Comparison and alternatives articles are most useful when they are built on what real users of each competitor say: what they praise, what frustrates them and who each tool suits. Collect it from review sites, Reddit and forums once per competitor, with links, and reuse it. Quote fairly, include praise as well as complaints, and never invent a review.
Key takeaways
- Buyers searching "alternatives to X" want to know what users of X dislike, and whether another option fixes it.
- Research each competitor once, record praise, complaints and fit with links and dates, and reuse it across articles.
- According to University of Toronto researchers, AI search engines strongly favour third-party sources over brand-owned content.
- Google's partnership with Reddit gives it structured access to Reddit content, a sign of how much weight user discussion now carries.
- Fairness is a legal issue as well as a trust issue: the ACCC treats misleading reviews seriously.
Why use review sites for comparison content?
Because they hold what buyers actually want to know: how a product behaves after the sales call. Feature lists and vendor pages say what a tool claims to do. Reviews and forum threads say where it struggles, what support is like and who it suits. Comparison content built on that is more useful and more credible.
Searchers looking for alternatives are usually frustrated with something specific. An article that names the common complaints about a competitor, and says honestly whether your product fixes them, answers the question they came with.
AI search adds a further reason. According to researchers at the University of Toronto, AI search engines show a "systematic and overwhelming bias towards earned media" over brand-owned content. User discussion shapes what assistants say about every product in a category.
What should you collect about each competitor?
Collect what users praise, what they complain about, who they say the tool suits or does not suit, recurring themes about pricing, support and setup, and a few representative quotes. Record the source, link and date for each point, so claims can be checked and refreshed when the product changes.
| Field | Example |
|---|---|
| Praise | Easy setup, strong reporting |
| Complaints | Slow support, price rises at renewal |
| Suits | Teams under 20 with simple workflows |
| Not for | Multi-site businesses needing custom roles |
| Evidence | Link, site, date, short quote |
Store it in the competitor's profile, not in a single article. Every comparison, alternatives list and buyer's guide can then draw on the same research, and updating it once updates them all.
How do you research reviews efficiently?
Start with the main review sites for your category, then Reddit and specialist forums, reading recent reviews from businesses like your buyers. Look for patterns across many reviews rather than a single angry post. AI can sort and summarise saved reviews quickly, but a person often has to save the pages first.
Access is a practical limit. Some sites block automated tools, and full review pages on platforms such as G2 or threads on Reddit may need a person to open and save them. Plan for that step rather than relying on whatever an AI tool can reach.
Reddit carries growing weight. According to Google, its February 2024 partnership with Reddit gave it access to Reddit's Data API for "real-time, structured, unique content", which it uses to understand Reddit content and surface more of it. Discussion there increasingly appears in search results.
How do you use review research fairly?
Report patterns honestly, include praise as well as complaints, quote accurately with the source, and date the research so readers know how current it is. Never invent a review, edit a quote to change its meaning or present one bad experience as typical. Be clear when the article is written by a competitor.
The law backs this up. According to the ACCC, creating fake or misleading reviews is against the law, and leaving out negative reviews can mislead as much as posting fake ones. The same thinking applies when you summarise a competitor's reviews: cherry-picking misleads.
Fairness also helps the article work. Readers trust comparisons that admit where a competitor is strong. A piece that says "choose them if you need X" earns credibility for the parts that favour you.
Where does AI help with review research?
AI helps by sorting saved reviews into themes, counting how often each complaint appears, pulling representative quotes, flagging out-of-date points and drafting the comparison from the research. A person saves pages AI cannot reach, checks the themes are fair and approves the finished article.
The research then feeds the writing. A comparison brief built from real complaints and praise produces a far better draft than one built from feature pages. The guide to an AI content pipeline shows where competitor research sits.
Customer words work the same way. The guide to customer quote banks covers collecting your own customers' language alongside competitors' reviews.
Skein researches what users of each competitor praise and complain about once per competitor, with a person saving the pages AI cannot reach, and builds comparison articles from it; the AI engineering page shows how. That suits a B2B company in a crowded category where buyers compare options. A business with no direct competitors gains little from comparison content.
Frequently asked questions
How do you research competitors using reviews?
Read recent reviews on the main review sites for your category, Reddit and specialist forums, focusing on businesses like your buyers. Record what users praise and dislike, who the product suits, and representative quotes, with the source and date for each. Look for patterns rather than single posts.
Can I quote competitor reviews in my content?
Short, accurate quotes with a clear source are common in comparison content. Quote fairly, include praise as well as complaints, never edit a quote to change its meaning, and date the research. Presenting a cherry-picked selection as typical can mislead readers and raise legal concerns.
Can AI read Reddit and G2 reviews?
Some AI tools can reach parts of these sites, but many pages block automated access or show only partial content. Plan for a person to open and save the relevant pages. AI can then sort, summarise and theme the saved reviews quickly and consistently.
Why does Reddit matter for SEO and AI search?
User discussion on Reddit often appears in search results and AI answers. Google's 2024 partnership with Reddit gave it structured access to Reddit content to understand it and surface more of it. What users say about your category there shapes how buyers and assistants see it.
How often should competitor review research be updated?
Refresh it at least every six months, and sooner after a competitor launches a major feature, changes pricing or is acquired. Dated research lets you see which points are stale. Updating the competitor's profile once then updates every article built on it.
Related reading
- Chen, Mahe, Xiaoxuan Wang, Kaiwen Chen and Nick Koudas. "Generative Engine Optimization: How to Dominate AI Search." arXiv 2509.08919, 10 September 2025. https://arxiv.org/abs/2509.08919
- Google. "An expanded partnership with Reddit." Google, 22 February 2024. https://blog.google/inside-google/company-announcements/expanded-reddit-partnership/
- ACCC. "Online reviews for products and services." Australian Competition and Consumer Commission, accessed 30 October 2026. https://www.accc.gov.au/business/advertising-and-promotions/online-product-and-service-reviews