“The hidden truths about chocolate.”
Ask chocolate lovers if more chocolate is better and you will get an emphatic “YES”! But from a business perspective, this isn’t always the case. Too many choices can work against a brand, retailer and even consumer. This is often called the ‘Paradox of Choice’.
An iconic global brand was having some chocolate challenges. Namely, their retail stores were growing overstocked with product options, often making their small, upscale retail footprints sometimes cluttered and confusing. Merchandising variations were hit or miss and out of stocks, a dreadful occurrence. Sales of products in 3rd party retail were also flattening, spread across too many SKUs. And, the online experience was not much better in the U.S., Canada and the U.K. which ,along with Japan, made up the bulk of the company’s’ global e-commerce sales.
The company was tipping the scales at a hefty 4,600 SKUs. Inventory management costs were climbing, as were logistics costs for e-commerce required to ensure shipped product arrived at the consumer ‘s door pristine, rather than a soggy or melted mess. Managing thousands of SKUs, especially fruit-based ones, was a constant headache for the company. Seasonal variations in size, shape, texture, and taste made it nearly impossible to maintain consistent quality.
Conventional Wisdoms Collide with Cognitive Bias
Yet, the company clung to the belief that ‘more is better.’ The fear of losing sales kept them from cutting down on product options, even though there was no data to support this assumption. It had simply become accepted wisdom, despite the lack of evidence.
Because this was the ingrained belief, it had become the accepted fact. The problem was that there was no empirical evidence to back this ‘accepted fact’ up. Still, the global CIO had a hunch. New to the organization, he saw things with fresh eyes. He believed that the perception and the internally shaped guidance advocating status quo was wrong and was being enhanced to support the conventional wisdom and status quo. To prove this out and find an optimal and profitable path forward, a project was established using Fingerprinting to rationalize and optimize omni-channel mixes , marketing and merchandising efforts.
As FELIX analyzed the brand’s product, customer, merchandising and sales data, as well as a voluminous body of external, related data FELIX could tap into, it began to isolate and amplify some very hidden, yet very important patterns.
One critical insight FELIX uncovered was ‘Product Anchors’—key products that influence customer behavior and drive sales across related items. These anchors act as hubs, linking consumers to a broader range of SKUs through shared characteristics and incentives. DecisionArts’ Fingerprinting™ process revealed these connections, enabling smarter merchandising strategies.
How these Fingerprinting linkages and Product Anchors work is also illustrated in DecisionArts’ Use Case, “The Myth of Brand Loyalty - how data reveals what’s truly driving consumer choice”.
FELIX was able to identify the hidden ‘Strong Bonds’ that exist between the Fingerprints of consumers, incentives, geographies, marketing and merchandising content, CRM content, return data, SKU data, nutrition panel data, packaging and pricing data. All this information is plotted in FELIX’s knowledge graph.
Fingerprinting allows FELIX’s AI tools to begin making assessments within the graph between visible and invisible linkages. In other words, FELIX began to plot a road map of truth which illuminates what will increase customer satisfaction, SKU reduction and growth in revenue and profitability.
FELIX provided SKU-level guidance on:
· Optimal e-commerce product assortments and merchandising options within the U.S., Canada and U.K.
· Optimal composites for the branded stores; for third party retailers and for BOPIS (Buy Online, Pick-up in Store), to ensure quality and maximize basket sizes.
· Provide the necessary options for each market and location while at the same time narrowing the nearly endless universe of options and variations currently bogging the company down.
FELIX successfully identified over 30% of SKU’s that made up 66% of the long tail, which fit the company’s classifications for product sunsetting.
“What’s the big deal? SKU Rationalization is relatively easy and straight forward.”
Identifying low performing SKUs seems relatively straight forward. However, it isn’t always quite as simple as it appears on the surface.
Let’s look at one such example
Chocolate covered strawberries seem like a great product to sell. They are iconic; visually appealing and can deliver a variety of pleasing flavors in each bite.
Seems like a no-brainer product to create and merchandise. Right?
Turns out, the reality of manufacturing them at scale isn’t quite as straightforward as their small batch or homemade cousins. Commercially manufactured chocolate covered strawberries are expensive to source consistently, perishable with limited shelf life and e-commerce delivery in hot weather can be an issue. Plus, for this brand, the product only seemed to sell during certain holidays and seasonal windows.
So, selling chocolate covered strawberries is a bad idea. Kill them.
Hold on…On the surface killing them makes as much sense as the original idea to sell them. But killing the SKU would have far-reaching and unintended consequences. Identifying these hidden realities is one of FELIX’s skills.
Finding the hidden-and valuable middle ground
FELIX identified that chocolate covered strawberries were a Product Anchor which had strong bonds with over 18 other products and nearly 50 SKUs.
Because the product was an Anchor, when it was merchandised with the other strong bonded products and SKUs, the consumer could easily move from the anchor product (the strawberries) to one or several of the linked products for purchase if merchandised correctly.
Instead of the consumer purchasing the lower margin, difficult to manage strawberries, they were instead seamlessly directed to other higher margin items which were tightly aligned with the consumer’s characteristics, attributes and criteria.
With this change, conversions of chocolate covered strawberries decreased 40% online, however, profitability on the product, as well as each sale including the product went up.
Product sales which began with chocolate covered strawberry search but did not include chocolate covered strawberries in the purchase also increased by nearly 20%.
Furthermore, returns and QA complaints related to the strawberries decreased by nearly 90% AND baskets value associated with chocolate covered strawberries increased by 20% and repurchase rates within a 90-day window increased by 38%.
Killing the SKU would have wiped this significant financial gain out entirely, as all the value was hidden, having only been uncovered by FELIX’s Fingerprinting process.
FELIX revealed that over 30% of the company’s discounting tactics were counterproductive. These promotions often backfired, leading customers to only buy the discounted items in bulk, rather than a variety of products. This strategy hurt the brand by reducing basket diversity and limiting overall sales growth.
When FELIX mapped out the clusters of strong and weak bonded items visually, the brand’s management was shocked to learn that the majority of the underperforming products were ‘Clones’ of other better selling products or ‘Orphans’ consuming valuable space and resources, apparently unbeknownst to everyone.
Let’s look at Clones and Orphans in greater detail:
CLONE: A SKU that is an extension of another and whose characteristics are substantially alike to the product it was cloning. Nearly universally, this was unit size or flavor, or flavor-assortment based. Think of a package of two chocolates rather than four.
ORPHAN: A SKU that stands alone as a unique flavor, size, packaging combination. Think white chocolate/hazelnut clusters. Orphans seem like a good idea on the surface but are not. They must be subsidized by other products that are not in the long tail.
In addition to tagging the previously hidden clones and orphans, FELIX was able to successfully identify that the bond strength between products varied online and off, including Orphans. ‘Bond Strength’ determines whether dissimilar products will be desirable, and likely to be purchased by certain consumers whose Fingerprints match the products and when assortments and merchandising are optimized for this. An Orphan offline might not be an Orphan online and may easily be paired with another item.
The whole truth is rarely found on the surface.
The result of this initiative had an impact well beyond sales and product marketing. These improvements also reached the company’s supply chain, distribution and logistics, as well as customer satisfaction, retention and profitability. What appears to be true on the surface isn’t always the case.
FELIX’s output can be delivered on-demand or as intelligence feeds which can be embedded into other enterprise tools. In either delivery model, FELIX can effectively provide decision support and guidance to professionals who seek to understand what exists beyond what is traditionally visible and the implications of available options.