Customer information to the rescue

Editor’s note: Elizabeth Bergman is an adjunct professor at California State Polytechnic University Pomona.

Many American companies collect customer satisfaction data, but one has to wonder what effect that customer information has on their businesses. The 2002 holiday shopping season turned out to be the worst in 30 years, and the list of troubled companies that are ailing because they have fallen badly out of sync with their customers is long. Consider McDonald’s, which recently faced its first quarterly loss in 37 years. Nimbler competitors with menus in tune with increasingly diverse tastes are eating the burger chain’s market share. Profits at Levi Strauss and The Gap have faded more than their jeans. Kmart, Ford, and a host of telcos, once poised to dominate, are scrambling to eliminate jobs and survive. The lesson? As long as customers have the luxury of choice, corporate profits will remain linked to satisfying them. The problem? Insufficient understanding of the mountains of customer data collected. Only companies that know their customers’ needs will thrive. This is a tremendous opportunity for the research community.

Arguably, companies are not sufficiently mining their customer information nor using it in creative ways. Often overlooked, customer satisfaction data incorporated as a part of market segmentation efforts conducted during the business planning process provides results. Admittedly, business planning may not be the traditional province of research managers. However, it’s an effective point at which to begin establishing the importance of customer satisfaction information.

Planning 101: customer satisfaction meets customer segmentation

Customer segmentation is typically part of the planning regimen as it answers the critical “Who do we sell it to?” question. However, once product managers determine the answer, they very rarely carry the same logic to the next step, asking “How satisfied are our customers in each of those market segments?” And further still, “Are we treating different customers differently?”

Companies typically segment satisfied vs. not satisfied customers - creating programs aimed at each, or choosing to address the dissatisfied segment only. We all know how expensive it is to gain a new customer, so customer retention receives heavy attention. An example from Johnson Controls is illustrative: of the company’s 80,000 customers, 82 percent were viewed as very satisfied or satisfied, as indicated by a 5 or 4 response on a 5-point survey scale. That meant that there were 65,600 satisfied customers; of these, about 10 percent (6,560) would probably leave during the year based on calculated retention rates. Conversely, 18 percent were dissatisfied customers; however, defection rates for the dissatisfied group are much higher - as much as 50 percent. Multiplying the defection rate times the dissatisfied customers meant 7,200 customers would leave. Combining the two defecting customer pools yields almost 14,000 lost customers - the focus of Johnson Controls customer satisfaction improvement program (Naumann & Hoisington 2001).

That said, simply segmenting according to who is happy and who is not doesn’t reveal what may be important nuances about your customers. For example, a mid-cap software manufacturer took the extra step of matching customer satisfaction scores to market segmentations created in the business planning process. What this revealed was differing levels of satisfaction across groups of customers. Upon investigation and examination, it was revealed that these different customer groups did in fact receive different levels of service. This is not necessarily a bad thing. It may be appropriate to provide high levels of service to highly profitable customer segments. Customer satisfaction data can serve to illuminate and validate such practices.

The process described in this article may appear unique to an industry and its customer base, but it can be easily replicated across industries by discerning the following:

  • Identify the buying behavior of your customers. (What are customers buying? In what combination? Based on what needs?)
  • Determine the types and amount of service customers receive. (For example, in many industries, companies designate Level 1, Level 2 and Level 3 support.)

This purchasing and service information must be transformed into data; create new variables for each in a meta file (an example is shown in Table 1). Then customer satisfaction data and customer revenue data must be merged into a meta file. If possible, it is beneficial to also have Standard Industrial Classification (SIC) codes, among other data, appended to the meta file. Dun and Bradstreet can do this for a nominal per record fee.

Table 1

Now comes the fun part - data mining. There’s certainly no limit to the types of analyses that can be conducted on a data file chock full of company and customer information (factor, cluster, Pareto, correlation - to name just a few). An important part of the value-add that client-side research managers bring to their employers is an understanding and knowledge of the company’s business; for an adept, astute researcher that exposure and this data can generate eye-opening results. For instance, running a crosstabulation of revenue by segment will likely reveal critical information about customer spending that can be used to figure out segment profitability. An example is shown in Table 2. In addition, conducting a Pareto analysis based on the delineated buying and service groupings can be very useful. A sample is shown in Figure 1.

Table 2

Case study

For the case study company, defined as Company X for present purposes, the major challenge is to balance the cost of software development, which is driven upwards by the need to keep customer satisfaction high, with the opportunity to sell to new customers, which is low, given the mature state of the market. Unlike a growing market, where product investment drives both new revenues and the satisfaction of existing customers, ensuring a good return on investment in a mature market poses a challenge. In the past, Company X’s approach has been centered on the innovators and early adopters of technology, satisfying their needs and reaping the trickle-down rewards in the more conservative and late adopting customers. However, this approach became problematic in a technology-lagging market. In many cases the powerful, flexible solution the company built for the innovators became overly complex and too difficult for the other customers to use. As a result, satisfaction and sales fell year-over-year and management was desperate for a new approach.

