Walmart and Big Analytics

Executive Summary

eCommerce has become an extremely important part of the marketing mix with the increase of online shopping and access to technology and the internet. eMarketer tracks 180 companies and have reported a total annual retail eCommerce sales figure of $201 billion. Walmart is currently ranked third in total annual eCommerce sales at $13.5 billion (Zaczkiewicz, 2016). “From online activity to in-store purchases and social mentions, Walmart has more customer connections than any retailer in the world. According to Daniel Thorpe, Senior Director of Analytics for Global Customer Insights, the company sees 300,000 social mentions per week (Four ways Walmart uses analytics, n.d.).” This case study will highlight findings in relation to Walmart’s use of digital analytics and recommendations for their strategy moving forward.

Findings

DeZyre highlights key big data points for Walmart:

•          245 million customers visiting 10,900 stores and 10 active websites across the globe
•          Close to 300,000 social mentions every week
•          Walmart collects 2.5 petabytes of unstructured data from 1 million customers every hour
•          Walmart has exhaustive customer data of close to 145 million Americans of which 60% of the data is of U.S. adults and they track and target each customer individually

But how does Walmart use the big data? DeZyre provides the following insight:

•         The analytics systems at Walmart analyze close to 100 million keywords on a daily basis to optimize the bidding of each keyword
•          By incorporating big data into their overall strategy framework Walmart observed a 10% to 15% increase in online sales for $1 billion in incremental revenue

Bridg further breaks down exactly how Walmart tracks their customer’s lifecycle from their web data:

Mining Sales Data

“Data mining helps Walmart find patterns in their sales data that can be used to provide personalized product recommendations and promotional offers. They use a matching algorithm to discover products commonly purchased together or purchased in a particular sequence (The Walmart Big Data Case Study: Think Large, Act Small, n.d.).”

Connecting In-Store and Online Customer Behavior

“Walmart pulls data from common sources like clickable actions on their website, contact information from their e-club, and POS transactions, as well as from one-of-kind programs developed by Walmart Labs (The Walmart Big Data Case Study: Think Large, Act Small, n.d.).”

Personalized Email Marketing

“Walmart’s extensive inventory of actionable data has given their marketing teams incredible power in driving new revenue through best-in-class email marketing (The Walmart Big Data Case Study: Think Large, Act Small, n.d.).” Their email marketing includes personalized recommendations, time of spend and personalized subject lines creating a more intimate experience with their customers.

Conclusion

Walmart is a leading retailer for many reasons and their recent success can be attributed to their use of web data to drive strategy resulting in more online sales and conversions. One of Walmart’s strength is that they are open to new data and find new ways to use and manipulate what they have to find the right people at the right time while maintain personal communication with existing customers.

Recommendations

I think one of Walmart’s great opportunities (and most retailers) is within predictive analytics. I know most are using these analytics in some capacity and starting to scratch the surface but this information is so, so valuable.

Improve Customer Engagement and Increase Revenue

Predictive analytics allow retailers to manipulate variables to create environments that present the engagement most likely by a consumer. “This could mean signing up for a newsletter, clicking on a promotion or or some other form of engagement (Mehra, n.d.).”

Launch Promotions That Are Better Targeted For Your Customers

Predictive analytics help take multiple touch points into consideration – personalize promotions, targeted customer segments, browsing behavior – to provide the right promotion to the right customer (Mehra, n.d.).

Minimize Fraud by Proactively Detecting It

Fraud has been a huge issue with retailers in recent years with more hacks happening every day compromising valuable customer information. Incorporating predictive analytics can help utilize the information their website is gathering to actually prevent fraud. There are solutions available that take into account browsing patterns, payment methods and purchasing patterns to detect and reduce fraud (Mehra, n.d.).

Although predictive analysis is a newer solution and requires additional plugins the outcomes are extremely beneficial to any retailer in the eCommerce world. I think Walmart could benefit tremendously by continuing to evaluate these tools and implement when possible. 

References 

Four ways Walmart uses analytics. (n.d.). Retrieved November 21, 2016, from                http://www.sas.com/en_us/insights/articles/analytics/four-ways-walmart-uses-analytics.html

How Big Data Analysis helped increase Walmarts Sales turnover? (n.d.). Retrieved November 21, 2016,from https://www.dezyre.com/article/how-big-data-analysis-helped-increase-walmarts-sales-turnover/109

Mehra, G. (n.d.). How Predictive Analytics Is Transforming eCommerce & Conversion Rate Optimization.Retrieved November 21, 2016, from http://conversionxl.com/predictive-analytics-changing-world-retail/?hvid=352IDw

The Walmart Big Data Case Study: Think Large, Act Small. (2015). Retrieved November 22, 2016, from http://bridg.com/blog/walmart-big-data/

Zaczkiewicz, A. (2016, March 7). Amazon, Wal-Mart Lead Top 25 E-commerce Retail List. Retrieved November 21, 2016, from http://wwd.com/business-news/financial/amazon-walmart-topecommerce-retailers-10383750/