Research: Community Intelligence

The internet's most honest conversations about your industry - the buying decisions, the frustrations, the competitor comparisons, the questions that nobody knows how to answer - happen in communities: subreddits, Hacker News threads, Twitter/X replies, niche forums. These conversations are public and searchable, but monitoring them manually is a full-time job.

Bingly's Research feature automates that monitoring. It ingests posts from across the major community platforms in real time, classifies each one by intent, and surfaces the signals that matter - buying signals, competitor mentions, brand mentions, questions your content could answer - in a single filtered feed.

This document explains how the feed works, how to get the most from it, and how to turn community intelligence into action.

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What the Research Feature Monitors

Reddit

Reddit is the largest open forum on the internet and one of the richest sources of unfiltered buying intent and competitor opinions. Bingly monitors posts and comments across relevant subreddits for your tracked keywords. Subreddits vary enormously in signal quality: r/entrepreneur and r/SaaS are high-signal for B2B software; vertical subreddits (r/webdev, r/marketing, r/DataEngineering) are where your actual prospects spend time and ask genuine questions.

Bingly surfaces both posts and high-engagement comments. A comment thread on a two-year-old post can still be actively receiving replies and driving purchasing decisions today.

Hacker News

Hacker News (news.ycombinator.com) is smaller than Reddit but carries disproportionate weight in technical and developer audiences. HN posts and comments frequently appear in AI training data, which means high-ranking HN threads can directly influence what AI models know and cite about your industry.

Beyond AI visibility, HN is a critical channel for developer tools, infrastructure products, and anything targeting a technically sophisticated audience. A "Show HN" post that gains traction, or a "Ask HN" thread about a problem your product solves, can drive significant qualified traffic and brand awareness.

Bingly monitors HN for keyword matches in post titles and comment text, ranked by engagement (points and comment count).

Twitter/X

Twitter/X is the primary real-time channel for technology and marketing professionals. It is where trends surface earliest, where competitors announce product changes, and where opinion leaders form and spread narratives about tools and categories.

Bingly monitors Twitter/X for keyword mentions, tracking posts from accounts with meaningful reach as well as organic posts from everyday users. Twitter/X is particularly valuable for detecting emerging competitor narratives, brand sentiment shifts, and early buying signals from high-intent accounts.

Other Sources

Depending on your plan, Bingly can also monitor:

• LinkedIn - for professional audience discussions, particularly relevant for B2B
• Dev.to and Hashnode - for developer-focused communities
• Product Hunt - for launch activity and competitor tracking
• Specific subreddits or communities on request

The source selection on the search screen lets you choose which platforms to include in any given search run.

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How the Feed Works

Real-Time Ingestion

Bingly polls each platform's public API and content feeds continuously. New posts matching your tracked keywords are ingested, normalised into a common schema, and added to your feed within minutes of publication on the source platform.

The normalised schema stores:

• Source platform and post URL
• Author identifier (anonymised where required by platform terms)
• Post title and body text
• Engagement metrics (upvotes, comments, retweets - normalised per platform)
• Publication timestamp
• Extracted keyword matches
• AI-assigned intent classification and confidence score

Deduplication

The same conversation can surface multiple times - a Reddit post shared to Twitter, or the same story appearing in both a subreddit and a HN thread. Bingly deduplicates by content fingerprint and URL canonicalisation, so you see each unique conversation once, regardless of how many times it was syndicated or reshared.

Cross-platform deduplication is surfaced as a "seen on" badge - you might see a Reddit post with a note that it was also discussed on HN. This is useful signal in itself: a topic discussed across multiple platforms simultaneously is a stronger trend signal than one isolated to a single community.

Sorting and Ranking

The default feed order is a relevance-weighted recency score: recent posts are ranked higher, but lower-engagement posts are down-ranked relative to posts that are attracting active discussion. This means a three-day-old Reddit thread with 200 comments can outrank a ten-minute-old post with no replies.

You can re-sort the feed by:

• Recency - newest first, regardless of engagement
• Engagement - highest comment/upvote count first
• Intent score - highest-confidence buying signals and competitor mentions first
• Relevance - closest keyword match first

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Intent Classification - What It Means

Every post in your Research feed is tagged with one of five intent labels. These labels are assigned by an AI classifier trained on community content, and they are the most important filter in the feed.

Buying Signal

A Buying Signal post is one where the author is actively in-market: evaluating options, asking for recommendations, or signalling imminent purchase intent.

Examples:

• "Switching from [competitor] - what do people recommend?"
• "My team needs a solution for X by end of month. What are you all using?"
• "Finally getting budget approved for Y. Which tool did you end up going with?"

Buying Signals are the highest-value posts in your feed. They represent real prospects who have self-identified their intent publicly. A timely, helpful reply to a Buying Signal post can directly influence a purchasing decision.

Competitor Mention

A Competitor Mention post is one that names a competing brand - whether positively, negatively, or neutrally.

Examples:

• "[Competitor] just increased prices again. Looking at alternatives."
• "Really impressed by [competitor]'s new feature"
• "How does [competitor] compare to [other competitor]?"

