Modeling for Better Customer Insight
In practice, that has not always turned out to be the case.
It is true that understanding more about your customers improves your chances of offering the right product or service. But simply gathering data is not enough. Marketers need a framework to transform data into information that can be used to predict customer behavior, a key to strengthening the relationship between company and customer throughout the customer's lifecycle.
Behavioral modeling can outline that framework. At a minimum, it can be used in the following ways during a company-customer relationship:
Upsell and cross-sell. Behavioral modeling helps determine which products/services each customer is most interested in. Upselling and cross-selling, when done correctly, can bolster a relationship as the customer displays more trust in your company by allocating a greater share of its overall spend to you.
One method of behavioral modeling - response modeling - is the bread-and-butter method of guiding you in upsell/cross-sell decisions.
Response modeling uses historical data to develop profiles of buyers and non-buyers for each product/service. These profiles can be applied to each of your current customers. Using historical buy rates for each profile in the model, the likelihood of purchase can be calculated for each customer/service combination. This lets you make the most relevant offer for each customer. Using tenure as a key element in the response models will help determine timeliness of offer.
Along with helping target offers correctly, response modeling allows general profiling of your customers. These profiles paint a picture of your different customer groups, helping you tailor offer messaging and creative.
Upsell and cross-sell are the lifeblood of any business and the key to sustainable growth. Using behavioral modeling to determine the best offers is the most efficient way to execute your upsell and cross-sell programs.
Retention modeling. If upsell and cross-sell are the fuel for your business, then customer retention is the preventive maintenance that keeps your business out of the repair shop.
It has been proven time and again that keeping a customer is far more efficient than replacing lost customers with new ones. Therefore, identifying what keeps customers around and what drives them away is a vital business practice. You can find these answers in your customer data through retention modeling.
By contrasting customers who left you in the past with your most loyal customers, retention modeling can discern attributes that identify and define both groups. Data from across your business - such as demographics, purchase history, channel preferences, customer care and billing activity - can help identify the differences between the two groups.
Using retention modeling, you also can identify trigger points for customer attrition, which might include a customer/technical service issue or cumbersome billing procedures. The model not only identifies trigger points, but measures the financial effect of a change in the occurrence of those triggers. Your retention model lets you take action to minimize these difficulties and develop plans to retain customers when problems occur.
A good retention model also identifies actions that make your customers more likely to stay with you. Once identified, you can implement these activities with your most valuable customers, strengthening customer loyalty.
Finally, ranking your customers by risk of leaving, your retention model will help focus retention dollars on those customers that truly are at risk, saving you from spending precious resources on those who are likely to stay with you through thick and thin.
In summary, using behavioral modeling can help focus your activities on your most relevant customers. By doing so, you'll bolster your relationships and improve your bottom line.