Product assortment planning provides retailers with a clear direction as to how to break up the spend on the digital shelf, store, or location in a meaningful range, which supports sales, fits into the customer needs and maximizes revenue.
In 2009, Walmart began an initiative to declutter its stores. Their business case rested on two primary reasons:
- Based on customer surveys, their customers wanted less clutter.
- To challenge Target, Walmart felt it needed to attract higher-income shoppers.
With an aim to declutter its stores, Walmart cut back their merchandise by about 15 percent. Most notably, they removed the displays that previously sat in the middle of aisles.
In the immediate aftermath, customer satisfaction scores soared. People apparently loved the new stores. Yet for as much as they loved the stores, customers bought a lot less.
Even before fully rolling out the complete program, Walmart lost an estimated $1.85 billion in sales. The initiative was shelved and Walmart’s Chief Merchandising Officer resigned.
Of course, the consequences of poor product assortment planning from Walmart occurred on a magnified scale. Even so, it’s clear that retail merchandising decisions made solely based on human judgment are prone to error.
Assortment Planning: Bringing Science to the Art of Retail
Early retailers with one store, or a small handful of stores, knew intimately what was selling and not selling. Retail and supply chains were less complex and less global.
The scale, volume, and revenue of large retailers require more sophistication, insight, and analysis to be competitive and profitable. Visual merchandising, for example, requires quick, constant synthesis of countless, rapidly changing parameters. Data and analytics, especially when it’s driven by machine learning and/or AI, thrives on large datasets.
In short, product assortment planning and data analytics make an incredible match… in theory.
The trouble is, in the real world, product data is never consolidated, let alone formatted. Retailers are left to cobble together disparate sources of data in clunky, error-prone product assortment planning processes.
The missing piece is product information management (PIM) software.
How Product Information Management Helps
You can think of a PIM solution like a network of pipes that connect data analytics to retail planning.
The “pipes” of PIM consolidate your product data, clean it up, and otherwise make it usable. As part of making the data more usable, PIM software provides insights to product assortment planners.
For example, in addition to optimized product mixes, PIM software can provide predictive analytics. Among other things, these predictive insights help retailers anticipate demand changes. The result is lower inventory costs, price intelligence, fewer lost sales, and larger profit margins.
To see assortment planning optimization in action, we’ll take an example from The Harvard Business Review. In the example, we consider an auto-parts retailer that sells a large volume of two things:
- Honda Accord parts
- Brake pads (but not for Accords)
Of course, it doesn’t take a computer to tell you that adding brake pads for Accords is a good idea. However, without PIM software to enrich and deliver your product data, it’s easy to miss these opportunities.
To be clear, this is but one example of PIM’s power in action. PIM informs a comprehensive range of merchandise financial planning functions. This includes:
- Pricing optimization strategies
- Product categorization
- Lifecycle management
- Supply chain management
- Open-to-buy planning
The reality is, with clean, usable data, an intelligent PIM solution can find a world of opportunities in your product line for you. They can also provide you with insights you may have previously overlooked.
To show you a few of the possibilities, in the following sections, we’ll review the benefits retailers can achieve with PIM.
Dynamic Channel and Store Clustering
Clustering, at the store, category, or channel level, has costly knock-on effects on many diverse, related business functions. With help from PIM software, you can more easily see and anticipate previously unforeseen negative impacts. Even better, it’ll be far easier to extract insights that inform profitable clustering decisions.
Optimizing and Enriching Depth and Breadth of Product Ranges
Retail planning is an exercise in balance. Nowhere is this more true in determining the optimal product range depth and breadth. Without rich data, striking the balance quickly and precisely in a constantly changing environment like retail is near impossible. That is unless you have PIM software to help you identify the ideal balance.
Creating Harmony Between International and Localized Product Ranges
With international expansion comes new challenges. In e-commerce assortment planning, the primary challenge is balancing standardization with the flexibility to adapt to local customer segment needs.
By delivering enriched product data analytics to the right place at the right time, PIM helps you overcome this challenge. In this way, PIM software empowers retailers to cost-effectively expand into new markets.
Determining Space-Constrained Assortments
Physical space planning across various store sizes, layouts, geographies, and inventories is made far more efficient with PIM software. In fact, Pets at Home, a pet supply retailer with 400+ stores, used AI to create demand-based assortment optimizations. Of course, to feed the AI models it used to optimize merchandising, Pets at Home needed clean product data.
Increase Agility in Product Assortment Planning
Rich product data from PIM doesn’t just help to determine variety, assortment, and product availability. It also enables retailers to pivot quickly—using predictive analytics—when customers’ needs change. In an age where personalization at scale is the baseline expectation, agile product assortment planning is a must-have.
As the case of Walmart shows, no one’s immune to the negative effects of human error in assortment planning. As the necessity for personalization grows and markets become even more globalized, retail planning will only get more complicated. To cost-efficiently balance digital and physical shelf space constraints with customer demands will require the help of computers.
Embracing the Opportunity of PIM
Among the e-commerce trends shaping product experience are:
- AI and AR-powered back-office optimizations
- A rising need for trusted and rich product content
- The existing and increasing importance of personalization at scale
Notably, robust data analytics capabilities are key for capitalizing on each of these trends. But the promise of data as a transformational force remains unfulfilled for many top enterprises. The culprit is a lack of effective product information management, a problem solved by PIM software.
Riversand’s Product Experience 360 (PX 360) brings science to the art of retail. Our retail solution helps determine variety, assortment and product availability, while being able to pivot quickly to customers’ needs and changes. With PX 360, you can place the right product in the right place at the right time across all channels.