A major North American direct marketer, with over $1 billion in annual sales, segmented their database three years ago, and took a close look at where its sales were coming from. It discovered something fairly ordinary: 50% of the sales were to consumers, and 50% were to business. However, it was very shocked to discover the profits on the business sales were 500% better than those to consumers. It was like night and day. Most consumer sales were not even profitable although they represented the majority of customers, transactions and expenses.
Armed with this information, top management called a retreat to figure out what they should do. After much soul searching and disagreement, they decided to scrap their overtures to consumers, and concentrate on the profitable side: business to business sales. How could they go about it?
Prior to this decision, the company had relied on inbound calls from their catalogs and print ads. They had nearly five hundred employees taking calls from customers, and less than 100 making outbound to previous business customers. The new strategy required a total turnaround. Two years after the shift, they had 700 outbound callers, and less than 100 taking inbound calls. How did they do it?
In the first place, the company identified where their business sales were coming from. They overlaid their file of business customers with SIC code data, annual revenue, and number of employees. In addition, each company in the database had RFM scores, credit information, and actual products purchased over the past three years. They ran models to determine the ideal targets for retention and further acquisition. They did penetration analysis to see which market segments they could exploit the most easily. SIC penetration analysis was based on dividing the number of active customers into each four digit SIC code by the total number of North American companies in that same SIC code. Four separate data suppliers were used to validate results. The resulting penetration ratios were used to create SIC specific suppression files, establish credit lines for new prospects and rank market opportunity by SIC, company size and past customer performance.
From this analysis, the company knew where the increased business sales would come from and how big the sales opportunity could be in four-digit detail. The models identified which products customers and prospects were most likely to buy, and which, therefore, should be suggested by the callers.
The next step was more difficult. The company had to shift their overwhelmingly inbound call center staff to become overwhelmingly outbound. It was not easy. Many, if not most, inbound people cannot easily change to outbound. Outbound involves rejection. It involves bothering people who are not thinking about buying right now, whereas inbound callers are always in a buying or inquiring mode. Outbound callers have to have a thick skin and a strong personality. The company had to identify the skill sets in their inbound sales staff which would enable them to sell outbound. Many inbound employees would not survive the switch. The company had to recruit and train most of its 700 outbound callers. New outbound callers had to prove themselves in training and make 200-300 prospecting calls a day. After training the requirements dropped to around 100 calls per day. For a new outbound employee, it took about nine months before the sales person could support himself or herself on the commissions from the sales.
One of the difficulties in the transition was the selection and distribution of the customers among the 700 outbound callers. Each employee was given a share of existing businesses to call, plus a group of new businesses selected by a model. The idea was that there should be a level playing field with each employee getting a shot at profitable and unprofitable business.
What happened if a business called in with an order without identifying (or remembering) their assigned outbound sales rep? These orders were taken by the remaining inbound callers. Commissions were paid to the inbound rep and the assigned outbound rep.
Eliminating Unprofitable Customers
With the new models, it was possible, for the first time, to see who was profitable and who was unprofitable. Early in the transition, the company identified unnecessary product lines. These were eliminated. Unprofitable customers, were the next hurdle. Using several models, the marketers were able to determine the type of customers they did not want. Using past purchase history including returns, credit history and profit margins, the marketing staff was able to compile a suppression file of nearly one million firms and individuals that it did not want to do business with. Changes in merge/purge logic, circulation planning and suppressions allowed the company to eliminate all catalog growth. The million-name suppression file was used as a stop file for all catalog mailings.
Shifting To The Web
While all this was going on, the company was rapidly moving to sales over the Internet. At first, the company’s Web site was highly experimental, yielding many awards and strong traffic but marginal sales. Roughly eighteen months after the web site was set up the focus changed to selling product in tandem with sales reps and product management. Today, about 10% of all company sales are “hands free” sales. In the other 90%, the caller frequently uses the Web to browse products, and then calls in his order. Pure Web sales, of course, are cheaper to process, since no employees have to touch the order. On the other hand, the Web, so far, has not proved as successful in upselling as a live operator. Average line items per order are lower on the Web than the average with outbound operators. Volume is not as high, although “hands free” are more profitable.
Result Of The Turnaround
After two painful years, the company now has 95% sales to business and only 5% sales to consumers. Sales which were growing at 21% before the shift, now average above 50% and peaked much higher in recent quarters. Profit growth has been equally as dramatic. The shift was definitely worth it. This is a great example of profitable database marketing. The steps are these:
- Build a customer marketing database with purchase history, RFM, Lifetime Value, SIC codes and other data so that modeling can take place.
- Segment the customer database so as to determine where the profits are coming from and where they are not coming from.
- Make some tough decisions about what to do to increase sales and profits. Get everyone in the company, from the top down to understand the implications of the change. It may be rough, as it was in this case. Hundreds of employees lost their old jobs, and were not suited to the new ones. Management had to understand what the goal was, and why the pain was necessary.
- Do penetration analysis and modeling to support the new sales staff. Determine which customers should be retained and which should be dropped. Predict which are the most likely products to be purchased by customers, and arm the outbound staff with the tools to make up sell and cross sell initiatives.
- Track the results carefully so that you prove to management that all the pain and suffering is worth it.
- Move rapidly to build up the net as a selling tool, but realize that human outbound efforts may still generate more bottom line dollars due to higher volume.
Arthur Middleton Hughes, vice president of The Database Marketing Institute, has presented 28 seminars on database and email marketing. Arthur has also authored several books includingStrategic Database Marketing 4th Edition (McGraw-Hill 2012). He and Andrew Kordek, chief strategist and co-founder of Trendline Interactive, are hosting a two-day Email Strategy Study Group in Fort Lauderdale March 26-27, 2013, featuring group competition for email marketers responsible for subscriber acquisition, lifetime value, ratings and reviews, boosting their email budget, and doubling their ROI. To learn how to attend the Study Group,click here
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