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ANYONE FAMILIAR WITH DATABASE MARKETING is aware of the cultural divide between creative types and data types. It's as if they two groups speak a different language. While maximum reponse and ROI are shared goals, how the two groups go about understanding the audience to craft campaigns that achieve these goals often is completely different. |
Data analysis typically is targeted around one goal: selecting the “best” names, the names that will bring the highest response. Different audience segments may be selected, but in the end, a name either is selected or it’s not.
The challenge is left for the creative specialists to fit the right creative message to the right offer that fits each segment of these best names.
Simply put, if the people creating messages and offers don’t clearly understand what each segment is, why it’s unique and what sort of behaviors are most likely for each, it will be very difficult for them to appropriately fit messages to each segment.
Data analysis should support all three aspects of a direct marketing piece: list, offer and creative. Maximizing these synergies can increase ROI, but first the analyst’s goals have to change to supporting all aspects of a direct marketing offer, not just tracking and list selection.
A management analytics database
While we often think of a database as a record of transactions, it is actually a record of customer behavior, and as such can provide critical marketing insights. While in a technical sense the database is built to track information, the real purpose is to understand the behaviors being tracked. Any list selections, messages and offers then are based on that understanding. (Our How-to Resource Library tells you more about What is a Management Analytics Database? and What Goes Into a management analytics database?)
The behavioral database perspective is especially powerful when used to explicate a new marketing model pioneered by Dr. Neale Martin, founder and president of Atlanta-based Ntelec Inc. His model explains why customer behavior often conflicts with customer attitude, especially the weak link between customer satisfaction and repurchase. Recent research in the fields of neurobiology and cognitive science reveal that the mind divides up tasks between the conscious and unconscious mind. The unconscious mind is responsible for up to 95 percent of our actions. This means the database is a more reliable tool to understand customer behavior than surveys or focus groups.
For example, a marketing database would track the RFM of each customer. It is a near certainty that the more recent, more frequent buyers will outperform older, less frequent buyers. But a lot of predictive information still is left out. (Learn more about RFM by reading Segmentation - Finding Your Best Customers and Show Me The Average.)
Consider a company selling valves, switches and fittings—all of which go together. A customer buying switches and valves but not fittings must be buying fittings from a competitor, and that firm probably is trying to sell him valves and switches, too.
With a behavioral database, you would find this customer and target him for fittings. A communication would be created that includes valves, switches and fittings as a package.
LOOKING AT PRODUCT CATEGORIES
A marketing database typically supports the activities of marketing and product managers. Often, each product group has a different product manager. While those product managers may work for the same company, odds are good they compete with each other for bonuses and raises. As a result, it isn’t likely they’re looking for cross-category behaviors.
With a behavioral database, which focuses on what customers are doing, cross-category behavior is critical. The individual product marketing managers may not want to look for it, but creative managers seeking to reduce costs and improve response by combining offers certainly will. Chart A (below) is an example from the aforementioned company, where the number of categories from which a customer has purchased is compared to its defection rate. The defection rate drops by about half with each additional product category purchase. Another analysis would consider the total number of defectors. For this company, 83 percent of defectors bought only from one product category.
Clearly, in this case one of the best ways to reduce defection and have a more loyal customer base is to cross-sell product categories. Focusing on the customer’s behavior, as opposed to the marketing goals of different product managers, can give creative managers the ammunition they need to find and produce better creative packages. (Learn more about how data mining can guide cross-selling strategies in Cross-Selling - The Fast Way to Raise Revenues.)
THINKING OF PATTERNS AS HABITS
With what regularity people buy can be more important than how many times they buy. For companies selling B-to-B products and services, customers could buy literally every day. But that doesn’t mean they buy all year long. A customer could buy 50 times in three months, and another could buy 50 times total but buy in each of the 12 months.
If we look at customer behavior by how many months someone purchased in a year, as opposed to frequency, we get a different picture. Chart B (below) compares defection rates after one year by months purchased. As we see in this example, customers that were in the habit of buying every month simply did not leave. Those that never had the habit, or didn’t build the habit, tended not to be loyal. Clearly, designing messages and offers to encourage the habit of regular buying makes sense.
LOOKING AT BUYER ROLES
Marketers tend to think of customers separately from customers’ buying roles. Either a name is attached to a sale (a customer) or a name is not (a prospect). But even in consumer marketing, we can consider B-to-B buying roles, which can be summarized as:
• Buyer (makes the actual purchase)
• Decision maker (approves the purchase)
• Specifier (recommends or selects the item/service)
• User (actually needs and uses the item/service)
Understanding the behaviors of each role is critical to creating effective communication for each. For example, a buyer works at getting better terms and financial arrangements; a decision maker works at fitting things into a bigger picture; a specifier works at finding the right functionality and specifications; and a user works at using features to maximize benefits.
Building a behavioral database to support creative should include gathering each customer’s role in the buying process. It is entirely possible that names in a database may not be “buyers” (if that role falls strictly to purchasing) but are critical links in the chain. It’s just as possible that if “the buyer” is in the purchasing department, he is simply buying what he was told to buy. Any messages to this type of “buyer” about specifications, features or benefits likely will have no impact. (Learn more about how B2B customer lists differ from B2C customer lists in Selling to Both Businesses and Consumers.)
BUILDING BUYER ROLE DATA
Titles usually correlate (although roughly) to a buyer’s role. Most databases track title, but few track by “functional title.” Functional title is a preselected category of title, such as purchasing, sales, engineering or production. These generally run along the same lines as buyer (purchasing), decision maker (sales often will determine what it needs to sell and how many), engineering (specifies the exact items required) and production (an end-user receiving or using the item.)
B-to-C marketers also can consider buying roles. A parent might be a decision maker/buyer, where a child might be a user/specifier. For example, the child might pick out and use a video game, but it is the parent who says “OK” and buys it. Each party has a very different interest in the product, and each looks for very different information before the sale is made.
It should be noted the variations in title from industry to industry are tremendous. It can be a significant challenge to take an existing database of titles, where there are sometimes literally thousands of different titles on file, and boil it down to a few functional titles. However, the challenge usually is not impossible and the benefits can be tremendous.
Most companies that are not using functional title to their advantage probably still are collecting names and titles. Generally, knowing and interacting with more functional title areas with a given firm results in higher sales for a company. Chart C is an example in which customers were segmented by the number of different functional titles in the database; one means the company has customer contact(s) in one functional title area, two means it has customer contacts in two different functional title areas, and so on. Clearly, the broader the contacts base within a customer company, the higher the average annual sales. In fact, with all of its “best” customers, this firm knew at least one person in each of the four functional title areas. With lower value customers, it rarely knew more than one or two.
Building buyer role information into the behavioral database offers a real improvement that creative can capitalize on. It allows a level of understanding and ability to appropriately communicate that otherwise could not exist.
FOCUSING UPON CREATIVE AS A GOAL
Whether database specialists like to admit it or not, it’s what is designed and written by creative that goes into the marketplace and gets results. Reaching technical goals of faster updates or larger storage capacity may have no impact on sales. But giving designers, copywriters and planners practical understanding so they can communicate more effectively will.
The key to making this happen is the behavioral database. Focusing on what people do, their behavioral patterns and their habits, is a way to bridge the cultural barrier between database and creative. The behavioral database becomes the common source of understanding and actionable information for both marketing and creative inspiration.
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