Marketing Analytics to the Rescue: The Next Big Thing?
Information Management Special Reports, February 2003
CRM has become today’s business buzzword. Despite $125 billion spent on CRM initiatives over the past five years, nearly 70 percent of companies have yet to realize positive return on their investment. Yet, a new savior appears emerging from the ashes: marketing analytics – a.k.a. the next "big thing."
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Figure 1: Marketing Analytics
Analytics Technology
Analytics and supporting technology are not the panacea to customer loyalty. Analytics are most successful when applied in the context of a solid strategy that considers the people, processes and technologies necessary to grow valuable customer relationships. These solutions can serve as effective enablers when applied in the right way. Moreover, the vast improvements in analytics technology no longer mandate the need for an advanced statistics degree to run modeling tools.
Bottom line: Understanding the technology best suited for an organization’s needs can eliminate big headaches down the road.
Figure 2: Which Technology is Right for Your Organization?
Why Now? Why Today?
The strategies, processes and technologies used to identify, acquire and retain profitable customers, as we now know it, are changing. Companies battle each other for buyer attention by barraging consumers with an unprecedented number of messages across every conceivable medium.
One recent study by NFO Research suggests that the typical American consumer absorbs fewer than two percent of messages cross channel. Budget-strapped marketers are desperately seeking ways to both through the buzz and sustain the attention of profitable customers through messages delivered at the right place, time and through the right channel.
No, this is not a state of fictitious one-to-one marketing utopia. In fact, perceptive organizations reach these goals by applying basic math and understanding that any consumer behavior (Stats 101: Dependent Variable) can be predicted with statistical precision using historical observations of actual behaviors and interactions (States 101: Independent Variables).
Figure 3: Applying Basic Math and Predictive Statistics
In the big budget heydays of the 1990s, marketers could experiment with unproven tactics. Customer churn in the days of the booming economy was less of a crisis. Those days are distant memory, and marketers need to be smarter and hit their target audience with a precision that would make a highly trained marksman jealous.
Information Everywhere and not a Drop to Use!
Companies struggle to find out what makes their customers "tick" through surveys and offers. New customer-facing technologies have made the opportunity larger but situation even worse because customer data can be captured from so many touchpoints. Unfortunately, without an adequate way to manage this information, companies are now finding themselves prisoners of their data warehouses.
The situation may not be quite that dire, but the predicament of having lots of information without an effective way to utilize it is certainly a very real business issue. Until recently, companies have not been able to integrate the intelligence from the data from their operational touchpoints, such as their call centers and Internet site. Data in of itself has no value. This is where analytics enters the picture – analytics turn data into action.
The Analytics Solution – Not Russian Roulette
While analytics is not the cure-all for all of marketing’s woes, it certainly enhances a marketer’s ability to reach their target customer in the most effective and efficient manner. Today’s analytics tools provide organizations with the means to evaluate data and create easy-to-use conclusions. More importantly, a key benefit to utilizing analytics is that it helps companies measure the previously immeasurable.
Many CRM projects have failed because they lacked consideration of financial objectives. They sought to "improve customer satisfaction" rather than solve more specific, measurable points of pain (i.e., reduce call transfers, increase repeat buys, decrease product X attrition by X percent).
Real results support the difference analytics deliver. Researchers from Forrester, Jupiter, Amazon.com and Ovum analyzed different metrics to measure performance when analytics targeted certain consumers – cross-industry and channel. The results were dramatic as shown in Figure 4.
Figure 4: The Effect of Analytics
The repeat buyer rate metric – considered the Holy Grail for marketers – indicates the significant value associated with using analytics to target loyalty marketing and cross-selling efforts. A recent report published by McKinsey Consulting indicates that 80 percent of direct marketing budgets will go towards post-acquisition loyalty marketing between 2002-2005. The advantage of analytics in allowing companies to focus their spending on the areas of greatest return fundamentally shifts the direct marketing industry away from "blind" acquisition toward "intelligent" retention and value expansion.
The researchers also benchmarked best practices as shown in Figure 5.
Figure 5: Benchmarked Best Practices
There are many tangible examples of how organizations successfully used analytics to create these types of gains. One telecommunications company implemented churn and customer value models deployed through its call centers. By targeting high-value customers at risk of switching to a competitor and routing calls to its best service representatives, the company experienced a 37 percent increase in revenues, 12 percent increase in per customer profit and a 17 percent reduction in churn. A bank implemented a similar program through the Web that drove a 29 percent increase in customer self-service usage, a 51 percent increase in customer satisfaction levels and a 64 percent decrease in attrition – huge savings for them and better service for their customers!
Take the Good with the Bad
Analytics is all about math. Yet, it is sometimes hard for more experienced business people to trust the mathematical "black box" rather than their professional judgment. They may think that they "know their customer" and can out predict a model based on experience. More often than not, their experience is biased – and wrong.
With the advent of advanced tools like neural networks that continually "learn and objectively adapt" based on actual customer behaviors, analytics are 40-60 percent more accurate that judgmental decision making alone. Typically, this is an organizational and change management issue, requiring structure, standards and policies necessary to remove the guesswork from these 21st century marketing best practices.
Honesty is the Best Policy
Another frequent objection to the application of analytics is the potential for infringement on consumer privacy. This gained steam in recent years with intrusive advertising and e-mail spam, made worse by identity theft incidents where hackers gained access to social security and credit card numbers. The consumer community is generally leery about the potential for information abuse and the "big brother" connotations inherent in predictive analytics.
Some companies are seeing great success in merely "asking" for permission in bold print (note: not fine print hidden at the bottom of a Web form). They also offer to share the results of analytics with their customers, grant customers access to their own data and explicitly refuse to sell the results to others for their own selfish marketing purposes – especially to outside third-party solicitors. This helps establish trust with the consumer and creates a comfort level to share more information without fear.
The Bottom Line
Analytics targets the right individual for the right offer or promotion. Keeping that customer happy and loyal is an ongoing effort made consistently by your organization at any possible opportunity. The more intuitive you can be about your customer’s needs and wants, the more cared for the customer will feel and the better his or her perception of your company’s customer service level. It’s this trust that establishes the most lasting loyalty. Analytics is the tool that will help you create it and has never been more user friendly and affordable. However, the best analytics tools are only half as good as those used in conjunction with a solid customer strategy.
David J. Santoro, Jr., CPA, is a principal and senior specialist within The North Highland Company’s Marketing and Customer Interaction practice. Santoro has more than 12 years of experience in large project management and consulting, and specializes in information-driven marketing. He is skilled at helping organizations use data and analytics to build valuable, intimate customer relationships. He also has considerable international experience across multiple industries as well as in the e-business arena.
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