# What We Learned From Analyzing 9,658 Reddit Threads In Google 7 min read OK SEOs, so really excited to share some new research we've been working on at Nectiv. Reddit is everywhere in Google right now. It shows up in the organic results, in the "Discussions and forums" box, and it's obviously one of the biggest sources for AI search. This is doubly true for a lot of commercially based queries where people ask for recommendations. But here's the question we kept coming back to: when Google ranks a Reddit thread, why does it pick _a specific_ thread? There can be dozens of Reddit threads on any given topic. Most of them never make page 1. So we wanted to get data on what the winners actually have in common. Without further ado, let's get into it. ![](https://firebasestorage.googleapis.com/v0/b/nectiv-website.firebasestorage.app/o/public%2Fmedia%2F1793908846696-image1.png?alt=media) ## **Key Findings (Because I'm Legally Obligated To At This Point)** - **Title match is the most consistent factor.** In 64% of head-to-heads, Google ranked the Reddit thread whose title more closely matched the search. Average title similarity drops from 0.79 in positions 1–3 to 0.73 for threads not on page 1. - **Using the exact query helps even more.** When only one of two threads had the exact query in its title, that thread won 74% of the head-to-heads. It's also 2.8x as common in top-3 titles (13% vs 5%), but only 13% of top-3 titles do it. - **Winning titles ask for recommendations.** 68% of top-3 titles are recommendation questions, compared to 52% of threads that didn't rank. - **Personal titles do worse.** Titles that describe the poster's own situation lost 58% of their head-to-heads. - **Comments help, but less than the title.** The thread with more comments won 58% of head-to-heads, compared to 64% for the closer title match. - **Freshness isn't an advantage.** The typical top-3 thread is about 1.5 years old, the same as threads that don't rank. ## **First Up, Our Methodology** For this analysis, we pulled the "best" keywords Reddit ranks for in Google from Ahrefs, removed branded terms and took a sample of 1,567 across low, medium and high search volume. For each keyword, we ran two live Google searches through SerpAPI: 1. **The keyword itself**, to see which Reddit threads Google actually shows on page 1 and where. 2. **The keyword + "reddit"**, to find the other relevant Reddit threads on the same topic that _didn't_ make page 1. That gave us two main groups to compare for the same query: **1,008 threads ranking in the top 3** and **8,695 relevant threads that weren't on page 1**, plus 391 threads in positions 4–10. The most important comparison is what we're calling a head-to-head. For 902 queries, Google ranked one Reddit thread in the top 3 _and_ we found another relevant thread for the same query that didn't make page 1. Same query, same intent, same difficulty. So any difference between the two threads comes down to the thread itself. For each thread, we looked at the title (how closely it matches the query, whether it's a question, first person, etc.), comment counts, post age and more. Here are the findings ## **1\. Title Match Is The Most Consistent Factor (64% Of Head-To-Heads)** The most consistent signal in the entire data set was extemely simple: **Does the title say what the searcher typed?** To measure this, we scored how closely each title matched its query in meaning (semantic similarity, on a 0–1 scale). Then we grouped the threads by where they ranked. The average similarity steps down with every tier: ![](https://firebasestorage.googleapis.com/v0/b/nectiv-website.firebasestorage.app/o/public%2Fmedia%2F1793909108651-image3.png?alt=media) The biggest gap is between page 1 and everything else. Top-3 titles are 2.7x as likely to score 0.9 or higher (a near-exact match to the search) as threads that didn't make page 1 (23% vs 9%). Within page 1 the averages keep stepping down, but the differences between tiers are small and the 4–6 and 7–10 groups have far fewer threads, so I'd treat that part as directional. ![](https://firebasestorage.googleapis.com/v0/b/nectiv-website.firebasestorage.app/o/public%2Fmedia%2F1793909207429-image2.png?alt=media) **In 64% of head-to-heads, Google ranked the thread whose title more closely matched the search.** It also held up when we controlled for comments, post age, title length, search volume and keyword difficulty. Title match was the strongest predictor in that model, ahead of comments. So if you take one thing away from this study, it's that title is extremely powerful when it comes to the chosen Reddit thread. ## **2\. The Exact Query In The Title Wins 74% Of The Time** Taking that a step further, we looked at titles that contain the exact search query word for word. Only 13% of top-3 titles do this, so it's not common. But it's almost 3x more common than in threads that didn't rank (5%). **When only one of the two threads in a head-to-head had the exact query in its title, that thread won 74% of the time.** That's the highest win rate of anything we measured. Top-3 titles also used more of the query's words overall: the typical top-3 title contained 67% of the query's words, compared to 50% for threads that didn't rank (medians). ![](https://firebasestorage.googleapis.com/v0/b/nectiv-website.firebasestorage.app/o/public%2Fmedia%2F1793909285741-image5.png?alt=media) ## **3\. Winning Titles Ask For Recommendations But Aren't Too Personal** Another interesting insight was the type of language used in high performing Reddit threads. In general, Reddit threads that asked for recommendations were more likely to show up on the first page - winning 68% of head to head comparisons. On the flip side, titles that get personal tend to lose. These are the "I'm 35, have a $500 budget and bad knees, what should I buy?" style posts. **Titles that describe the poster's own situation lost 58% of their head-to-heads.** They make up 15% of top-3 titles but 21% of threads that didn't rank. ![](https://firebasestorage.googleapis.com/v0/b/nectiv-website.firebasestorage.app/o/public%2Fmedia%2F1793909370948-image4.png?alt=media) I'm guessing this comes back to the title-match finding. A broad question like "What's the best running shoe?" is a much closer match to what most people search than a question about one person's very specific situation. Those threads can be super helpful to read, but they're answering a narrower question than the query. ## **5\. More Comments Help, But Less Than The Title** Engagement does matter. 28% of top-3 threads had 100+ comments, compared to 18% of threads that didn't rank, and **the thread with more comments won 58% of head-to-heads** (vs 64% for title match). In our model, comment count was the second-strongest factor after title match. One caveat here: we're using the comment counts Google displays in the search results ("50+ comments"), which are rounded. Upvotes and post text aren't available without Reddit's API, so we couldn't include them in this round. ## **6\. Freshness Doesn't Matter** This was one of the more surprising ones. With all the talk about freshness in AI search, I expected newer threads to have an advantage. Put simply, they don't. **The median top-3 thread is about 1.5 years old, the same as threads that didn't rank.** Only 6% of top-3 threads were less than 3 months old. Most ranking threads were somewhere between 1 and 5 years old. ![](https://firebasestorage.googleapis.com/v0/b/nectiv-website.firebasestorage.app/o/public%2Fmedia%2F1793909561798-image7.png?alt=media) My read on this is that Google favors threads that have had time to collect real discussion, but aren't so old that they're out of date. A brand new thread with three replies isn't going to beat an established one. ## **So What Are The Takeaways Here?** If your brand is investing in Reddit, here's how I'd use this: - **Find threads whose titles mirror your target queries.** If you're choosing which conversations to join, the ones titled like the search are the ones Google is most likely to rank. - **Prioritize broad recommendation questions.** "What's the best X?" threads beat narrow, personal ones. - **Look for threads with real discussion.** More comments won more often. - Don't write off older threads. A 2-year-old thread with an active discussion is often the one ranking.