THE IMPORTANCE OF MARKETING ANALYTICS

by Dr. Raymond Pettit, Senior Consultant, Cutter Consortium

Investments in technology have enabled corporations to gather vast amounts of data about their customers and markets. However, market research and measurement techniques are just beginning to come to grips with the amount of consumer and marketing data that today's organizations are generating and collecting. To date, the development of techniques and tools for extracting insight has lagged behind the development of tools for collecting and storing data, thereby limiting return on investment (ROI) of marketing actions.

As a result, C-level executives and marketers get data, but not the right data -- and not the holistic 360-degree view they need for actionable insights into customers and markets. The following scenarios are problems typically faced by today's corporate executives:

• Fragmented information: missing data, lying fallow in corporate silos of information, segregated by systems and business units

• Information overload: too much data, but not the right data

• Information without context: nonactionable behavioral data

Technology, by itself, cannot solve such problems. Although a company's customer transaction database is used to collect information about customer behavior, such behavioral data is limited in its ability to provide meaningful perspectives, such as the "why" of customer behavior. Context is essential to rendering a holistic view and actionable insights. Without knowing why customers behave the way they do, marketers can't devise effective predictive models and marketing strategies. Attitudinal, preference, and perceptual data, for instance, are essential to providing context and cannot be supplied by technology alone -- instead this contextual data must be collected via marketing research techniques, such as survey research via a random sampling of customers.

Example: Enhanced Segmentation

Enhanced segmentation, a data augmentation technique, has a broad range of applications. It is used to explain and predict consumption, preference, or usage of new or current products/services by existing customers who, as yet, do not use them. This technique extends current predictive/analytic techniques in use by marketers so that organizations can learn from the behavioral patterns of all customers in the database fused with the knowledge from external (attitudinal, preference, emotional) data gathered from a survey of a sample of customers. This enhanced database enables the organization to identify, for example, loyal customers for cross-selling, up-selling, or retention. In addition, this technique can be used to link loyalty and retention efforts focusing on customers who are actually most profitable. The resulting actionable insight and intelligence, culled directly from the voice of the customer and captured with the appropriate technological systems, confers many advantages:

• More precise and accurate fit of attitudes, behaviors, and demographics to your real customers; you ask the questions you want answered

• Less expensive than current target marketing approaches, with better results

• The ability to micro-segment relevant and actionable groups to develop creative pricing, messaging, promotions, and so on

• The ability to better understand precisely who your customers are so that you can attract people most like them to grow your customer database

• The ability to develop more precise tests of what works for key advertising and marketing actions

Take Your Company to the Next Level of Marketing Analytics

The sophistication of technology architecture -- embodied in the enterprise data warehouse, Corporate Information Factory, and new Web-based techniques for real-time movement of data -- fully supports the evolution of superior analytics and decision support systems. Although this movement and evolution is not complete, organizations are gradually moving up the analytic ladder from aggregate-level marketing, segment-level marketing, and individual- level marketing to the following:

• Campaign-based marketing: customized offers, optimization of marketing resources/allocations, relevant, right-time offers

• Interactive marketing: real-time/right-time offers, 360-degree view of the customer, and prioritizing highest-value opportunities based on understanding and managing loyalty and profitability simultaneously

Customer relationship management (CRM) and data mining software, seeking to automate analytics based only on transactional data, are not necessarily the best route to success. Verticals and industries differ greatly in the type of customer data collected and in the orchestration of the best customer pathways. Customer behavior is profoundly influenced by attitudes. To rise to the next level of marketing analytics, a combination of marketing experience and the application of sophisticated measurement and market research techniques is required. Technology can then be used to automate these new solutions, under the careful guidance and advisement of marketing scientists and measurement specialists. The result will be increased marketing effectiveness, efficiency, and accountability.

-- Dr. Raymond Pettit, Senior Consultant, Cutter Consortium