Reddit (r/BuyItForLife, r/skincareaddiction, niche subs)
AI assistants over-cite Reddit consensus for product recommendations. A single highly-upvoted thread can name 3–5 brands and become the answer for a year.
Use case · E-commerce & DTC
The new "best of" list isn’t on Google. It’s in a chat.
Shoppers now ask AI for product recommendations. Three to five brands come back, with a one-line endorsement each. Intendity tracks whether you’re named, what your reviews actually sound like inside the answer, and the moves that put your name back on the list.
The prompts
Buyer questions, not keywords.
Search-style intent rephrased as conversation. Same question your buyer used to type into Google — now answered with three named brands and a sentiment summary.
- › best running shoes for flat feet under €150
- › is [your brand] worth it for sensitive skin
- › most ethical European fashion brands
- › best gifts for a coffee enthusiast 2026
- › alternatives to [competitor] with better return policy
Four moments where AI shapes the purchase.
Discovery, comparison, validation, repurchase. Different prompts, different sources, one shared scoreboard.
- 01
Discovery
Buyer asks AI: "best [category] for [use case]." Models return three to five brands with a one-line value prop each. The brand framing here often comes from Reddit and Wikipedia.
- 02
Comparison
Buyer asks AI: "is X better than Y?" Models compare features, price, return policy, sustainability claims. Sentiment in cited reviews drives the verdict more than star averages.
- 03
Validation
Buyer asks AI: "what do real customers say about X?" Models surface Reddit consensus and Trustpilot themes. A single negative pattern ("sizing runs small") propagates across answers.
- 04
Repurchase & loyalty
Buyers ask AI again at re-up time. If your competitor has shipped a sustainability story or a returns improvement and you haven’t, the models notice within weeks of the change being indexed.
The sources models cite for products.
The pool is small. Influence is concentrated. Win the right five sources and your mention rate compounds across every adjacent prompt.
Trustpilot, Google reviews, niche review sites
Star averages matter less than the language inside the reviews. Models pull verbatim phrases like "fits true to size" or "smelled chemical out of the box."
Wirecutter, Strategist, This Is Why You're Single-style buyer guides
High editorial weight. A single feature can flip the model's default recommendation for an entire category.
Wikipedia (for category articles)
For categories like "running shoe" or "espresso machine," Wikipedia frames the language models use. Influence here pays back across thousands of prompts.
Your product schema
Product, Offer, AggregateRating and Review JSON-LD. Models cite verbatim from these. Most DTC sites have partial schema; complete coverage is a same-day fix.
Influencer & creator content
Less than you'd think. YouTube and TikTok creators are influential but inconsistently cited — assistants prefer text-first sources for recommendations.
Six plays Intendity will recommend.
Each play is tied to specific evidence — the exact PDP, the exact review thread, the exact listicle that’s currently driving (or losing) your shortlist position.
Complete product schema
Ship Product, Offer, AggregateRating and Review JSON-LD on every PDP. Models verbatim-cite these. Same-day engineering work, immediate visibility lift.
Review-language audit
Mine your Trustpilot/Google reviews for the phrases buyers ask AI. Surface the answers in product copy and FAQ schema so models pull from your domain, not the reviews.
Targeted Reddit engagement
Identify the three threads that rank in the citation pool for your category. Engage with specifics — sizing notes, ingredient detail, durability data. Models reward signal density.
Localized recommendations
AI answers vary by country. A brand strong in EN-US can be invisible in DE-DE. Track per locale, then localize PR placements where the gap is largest.
Returns & shipping FAQ schema
These questions dominate "is X worth it" prompts. FAQPage schema with the buyer’s exact phrasing pulls the answer onto your domain instead of a third-party listicle.
Sentiment defense
Negative themes ("runs small," "scent fades") propagate across answers. Intendity flags emerging negative patterns weekly so PR/CX can correct upstream before they cement.
See your AI-shortlist position.
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