Four of our five senior team members started in B2C, and all five have developed deep expertise in the area. However, Wheaton Group has been working intensively with B2B clients since 2001. As a result, we understand that B2B and B2C are totally different. We know that, from a data management and analytical perspective, B2B is often much more difficult than B2C. For example, who is the customer? Is it the individual, the location or the overall organization?
The fact is – it is all of the above. Organizations do not buy, people do. But, organizations – both headquarters and the other individual locations – have a lot to say about what, and how, the people buy. All of these complex relationships have to be sorted out, tracked, analyzed and understood. To do this well requires extensive experience.
Selling to Institutions such as schools is, in many ways, B2B selling. However, there are unique characteristics about B2I that often trip-up marketers. We have years of experience doing data-driven marketing within B2I environments. For example, we have worked extensively with multiple clients whose collective target markets span the Education Industry, including Pre-school, Kindergarten, K-12, Continuing Education, and Self-Education.
Our expertise in B2B and B2I, as well as B2C, is valuable for hybrid clients. For example, one client thought that its target audience was B2C. However, the building and analysis of the client’s marketing database precipitated the following “chain reaction”:
- For the first time, customers could be defined and tracked at multiple, linked levels; that is, at the individual-to-household levels for B2C, and at the individual-to-location-to-organization levels for B2B.
- This supported accurate long-term value estimations (“LTV”).
- This revealed the presence of high-LTV B2B customers; customers who had previously been hidden within the client’s operational systems because many were sales professionals working out of their homes.
- This led to the addition of third-party data to the marketing database, to assist in the accuracy of a statistics-based predictive model to identify the likely B2B customers.
- This resulted in a multi-year effort to cultivate and grow B2B customers, and a corresponding dramatic increase in revenues and profits.