Competitor mentions are valuable for two reasons. First, negative competitor mentions are warm leads - someone dissatisfied with a competitor is a prospect for your product. Second, positive competitor mentions tell you what the community finds compelling about your competition, which is direct product and positioning intelligence.

Brand Mention

A Brand Mention post is one that names your tracked brand directly.

Examples:

• "Has anyone used [your brand]? What do you think?"
• "[Your brand] was just acquired - does anyone know what this means for existing customers?"
• "Shoutout to [your brand] support team, incredibly helpful"

Brand mentions give you a pulse on what people are saying about you. They surface reputation signals - praise, complaints, misconceptions, feature requests - that would otherwise require active social listening to catch.

Question

A Question post is one where the author is asking for help, information, or guidance on a topic your content is designed to address.

Examples:

• "How do I set up X to work with Y?"
• "What's the best way to measure Z?"
• "Does anyone have experience with [workflow your product enables]?"

Questions are valuable because they represent content opportunities as much as sales opportunities. A frequently-asked question that your content doesn't directly address is a gap in your content strategy. A question your content answers perfectly is an invitation to reply with a link - tactfully, naturally, and helpfully.

General Discussion

General Discussion posts match your keyword but don't fit cleanly into any of the above categories. They might be industry news, opinion pieces, tangential mentions, or casual conversation.

General Discussion posts have lower immediate action value, but they are useful for:

• Understanding the vocabulary and framing your audience uses
• Spotting emerging topics and trend shifts before they become competitive
• Content ideation - the topics that generate the most organic discussion are often underserved by existing written content

Confidence Scores

Every intent classification comes with a confidence score expressed as a percentage. A post tagged "Buying Signal - 94% confidence" is a very clear buying signal; "Buying Signal - 61% confidence" is a probable buying signal but with some ambiguity. You can filter the feed to show only high-confidence classifications if you want a tighter, lower-volume signal.

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Using the Search and Filters

Keyword Filter

The keyword filter at the top of the Research feed lets you narrow the visible posts to those matching a specific term or phrase. This is useful when you are tracking a broad keyword (for example, "email marketing") but want to focus on posts about a specific aspect (for example, "email deliverability") without running a new search.

The filter operates on the extracted keyword match field, not a full-text search of the post body, so it is fast and does not require a new API call.

Source Filter

The source filter lets you show posts from one platform at a time. If you want to see only Reddit posts, or only HN threads, toggle the other sources off. This is particularly useful when a specific platform is the primary channel for your audience.

Intent Filter

The intent filter is the highest-signal filter in the Research feed. Selecting "Buying Signal" alone reduces the feed to its highest-action-value subset. Selecting "Competitor Mention" alone gives you a competitive intelligence briefing.

Common filter combinations:

Date Range

The date range filter limits posts to a specific time window. Useful for reviewing what was discussed in the past week before a sales call, or for comparing this month's conversation volume with last month's.

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The Detail Panel

Click any post in the Research feed to open the detail panel on the right side of the screen.

AI Summary

At the top of the detail panel, Bingly displays a two-to-three sentence AI summary of the post's content and intent. This is faster to read than the full post text and is particularly useful when scanning a high-volume feed.

Full Post Context

Below the summary, the full post text is displayed - including any replies or comments that Bingly captured at ingestion time. For Reddit threads, the top-ranked comments are shown. For Twitter/X, the reply thread is shown if available.

Reading the full context before responding is important. A post that looks like a buying signal from its title might, in context, already have received several good answers - in which case adding another reply adds less value and more noise.

Intent and Confidence

The intent label and confidence score are displayed prominently in the detail panel, along with a brief explanation of why the classifier assigned that label - which phrases or signals triggered the classification. This helps you calibrate whether you agree with the classification and whether the post warrants action.

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Draft Reply Feature

The Draft Reply button in the detail panel generates a suggested reply to the post, tailored to its content, intent, and community context.

How It Works

Bingly's reply drafting takes four inputs:

1. The post content - what the author is asking or saying
2. Your brand profile - what your product does and who it serves (configured in your account settings)
3. The community context - which subreddit or forum this is, and what tone is appropriate for that community
4. The intent classification - whether this is a buying signal, a question, a competitor mention, and so on

The draft is designed to be genuinely helpful rather than promotional. For a Question post, the draft leads with a direct answer to the question. For a Buying Signal, the draft acknowledges the need and explains how your product addresses it - without opening with a sales pitch. For a Brand Mention, the draft engages with what the author said rather than simply promoting.

Crafting Authentic Replies

The draft is a starting point, not a finished response. Before posting, you should:

• Edit for your voice - the draft is written to be natural, but you know your brand voice better than the AI does
• Add specifics - if the post mentions a particular use-case or industry, make your reply specific to that context
• Check the thread - read any existing replies to avoid duplicating points that have already been made
• Remove anything that sounds like an ad - community members are extraordinarily sensitive to promotional content; the moment a reply reads like marketing copy, it loses all credibility

The best replies to buying signal posts often don't mention your product at all in the first paragraph. They lead with a genuine answer to the question, establish credibility, and then mention your product as one option - not the only option.

