To improve sales efficiency, our client needed an “At-a-Glance” customer segmentation model that could evolve with their business.
As an international agriculture services provider, our client’s B2B customer base has grown exponentially over the years. Because of this expansion, their customers’ preferred products, services, and range of buying habits have also grown, making it difficult for their sales teams to quickly assess which customers were likely to be long-term buyers, which would need the most help on their journey, and which could be converted away from the competition.
To help their teams be more efficient while providing the best service possible, our client wanted to build an At-a-Glance customer segmentation model.
From both the client’s long tenure in their industry and the broad customer base, the number of variables for segmentation posed a challenge.
While primarily a tool for the sales teams, the final segmentation model would affect several departments, requiring significant collaboration and alignment on goals and definitions.
Though leadership understood the need for such a tool, they had attempted similar initiatives before, with the new tools sitting untouched and ultimately growing outdated, thanks to low adoption by the intended end users.
Our client had heaps and heaps of customer data in an ever-evolving industry. This meant that there were infinite ways to slice and dice potential customer segments. However, it also meant that segmentation done this year could potentially need an update in a few years’ time.
Key to developing this model would be collaboration and inter-departmental cooperation between all stakeholders and end users. To facilitate this, we conducted individual interviews and led a cross-functional workshop to bring everyone together to align on and refine the model.
[Read more: Growing Revenues through a Data-Driven Pricing Strategy]
Our final model consisted of three customer segments with only twelve easy-to-understand variables across four key areas of the business.
We used stakeholder interviews and surveys to gather qualitative customer data, as well as understand the sales teams’ goals and strategies, to ensure we had an accurate picture of how this segmentation would be used.
With this qualitative data, as well as quantitative sales, demographic, and other customer data, we crafted an initial version of the segmentation framework to present and iterate upon.
Through an in-person workshop, we presented our segmentation model, defined operational definitions of various customer attributes, refined areas of the model based on feedback, and aligned key stakeholders on usage and how to drive adoption within the organization.
The final segmentation model was delivered after carefully considering all feedback and could immediately be used by the sales teams.
Our model accounted for twelve variables in four categories that then translated into three separate customer tiers, which could be used to design marketing outreach and sales efforts, and better target new leads. This simple model could be read at a glance, while still providing critical information about a new or existing customer.
We also identified five key variables to serve as “trigger points” to evaluate whether a customer is in the correct segment. When any one of these five variables changed, it automatically moved a customer from one segment to another, allowing the sales teams to be flexible in their pursuits while remaining data driven.
By ensuring that all stakeholders felt heard during the extremely collaborative process, and with additional training held during the workshop, the path was laid towards high adoption of the new segmentation model.
With these variables identified, and new data being collected, we also laid the foundation for a next generation version of this segmentation model that would be AI-enabled to provide even greater customer insights.
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