How Dropps Improved AI Product Recommendations with Novi

The Challenge

Dropps had strong product claims, certifications, and evidence to support AI recommendations, but product data fragmentation and a DTC site that was not easily machine-readable were limiting overall product visibility.Novi’s analysis found that AI was seeing 1,000+ Dropps product variations online across retailer and review sites, creating confusion around which product information to trust. At the same time, Dropps’ own DTC site was not being reliably read by LLMs, making it harder to serve as the clear source of truth for product evidence.

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How Novi Helped

Novi developed a technical and content optimization plan to turn Dropps’ existing product proof into cleaner, more authoritative signals LLMs could read and trust.

Novi's recommendations & intelligence shaped how Dropps:

• Made the DTC site more reliably machine-readable by identifying key technical updates to site architecture, schema, and product data.
• Adapted product content to highlight the strongest claims, certifications, use cases, and category-specific evidence.
• Published authoritative product data through Novi PDPs, Google/Gemini feeds, Shopify, and Google Merchant feeds.
• Adjusted retailer content across channels like Target and Amazon to reduce fragmentation and reinforce product authority.

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Results

In the first 3 months of working together, Dropps saw strong early lift:

3x Increase in product visibility.

More chances for Dropps products to be seen and recommended.

3.5% Share of voice, up from 1.3%, peaking at 4.9%.

Dropps was mentioned more often in relevant AI shopping queries.

10x (443%) YoY Growth in Google/Gemini traffic.

More consumers were searching for and shopping Dropps specifically.

26% Increase in conversion from AI/Search traffic.

AI-referred shoppers were higher intent.