Who is Minding the Customer Expectation Gap?

The customer expectation gap is nothing new. Simply put, the gap is the difference between what a customer expects from an interaction and what they actually receive. Expectations are subjective and based on many things like: past experience, family, lifestyle, personality, demographics, life stages, behaviors and more. So, no two consumer expectations are the same.

Another driver of expectations is the growth of high touch retailers. These retailers focus on consumer intimacy and consistent experience across the client touchpoints. In order to do that, retailers are leveraging business analytics. Lastly, consumer acceptance of alternative delivery channels have added a new dimension to minding the gap. Consumers view these new channels an extension of the organization.

The bottom line – consumers expect, and want recommendations from retailers they do business with. They want to feel they are understood and to see offers and communications tailored to their needs.

For years financial institutions have relied on a “one size fits all” communications strategy. That won’t work any longer. In fact, making recommendations that aren’t targeted to the individual consumer could cost you relationships. To be successful, financial institutions need to understand their clients by leveraging the tremendous amount of data they already have about them. The need for minding the gap grows exponentially for those retailers who deliver commodity products and services. When the product and price are in parity, experience becomes a dominant driver that influences purchase.

Where to begin? Start with your customer. Understanding their unique needs and behaviors is necessary to close the gap. While business analytics solutions have been available since the 1980’s, the industry has been slow to embrace the technology.

Business analytics is key to understanding the customer and identifying needs and opportunities. Analytics allows the financial institution to aggregate client account data from disparate systems into a single database. Data enhancements like demographics and behavioral models are overlaid and profit assumptions are added to enhance the information. Finally, account data is rolled up to individual customers and then households they are associated with. From here business analytics turns data into information that can be used to narrow the customer expectation gap.

Leveraging analytics, financial institutions are tailoring messaging and product offerings. Think about your interactions with retailers and institutions you do business with. Using business analytics, web click tracking, behavioral and geographical data, Amazon makes recommendation and suggestions during every interaction. Disney is tailoring guest experiences daily. By monitoring activity in the parks combined with 3rdparty data enhancements, Disney can make recommendations in real time.

It starts with segmentation, the process of dividing the customer base and market based on similar characteristics. A segment needs to be a clearly identifiable group with common characteristics that drive similar behaviors. It should be large enough that it will cover the costs of communications. The group must be able to be reached.

Financial institutions have segmented their client base using a variety of schema. Geographic Segmentation is often used in cases where the institution operates in multiple counties, regions or states. Demographic segmentation divides the client base on variables like age, gender, presence of children, occupation, education and so on. Demographic information is readily available and an inexpensive way to enrich client data. Psychographic Segmentation is used to subdivide based on lifestyle factors.

Which clients have the highest propensities to purchase specific products? At what channels do clients prefer communications? Who are your best prospects for investment services? Where is there attrition risk? Which relationships are most profitable and how to grow existing relationships? Business analytics will uncover information like this and more. With this information we begin to close the expectation gap and increase success in marketing campaigns.