Digital Transformation for Pre-Season Planning
Penti – Apparel Retailer
Penti achieved end-to-end integration and digital transformation for pre-season planning
With the growing emphasis on building customer-centric product offerings, statistical store clustering is taking its place as the first step in understanding the similarities and differences across the stores in terms of how customers respond to products and pricing
Strong store-level growth requires more than ‘one-size-fits-all’ approach. The retail world is moving towards more customer-focused product and price offerings, requiring planning localized assortments, promotions, and markdowns. For a successful execution of localized strategies, the first step is to understand differences and similarities across stores regarding customer shopping behavior.
Store Clustering is the process of grouping similar sales locations based on attributes, sale performance, or price elasticity. It is an integral part of Retail Analytics and has many uses in Retail planning and execution, including Assortment Planning, Pricing, Promotions Planning, and Markdown Management. With the growing emphasis on building customer-centric product offerings, statistical store clustering is taking its place as the first step to ensure the right products are placed at the right time at the right location.
A more dynamic and automated process
For fashion and apparel retailers, this is the part of the pre-season planning process that is often performed as an off-line step in statistical analysis tools or spreadsheets, usually by central planning or analytics teams. This is a strategic process for grocery retailers, revisited periodically to look for opportunities for editing assortments and store formats. Customer needs and market dynamics are constantly changing; therefore, store clustering needs to be a dynamic and automated process integrated into the planning software to evaluate different clustering strategies for individual categories as often as possible.
Start your digital transformation journey
Solvoyo Store Clustering solution can help you to group similar stores along multiple dimensions such as sales, price, and space allocation simultaneously. Our fast, user-friendly, multi-dimensional clustering tool enables retailers to identify and pursue opportunities for customer-centric retailing. Category managers do not have to rely on other teams to present the store clusters; they can create their clusters within seconds and move on with assortment and pricing decisions.
"Now, each planner can create store clusters within seconds, tailored to their category. Then using those clusters, they can create localized assortments for all of 30+ countries within minutes. We can optimize size breakdowns and the pre-packs for each product based on similar item sales."
Cluster your stores based on how different product categories contribute to sales
Provide a better shopping experience and save resources by offering the right products at the right place, at the right time
Develop optimal assortment, pricing, and promotion planning based on shopper behavior while maximizing sales opportunities
Automatically determine homogeneous store groups for new product introduction or any kind of testing
Easily identify and visualize similarities between your stores at every location
Try different clustering methodologies and metrics as much as you need before choosing the best suitable option for your business
Penti – Apparel Retailer
Penti achieved end-to-end integration and digital transformation for pre-season planning
“Getting Closer to the Customer” has been one of the top priorities for retailers in the last few years. What does that really look like?
Imagine you are the owner of a modest grocery store in your neighborhood. You know most of your customers in person, and you do a
Detect and react to the different purchasing patterns across stores
Detect and react to the different purchasing patterns across stores
Use the same tool for different clustering strategies based on evolving business demands using different methodologies and metrics
Try different clustering schemes and find the right one that fits with your operational capabilities while going after significant opportunities for localization
Use the same tool for different clustering strategies based on evolving business demands using different methodologies and metrics
Try different clustering schemes and find the right one that fits with your operational capabilities while going after significant opportunities for localization
Selection of the best feature set and clustering method for your business case
Multi-dimensional clustering where users can select from a list of metrics related to sales, store capacity, price, store turn, and store attributes to create store clusters based on a statistical analysis
3D and location-based visualizations to view stores in different clusters
Store and Segment reports displaying metrics used in clustering
Drag and drop capability for managing store groupings and outliers
Easy integration of clustering with other tools (Assortment planning, markdown optimization)