Reddit keyword research: how to find what your customers actually search for

The best keyword research tool you are not using is Reddit. Not because Reddit tells you what people type into Google - it tells you something more valuable: the exact words people use when they describe their own problems.

This distinction matters. Traditional keyword research tools show you search volume and competition. Reddit shows you the language of frustration, the phrasing of unmet needs, and the vocabulary your customers use before they have learned the polished terminology your industry prefers.

Here is how to use Reddit for keyword research, and how tools can automate what would otherwise take hours of manual reading.

Why Reddit keyword research is different

When someone searches Google for "project management software," they have already adopted industry language. They know the category exists. They are in evaluation mode.

When someone posts on Reddit about their project management problem, they say things like "I keep losing track of which tasks are blocked waiting on other people" or "my team has no idea what anyone else is working on and we keep duplicating work." Those phrases will never appear in a keyword research tool - but they are exactly what your landing page copy should address.

Reddit keyword research is not about finding terms to rank for. It is about finding the language of the problem your product solves.

The manual approach

Search Reddit directly with site:reddit.com [your topic] in Google. This works better than Reddit's own search because Google indexes Reddit deeply and ranks results by relevance.

Look specifically for:

Posts that start with "does anyone else..." - these signal widespread pain that the poster assumes others share.

Posts in the form of "why does [product/process] not..." - these signal a feature gap or expectation mismatch.

Posts asking "what do you use for..." - these are active buyers describing their requirements in their own words.

Comments that say "I just use..." - these reveal what people actually do versus what products promise.

Copy the exact phrases people use. Not summaries - the actual words. That is your content and copy input.

The subreddit approach

Find three to five subreddits where your target customer spends time. Search within each subreddit for your topic. Sort by Top > All Time to find the posts that resonated most with that community.

Pay attention to which posts get the most comments, not just upvotes. Comments mean the topic touched a nerve. Upvotes mean people agreed with a statement. Comments mean people had more to say.

Using the Algolia Hacker News API

Hacker News is indexed by Algolia and fully searchable via a free API with no rate limits or account requirements. If your customers are developers, founders, or technical teams, the HN corpus is valuable.

The Algolia HN search endpoint:

https://hn.algolia.com/api/v1/search?query=YOUR+TERM&tags=comment

This returns every HN comment mentioning your search term, with upvote scores and timestamps. Filter by points > 5 to surface comments that resonated. The language in highly-upvoted HN comments about a problem is often more precise and more quotable than anything you will find in traditional keyword research.

The G2 and App Store approach

G2 reviews and App Store reviews are public and scrapeable. They are structured complaint data: a person paying money for a product, describing exactly what it fails to do.

Search G2 for your product category. Filter for three-star reviews - low enough to find real complaints, high enough to filter out people who never engaged. Read the "What do you dislike?" sections. These are your competitor's unmet promises, written in the exact language buyers use.

App Store reviews follow the same pattern. Sort by Most Critical. The one-star and two-star reviews for apps in your category are a direct pipeline into customer pain language.

Turning Reddit language into SEO keywords

Once you have a set of phrases your customers actually use, run them through keyword volume tools to understand scale. Some will have zero search volume - they are still valuable for copy and messaging. Some will have meaningful volume - they are content opportunities.

The phrases with both authentic customer language AND search volume are your highest-priority content targets. They rank because people search for them. They convert because the language matches how your customer thinks.

What to do with what you find

Organise your findings into three buckets:

Problem language - how people describe the issue before they know a solution exists. Use this in problem-aware content and landing page headlines.

Solution language - how people describe what they are looking for once they know a solution should exist. Use this in product descriptions and comparison content.

Evaluation language - how people compare options when they are close to a decision. Use this in comparison pages and case studies.

Each bucket maps to a different stage of the buying journey and a different type of content.

Tools that automate this

Manually reading Reddit is time-consuming. Tools like Signal automate the collection and classification - ingesting posts and comments across Reddit, Hacker News, G2, and App Store reviews, then classifying each piece of content by intent: pain point, solution request, buying signal, or general discussion.

The output is a structured feed of what your target market is saying, organised by the type of insight it represents. It replaces hours of manual reading with a searchable, filterable intelligence layer.

Early access: bing.ly