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01 · Industry · E-commerce & D2C

AI is the new personal shopper.

Modern shoppers have abandoned basic keyword searches. They treat AI models like personal assistants and feed them complex constraints — ingredient lists, lifestyle filters, price ceilings — long before they reach a product page. CiteRank AI ensures your products are the ones recommended.

Vertical benches currently run 8 engines; full tracking covers all 8.

8
AI engines tracked
500+
Product-intent prompts
14d
Free trial
02 · Industry challenges

The digital shelf has been reordered.

AI doesn't show a grid of 20 products. It picks 2 or 3 that best match the buyer's natural language constraints. If your attributes aren't machine-readable, you're invisible.

Product-category & attribute prompts

'Find a silicone-free moisturizer under ₹800' or 'Best vegan protein for sensitive stomachs'. We track whether AI correctly identifies your USPs.

Review-source & sentiment signals

AI synthesizes thousands of reviews to form an opinion. We measure how sentiment shifts in Reddit, blogs and marketplaces affect your recommendation share.

Recommendation & 'best for' use cases

Buyers ask 'What's the best stroller for city living?' AI routes buyers to products that have been contextualized for specific lifestyles.

Social proof & third-party citations

Engines prioritize products cited in listicles, forums and expert reviews. We map the source graph influencing your AI visibility.

SKU-level prompt mapping

Every hero SKU benchmarked against the top 5 competing products on every relevant lifestyle and ingredient constraint.

Marketplace vs D2C routing

See when AI sends buyers to Amazon or BlinkIt instead of your own site — and what technical changes to make to recapture that traffic.

03 · AI visibility benchmarks

E-commerce AI visibility by category.

Sample prompt performance across high-velocity D2C categories. See who owns the recommendation share today.

Category promptChatGPTGeminiPerplexityAI OverviewsAnswer concentrationYou cited?
Sulphate-free shampoo for curly hairBrand X, Brand YBrand X, Brand YBrand X, Brand YBrand X, Brand Y2 of 45
Ergonomic office chair for back pain under 00Brand Z, Brand ABrand Z, Brand ABrand Z, Brand ABrand Z, Brand A5 of 12
Sustainable running shoes for marathon trainingBrand B, Brand CBrand B, Brand CBrand B, Brand CBrand B, Brand C3 of 20
Keto-friendly snacks with no seed oilsBrand D, Brand EBrand D, Brand EBrand D, Brand EBrand D, Brand E4 of 15

Illustrative modelled data — not live client results. Names anonymised.

04 · Case study

A clean-beauty brand's recommendation lift.

A D2C brand had superior ingredients but was being overlooked by AI in favor of legacy competitors with better-optimized metadata. By structured attribute tagging and seeding review signals, we shifted the engine consensus.

What we changed
  • Product-attribute schema (Ingredient, Material, IntendedUse) implemented sitewide
  • Contextual use-case pages created for 'Best for X' lifestyle prompts
  • Review signal monitoring across high-authority beauty forums and blogs
  • Entity resolution to ensure AI connects third-party praise to the correct product node
  • Weekly replay audits to monitor recommendation volatility
Modelled outcome
15% → 42%
Recommendation share on intent prompts
3.5×
Increase in direct AI-to-D2C referrals
90%
Accuracy of AI-generated product descriptions

Illustrative modelled data — not live client results. Names anonymised.

05 · Embedded demo

Track your products across the AI-verse.

SKU-level visibility dashboard with real-time recommendation tracking.

AI visibility · Share of Voice

AI Visibility — Share of Voice over time

12-week trend, weighted across the tracked LLMs.

Current
61/100
37 pts vs W1
020406080W1W2W3W4W5W6W7W8W9W10W11W12
Your Brand · PerplexityTop competitor

Tip: tab into the chart to focus a weekly data point, then use the left and right arrow keys to step through weeks. Press Escape to exit.

Share of Voice · per engine

AI recommendation share — you vs competitors

Per-engine Share of Voice across the last 30 days of replays. Hover or focus a bar for the breakdown.

Illustrative modelled data — not live client results. Names anonymised.

06 · FAQ

Questions from e-commerce & d2c teams.

How does AI find my products?

AI crawlers read your product pages, schema.org data, and third-party reviews. CiteRank shows you exactly which of these signals is working and where you are missing critical attributes.

Can you track my products on Amazon vs my site?

Yes. We track which destination AI recommends and help you optimize your own site to become the preferred citation for high-intent buyers.

What are 'attribute prompts'?

These are queries where a buyer specifies a constraint (e.g., 'gluten-free', 'travel-size', 'under 0'). We ensure AI knows your product meets those criteria.

07 · Get started

Is AI recommending your products today?

Run a free e-commerce audit and see your visibility score against your top 3 competitors.

Run Free Audit