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Personalizing Customer Experience Based on Customer Needs

Personalizing Customer Experience Based on Customer Needs

Today’s savvy, well-informed customers want to do business with companies that know them and their business needs intimately. With this knowledge, companies can create personalized experiences that meet customer needs. But this means companies must dig deeper to learn more about what individual customers want and value.

It was this intent that drove Ferguson to transform its relationship model to focus more deliberately on the needs and expectations of their customers. By thinking outside/in, Ferguson hoped to effectively align account team resources, improve customer experience and ultimately increase profitability and share of wallet.

Solution

Armed with a wealth of detail about customers, purchase behavior and customer perceptions, Ferguson partnered with Walker, who used cutting-edge analytic techniques to develop a customer needs-based segmentation model. This segmentation approach identifies the unique needs of groups of customers.

Business needs addressed with this segmentation include:

  • Are there subsets of customers with unique needs and characteristics?
  • Who are these customers?
  • What are their needs? What is the basis for these needs?
  • How big are the groups?

Several types of measures are recommended to create a successful segmentation. Walker used the following inputs to build Ferguson’s model:

Metric Inputs

Walker’s solution used cluster analysis, statistical profiling, and predictive analytics to create usable customer segments and an automated typing tool to drive customerfocused decisions and strategies. Data from a customer needs assessment was run through industry-standard clustering algorithms along with post-hoc profiling algorithms. These analyses yielded five customer needs-based profiles.

Profiles

Using internal metrics, Walker then created a predictive scoring algorithm able to forecast segment membership for all customers.

RESULTS

The segmentation analysis that grouped customers based on their needs and expectations allowed Ferguson to take specific actions to improve customer experience.

  • Resource allocation: Sales leaders were able to match the right account team members with the most compatible customer profiles, allowing Ferguson employees to spend an adequate amount of time with customers.
  • Customer messaging: Account teams received profiles and information about needs for each customer in their portfolio. Team members were trained on how to deliver on customer expectations for each segment, creating a more personalized and unique experience for customers.
  • Marketing: Ferguson’s marketing team used the customer profiles in aggregate to tailor marketing messaging around the needs of customers in each segment.

Ferguson’s financial return on personalizing the customer experience based upon customer needs has been substantial. Test markets implementing the segmentation strategy have seen a significant increase in sales, combined with a lower cost to serve.

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