In my last blog post on this topic, I argued that banks need to think differently about customer acquisition if they want to compete effectively without incurring prohibitively high operating costs. I think there are a couple of core pillars that should comprise a modern customer acquisition strategy. The first pillar—increasing the profitability of your existing customer base—has been covered in part one of this blog series. The second pillar
—intelligent acquisition of new customers—will be the focus of this blog post.
While it is critical for banks to get as much profit out of their existing portfolios as possible, it is also important to grow through the acquisition of new, profitable customers. The problem is finding them.
According to a recent CEB TowerGroup Webinar that I attended, the distribution curve of Americans’ FICO scores has shifted significantly to the left over the last 6 years. This kind of shift is perfectly natural during economic recessions like the one we just experienced. During that time, many credit worthy consumers experienced a crunch as their economic foundations (home value, job security, etc.) were shaken. As a result, many of those consumers saw a big drop in their FICO scores. As we start to emerge from the economic crisis, these consumers’ demand for credit (and their capacity to handle credit) is increasing. This presents a dilemma to financial institutions. A lot of these consumers are good credit risks and very profitable customers (as long as external economic factors are strong). You want to start building relationships with these consumers. The problem, once again, is finding them.
Some financial institutions are taking the shotgun approach to solving this problem. If the 500–650 FICO score ranges are where all the previously high score consumers are, then they send batch mail product offers to all consumers in those score ranges. While this approach will scoop up some of these “diamonds in the rough”, it will also scoop up a lot of ore. This process is not cost effective and it opens up financial institutions to unacceptably high risk.
A more targeted approach can yield the same value without the risk. The trick is to identify potential customers who your competitors don’t pursue because of an imperfect understanding of their value. The analogy I like to use here is from the movie Moneyball. For those of you who have not seen it, Moneyball is about the Oakland A’s innovative use of baseball statistics (sabermetrics) to identify baseball players who were undervalued by traditional, subjective scouting techniques. This use of sabermetrics allowed the small market Oakland A’s to cost-effectively compete with bigger market teams like the New York Yankees.
Just like the Oakland A’s, today’s banks have access to all the data and analytics that they need to play moneyball. I like to call it profitmetrics—the realtime application of cost, channel, risk, and profitability analysis in customer acquisition.
In the same way that sabermetrics helped innovative baseball teams find undervalued players, profitmetrics could enable banks to identify consumers who their competitors wrongly undervalue. Consumers who went upside down on their mortgages, but always pay their credit card bills on time; consumers who lost their jobs during the recession, but have since gotten back on their feet; consumers with professional licenses (doctor, lawyer, CPA) who habitually pay late, but always pay their bills because they can’t afford the reputational risk of a bankruptcy. These micro-segments of low-risk, profitable consumers tend to be excluded by the simple score cut-offs and traditional credit data used by many financial institutions. As a result, these consumers are not oversaturated with product offers. However, they want and deserve to be marketed to and are thus much more likely to accept product offers from banks that have a true understanding of their value.
Financial institutions can compete for new customers without driving their operational costs through the roof. By investing in technology that can facilitate realtime access to alternative data and advanced analytics, banks can create more intelligent customer acquisition strategies.
