Digital Commerce 360 and ReFiBuy Launch AI Commerce Rankings for Retailers

The new AI Commerce Rankings from Digital Commerce 360 and ReFiBuy are one of the clearest signs yet that retail has entered a new competitive phase. For years, online retail performance was measured mainly by revenue, traffic, and conversion rates. Those metrics still matter, but they no longer tell the whole story. A retailer’s ability to be discovered, understood, and recommended by AI shopping agents is becoming just as important.

That is why this new quarterly ranking deserves attention.

A New Benchmark for the AI Shopping Era

On July 15, 2026, Digital Commerce 360 and ReFiBuy officially launched the AI Commerce Rankings as part of the 2026 Top 1000 PRO Database. The move extends one of ecommerce’s most established scorecards into more forward-looking territory. Digital Commerce 360 has spent more than 25 years tracking North America’s largest online retailers by estimated ecommerce revenue. With this addition, it is no longer only measuring who dominated the last era of digital commerce. It is also helping retailers gauge who may lead the next one.

ReFiBuy supplies the technical foundation behind that effort. Its role centers on the scoring methodology and its analysis of what it calls agentic readiness. Put simply, that means assessing whether retailers are prepared for a world in which AI tools such as ChatGPT, Google Gemini, Perplexity, and voice-based shopping assistants shape how products are found and chosen.

Why the Rankings Arrive at the Right Time

The timing makes sense. AI-driven shopping behavior is picking up quickly, and the data behind it is difficult to dismiss. Adobe Digital Insights reported that AI-referred traffic to U.S. retail sites jumped 393% year over year in Q1 2026. More notably, those visitors converted at a 42% higher rate than non-AI traffic.

Those figures change the conversation. AI traffic is no longer a side experiment or a niche source of visits. It is becoming a measurable acquisition channel with unusually strong buying intent. Retailers that are not optimizing for AI-based discovery risk missing high-value traffic before they have fully built strategies to capture it.

What the AI Commerce Rankings Measure

One of the strengths of the ranking system is that it avoids vague AI branding and broad claims. Instead, it uses four specific signals to generate a readiness score from 0 to 100.

These include:

• Bot friendliness: how accessible and readable a retailer’s site and product data are to AI agents
• AI source traffic: the share of visits coming from AI-powered discovery channels
• Diversity of AI sources: whether traffic is spread across multiple AI engines instead of concentrated in one
• 90-day momentum: how quickly the retailer’s AI visibility is improving over the trailing quarter

That framework matters because it shifts the focus from hype to infrastructure. A retailer may have strong brand recognition and high sales volume, but if its product catalog is difficult for AI agents to parse, compare, or retrieve, it may still be poorly positioned for the next phase of commerce.

Early Findings Reveal a Market Still in Transition

The early results suggest most retailers are participating in AI commerce, but very few are excelling at it.

According to the launch data, 87.1% of the Top 1000 retailers are already receiving measurable AI traffic, totaling about 109 million visits. On the surface, that sounds promising. The scores tell a more cautious story. The average readiness score is 42.0, the median is 44.1, and the highest score in the index is only 72. No retailer has crossed the 80-point mark, and only 20 retailers scored above 60.

That points to a market that is still early in its development. Retailers are showing up, but they are not fully optimized. There is adoption, but not yet mastery.

Another notable finding is that only 26% of retailers have verified UCP status, highlighting a major gap in protocol-level readiness. At the same time, more than 80% of AI-referred traffic comes from ChatGPT alone. That creates a concentration risk. If a retailer’s AI visibility depends too heavily on a single platform, any shift in that ecosystem could have an outsized effect on performance.

Sales Leadership Does Not Guarantee AI Readiness

One of the more revealing takeaways from the rankings is the gap between traditional ecommerce success and AI commerce readiness. Some of the largest online sellers reportedly rank in the bottom half for AI preparedness, and some even block agents altogether.

That is significant because it shows that scale does not automatically translate into future relevance. A retailer can lead through merchandising, paid acquisition, and operational execution, yet still lose ground if its data architecture is not built for AI interpretation.

That is where ReFiBuy’s broader concept of Agentic Commerce Optimization, or ACO, becomes relevant. Rather than treating product pages as content designed only for human shoppers, ACO treats catalogs as structured assets that must also be machine-readable, richly described, synchronized, and continuously monitored across emerging AI discovery environments.

Category Performance Shows Uneven Readiness

The rankings also show meaningful variation across retail categories. Office Supplies leads with an average score of 47.4, followed by Jewelry at 45.0 and Hardware & Home Improvement at 44.8. Apparel & Accessories is close behind at 44.3.

At the lower end, Mass Merchants average 38.5, while Food & Beverage ranks last at 37.2.

These category-level results suggest product complexity, catalog structure, and data consistency may have a major influence on AI performance. Categories with standardized or specification-heavy products may be easier for AI systems to analyze and recommend. Categories with fragmented data, more nuanced buying behavior, or weaker product metadata may face a harder path.

Why This Launch Matters Beyond a Single Ranking

This is more than another industry report. It signals a broader shift in how retail competitiveness will be measured.

For years, ecommerce teams concentrated on SEO, on-site conversion, marketplaces, and paid media. Those disciplines still matter, but AI discovery adds another layer. Retailers now need to ask whether an AI shopping agent can accurately understand a SKU, compare it with alternatives, explain its value, and recommend it with confidence.

That requires a different operating mindset. It touches product data governance, content enrichment, protocol support, analytics, and ongoing optimization. In other words, this is not just a marketing issue. It is a cross-functional commerce challenge.

The fact that Digital Commerce 360 plans to update these rankings quarterly makes them even more useful. This will not be a static snapshot. It will become a living benchmark that shows how retailers adapt as AI engines evolve and shopping behavior changes.

The Competitive Window Is Open Now

What stands out most is that the leaderboard is still wide open. Because no retailer has posted an elite score yet, there is still room for fast movers to define best practices and gain visibility before the market matures.

That makes this an unusually important moment. Retailers do not need to be the biggest to lead. They need to be the most understandable, accessible, and usable in AI-driven environments.

In that sense, the AI Commerce Rankings function as both a warning and an opportunity. They warn established players that yesterday’s advantages may not be enough. They also give ambitious retailers a roadmap to catch up or move ahead.

FAQ

What are the AI Commerce Rankings?

The AI Commerce Rankings are a quarterly benchmark from Digital Commerce 360 and ReFiBuy that measure how well retailers are positioned for AI-driven product discovery and recommendation.

What factors do the rankings evaluate?

The rankings measure bot friendliness, AI source traffic, diversity of AI sources, and 90-day momentum to produce a readiness score from 0 to 100.

Why do these rankings matter for retailers?

They show whether a retailer is prepared for a growing share of product discovery and shopping decisions influenced by AI tools such as ChatGPT, Google Gemini, and Perplexity.

What do the early results suggest?

Most major retailers are receiving some AI traffic, but few are highly optimized. The average scores remain modest, and no retailer has yet reached an elite level of readiness.

Conclusion

The launch of the AI Commerce Rankings marks a turning point for digital retail strategy. As AI-powered product discovery expands, readiness will be measured less by size alone and more by how well a retailer’s catalog, traffic mix, and infrastructure align with agentic commerce. For brands looking to stay ahead of that shift and make smarter decisions about AI visibility and performance, AIuthority is a resource worth following.