{"id":5035,"date":"2017-04-05T14:02:52","date_gmt":"2017-04-05T18:02:52","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-digit\/submission\/can-data-save-us-all-lessons-from-attempting-to-transform-sears-and-kmart-through-data-analytics\/"},"modified":"2017-04-05T14:02:52","modified_gmt":"2017-04-05T18:02:52","slug":"can-data-save-us-all-lessons-from-attempting-to-transform-sears-and-kmart-through-data-analytics","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/can-data-save-us-all-lessons-from-attempting-to-transform-sears-and-kmart-through-data-analytics\/","title":{"rendered":"Can Data Save Us All? Lessons from Attempting to Transform Sears and Kmart through Data & Analytics"},"content":{"rendered":"

Disclaimer: I worked at Sears Holdings from 2013 to 2015. <\/em><\/p>\n

Data and analytics are often heralded for their ability to transform business \u2013 making companies smarter, faster, more collaborative, and better able to serve customers. Yet from my experience working in targeted marketing and data analytics at Sears Holdings, I know that data\u2019s promise isn\u2019t always delivered, and I wanted to offer some lessons from my experience.<\/p>\n

To set the context \u2013 Sears Holdings launched its ShopYourWay rewards program in 2009 as a customer loyalty program designed to facilitate customer purchases across online and in-store channels and across retail brands such as Kmart, Sears, and Lands\u2019 End.[1]<\/a> By the time I joined the company in 2013, ShopYourWay members represented 65% of total sales pof over $36 billion in the fiscal year ended 2014 and were involved in over 100 million transactions each year.[2]<\/a> In the four year history of ShopYourWay, we had amassed a unique data set, tagging individual people to specific SKU shopping behavior (not merely total basket data) gathered from purchases both online and in store.<\/p>\n

Where We Succeeded<\/strong><\/p>\n

Using data to communicate with shoppers more effectively and remind them of our value proposition \u2013 Driving from segment insights to more granular individual-level insights<\/span><\/p>\n

One of the most successful programs we implemented was a targeted marketing campaign around bringing back shoppers who exhibited a change in their frequency of shop. This \u201cmember reactivation\u201d campaign generated millions of dollars in weekly incremental transactions (as measured against a control group). From there, we constantly monitored shopping behavior to manage the profitability of individual members and maintain their shopping behavior. Furthermore, we moved from a baseline of a single customer segment of customers who hadn\u2019t shopped in a few months to a RFM (recency, frequency, and monetary value of shop)-driven model with over 100 customer segments with targeted offers to each segment based on the behavior we hoped to promote.<\/p>\n

Where We Failed<\/strong><\/p>\n

Our data strategy did not align with our corporate structure<\/span><\/p>\n

When I joined the company, ShopYourWay\u2019s data-driven marketing was being hailed as the center of the company\u2019s transformation efforts. The fiscal 2012 10-K stated Sears was \u201ctransitioning to a [ShopYourWay] Membership company\u201d.[3]<\/a> However, our internal organization was not organized with data and analytics at its core \u2013 instead we had a matrix structure of business units representing categories (e.g. home appliance and grocery), selling channels (e.g. online and store operations), and data operations (e.g. ShopYourWay).<\/p>\n

Most importantly, ShopYourWay member data was owned within a distinct business unit which provided analytic services to the other business units, complete with internal charge structures that impacted business unit P&Ls. The motivation was for the ShopYourWay analytics team to prove their value to the organization, but the outcome was an acrimonious relationship between the data science team and the operational business units. It would have been far better to share the data openly given data and analytics were meant to be at the core of the company strategy.<\/p>\n

The purchase data we used reflected a subset of the entire customer experience, missing data undermined our delivery of a complete customer value proposition<\/span><\/p>\n

Our data analytics team mostly focused on transactional data and product-related behavior such as online browse paths. However, delivery of a full retail business value proposition depends on creating an experience for the customer, not just understanding the products they buy\/consider buying. Our corporate team should have augmented our transactional data with qualitative data from focus groups and surveys to understand customer motives for shopping our owned channels, as this may have helped us address key issues in our business model. Instead we simply focused our data efforts on creating better merchandising and promotion, and perhaps missed out on opportunities for us to support other important elements of the customer experience based on data insights.<\/p>\n

Conclusion<\/strong><\/p>\n

At Sears Holdings, our focus on customer data allowed us to drive significant results for the business. Ultimately though, we were limited by the scope of our data and the organization we built to execute on it.<\/p>\n

Going forward, I will remember that data and analytics are only as good as the latest insights generated from them, and that thinking flexibly and involving an organization fully in the culture of data creates the best opportunity for analytics to drive a business forward.<\/p>\n

[1]<\/a> http:\/\/comparerewards.com\/archives\/1123<\/p>\n

[2]<\/a> http:\/\/www.chicagobusiness.com\/article\/20130823\/BLOGS10\/130829907\/another-thing-that-hasnt-saved-sears-loyal-shoppers<\/p>\n

[3]<\/a> Sears Holdings 10-K for period ended February 2, 2013<\/p>\n","protected":false},"excerpt":{"rendered":"

Lessons from attempting to transform Sears and Kmart through data & analytics. <\/p>\n","protected":false},"author":450,"featured_media":5036,"comment_status":"open","ping_status":"closed","template":"","categories":[1031,647],"class_list":["post-5035","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-customer-data-analytics","category-retail"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/data-and-analytics-as-digital-assets\/","yoast_head":"\nCan Data Save Us All? 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