The basis of the relationship between retailers and their suppliers across all channels is rarely collaborative, resulting in a typically combative approach on both sides. The retailer advocates for the shopper by negotiating lower prices, higher quality and better services from suppliers, which primarily want to make the consumer loyal to their brands. In successful trading partner relationships, the consumer sees the benefits and is loyal to the brand because she sees value in buying that product at that store. In less successful ones, the lack of collaboration results in mismatched messaging to the consumer, which diminishes the value of any offer or promotion and results in a situation where both the retailer and the brand lose.
The drug store retailer, whether stand alone or incorporated into another format, is unique in its relationship with some of its suppliers, particularly on the prescription side of the business. But when it comes to the remainder of the assortment, the issues and challenges are similar to most other merchants. Both could benefit from focusing their efforts on the customer and the extended supply and demand chains. This is where shopper-centric collaboration can help.
Shopper-centric collaboration is an approach designed to tackle these imperatives. It serves to streamline how retailers and suppliers conduct business and to deliver clear insights and more powerful outcomes. Shopper-centric collaboration works from a shared platform or portal, using retailer data to identify shopper behavior insights and opportunities for short-term performance and long-term growth. This collaboration process is based upon straightforward principles. Retailers and vendors must share a common platform so they can see and agree on the facts. Outcomes must be accurately measured and attributed to specific actions.
The very essence of shopper-centric collaboration is data and analytics. Data flows with the buying and selling of products, covering every aspect of the transaction, from date and time to variables including how often they shop in my store, was a coupon used, where are they on my value segmentation, did they buy because of a temporary price reduction or because the product was marked down, and what is their life stage? Collaborating on analytics also involves product ordering and fulfillment, shopper demographics and much more.
The lack or limited use of shopper-centric collaboration leads to a series of industry challenges, including misalignment of marketing investments, less than optimal understanding of the needs of shoppers, and an inability to create strategic partnerships with key partners for joint business planning. In addition, not sharing data in a consistent and effective manner leads to operating inefficiencies and increased costs, because the trading partners are not making decisions based on the same information.
Trading partners are demanding better insights and analytics so they can evolve past the “hard sell and negotiation” relationship they have with retailers in order to better serve the consumer. There are three key reasons for this, each with specific outcomes that lead to higher sales and/or lower costs for both parties.
To start, more shopper-centric collaboration around analytics ensures retailers and suppliers are working from a “single version of the truth.” Data needs to be consistent across the extended value chain to make fully optimized marketing and merchandising decisions. This includes the basic blocking and tackling of retailing such as temporary price reductions and flyers, as well as assortment decisions on what to list versus delist, and new product introductions.
More practically, both parties want to maximize their time together and focus on value-add discussions about new marketing campaigns and promotions that expand the joint business rather than level-setting the data to make sure decisions are based on the same information. In the drug store sector, this is critical because categories like fresh food and seasonal general merchandise, where there has recently been a categorywide expansion in assortment, requires different analytics than traditional departments.
For example, a prestige global beauty supplier wanted to better understand their new product launches and the impact on the category and the shopper. Previously, they would launch dozens of new SKUs several times a year and use every marketing tactic available to promote them. With shopper-based insights, they learned the trial and repeat levels of their product, how they compared versus the category (dragging or driving) and the overall contribution to growth, including shopper profiles by major urban center. This effort helped them take action that grew profitable sales for both the supplier and its retailers — while satisfying the needs of the shopper.
For both transactional and loyalty data, retailers and suppliers work with the same information to ensure that decisions are made with as complete of an understanding of the shopper as possible. Critical decisions like whether to delist a product require not only accurate movement data but the ability to match that information with which shoppers are purchasing the item and how it impacts their category behavior and overall loyalty to the retailer. For instance, there may be financial reasons to delist an item that are countered by loyalty insights that prove that, as a result of the move, there will be lost sales from the most profitable customers. Retailers clearly do not want to leave their best customers in the lurch looking for some other store to fulfill the demand.
A real-life example of this was seen by a large North American retailer that was working with a coffee manufacturer facing full brand delisting due to a competitive exclusivity agreement. Using shopper analytics, the manufacturer was able to show the retailer that the loss in sales would not be offset by the competitive sourcing of volume plus the funding the other vendor would provide. Also, that they would likely lose shoppers to other grocery stores that did sell the brand. The retailer averted a significant drop in coffee sales by relisting SKUs that were overall incremental to the merchandising set. Equally important, the analytics proved how the manufacturer’s brand contributes to shopper success by store, revealing the negative impact in some of the most profitable locations.
In drug stores specifically, the lack of substitutability on some prestige brands in the cosmetics area, such as fragrances, requires a tighter connection between the retailer and supplier to ensure on-shelf availability. For those categories where there is a higher-level substitutability, such as eyeliners, the supplier is still motivated to work closely with the retailer to understand at what points along the customer journey they can most effectively influence the purchase decision.
The third area where using data analytics to improve shopper-centric collaboration has a real and immediate impact is in the physical supply chain. Real supply chain efficiencies can only be accomplished by having granular data (store- and SKU-level, by day) for planning accurate forecasts. This can only be accomplished by retailers sharing their demand forecasts with suppliers, so the supplier can match that information to their production schedules.
Many suppliers extract the granular data sets, merge the data with their forward-looking planning tools, and create a consensus forecast with their demand planning teams that drive just-in-time production, reduce packaging waste, maximize plant efficiencies and improve the overall logistics of product movements.
To address all of these issues, retailers and suppliers need a common data platform with shared facts and insights available in a central repository that is frequently updated to eliminate discrepancies. They also need to share category and customer data at multiple levels of the store/product/customer hierarchies across various time frames.
The benefits of shopper-centric collaboration are many, including mutually beneficial insights that enable sales teams and category managers to enhance joint business planning in an operationally efficient manner. Giving suppliers access to retail item/brand, category, shopper and CRM insights also enables alignment of resources with the greatest shopper opportunities to grow the business.
Improved shopper-centric collaboration helps trading partners jointly generate incremental revenue and grow business faster by sharing clear insights and analytics. It helps open communication channels to build long-term strategic partnerships and enables retailers and suppliers to more easily identify actions to drive better results from existing resources, increasing sales and ROI.
Shopper-centric collaboration is indispensable when there is substantial stress on the extended retail supply chain as experienced during the COVID-19 pandemic. The ability of trading partners to work together for the benefit of the consumer is what helps keep store shelves stocked even in the midst of panic buying and related issues.
A key takeaway for drug store operators is that shopper-centric collaboration simplifies how retailers do business with suppliers by using a shared platform containing data that enables them to speak the same language, view common facts, and jointly act on valuable insights to fuel results. It is also critical for trading partners to stop arguing over “whose data is right” — and start working together to drive shopper-focused decisions.
Brian Ross is president of Precima, a Nielsen company that partners with retailers and brands to drive customer-centric growth.