Pitfalls of Poor Product Data: Using Merchant-Speak Instead of Shopper-Speak

Posted by Matt Sartor at 2:54 pm in Product Data, Retail Painpoints
pitfalls of poor product data: the top pains that under-optimized product data is causing retailers today

2) Using merchant-speak instead of shopper-speak

Product data – a retailer’s product vocabulary – can become “inside baseball” and more attune to how a manufacturer thinks about a product rather than how a shopper would talk about it. Merchant teams are always very close to their product and their intended uses, but many do not have the luxury of always keeping up with evolving shopper vernacular and product sentiment.

The end result is shoppers on your site who simply cannot find the right products for their preferences and needs. Product attributes for ‘size,’ ‘color’ and ‘price’ are standard and important, but only scratch the surface of the typical shopper’s actual vocabulary.

Staying in touch with the evolving ways consumers’ vocabulary is changing product-by-product is tough and time-consuming. It means being able to quickly mine and curate structured and unstructured content, on and off a retailer’s website. There are a myriad of sources to find the most relevant product attributes – the product page, lookbooks, user guides, Pinterest, Facebook, customer reviews, and guidance from sales associates. (Learn more in our infographic.) The trick is being able to key in on the data that matters regularly and quickly, and be able to react before your competitors.

Edgecase recommends:

When building a product data strategy for our clients, Edgecase leverages the inherent knowledge of smart merchant teams and melds it with our third party perspective on the market and competition. Our goal is to think like shoppers…all shoppers. How would someone who is an expert on this type of product describe it versus someone who may have only a vague idea of what they need? How would someone describe this product if they were talking with a sales associate? How would a shopper describe this product to their friend?

Answers to these types of questions help derive new product attribute categories. Determining the exact values for each category is also an interesting process. Oftentimes, the values already live on an information-rich product page. This is where our machine curation tools are most powerful in mining for that content. But sometimes the work is not so straight-forward. For instance, highly technical terminology (i.e. ounces or megapixels) is useful to a more informed shopper, but we’ve found that there is a huge opportunity to translate these types of attributes into more shopper-friendly, user-centric terminology. Another more complex curation need is in determining a scenario or style of a product (i.e. conservative vs. edgy). This is where the power of our human curators comes into play.

The real key is keeping up with how the shopper vernacular may change and ensuring product data evolves with it. The Edgecase team is a partner to our clients, acting as their eyes and ears on emerging trends and competitive opportunities.

Retailer results:

crate and barrel pillows back color filter edgecaseEdgecase clients have seen the power of differentiating their experience and driving more sales by incorporating a more shopper-centric vernacular into their product discovery experience. 

• Edgecase curators looked at how Crate & Barrel shoppers perused and interacted with pillows in the physical store. They didn’t just look at the front of the pillows; they picked each one up and looked at the back. This spurred the creation of new product data and new filters for ‘Back Color’ and ‘Back Material’ on the Decorative Pillows category page. Both are now highly used filters.

• Another Edgecase client in the home improvement space had product data and filters for ‘Horsepower’ in the Generators product category. The problem was, shoppers for these products were generally buying them to power other things that had requirements expressed in wattage. The Edgecase team utilized existing product details on wattage to develop new product data points and filters for this more relevant attribute.

This post is part of our blog series, ‘Pitfalls of Poor Product Data: The Top Pains That Under-Optimized Product Data Is Causing Retailers Today’. Read the first post in the series, Missing and Inconsistent Product Attributes and stay tuned as we continue to explore additional pitfalls.

Download the “The Pains of Poor Product Data: How to Evolve the Data That’s at the Heart of Your Business” whitepaper for a collection of tactics that can cure your product data pains.

Matt Sartor

Matt has spent the past decade working extensively with account management, sales, product, and engineering teams to deliver exceptional client experiences for Fortune 500, and IR 500 clients. As the VP of Client Services, Matt ensures that our clients are set up to experience the full benefit and value of our platform. His teams work to integrate, analyze, and iterate on our solutions to continually improve the ROI we deliver to our clients.

Follow Matt Sartor on Twitter @mattsartor

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