Competitor Intelligence
Copy-ready Claude prompt
Here are 10 threads mentioning our competitor {{competitor_name}} in {{product_category}}: {{paste_thread_excerpts}}. Summarize the three most common praise points and three complaints, and flag any thread where useful, disclosed input wouldn't read as an attack.Learning objectives
- Build a keyword configuration specifically for competitor names and product terms.
- Route competitor mentions to a dedicated intelligence board.
- Use account-analysis tooling to flag suspicious promotional activity.
- Budget for commercial-tier API costs if tracking scales beyond personal use.
Prerequisites: Module 5.2 in full.
Core concepts
Competitor intelligence reuses Module 5.2's stack, retargeted at a different keyword list. Add your top two to four competitors' names, product nicknames, and comparison phrases ("X vs Y," "X alternative," "switched from X to") as a separately-tagged set inside the same F5Bot/Syften account, the tool comparison from 5.2.1 applies identically, only the downstream question changes: not "is this a lead" but "what are people saying, and where are we absent from the same conversation."
Route alerts to a dedicated board rather than mixing into brand monitoring, Make.com's Reddit module (5.2.3) routes cleanly into Notion or Discord for a structured log (make.com). A durable structure: one row per thread, competitor named, sentiment (human-judged, not auto-scored, since nuance here is where LLM misclassification is costliest), what was praised/complained about, and whether you're also mentioned. That last column is the real payoff: threads mentioning a competitor but not you are your highest-value target list for genuinely helpful, disclosed participation.
wrhilton/Reddit-User-Analysis's karma/account-age checks and advertising-keyword spotting apply usefully here too, noticing when a suspiciously new or low-karma account posts unusually promotional content about a competitor helps you weight whether a glowing mention reflects a real customer or undisclosed marketing. You're not building this to retaliate; you're weighting signal correctly.
If tracking needs eventually justify commercial-scale access, revisit 5.1.1's numbers: ~$0.24/1,000 requests and a 2-4 week approval process (octolens.com). Most single-team tracking fits free-tier limits; budget commercial tier only once you have a concrete volume number exceeding it.
Video lessons
Supporting reading
- 13 Best Reddit Monitoring Tools in 2026, Syften (https://syften.com/blog/best-reddit-monitoring-tools/), revisit for Boolean/exclusion features separating competitor signal from noise.
- Reddit API Pricing in 2026, Octolens (https://octolens.com/blog/reddit-api-pricing), cost model before scaling to commercial volume.
- reddit Integration, Make (https://www.make.com/en/integrations/reddit), the routing layer for a dedicated intelligence board.
Exercise
Configure 10-15 competitor keywords/comparison phrases. Run one week alongside brand monitoring; build a log with at least five threads, human-tagged for sentiment and whether you're also mentioned.
Assignment
Write a competitor-intelligence summary: three common praise points, three common complaints, and one thread where the competitor is mentioned and you aren't, noting whether it's a genuine opportunity.
Claude workflow
- Skill idea: a competitor-digest skill returning a praise/complaint summary plus a ranked list of threads where you're absent but relevant.
- Automation opportunity: the monitor-and-log pipeline is automatable end to end; sentiment judgment and any reply require a human.
Expected outcomes
- Competitor keyword set live one week with a minimum five-thread log.
- Competitor-intelligence summary naming specific patterns.
- Explains why competitor sentiment should stay human-judged.