Simple Segmentation for Improved Sales
We live in an age of “big data” but sometimes this amounts to data overload. What we really need is more usable data that can translate into better customer service, improved sales, and greater profitability. One very effective way to organize data is to group customers or prospects into segments.
The old saying “birds of a feather flock together” is a simple way of describing the dynamic that people tend to group together with those of like interests and similar behaviors. Segmentation is just a way to find people (or businesses) with common behaviors so that marketers and salespeople can then approach each segment in an appropriate manner. These different approaches may show up in product design, media used, pricing or distribution design.
Bankers can gain tremendous benefits from even simple segmentation schemes that can help answer questions such as: How much time should be spent with a customer or prospect? How should the customer or prospect be contacted? And, when contacted, what should be communicated?
Consider small business segmentation. A bank may assign businesses into various fairly static segments based on industry type and sales size. By looking at their customer base, bankers may then see product demand patterns by segment and use that knowledge to fill in the holes for clients who likely need a product but don’t have it. Why does John’s portfolio within a segment only have a 10% penetration rate with treasury services products compared to Susan’s with 50%?
Sales people tend to sell what they know most about. With segmentation, every bank can unearth sales opportunities within their client portfolio. Once a segment demand analysis is in place, increasing sales could be as simple creating a target list or focusing on sales coaching. This is a quick and easy way to increase cross-selling right now but it can’t effectively be done without comparing apples to apples through the use of segmentation.
Segmentation can also help with prospecting. Not all segments provide the same value to a bank; some industries clearly outperform others in terms of bank profitability. It makes sense to focus on those businesses first and hold off calling on low-profit businesses. Second, by evaluating current client product holdings, it may help focus the discussion with prospects to those needs relevant to them. This “forewarned is forearmed” approach should not get in the way of consultative selling. Sales staff should always listen to their clients and prospects first. However, it pays in product sales to have a good idea about the needs of the segment prior to engaging in a dialogue.
Of course, sales size and industry can never tell the whole story. For example, factoring and asset-based lending is used heavily by the same group of industries, but the choice between them is psychological. What is the business owner or its chief financial officer most comfortable doing: managing receivables or handing them off? It pays to identify those key psychological differences and tune the sales force to ask the right questions. The first layer of segmentation is to identify the key opportunities for factoring or asset-based lending by looking at industry type and size. The next layer of segmentation is to identify credit quality since “A” credit clients rarely consider factoring or asset-based lending and “D” clients rarely get approved.
Besides static segmentation (e.g., sales size and industry groups where membership changes slowly if at all), there is also dynamic segmentation. A bank may wish to identify and actively manage these segments which are based on behaviors or circumstances. For example, customers with loans coming up for renewal in 180 days comprise a dynamic segment that banks often care a lot about. Active tracking can help improve renewal results by comparing portfolio renewal rates and reasons for non-renewal on a consistent and transparent basis.
Key dynamic segments should be defined by the bank and then tracked and compared. For example, companies that announce expansion plans should be called on by one or more lines of business as soon as possible. Should the bank subscribe to services that identify local expanding companies? If so, what are the processes that marketing and the sales team should follow to quickly grab those opportunities? Banks need to spend time identifying various key dynamic “triggers” or events that can lead to short cycle sales since the client or prospect has an immediate need. That immediate need requires quick action on the part of the bank or the opportunity dries up. That’s why it’s best practice to focus on a few key dynamic opportunities so that execution and tracking can be consistent and effective.
Some additional tools are available on the retail side of the house but the approach is similar. Static segments may be based on age by income or, even better, by psychographic profile. But adding more dynamic and behavioral data such as channel usage, number and age of children, magazine subscriptions (to identify interests) and other factors can significantly improve predictability of product purchase, balances and profitability.
By assigning the banks households to these segments, gap analyses may be performed on a segment, branch or portfolio basis. For example, banks will find disparities of product penetration rates by retail segment branch to branch. Segment X may represent high propensity for purchase and usage of home equity lines, but branches may have very different penetration rates. Three branches may have a 5% penetration of equity lines and four branches have a 20% penetration within the same segment. Simple coaching, combined with focused marketing, may be all that is required to move those three branches much closer to a 20% penetration rate.
Summing up, here are five suggestions for achieving segmentation success:
Household your consumer and small business accounts. If this sounds like starting at square one, it is. Yet, it always surprises us how many banks, even larger ones, are still looking at the individual accounts a customer has, not their overall relationship.
Append market data. Think about how much more you’ll know if you understand the customer life stages, buying habits and likely total financial wallet.
Take your house-holding to the next stage. Understand which of your consumers own small businesses and which of your small business customers have consumer accounts. Having this information enables you to penetrate your customer base more deeply and bring in all the banks services, not just those delivered by the line of business silo that manages the primary customer relationship.
Manage expectations. Any model is based on certain assumptions. The goal is to reveal opportunities and improve the probability of success, not to obtain perfection. Often the sales force, who may be the principal beneficiaries of your analysis, can become discouraged if the data is perceived as inaccurate. If you believe your model improved predictive accuracy from 60% to 80%, then communicate how you’ve provided better tools for the sales staff to achieve their goals but that the data still has limitations.
Keep it simple! That may seem like a contradiction when dealing with complex data. But complexity diminishes utility. Think of your internal customers, like sales or product management, and ensure they are fully involved in the development and maintenance of your segmentation process so that it is fully integrated with their day-to-day management routines.
Whether using static or dynamic segmentation, banks can have more relevant contacts leading to more sales and retention with their clients and prospects. This is not rocket science. But it does require discipline, follow-up analysis and day-to-day execution.
Mr. Hartfeil is a senior consultant at Austin, Texas-based Peak Performance Consulting Group, which specializes in retail, community, and small business banking. He can be reached at [email protected].