Platform-Specific Norms

Different communities have different norms around self-promotion:

• Reddit - most subreddits have strict rules against self-promotion; check the sidebar rules before posting. Replies should read like community member contributions, not corporate communications.
• Hacker News - the community is highly sensitive to inauthentic replies; if you disclose a product affiliation clearly and your reply is genuinely useful, it will be received well. If it reads like marketing, it will be flagged.
• Twitter/X - more tolerance for brand accounts engaging directly, but replies should still add value rather than just linking to your homepage.

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Alerts and Notifications

Setting Up Keyword Alerts

In your account settings under Alerts, you can configure email or in-app notifications for high-priority feed events. Alert triggers include:

• New Buying Signal - get notified whenever a post classified as a Buying Signal appears for a tracked keyword
• Competitor Mention - get notified when a competitor is named in a tracked keyword feed
• Brand Mention - get notified whenever your brand is mentioned across any monitored platform
• Engagement threshold - get notified when a post about your keyword exceeds a certain engagement level (useful for catching viral conversations early)

Alerts can be set per keyword or globally across all tracked keywords. You can configure separate alert rules for different keywords - for example, immediate alerts for brand mentions but daily digests for general keyword activity.

Alert Frequency

Setting too many alerts leads to alert fatigue and makes it easy to miss the genuinely important signals. A sensible default configuration for most users:

• Immediate alerts for: Brand Mention, Buying Signal (high confidence only, 80%+)
• Daily digest for: Competitor Mention, Question, General Discussion

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Use Cases

Brand Monitoring

Track your brand name as a keyword. Set up immediate alerts for Brand Mention and filter the feed to Brand Mention intent. This gives you a real-time reputation monitoring feed - you will know within minutes when your brand is mentioned positively or negatively in any major community.

Respond promptly to negative mentions. A frustrated customer who posts publicly and receives a helpful, direct response from the company within a few hours is much more likely to revise their opinion than one who posts into silence.

Competitor Research

Track your main competitors as keywords. Filter the feed to Competitor Mention and Buying Signal. Posts where users express frustration with a competitor, announce they are switching, or ask for alternatives are direct leads. Posts where users praise a competitor tell you what that competitor does better than you - or is at least perceived to do better.

Maintain a running list of the most common competitor complaints in your Research feed. This is the most direct source of product positioning intelligence available.

Content Ideation

Filter the Research feed to Question intent for your core topic keywords. Sort by engagement. The most-upvoted, most-commented questions are the topics your audience cares about most but isn't finding satisfying answers to elsewhere. Each one is a potential article, guide, or documentation page.

Cross-reference these questions against your existing content. If you have an article that answers a highly-upvoted question, that article is underperforming its potential - it either isn't visible enough or doesn't answer the question clearly enough to be surfaced by search or AI.

Sales Intelligence

For B2B products, the Research feed can be integrated into a sales workflow. Buying Signal posts - particularly those naming competitors and asking for alternatives - are warm inbound leads. Some teams build a Slack integration that pipes Buying Signal posts directly to a sales channel, where a team member can respond within the hour.

Speed matters here. A prospect who posts "looking for an alternative to [competitor]" is in active evaluation mode. A helpful reply that appears within an hour is far more likely to influence their decision than the same reply posted three days later.

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Best Practices

What Keywords to Track

Track the question your buyers are asking, not just your product name. "Best [category] software" and "alternatives to [competitor]" are often more signal-rich than your brand name itself, because they surface buyers at the point of decision.

Track competitors' brand names. This surfaces dissatisfied competitor customers - the warmest leads available anywhere.

Track the problem your product solves, not just the category name. If your product helps with "contract renewals", track "contract renewal process", "missed contract renewals", "contract management problems" - the vocabulary of pain, not just the vocabulary of solution.

How Often to Check

For brand mentions and buying signals: check daily, or set up immediate alerts for high-confidence signals.

For competitive intelligence and content ideation: a weekly review is usually sufficient. Set aside 20-30 minutes each week to read through the week's feed, note recurring themes, and identify posts worth responding to.

For trend monitoring: a monthly review of the General Discussion feed, sorted by engagement, gives you a good read on which topics are gaining momentum in your space.

How to Act on Signals

Not every post warrants a response. Before replying, ask:

1. Is this post still active? (A six-month-old Reddit post with no recent comments is not worth responding to)
2. Has the question already been answered? (Adding a duplicate answer adds noise)
3. Can I add genuine value? (If your only response is "try our product", do not reply)
4. Am I the right person to reply? (Some posts warrant a response from a product expert, some from a customer success lead, some from an executive)

The Research feed is most powerful when it is connected to a clear ownership model inside your team. Someone should own brand mentions, someone should own buying signals, and someone should own the content ideation pipeline. Without that ownership, the feed becomes a dashboard that people check but nobody acts on.