This blog is the final post of a 4-part series. You can read the first blog posts, here: 1. Get to Know Your Retail Customer: 2. Accelerating Customer Insight and Relevance; Improving your Customer-Centric Merchandising with Location-based in-Store Merchandising; and 3. Maximizing Supply Chain Agility through the “Last Mile” Commitment
Brick and Mortar Stores will Need to do it Differently to Stay Alive
In my last three blogs (Get to Know Your Retail Customer: Accelerating Customer Insight and Relevance; Improving your Customer-Centric Merchandising with Location-based in-Store Merchandising; and Maximizing Supply Chain Agility through the “Last Mile” Commitment) I painted a picture that showed an ever-changing landscape in retail, considering that consumers are more in control than ever, mobile (at least somewhat digitally mobile considering the pandemic) and socially connected. They are armed with more knowledge than ever before, as a result, four strategic pillars have emerged that have resulted as leading retailers and brands have deployed a data-centric strategy enabling a customer-first approach. The retailers and brands have integrated more tech (data, analytics, and devices) into every step of the consumer purchase path that is revealing an entirely new retail experiences – starting with production, replenishment and continuing into merchandising, marketing and on to fulfillment and returns— that has an opportunity (and challenge) to shape the customer perception.
The three pillars previously discussed: personalized interactions, customer-centric merchandising, and supply chain agility all share the same thread – all deploy a data-centric strategy enabled by an enterprise data platform streaming data at high volume and high scale, managing and monitoring diverse edge applications and providing data scientists with tools to build, test, refine and deploy predictive machine learning models.
With more than 78% of global retail sales projected to still occur in-store by 2023, traditional retailers are increasingly realizing that the brick-and-mortar footprint is a competitive differentiator and with this realization, they are reimagining stores morphing them from a simple place products to wait to be purchased to micro-fulfillment centers or in-store pickup locations as examples. Blended use brick and mortar enable better pricing and convenience to consumers than digital pure-plays, and physical stores now serve as micro-fulfillment centers—through BOPIS (buy online, pick-up in-store) or curbside delivery—and drive down overall cost-to-serve.
In-store customer insights and engagement opportunities are now possible using data captured from sensors, video, and beacons. This technology allows retailers to measure and respond in real-time to shopper behavior, measure geolocation, traffic, dwell times, and conversion metrics. For merchants, the ability to capture shelf, rack, table, and bin inventory levels allows them to prevent out-of-stocks (lost sales), monitor merchandising (display, pricing, promo, POG), meet compliance initiatives, and share these new insights with trading partners they may have. Traditional retailers now have access to an entirely new data monetization opportunity that many have been missing out on for years.
Cloudera recognizes ten top retail IoT use cases that are transforming brick and mortar stores, as you can see below, and they are transforming all aspects of the retail experience.
Reinventing Brick and Mortar is Delivering Fresh Customer Experiences
In my earlier blogs, we demonstrated some pretty remarkable benefits from the use cases associated with improving customer insight (producing relevant offer response time) or improving supply chain agility (saving nearly $21m/year in product delivery costs). This last use case looks at the pervasive amounts of waste the supermarkets generate, as it is estimated 43 billion pounds of food every year is discarded by supermarkets, according to a recent study.
Retail grocers are committed to doing better, but food waste is still such a pervasive problem that only one supermarket chain earned a B on the food waste “report card” recently issued by the Center for Biological Diversity. Just a handful of chains earned Cs, while the rest of the country’s most recognizable grocery stores scored Ds or Fs.
The leading global mass merchant—that scored highest in rankings—recognized a need to improve cold storage temperature fluctuations on grocery products, understanding that both high and low-temperature variations could lead to excessive shrink (waste).
This retailer deployed Cloudera DataFlow to tap real-time streaming data from thousands of cold storage sensors across its vast network of brick-and-mortar stores. The solution ingested and aggregated data from these temperature sensors with location and on-hand inventory data to predict, monitor, and respond to possible changes in perishable food products such as produce, dairy, and meat.
Predictive analytics allowed the retailer to proactively respond not only to product life cycle impacts, but also the potential risk of cold storage equipment down-time. Automating the closed-loop process using pre-built business rules and alerts gave individual maintenance teams and store department managers actionable instructions to ensure product freshness and reduce waste. The resulting application of streaming data and advanced analytics is expected to be a major contributor to improving freshness, reducing food waste, and cutting cold.
The benefits described in my last four blogs are realized through the Cloudera Data Platform that enables retailers and consumer goods companies to maintain their momentum and accelerate digital transformation by leveraging data from any source whether on-premises, cloud or hybrid platforms—powered by open-source technology. Cloudera delivers this data lifecycle solution through the Cloudera Data Platform, from edge to AI.
Look for more of my insight into Retail’s digital transformation at this link