsey found that biopharma companies typically spend 20% to 30% of their revenues on selling, general, and administrative [activities]. If these companies could more accurately align their selling and go-to-market strategies with regions and territories that had the greatest sales potential, go-to-market costs would be immediately reduced.” This is true for almost all industries, not just biopharma.

7. 58% of Chief Marketing Officers (CMOs) say search engine optimization (SEO) and marketing, email marketing, and mobile is where big data is having the largest impact on their marketing programs today. 54% believe that Big Data and analytics will be essential to their marketing strategy over the long-term.”

8. Market leaders in ten industries Forbes Insights tracked in a recent survey are gaining greater customer engagement and customer loyalty through the use of advanced analytics and Big Data. The study found that across ten industries, department-specific analytics and Big Data expertise were sufficient to get strategies off the ground and successful; enterprise-wide expertise and massive culture change was accomplished after pilot programs delivered positive results.” Because cognitive computing systems can collect, integrate, and analyze both structured and unstructured data, they are ideal cross-enterprise platforms.

9. Big Data is enabling enterprises to gain greater insights and actionable intelligence into each of the key drivers of their business. Generating revenue, reducing costs and reducing working capital are three core areas where Big Data is delivering business value today.” Of course, it not the data that delivers insights, it’s the analysis of that data. Nothing is better than cognitive computing for delivering actionable insights.

10. Customer Value Analytics (CVA) based on Big Data is making it possible for leading marketers to deliver consistent omnichannel customer experiences across all channels. CVA is emerging as a viable series of Big Data-based technologies that accelerate sales cycles while retaining and scaling the personalized nature of customer relationships.”

Barry Levine (@xBarryLevine), notes, “Way back in the last century, one of the most common put-downs of computers was the accusation that they only did what they were programmed to do. Not any more. These days, it is increasingly common for marketing and many other kinds of systems to employ some variety of ‘machine learning,’ which moves away from the days when programmers dictated computers’ every move.”[5] Newton concludes, “If you do it right, customers may actually want this type of customization. There’s already a whole field of marketing growing around the idea — GPS marketing. Although it’s just now starting to catch on, once they get the data management right, it’s easy to see that level of personal marketing — Minority Report style — taking over everything. Why send a blast e-mail or place an ad when you can sell me exactly what I’m shopping for — at the exact moment I’m shopping online or in the store?” Why indeed.

Footnotes
[1] Derek Newton, “Coming Soon: Marketing Targeted Only at You,” Entrepreneur, 9 May 2016.
[2] Tony Blankemeyer, “Marketing With Machine Learning Begins With Show and Tell,” American Marketing Association, April 2016.
[3] Murali Nadarajah, “Machine Learning and the Great Data Analytics Shake-Up,”Information Management, 2 March 2016.
[4] Louis Columbus, “Ten Ways Big Data Is Revolutionizing Marketing And Sales,” Forbes, 9 May 2016.
[5] Barry Levine, “MarTech Landscape: What is machine learning and why should marketers care?Marketing Land, 10 May 2016.