"Thank you for purchasing [Book A]. Other customers who were interested in this also purchased [Books B, C, and D]." This is the message that appears every time I purchase a book on Amazon. Oftentimes, I find these recommendations helpful as they become more targeted as I make more purchases through the site.
Now what if my bank could do the same thing? Analyze my personal information, prescreen that information to make offers that are relevant, and make these offers more targeted as my number of interactions increased? While Amazon may feature the Kindle as their premier product, I have never bought an ebook or any product that would give an indication that I would buy that product. I have, however, bought books on very specific topics, and many of the recommendations Amazon makes are for these niche interests. If banks could offer similar services, my likelihood of accepting prescreen offers would increase. Rather than offering their newest or most popular product to every consumer that walks in the door, they could instead make the offers that each individual consumer is likely to accept. Instant prescreen can be used to analyze customer data at the point of interaction and present the offer that the customer is most likely to accept.
Through instant prescreen, banks can provide the cure to various existing pain points. Just as I am likely to buy more books when the offers are relevant, I am more likely to accept cross-sell offers for financial products when they are relevant. This leads to higher acceptance rates, as well as increased wallet share. When I, the consumer, am made offers for products that directly relate to my needs/interests, I start to feel as if the bank knows me and is trying to help me succeed. This increases my customer satisfaction and loyalty to the institution. Just from this solution the bank has conquered three classic issues: increasing acceptance of cross-sell offers, increasing wallet share, and increasing customer satisfaction.
This win-win interaction happens at the point of interaction. Once the consumer has identified themself, the bank can analyze all consumer information against criteria for their products and find which product is the most relevant to the consumer. By making a tailored offer to each consumer, the bank can capitalize on the interaction by making the most appropriate offer and consumers are offered the product that is the best fit for them and will provide the most benefits.
Just as Amazon uses all of my interactions to make the most personalized offer, banks can do the same thing. By incorporating and connecting as many channels and lines of business as possible, banks can gain a plethora of information. Especially when products or services are offered that are used extensively on an individual basis, like personal financial management tools, banks have the opportunity to gain additional insight into the goals and behaviors of their consumers. While these services may require additional infrastructure, they provide valuable insight into what consumers value. When banks have this level of insight they can make highly specific, targeted, relevant offers, leading to an even higher rate of acceptance of offers among consumers.
Through prescreen, banks can alleviate some of the frustration that comes from customer service representatives (CSRs) unsuccessfully offering products day after day. In fact, they can provide a way for the CSRs to make offers that are more likely to be accepted and leave customers with a positive, rather than frustrated, image of the bank.
