The Next Big Thing: Advanced Marketing Analytics

Executives have heard the following phrase countless times: marketing needs to get more analytical. The strategies, processes and technologies used to identify, acquire and retain loyal customers, as we now know them, are changing. Companies struggle to find out what makes their customers "tick" while budget constraints make finding the best customers and prospects more difficult. Add to this the barrage of an unprecedented volume of messages across every conceivable channel and the world of marketing becomes a very difficult place.

New technologies have made the opportunity for marketing success larger, but have also made the situation worse because customer data can be captured from so many touch points, such as call centers and Internet sites. Without a way to manage and utilize this information effectively, companies are finding themselves prisoners of their data warehouses and databases since data in and of itself has no value.

This is where analytics comes in — advanced marketing analytics turn data into action by targeting the right individual with the right offer or promotion with the right message. Analytics is no longer a “nice to have” tool but a “need to have,” integrated component of a marketer’s overall execution platform. Furthermore, the dynamics of the marketplace are demanding a new type of analytic platform — one that is truly integrated with the entire marketing process and furthermore, continually updated and maintained so relevancy is assured for the marketing user. Analytics is no longer a project or side car; it is an integral component of the marketing business and must be provisioned, integrated and structured as such.

The New Analytic Paradigm

Today, marketers require advanced insight into customer and prospect behavior, well before the creative is completed or the marketing program is put into action. This however, creates an operational challenge. Where in the past, models were used to predict behavior for a program, campaign, or series of events, today marketers need to know more about the customer’s needs and behaviors in general. The idea of developing a model for a campaign or program simply can’t work in today’s environment.

To address this, marketers are building up a broad array of advanced analytical knowledge about the customer. To this end, firms have deployed models that provide:

• Knowledge about a customer’s likeliness to purchase each and every product.
• Knowledge about a customer’s likeliness to upgrade from a current product/service to a new package/service.
• Knowledge about a customer’s expected churn rate and timeframe.
• Knowledge about a customer’s expected lifetime value.

Even in a “simple” model with only a few services in say, telecommunications, it’s easy to understand why a cellular provider would need nearly a hundred models to provide truly advanced knowledge about a customer’s expected behavior across say, a half dozen service plans.

In other words, statistics is no longer a means to an end for increased lift on a certain campaign, mailer or program. It is now viewed as the mechanism by which marketers must discern or uncover advanced knowledge about a customer’s behavior, and most importantly, be able to use this knowledge in all marketing and sales activities. As a result, the challenge of providing advanced analytics not only requires a new paradigm, but a renewed focus on the infrastructure and platform requirements that can get the modeler out of the business of fixing data issues and onto the task at hand; creating accurate predictions of customer behavior.

The Application of this Advanced Knowledge

Armed with this knowledge, the marketer can better manage the entire marketing lifecycle from planning to measurement (and learning of course). For example, in one firm we have worked with, the marketing plans for the year are based on the expected results (driven by advanced analytics of course), expected from the customer base. As a result of this new analytical paradigm, the firm’s marketing executives can contemplate shifts in marketing spend across programs and have a very real sense of the expected lift and return on these dollars.

As a result of this new paradigm, a proper platform must be put in place to handle the entire analytical modeling process. The platform needs to fully support all analytical model development, scoring, accuracy checking, performance verification, and integration with the marketers toolset; campaign, measurement, ad-hoc and reporting platforms. Furthermore, the analytical capability and integration must be truly automated, saving the modeler over 80% of the his/her time dealing with data integration and scoring issues and letting the advanced analytic resource focus on providing value — by developing analytics that can help support and drive the business.

Best Practices with Advanced Marketing Analytics

One of the most common best practices using advanced analytics is the redistribution of contacts from one customer group/segment to another during marketing strategy discussions very early in the marketing planning process. With an integrated analytics platform, marketers can now view future contact plans in light of expected response and returns, and redistribute marketing dollars (and contacts) on all outbound channels to address their strategic needs (e.g. units, sales, profit, lifetime value). By adjusting the marketing plans and strategies early in the planning process, marketers we have worked with are easily able to increase their return on marketing investment by 20% and moreover, have a clear picture of expected results. During the execution stages of each program and below that, campaign, the marketer can evaluate the results against expected results provisioned by the advanced analytical platform, and further reallocate contacts while programs are in market (currently being executed with programs and communications being sent to customers/prospects).

By leveraging the advanced analytical platform, marketers can now optimize offers on inbound channels like customer service and inbound sales. Our experience shows that optimization using the advanced analytic platform typically creates lifts of over 25 % and can provide complete justification for the marketing platform in as little as 45 days through this best practice. By leveraging the platform, marketers can provide straightforward recommendations to the sales or service representative in the call center or at the retail service desk or cash register. These recommendations are often two to three times more likely to be accepted by the customer as a result of the unique combination of the advanced analytic platform and the timing of the offer in the context of a customer initiated conversation.

Summary

While the new advanced analytic paradigm requires a different view on advanced analytics and their deployment across the entire marketing lifecycle, today’s increasing message-oriented world is making it a core necessity for direct marketers. At the same time, firms that deploy this capability with even a few best practices are likely to see payback very quickly and furthermore, be provided a platform that gives the marketing executive a lever of confidence and control that cannot be achieved using traditional analytical methods or processes.