Success in B2B sales has little to do with individual behavior and professional selling skills. It depends on sales leaders’ ability to set the right direction and to empower the organization with the right tools. One tool is a customer segmentation and targeting model. Here are three steps to help you build a successful customer segmentation and targeting model.
As an experienced sales leader, you have probably faced multiple challenges over the years. One challenge is to continuously meet your revenue growth goals. If goals are not met, sales leaders need to face the consequences. Besides the obvious financial loses, there are hidden costs such as time and resources wasted and the motivational impact on the sales team, just to name a few. What do you think is the main reason why your organization does not achieve its revenue goal?
Despite customer claims (or excuses) that prices are too high, you know your sales team is doing the wrong business with the wrong companies. In reality, many deals are lost because: 1) traditional salespeople with standardized offers meet buyers who seek customized products or services and 2) sales teams invest time on customers with no future revenue potential.
The problem is sales leaders rely on generic and limited segmentation and targeting models that treat all customers as one homogeneous mass. Unfortunately, the vast majority of sales organizations still utilize demographic data –such as size, location or industry sector –as the only factor to segment and target customers. While a model with demographic information is useful, it is incomplete. Here are two reasons why demographic data on its own is not enough and why you need a different customer segmentation and targeting model:
1. Not all customers buy in the same way
Let’s suppose you scan your territory and identify two SMEs in the IT and Telecom industry. Should you engage with both customers using the same B2B selling approach? It would be naive to assume both SMEs make purchasing decisions in the same way. As a matter of fact, chances are they behave differently even if they appear identical on the surface. For instance, one customer can make buying decisions based on your ability to customize your offer, while another one can focus on finding the lowest priced supplier. Even the same organization can shift its purchasing behavior depending on the risk and the complexity of the purchase.
2. Big data and analytics allow for smarter segmentation models
Moreover, why limit your analyses by carrying out segmentation according to demographic data on its own, when you can have a more comprehensive description of the segment to target. In today’s digital B2B environment, characterized by abundant data and modern analytic tools, sales organizations cross-reference data from a variety of sources within the organization (ERP, CRM, etc), as well as external data (social media, web analytics, location-related data, etc) to expand their segmentation model and gain an edge over competitors.
In fact, findings from Nordic Sales Analytics show that leading sales organizations are 5% more prone to use sales analytics and use multiple sources to improve customer segmentation efforts.
Moreover, sales organizations are increasingly implementing a more granular approach to customer segmentation and targeting. Known as micro-segmentation, organizations explore customer data, in detail, in order to discover additional buyers, identify the most/least profitable customers, target customers with the greatest potential and/or recommend complementary products/services. The trends of exploring multiple data sources and discovering micro-segments enables sales leaders to increase their chances of sending the right sales person to right customer with the right offer at the right time.
So what can you do to build an effective customer segmentation and targeting model? Here are three steps for getting you started:
Having outlined the three points in the checklist let me now elaborate on each of them.
1. Segment customers based on purchasing behavior
Begin by understanding how customers make buying decisions. Do they focus on price, performance and terms of delivery? Are they looking for standardized or customized products and/or services? Are they willing to collaborate and invest time and effort?
2. Focus on customers (new and current) with the greatest future potential
The next step is to focus on customers with the greatest potential and where your organization has the best opportunity to win. In this phase, trusting your instinct can be good, but it can also be devastating. Instead, we recommend to apply a systematic and data-driven approach to find those customers with the greatest potential. Not sure how to identify customers with the largest future revenue potential?
3. Match purchasing behavior with the corresponding sales logic
Last but not least, align sales resources and sales activities with the purchasing behavior. After all, sales approaches that work for buyers seeking standardized offerings, do not work for buyers seeking customized ones. Make sure to divide your sales force into two organizations: traditional and complex sales. Finally, decide which sales organization is more qualified to meet customers’ needs and demands. The purpose of splitting the organization in two is to treat each unique customer they way they want to be treated. If done properly, it enables sales organizations to send the right salesperson on the right opportunity with the right support. Want to learn more on the different types of sales logics that you need to take into consideration?
Keep in mind that its always better to get started than to wait until you find the perfect customer segmentation model.
To learn more about how Prosales and Membrain combined to help Scania Mining transition to the complex sales logic, download the case study.
Jorge is a Trend Analyst at Prosales Institute, providing sales leaders with information on the latest developments in the business-to-business environment and recommendations for strategic and operational decision making. With a solid research department collecting data from hundreds of companies and their staff, Prosales produce knowledge based on facts rather than assumptions. The clients of Prosales use this knowledge to benchmark their performance and to analyze their position. The scientific approach combined with experienced consultants has made Prosales clients reach better results, when turning strategies into sales effectiveness.