Competitor Research Automation
Let AI agents monitor competitor accounts, content patterns, ecommerce listings, search visibility, engagement surfaces, communities, and campaign signals with reusable browser workflows.
Review competitor profiles, content lists, post surfaces, and audience interactions.
Gather consistent fields across competitors so research is easier to compare.
Move repeated monitoring into a workflow that teams can run before planning campaigns or product moves.
Operating Model
A repeatable research loop for marketing and operations teams
Competitor research is often a mix of browsing, checking public profiles, collecting posts, reading comments, reviewing listings, comparing search results, and saving useful signals. MultiAgentor Skills help AI agents run these steps consistently across platforms without turning every research request into a new manual project.
See what competitors publish, how often they post, and which surfaces they use.
Review visible comments, likes, shares, community replies, and engagement context.
Check how the same competitor behaves across Instagram, TikTok, YouTube, Reddit, Twitter, and Facebook.
Turn weekly or campaign-based research checks into named workflows.
Workflow
From research question to repeatable signal
List competitors
Prepare competitor names, profile URLs, keywords, communities, or product terms to monitor.
Choose signals
Decide whether you need post lists, profile metadata, comments, search results, or engagement surfaces.
Run research Skills
Use platform-specific Skills to open, collect, or review the relevant pages.
Compare findings
Review collected context, identify changes, and update the next research cycle.
Automation Plays
Research plays that fit Skills
Use Skills to turn recurring market checks into routines that can be assigned, repeated, and improved.
Profile monitoring
Open competitor profiles and collect visible profile or account information.
Content trend review
Collect recent posts, videos, titles, captions, and visible engagement signals.
Comment and community insight
Review what audiences say around competitor content or category conversations.
Platform Fit
Research competitors where they actually operate
Different platforms reveal different competitive signals: creator cadence, post format, comment themes, community traction, search visibility, and audience engagement.
Review competitor videos, creator pages, search surfaces, and engagement patterns.
Monitor creator profiles, posts, comments, explore surfaces, and follower-facing activity.
Track channels, videos, search results, titles, and visible engagement.
Watch communities, discussions, comments, and category-specific threads.
Recommended Skills
Start with ready-made Skills
Amazon Asin Url Extract
Amazon Asin Url Extract is an Amazon Skill for data processing. It runs in a real browser session to perform the configured browser workflow in a repeatable way. It accepts amazon entry url, language, delivery zip code, url list, keyword, content, whether content url, content url content as input. It can produce asin list, content url list, content count, page url as output.
Amazon Badge Label Collect
Amazon Badge Label Collect is an Amazon Skill for data analysis. It runs in a real browser session to perform the configured browser workflow in a repeatable way. It accepts amazon entry url, language, delivery zip code, keyword content asin, content, page content as input. It can produce content asin, page url as output.
Amazon Best Sellers Collect
Amazon Best Sellers Collect is an Amazon Skill for monitoring. It runs in a real browser session to perform the configured browser workflow in a repeatable way. It accepts amazon entry url, language, delivery zip code, best sellers url, content name, content, whether content details as input. It can produce content, asin, title, price, rating, content name, page url as output.
Amazon Brand Storefront Collect
Amazon Brand Storefront Collect is an Amazon Skill for data analysis. It runs in a real browser session to perform the configured browser workflow in a repeatable way. It accepts amazon entry url, language, delivery zip code, brand content url content asin, content product content as input. It can produce brand name, content list, product content, product content, page url as output.
Amazon Breadcrumb Taxonomy Collect
Amazon Breadcrumb Taxonomy Collect is an Amazon Skill for data analysis. It runs in a real browser session to perform the configured browser workflow in a repeatable way. It accepts amazon entry url, language, delivery zip code, asin list, path content as input. It can produce content path, asin, page url as output.
Amazon Buybox Offer Collect
Amazon Buybox Offer Collect is an Amazon Skill for data analysis. It runs in a real browser session to perform the configured browser workflow in a repeatable way. It accepts amazon entry url, language, delivery zip code, asin or product url, whether content as input. It can produce buy box content name, price, content asin, page url as output.
Amazon Category Browse Collect
Amazon Category Browse Collect is an Amazon Skill for data analysis. It runs in a real browser session to browse the feed in a natural, randomized way. It accepts amazon entry url, language, delivery zip code, content url, content product content, whether enter content as input. It can produce content name, content list, product content, page url as output.
Amazon Competitor Related Collect
Amazon Competitor Related Collect is an Amazon Skill for data analysis. It runs in a real browser session to perform the configured browser workflow in a repeatable way. It accepts amazon entry url, language, delivery zip code, asin or product url, content product content as input. It can produce content product list, content product, asin, page url as output.
FAQ
Common questions
Is competitor research only for marketing teams? +
No. It can support growth, product, operations, ecommerce, and research teams that need recurring visibility into public market activity.
Can Skills decide what strategy to choose? +
No. Skills help collect and organize the browser work. Strategy still comes from the team reviewing the signals and context.
How should teams start? +
Start with one platform, a short competitor list, and one or two signals. After the routine is useful, expand to more platforms or deeper collection.
Make competitor monitoring less manual
Give your team reusable Skills for recurring checks instead of starting from a blank browser session every time.