Today, customer-centricity is at the heart of any successful retailer. Sales and profit are no longer the only key measurements of success, with retailers now placing an increased amount of focus on the total retail experience. Given this new focus, the stores’ role is becoming ever more important as a means of delivering a differentiated and satisfying shopping experience. While category insight data such as product performance, area demographics and demand patterns are widely used to aid the production of more customer-focused assortments, many retailers fail to leverage the knowledge of those closest to the customer – the local store staff.
In this blog, we will outline the key principles and focus on how retailers can increase customer-centricity by leveraging local store knowledge as part of the category ranging process.
The customer is at the heart of all we do
Customer-centricity is the art of building and operating an organization based on its customers and not on its products or the organization itself. For a retailer said to be operating in a customer-centric way, the following statements would be true:
- The organization and its stores are built considering the customers perspective
- Customers have more input on the entire retail experience
- Customers information is used appropriately to enhance the shopping experience
- Stores are tailored to different customer profiles and shopping goals
Implemented correctly, a customer-centric strategy will help create a more positive shopping experience for customers, which will, in turn, drive customer satisfaction, loyalty and increased sales.
Localized means optimized
Optimizing on store-level is made complicated by the number of stores, and the geography and demographic spread that they represent. The most common and effective way retailers mitigate this is by building product assortments focused on localized consumer demand, meaning that the products in store reflect the demand for that area.
To facilitate this, retailers must first fully understand their categories and the consumers that shop them. Centrally collected information such as product sales, consumer wealth, ethnicity, age and lifestyle help the retailers to gain an understanding of the demographics of an area and therefore what consumers are likely to buy. By bringing about a more granular understanding of the consumer through an awareness of the role of localization by category, these valuable insights give retailers the opportunity to enhance their assortment offering, considering the following:
- National Core – Items sold in all stores regardless of cluster or size
- Cluster Core – Items sold in all stores in the cluster, in addition to the national core
- Cluster Optional – Items sold where possible, but may be dropped
- Local – Items required for one / group of stores (e.g. locally sourced)
Given a typical business process, once the cluster-level assortments have been created, store specific product performance data is fed into the retailer’s planogramming software.
This software will then recommend, based on rates of sale, the inventory that each store should carry to satisfy their local demand and build the planograms to suit. As discussed in one of our whitepapers, this is believed to be the most optimal levels of assortment and inventory when considering both commercial and supply chain perspectives.
The challenge lies in collaboration
Consumer and category insight paired with product performance data is an essential part of building localized assortments for stores. These assortments provide a credible reflection of localized demand and will undoubtedly increase category performance and customer-centricity.
The problem with averages is that that they do not suit everyone and quite understandably, these insights cannot cater for every bespoke and local edge case. Typical examples of these are where the cultural makeup of an area has rapidly changed, or where a loyal customer’s favorite product has been delisted for another.
The challenge for retailers, therefore, is how to produce a cost-effective assortment that satisfies average local consumer demand, whilst understanding and satisfying those smaller, local edge cases that tend to be known only by the store staff.
The challenge for retailers is how to produce a cost-effective assortment that satisfies average local consumer demand, whilst understanding and satisfying those smaller, local edge cases that tend to be known only by the store staff.
To better meet local consumer assortment requests would require intervention from those closest to them who know exactly what they want – the store staff. This is especially true for convenience retailers where stores tend to be situated at the heart of neighborhoods and for whom satisfying local demand is even more critical to success.
Collaboration between stores and central teams based at the retailer’s HQ does exist in some retailers today, however, the mechanisms currently used to facilitate it requires major improvement. Traditionally, collaboration has been done through either email, telephone or face-to-face meetings resulting in poor traceability and visibility, and limited reporting capabilities.
Without stores having clarity on factors such as core products, product dimensions, performance data and merchandising strategy, retailers often feel a nervousness in allowing their stores to request changes to centrally proposed planograms. This lack of visibility frequently leads to many store requests being declined and thus reducing buy-in and wasted time.
Solving the challenge by leveraging in-store knowledge
The key to solving this challenge is by augmenting an optimized planogramming process with the ability to leverage in-store knowledge. That is to provide a single mechanism enabling centralized merchandising teams and stores to collaborate on proposed assortments while providing the visibility and guidance to support such decisions.
It is this visibility and guidance, so often overlooked, which can be the key factor as to whether a collaboration process fails or succeeds. It is essential to remember that store employees, generally speaking, will not be as well-versed in industry talk or space planning as those within retailers’ central merchandising teams. Therefore, it is imperative that a mutually understood communication method is used when communicating between stores and their support-centers… and there’s one that immediately springs to mind.
Planograms are used by central merchandisers to communicate how assortments should be displayed in stores. They are centrally created and communicated to stores where they are reviewed and implemented in accordance with their live date by the store’s employees. Planograms are omnipresent across most forms of retail and it’s clear to see why, as they present a clear depiction of what products should be placed where and in what quantity.
Wouldn’t it, therefore, be logical for stores to also use planograms as a means of communicating suggested assortment changes to their colleagues at the support centers to review? When stripping away complications such as repository location, versioning, statuses and blocking the fundamentals of modifying a planogram is relatively simple. Unlike 10 or 15 years ago, it is no longer an alien concept to select a box on a screen, a product in this case, and drag it into position on another part of the screen it is to be placed (the planogram).
Unlike 10 or 15 years ago, it is no longer an alien concept to select a box on a screen, a product in this case, and drag it into position on another part of the screen it is to be placed.
To ensure that the support-center reviewal process is streamlined, planograms coming from stores should have already run through some merchandising quality control. This can be achieved by informing and guiding store employees at the time of suggesting these changes so that requests are more likely to be approved. Guidance can be given in many ways, and it is therefore important that focus is given to the most common reasons assortment change requests may be declined or require support-center intervention.
One of the most important factors when choosing what products to include in an assortment is performance. Therefore, enabling store employees to see product performance data is vital in ensuring that informed assortment change decisions are made, lessening the need for input by support-center staff. For additional insight, performance data should be visible for only the store that is suggesting changes or where not available, for similar stores such as those in the same cluster.
Another critical factor when defining an assortment is finding the right balance between core and non-core (optional) products. Providing that central merchandisers have the ability to define their core assortment, stores suggesting changes should be made aware of which products are core and therefore cannot be changed, and which are optional. Further controls could be put in place to actually stop store staff from making these changes, if the retailer wished.
Once stores have submitted their change requests, central users should be automatically notified, along with supporting information such as which store has requested the changes and what the changes are. It is important that the store-requested changes are easily reviewed as either a planogram, where there are only a few stores requesting changes, or a report where there are many. The authorization process is another area that should be as slick as possible to ensure little or no manual steps from the central team. Changes should be easily approved or declined, and the subsequent communication sent to the relative stores where the process can begin again (or not).
Implementing an in-store collaboration process enables retailers to tailor assortments to their customers’ needs, improving customer loyalty, business revenue and overall shopping experience.
To summarize, implementing an in-store collaboration process enables retailers to tailor assortments to their customers’ needs, improving customer loyalty, business revenue and overall shopping experience. In addition to centrally collected data, retailers can now leverage the knowledge of those people closest to their customers, to create a truly bespoke customer experience.
RELEX’s Online Collaboration application enables central merchandising teams and stores to work together to create a more customer-focused assortment, improving the in-store customer experience and maximizing sales.
As with customer-centricity itself, the return on investment of an in-store collaboration process is not only measured in additional revenue but also in customer satisfaction. In an increasingly competitive marketplace, catering to customer needs at these micro levels could well be the key differentiator for customers when choosing where to shop.
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