Map which of 25k+ subreddits contain your ideal buyers. Filter by category and activity.
Traditional market research is expensive and slow. User interviews take weeks to organise, surveys have self-selection bias, and industry reports are $5,000–$20,000 for data that's already 12 months old by the time it's published. By the time you have your research, the market has moved.
Reddit is, for many categories, the most honest and unfiltered source of customer voice available. People talk about exactly which products they use, which features frustrate them, why they switched, and what they're willing to pay. This data exists in real time, publicly accessible — but only if you can find the right communities at the right scale.
The problem is that Reddit has 100,000+ active communities and no reliable way to identify which ones contain your target customers. Searching by keyword gives you posts, not communities. You need a community-level database that lets you filter by category, activity, and size — exactly what the Reoogle subreddits API provides.
The Reoogle subreddits API gives you a queryable database of 25,000+ monitored communities with member counts, activity data, language tags, and category classifications. Start with GET /categories to map the Reddit landscape, then drill into specific verticals with GET /subreddits filtered by category and activity floor. For your top candidates, pull hour-of-day engagement data to find the best posting times. The result is a precise, data-driven map of where your customers actually are — built in an afternoon, not weeks.
Map the category landscape first
Call GET /categories to get every category tag in the Reoogle database along with subreddit counts. This 30-second API call gives you a complete picture of how Reddit is segmented and reveals categories you might not have considered. Sort by count to find the most populated verticals, then look for niche categories that map closely to your product.
Query subreddits in your target categories
Use GET /subreddits with a category filter to surface every monitored community in your vertical. Start with broad categories (e.g. "Technology", "Finance") and then narrow. Set min_members=1000 and min_posts_60d=5 to exclude inactive communities and filter the results down to living, active audiences.
Cross-reference multiple categories
Your ideal customer probably lives in more than one subreddit category. A B2B SaaS founder exists in "SaaS", "startups", "entrepreneur", and "productivity" communities simultaneously. Run the same query across all relevant categories and deduplicate results — the overlap reveals your core audience clusters.
Profile each community with activity data
For your top 20 candidates, call GET /subreddits/{name}/activity to get hour-of-day and day-of-week engagement data. High variance between peak and off-peak times indicates a community that's active in bursts — great for time-targeted posting. Low variance indicates steady, always-on communities.
Estimate total addressable Reddit audience
Sum member_count across your target community list. This is your total addressable Reddit audience (TARA) for organic content marketing — a concrete metric you can use in marketing strategy documents and fundraising pitches. Be conservative: overlap between communities means the actual unique audience is 30–50% smaller than the sum.
Identify content gaps by reading top posts
For each target community, look at the top posts from the last 30 days to understand what content gets traction. What questions do people ask? What pain points come up repeatedly? What products do they mention? This qualitative signal shapes your content strategy far more accurately than keyword research tools.
Export and prioritise
Build a prioritised target list: avg_comments × quality_score as a proxy for engagement quality. Export to a spreadsheet and segment by audience size (micro: <5k, mid: 5k–50k, large: 50k+). Plan your posting cadence around this segmentation — different copy styles, different scheduling frequency for each tier.
Map all active SaaS communities
async function mapSaasAudience() {
const all: { name: string; members: number; avgComments: number }[] = [];
let page = 1;
while (true) {
const params = new URLSearchParams({
category: 0 , min_posts_60d: 1 ,
sort_by: 2 , order: 3 ,
per_page: 4 , page: String(page),
});
const res = await fetch( 5 , { headers: HEADERS });
const body = await res.json();
all.push(...body.data.map((s: any) => ({
name: s.name,
members: s.member_count,
avgComments: s.avg_comments,
})));
if (page >= body.pagination.total_pages) break;
page++;
}
const totalAudience = all.reduce((sum, s) => sum + s.members, 0);
console.log( 6 );
console.table(all.slice(0, 20));
return all;
}Find best posting time per sub
import requests
API = 0
HEADERS = { 1 : 2 }
def best_posting_time(subreddit: str) -> dict:
resp = requests.get(f 3 , headers=HEADERS)
activity = resp.json()[ 4 ]
best = max(activity, key=lambda r: r[ 5 ])
return {
6 : subreddit,
7 : best[ 8 ],
9 : best[ 10 ],
11 : best[ 12 ],
}
targets = [ 13 , 14 , 15 ]
for t in targets:
print(best_posting_time(t))Treating member count as audience quality
A subreddit with 500,000 members and 0.3 avg comments per post has less engaged audience than one with 8,000 members and 15 avg comments. Always prioritise avg_comments over raw size for any content marketing use case.
Researching once and never refreshing
Community composition changes. A subreddit that's active today may go dead in 3 months. Re-run your market research query quarterly and update your target list — don't set it and forget it.
Only looking at large communities
Micro-communities (500–5,000 members) often have the most concentrated, relevant audiences for niche products. Your best customers might be in r/specificvertical with 2,000 members, not in r/generaltech with 200,000.
25,000+
Subreddits in database
Actively monitored communities across all categories, refreshed continuously.
90% less
Research time vs traditional
Time to build a complete audience map using the API vs manual research or paid reports.
50k–5M
Addressable audience per niche
Typical total member count across all relevant communities for a B2B SaaS product, summed across categories.
How are subreddits categorised in the Reoogle database?
Categories are human-curated and supplemented by ML classification based on community description and top post content. Each subreddit has a primary_category and optional secondary_categories. You can browse all available categories via GET /categories before deciding which ones to target.
Can I search for subreddits by keyword rather than category?
Yes — use GET /search with a q parameter for full-text search across community names and descriptions. This is useful for finding very specific communities where the category tag is too broad. Combine search results with category-based results for the most comprehensive list.
How fresh is the member count and activity data?
Member counts and activity metrics are updated weekly. For high-activity communities, updates run more frequently. The last_updated field on each subreddit record shows when data was last refreshed.
Is this useful for pre-launch validation?
Extremely. Before building anything, you can quantify how many active Reddit communities exist for your target category, estimate the total engaged audience, and read the top posts to validate (or invalidate) your core value proposition assumptions — all before spending a dollar on development.
Business value
Most companies spend $5k–$20k on market research surveys and user interviews. The Reoogle API gives you a live, continuously refreshed picture of your Reddit audience in a single afternoon — for a fraction of the cost.
Generate an API key from your developer dashboard and make your first request in minutes.