Navigating the Digital Aisle: A Case Study on AI-Enhanced Grocery Listings

The online grocery market is expected to grow 12% annually for the next five years. By 2025, it will represent 250 billion in annual revenue. Brands are working to improve their competitive advantage in a crowded market where the slightest advantage could mean massive bumps in discoverability. A multitude of brands, representing more than 128,000 products, were looking for improvements to user experience, discoverability, and conversion rate. Manual updates to every listing would take months or years to complete, along with 10s of thousands of employee hours. An automated, AI solution would be necessary to maximize accuracy.

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The Challenges

Product Visibility

Grocery is already a competitive market, and carving out market share online is important for brands needing to capitalize on the growth and shift of the online market. As consumers continue to shift towards online shopping, growth slows in the brick-and-mortar segment. 

Keeping products at the top of search pages, eligible for paid placements, and featured in retailer online displays will be the next battleground for customer attention.

Buyer Anxiety

When it comes to grocery, customers want to touch and feel the good that they bring home. In one study, as many as 75.5% of shoppers cited wanting to pick their own products as the biggest barrier to online grocery shopping.

Grocery is unique in that the quality of a product can vary from one to the next with things like fresh meat and produce. This also extends to non-perishables where the average shopper isn’t sure what they want to begin with. 

Many grocery shoppers are browsing as they shop, looking for products that match their preferences of price, nutrition, display, and lifestyle match. When the number of attributes are limited on grocery products, buyer anxiety is heightened, making decisions hard for the everyday consumer.

Solution: AI Attribute Enrichment

The brands implemented AdVon's AI attribute enrichment strategy to tackle these challenges. By enhancing and refining product attributes, the brands sought to boost searchability and attract a wider audience. AdVon's attribute enrichment solution, AdVonAI, utilizes existing product listings, images, metadata, and consumer information to optimize each product. We'll let the results speak for themselves:

The Results

Discoverability

More products found their way in front of more consumers. Enriched products improve conversion because consumers find the products they want easier and with less chance of return.

  • Across the entire range of products, there was an average improvement of 20 in search rank. 
  • The brands also saw a 17% increase in the top 10 keyword placements. 

Retailer Compliance

An improvement in retailer compliance leads to higher organic rankings, more opportunities for ads, and an improvement in user experience.

  • The enriched brands saw over an 18% increase in average retailer quality score within 60 days of enrichment. 

Sales

A combination of perishable and shelf-stable products were enriched including in-house retailer brands and 3rd party CPG brands

  • ⅔ of the enrichment batch saw a 6% increase in 30 days resulting in $912,000 in additional revenue. 

The Numbers

17%

increase in top 10 keyword placements.

128,000

products enriched with AI

$912,000

in additional revenue in 30 days.

Solutions Used

An Advon catalog audit pulls out all the information needed to diagnose and treat your catalog. We look at the number of missing attributes, and taxonomy shortcomings to determine where consumers are falling through the cracks. Don't lose more customers due to bad data.

Product attributes are, by definition, the defining feature of products. When consumers are searching, they do so by attributes. Size, weight, durability, number of pieces, etc. These are what consumers use to find products, whether through organic search, or through filtering on an online retailer. AdVon uses AI and human-in-the-loop verification to make sure that all your data is utilized so that the most products meets the most purchasers.

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