UIS: Conversion to leads from AI search results is 70% higher than from contextual advertising

Audience behavior patterns. Users ask neural networks complex scenario-based questions: choose a solution, compare companies, find the right service, and get a recommendation before buying. The "trust threshold" for a company drops — the neural network provides reasoning for the choice and warms the user up to a purchase, unlike an ad.

Funnel stage. Contextual and targeted ads work at the top of the funnel, while users turn to AI search results at different stages: finding a solution, comparing competitors, readiness to buy. At the same time, a marketer may not know that a customer interacted with AI before calling. The marketing task is to track the influence of neural networks on the customer's path to purchase.

What businesses should do

AI sources are at a stage where traffic volume is small, but contact quality is high. Companies can secure positions in AI search results before competition for the channel catches up with search and contextual advertising.

UIS outlines four recommendations for marketers.

1. Measure quality, not quantity. Assessing traffic volume from neural networks is not yet appropriate. What's needed is an analysis of lead loyalty and awareness: alignment with target audience, sales conversion, and traffic quality by each AI source.

2. Analyze AI sources separately. Different LLMs bring users with different scenarios: some produce informational clicks, others — commercial intent, while still others are used for comparing options.

3. Optimize your site for AI search. The customer has already studied the offer in the neural network's responses, so a complicated path to conversion will reduce conversion rates. A site needs case studies, research, and how-to articles — so the neural network can suggest a specific landing page. It's also important to maintain the company's "profile": reviews, Yandex Maps, and Yandex Business. These services are indexed first by Alice — the leader among LLMs on the Russian market.

4. Connect analytics for neural network leads. AI-click tracking services show the entire customer journey, including touchpoints through AI search results, and allow marketers to measure conversion, CPL, customer acquisition cost, MQL and SQL leads, and ROMI by AI source. With this data, a marketer can tackle one of the main challenges of 2026 — measuring the impact of neural networks on the user's path to purchase.

Conclusion

Neural networks haven't yet become a mass traffic source, but audience warming within them is more effective, and contact quality is higher. The key performance metric for GEO promotion isn't the number of clicks from neural networks, but the impact on business outcomes: leads, qualified leads, deals, and revenue. UIS advises diversifying and measuring traffic from AI search results now, before competitors do.