14 Analytics Case Studies for Retailers

Carrefour & Esri’s ArcGIS

Carrefour Group is a world leader in distribution and retail with more than 15,000 company-operated or franchised stores. It implemented a worldwide platform for geomarketing using Esri’s ArcGIS platform together with Galigeo’s Location Intelligence software. The solution combines key business data with spatial location to improve store performance through better marketing decisions. ArcGIS, combined with solutions such as Galigeo’s, assists people with different geospatial analyses. It helps people at all levels make decisions, ranging from the store manager who needs reports to operate the store, to the expert in charge of the site selection. By representing and displaying business intelligence on maps, businesses can identify hidden trends,customer relationships and behavior, as well as enable a deeper marketing analysis and thus improve business outcomes.

JC Penny Optical & SEER Interactive

JCPenney Optical, the one-stop shop for family eyewear in JCPenney stores, wanted to increase its in-store sales and brand awareness. Working with SEER Interactive and partner U.S. Vision, the retailer focused on the digital campaign for the April 2014 Spring Collection. JCPenney ran Lightbox Ads and YouTube TrueView ads across the Google Display Network to reach a broad audience. To help boost its mobile presence, it adjusted bids to ensure that ads were prominently featured on mobile devices. Their efforts resulted in an 830 percent increase in online exposure and a 285 percent rise in conversions.

Marks & Spencer & Tibco Spotfire

Marks & Spencer started using Tibco Spotfire for better decision making with proper insights into the available data. In the dot-com side of the business, Spotfire was used for problem solving, supply-chain analytics, analyzing historic data, and forecasting. In IT, Spotfire was used to manage infrastructure and provide data quality improvements; in the supply chain it is more generally used to forecast levels of demand for food and non-food items at individual stores; in other departments, it is used to quickly test the results of decision making and to build analytical models. The retailer is currently looking to broaden its scope to integrate less traditional sources, such as HR data.

Staples Canada & Leger Metrics VOC platform

Staples Canada adopted Leger Metrics' next-generation VoC platform, which offered flexible, customized reporting to view sophisticated insights into the customer journey based on the retailer’s specific needs and infrastructure. With Leger Metrics, Staples Canada implemented multiple in-store surveys, each with separate invitation protocols, questionnaires, and reporting. This gave stakeholders a better understanding of the customer experience within its core retail channels, including general office supplies, copy & print and easytech departments. The ability to quickly add and alter surveys, look at various aspects of the business independently, and roll the feedback data together to compile one customer satisfaction score, empowered Staples Canada to ensure the customer’s voice was at the forefront of every business decision.

ToysRUs & ESV Digital

ToysRus wanted to maximize their Return on Investment (ROI) and minimize Cost per Click (CPC) while exposing their product range to potential clients through Google and Bing. ToysRUs partnered with ESV Digital to arrive at a solution. ESV Digital started by testing most of the product categories, which helped them identify which keywords generate the most traffic with minimum CPC. After the test period they learned that focusing on best sellers and known brands generated the most traffic. However, good keywords are also often expensive, and the CPC increased higher. Focusing on specific keywords, ESV was able to minimize CPC, while increasing both the ROI and the resulting high traffic rate. With a product feed, they were able to promote only products that were actually available in-stock which increased the probability of conversion. The analysis led to the decrease in CPC by 30%, as well as a significant increase in the conversion rate, and increased sales by 879%.

Hallmark & QuantiSense

Hallmark used QuantiSense to better manage and analyze the retailer’s large data set. Before using Quantisense, Hallmark retail analysts had to run each report one by one, then had it processed and answered before they ran the next one. The team had to access report after report to get to the final findings. Due to this, the report processing speed was very slow. Often, it took 30 minutes to generate an answer. To overcome this, Hallmark used QuantiSense and loaded the data warehouse on its Teradata machine and sourced and loaded all retail data history which helped Hallmark in defining the metrics and creating basic reports and dashboards. The biggest benefit was the speed of being able to build a retail data model with over 300 metrics and a set of base reports that they used along with the metrics to create their own new reports. Quantisense helped the company’s ability to speed up the process of generating reports for better decision making.

Hudson’s Bay Company & QuantiSense

Hudson’s Bay Company has also selected QuantiSense retail analytics and business intelligence application to help standardize the company’s enterprise-wide approach to inventory accounting. Hudson’s Bay Company is Canada’s largest diversified general merchandise retailer with more than 600 retail locations across the country under the banners Zellers, the Bay, Home Outfitters, and Fields. The company’s North American parent company, Hudson’s Bay Trading Company (HBTC), also owns and operates Lord & Taylor, the well-known department store located in fine malls across the United States. The QuantiSense solution will source data from Hudson’s Bay Company’s existing Teradata data warehouse, which serves more than 4,000 users, as well as from Retek and SAS’s planning solution.

