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Case Studies

Discover how we are helping organizations use data analytics for evidence-based decision making to improve marketing, guide their high-level strategic planning and drive operational improvements.

 

 

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Part of the world’s largest retailer, Walmart Canada was established in 1994 and has grown to more than 400 locations serving over 1.2 million customers daily. Its online store, walmart.ca, draws 600,000 customers daily. And with more than 95,000 associates, Walmart Canada is one of Canada’s largest employers and ranks among the most influential brands. 


  • “The project has shown that there is a wealth of information available about customers beyond in-house databases that can be leveraged in innovative ways throughout an organization.” 

    —Tom Maryniarczyk, Director of Site Experience & Analytics | Walmart Canada

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Challenge

Before launching a nationwide online grocery business, Walmart Canada wanted to better understand the shoppers who had been using the service in test markets so they could extrapolate and apply the results to other markets. For such a major project the retailer wanted to anticipate their customers’ behaviour and predict sales from the new service at an individual store level. The analysis needed to be grounded in data so that executives would be confident in their decision to expand the online grocery program and the major investment it entailed. In particular, Walmart Canada wanted to know if there were any common demographics, behaviours, lifestyles and attitudes exhibited by online grocery shoppers in both the test markets and markets across Canada.

 


Solution

One-NoText

Drawing on the PRIZM5 segmentation system, analysts examined the behaviour of Walmart’s online grocery customers in its test market stores over an eight month period. After linking lifestyle and transactional data to consumers’ postal codes , researchers identified the best performing lifestyle segments, their demographic profile, preferred purchase categories and level of loyalty.

 


 

The second step is analytics


Our analysts then developed an innovative machine learning model that identified a unique combination of five variables—from more than 70 that were evaluated—that proved effective in predicting online grocery order volume at the individual store level. The analysis indicated that Walmart’s most loyal and frequent online shoppers tended to be higher income, diverse and living in urban and suburban communities.

 

 


 

Step three is actionable outcomes


Walmart then prioritized the roll-out of the new service according to the lifestyles and demographics of each store location’s customer base. In addition, marketers used the insights from the analysis to develop more targeted messaging for print media campaigns.

 


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Results

Walmart Canada’s online grocery expansion was a strategic and financial success, with annual sales in 2016 exceeding the company goal by more than 40 percent. Building on this initial achievement, Walmart stated expanding the program to more cities in 2017. At the same time, executives are using customer segmentation insights from the project to refine offerings beyond online grocery and to optimize day-to-day marketing. Analysts now examine online sales by PRIZM5 segment daily and integrate the results into the company’s CRM database for email marketing and customer profiling by commodity and category. Walmart Canada has also created an in-house data science team dedicated to predictive analytics and forward-looking data for planning and allocating resources.