Figure 1

Needs and buying behavior
The first step was to find out customers’ needs relative to Company X’s products based on the business criticality of a customer’s underlying business applications. Clearly this is dependent on the customer’s own business segment: a financial trading company will have highly critical business applications whereas an educational establishment’s applications will be less critical. A “criticality” variable was assigned to customers based on industry type taken from the Dun and Bradstreet database.

Next, customers’ views of systems management as a core competency or as an unavoidable chore was determined. Some organizations see the ability to deliver high performance and high availability as a key asset to their business; we referred to this as “core.” Other customers see systems management as a necessary evil: applications need to stay up and performing but achieving that does not add anything to the business. This was labeled “chore.” I created proxy measures for “core” versus “chore” by identifying the historic product buying behavior of customers. Customers with only the most simplistic products were assumed to be in the chore category, seeing their purchase of these products as insurance against systems problems. Customers adding more complex products were viewed as taking a more proactive approach to systems management as a core need.

Segmentation
To its surprise, the company discovered that its customers are not homogeneous, and “being a Company X customer” does not describe their needs as individual customers. The results of this segmentation are shown in Figure 2. Each segment is named and has a set of unique characteristics.

Figure 2

The Service Visionaries are the critical and (hard-) core customers. This is a small number of large-enterprise customers, typically in banking and financial services that manage large-scale mission-critical applications and approach the system management challenge through high levels of automation and integration. These customers are typically trying to build “single points of control,” and they take their enterprise systems management seriously.

On a revenue-per-customer basis, the Service Visionaries are the best customers but as a group they are not the biggest source of revenue. They are however, the biggest source of work and cost in terms of hand-holding, support and general account management. In short, the Service Visionary segment of customers are the company’s greatest supporters and worst critics. The Service Visionary customer satisfaction score as a group is low; they will always want more features (their features!) and tend to stress product capability to the maximum.

The good news on the Service Visionaries is that they have highly customized and integrated environments. That makes them very loyal as the costs of switching to another vendor are very high; it’s not surprising then that the amount of customer churn in this segment is very low.

In stark contrast to the Service Visionaries, the Insurance Seekers are those customers in non-critical (or low-critical) businesses who have no interest in systems management beyond, perhaps, problem-solving. These customers are typically smaller enterprises and, while they are valuable customers, they probably receive little care and attention from the company. Nevertheless, this lower level of attention is acceptable as these customers are essentially product users only and, as their high satisfaction score indicates, tend to be happy with the product. The Insurance Seekers are the smallest revenue-generating segment, both as a group and on a per-customer basis. However they are also the cheapest customer segment to service and support.

Between the Visionaries and the Insurance Seekers exists the largest segment, made up of two groups, the Performance Managers and the Availability Managers, collectively referred to as the P&A Managers. This segment consists of customers who are either running critical applications or fall into the “core” group. Each customer’s defining characteristic — “criticality” or “core” — changes their management needs somewhat, but a bigger overriding segmentation driver applies to this group as a whole: The P&A Managers as a group form a classic conservative, late-adopter, buying segment. The P&A Managers want to solve their system management problems “the way everyone else does” and they don’t want that goal to be disrupted by vendors delivering new and complex innovations. They don’t want to buy new products that will require them to change their ways and they don’t buy into any “vision.” They also form the company’s single biggest market segment by far.

Company X results

Critical new strategies that would help transform Company X had come about as the direct result of one research manager’s transformation of satisfaction and segmentation data during the planning process.

After examining its customer segmentation, Company X discovered that it typically didn’t sell - in terms of marketing, positioning and messages - to the larger conservative customer base. As is the case with many technology companies, developers and engineers were enamored of sophisticated, complex technology, and while being long on vision is great for innovative customers, connecting to the more conservative buyer was critical for future success.

Furthermore, Company X discovered that it needed to carefully allocate internal resources while being cognizant of each customer segment. Sales, R&D and all the other necessary internal forces could not be marshaled to serve only those visionary, leading-edge customers that demanded so much, yet were never satisfied - and did not provide the largest profit margin.

Survive and profit

Companies that figure out how to satisfy customers will survive and profit in the 21st century. This article has shown how placing customer information front and center in the planning process can produce dramatic results and transform the way a company does business. Research managers, key cogs in the wheel, are in a unique position to offer vital information and answers.

References

Naumann, Earl and Steven H. Hoisington. 2001. Customer Centered Six Sigma: Linking Customers, Process Improvement, and Financial Results. Milwaukee: ASQ Press.