Coalgram & Nomi

Colgram, with the assistance of Nomi and SkillUp’s FollowUP solution, helped the company to receive highly accurate real-time metrics and reports on in-store occupancy, traffic paths, and more, giving store managers the insight they need to make better decisions related to staffing, service, and other key areas impacting retail performance. Previously, Colgram was using infrared beam technology to count shoppers entering or exiting their stores, but the retailer found that the data which was captured was not accurate, not comprehensive, or not timely enough for it to support its evolving analytics requirements. In particular, Colgram wanted a solution that would distinguish between adults and children, so that parents shopping with kids would be counted as a single shopping unit, rather than independently. The sophisticated real-time data capture capabilities, provided by Nomi, combined with the granular analytics and reporting provided by SkillUp’s FollowUP solution, gave the company immediate access to accurate information about store traffic and allowed them to count children and adults as a single shopping unit, and understand other key metrics.

Otto & Blue Yonder Predictive Analytics

Otto wanted to manage large data volumes in online retail commerce which had to be handled in a profitable way. Blue Yonder Predictive Analytics software assisted Otto to exploit its data volumes. OTTO is a German multi-channel retailer which successfully mastered the transition from a classical mail-order retailer to an online retailer by permanently adapting its business processes and by successfully reorienting its enterprise with analytics. Today, Otto focuses on its online business, accounting for 80% of its annual sales of over 2 billion euros. One of the basic prerequisites for this positive development is the company‘s very extensive product offering. Alongside fashion items and technical products, OTTO also sells furniture, sports articles, shoes, and toys. The online shop has a total of about 4,000 brands and more than two million items.

Argos & Brandwatch Analytics

Argos, with over 123 million store customers per year, had a large chunk of social data for managing, dissecting, and understanding the volume of conversion. With Brandwatch Analytics, Argos was able to implement rules to categorize the data by store sentiment. By implementing Brandwatch demographics, Argos was able to segregate data by gender, profession, and location. Eg: Brandwatch demographics identified that men and women reacted differently to the new digital stores. Overall, men seemed to approve of the digital change and were especially interested in the high-tech features. Women, however, spoke more positively about the new approach to customer service. Equipped with real time insights, Argos could quickly understand which stores were performing well and which elements of the new digital stores customers loved and what elements they weren’t so keen on.

Croma Retail & Infinite Analytics, a subsidiary of Tata Sons, has tied up with MIT – backed Infinite Analytics, Inc. (IA) to provide personalized recommendations to its online users. IA’s personalization platform has allowed consumers to discover related and new products serendipitously, based on an understanding of the user, the product catalog and the contextual data.

With a broad range of products and categories, the key challenge for is to help the site’s users effectively and seamlessly navigate through the store to discover what is most relevant to them. Infinite Analytics uses a multi-dimensional approach to personalization. One of the key benefits over other solutions is that implementation for Infinite Analytics customers has been anywhere from four hours to two weeks because it doesn’t rely solely on historical data.

Neiman Marcus & MarketShare

Neiman Marcus is using MarketShare’s advanced analytics technology to generate more customer-focused marketing, while also seeking to:

  • Combine and evaluate online and offline data
  • Model behavior at the individual customer level
  • View attributed sales for all order channels, including stores, web, mobile, and call centers
  • Understand how best to target catalog drops to drive sales and clearly see the effectiveness of each marketing channel and how they performed comparatively.

Kroger & Irisys’s QueVision

Kroger began using analytics to evaluate and improve operations in 2007. In 2010 the team implemented a project aimed at in-store pharmacies that would cut down on out-of-stock items, improve the customer experience, save money, and increase revenue. To date, they have reduced inventory by $120 million and the number of out-of-stock prescriptions by 1.7 million.The effort has realized $10 million in annual savings and $80 million in increased revenue. Another major breakthrough for Kroger analytics was using the QueVision solution, a data analytics package that combines historical shopping data with real-time information about the number of customers in the store and infrared camera technology that counts the number of people waiting in line. Once certain thresholds are reached, managers are alerted to open new checkout lanes.

Kohls & In-Store Technology

Kohl’s is using an indoor positioning system that walks the aisles with customers. This mobile-based technology allows shoppers to opt in for promotions as they enter the store. Throughout their visit, people receive lifestyle content in real time based on the products they appear to be looking for. The CRM strategy of Kohl’s led to the Big Data which Kohl’s could use to learn their customer’s and their preferences. The company knows what the customer purchased in the past, and with its in-store technology the company can track the customer’s behavior as they move through the aisles.