The presence of AI agents in ecommerce analytics is becoming more apparent. However, Dell’s ecommerce lead notes that it has yet to significantly impact the numbers.
Dell has observed an increase in visits from platforms like ChatGPT, Perplexity, and Claude, as stated by Breanna Fowler, head of global consumer revenue programs. While the rise is noticeable, it remains inconsistent and has a relatively small impact.
The company is currently in the testing phase of integrating with LLM-driven shopping. The focus is on early proof-of-concept work and internal deliberations regarding the long-term role of these systems.
Despite the presence of traffic, there has been no clear performance improvement.
Agentic AI is sending traffic but not driving results
Dell is receiving more sessions from AI-driven sources, but these sessions are not converting at the same rate as other channels.
Fowler described the growth as measurable but not groundbreaking, aligning with the experiences of many teams. There is interest and initial engagement, but not enough consistency to rely on it as a revenue generator.
The disconnect between traffic and outcomes indicates that AI agents are primarily influencing discovery rather than transactions. This also explains why companies are still in the experimental phase rather than committing to a specific strategy.
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AI agents look more like aggregators than storefronts
Currently, agentic AI functions more as a layer atop existing ecommerce systems. Fowler likens it to aggregation platforms, where users explore options and then finalize their purchases elsewhere. This behavior is reflected in how people are currently utilizing these tools.
AI agents excel at summarizing options and aiding in initial decisions, but they are not yet reliable for completing transactions. This pattern is unlikely to change rapidly, especially for high-consideration purchases.
Despite the focus on AI, the fundamentals remain unchanged. Fowler emphasizes that on-site search is crucial for ecommerce performance. If customers cannot easily find products, other aspects become secondary.
“If customers cannot quickly and effortlessly find your products, no amount of content or configurator capabilities matter,” she told Digital Commerce 360.
This applies regardless of whether the entry point is a search engine, a direct visit, or an AI-generated recommendation.
AI discovery may reward different signals
Dell’s performance in AI-driven discovery platforms presents an intriguing twist.
The company performs well in these environments despite not being one of the largest ecommerce players, indicating that AI systems may prioritize different signals than traditional search engines.
This could involve how product data is structured, how content is presented, or how frequently a brand is mentioned externally. For marketers, this introduces a new layer of optimization, while the core principles of discoverability remain unchanged.
