Manifold marketing data

link-building

When the user wants backlinks that help Google rankings, or a contact at any site to ask for a link, a list entry or a correction. Holds dated, sourced findings a model would not know (how much links still correlate with rankings, what Google's 2025-2026 spam updates neutralise, what paid placements cost and how to disclose them, how fast links decay, what domain rank, Ahrefs DR and spam score measure and where Manifold's backlink fields mislead), and the one copy of the steps that find and verify a publisher's contact. Also use when the user mentions link building, off-page SEO, growing DA or DR, link prospects, sites that link to competitors but not to us, guest posts, link insertions, unlinked mentions, lost or broken backlinks, link reclamation, 404 pages with links, broken link building, best X lists that rank on Google, disavow, toxic links, or buying links. Rankings and content go to seo, press campaigns to digital-pr, AI citations to ai-search, redirects and migrations to technical-seo.

linkedin

When the user wants to grow on LinkedIn without paying for it, as a founder, a team or a company page, or asks what works on LinkedIn now. Holds dated, sourced findings a model lacks (the 2026 feed rebuilt on LLM retrieval, reach for active posters down by a third to a half since 2024, the July 2026 cut to comment-keyword bait, what links and polls cost, the AI slop and pod crackdowns, how AI answers cite LinkedIn) and how to read Manifold's LinkedIn data honestly. Also use when the user mentions a LinkedIn strategy or 90-day plan, founder-led content, personal branding or thought leadership on LinkedIn, a company page audit or a competitor's LinkedIn page, what LinkedIn posts work, hooks, post length, why our posts get no reach, posts to comment on, a commenting routine, social selling, top LinkedIn voices in a niche, or people on LinkedIn asking for a tool like ours or complaining about a competitor. LinkedIn ads go to paid-ads, emails and outreach to the people found to outbound, X to x-twitter.

local-seo

When the user wants a business that serves a town or an area found on Google Maps, in the local pack and in AI answers, or asks what works in local SEO now. Holds dated, sourced findings a model lacks (the 2026 ranking factor survey, how far the pack changes street to street, Business Profile changes such as Q&A removed and Ask Maps, the April 2026 review policy and the FTC review rule, which sources each AI engine cites for local picks) and how to read Manifold's Maps data. Also use when the user mentions Google Maps ranking, the map pack, Google Business Profile or GMB, a profile audit, NAP and citations, a service area business, a suspended or unverified profile, getting more reviews, replying to reviews, fake reviews, a local rank grid or heatmap, near me searches, local competitors, multi-location SEO, local businesses without websites to pitch, or being recommended by ChatGPT for a local service. Classic rankings go to seo, AI answers beyond local to ai-search, pitching and reporting to agency.

manifold-get-started

When the user is new to the Manifold marketing skills, asks where to start, or wants to set up or update the context every other skill reads first. Writes .agents/product-marketing.md (the business type, what it sells, the customers, competitors, positioning, customer language, proof, goals, accounts and what to track) for any kind of business, from B2B software to a shop, a local service, an app, a creator or a nonprofit, drafting from the site and asking only for the gaps. Then recommends the two or three skills that fit the goal, and the first job to do in each, with what it costs. Also use when the user mentions getting started, I just installed this, which skill should I use, what can Manifold do, product or marketing context, describe my business, ICP, target audience, brand voice, or update our context after a pivot, a new competitor or a price change. A growth plan built on real data goes to growth-strategy.

market-research

When the user wants to size a market, map the players in a category, check whether there is demand for an idea, or decide whether to enter a new country, language or segment. Holds dated, sourced findings a model gets wrong (search volume is a bucketed 12-month mean, Trends disagrees with itself, AI search volume is a model, stated interest overstates paying, other countries use other search engines) and how to count accounts, demand and players with live data. Also use when the user mentions TAM, SAM, market size, how many companies fit our ICP, is the market big enough, a market map or landscape, who are all the players in X, segment the market, idea validation, is there demand for X, is anyone searching for X, is this market growing or dying, should we build X, a fake door or smoke test, expand into Germany, which country first, international expansion, localization, or moving into enterprise. Named rivals go to competitor-intel, pain points to voice-of-customer, a go-to-market plan to growth-strategy.

outbound

When the user wants B2B outbound that gets replies, a lead list, or to know what works in cold email now. Holds dated, sourced findings a model would not know (which Gmail, Yahoo and Microsoft sender rules bite on cold email to company domains, 2025-2026 reply-rate benchmarks and what moves them, whether AI personalisation works, why a third of B2B addresses cannot be verified, GDPR, PECR and CAN-SPAM basics) and how to read Manifold's leads data, email waterfall and verification statuses. Also use when the user mentions an outbound or ABM plan, cold outreach strategy, leads, a prospect or ICP list, decision makers by job title, enrich this CSV, append emails, verify or clean an email list, bounces, catch-all, intent data, buying signals, companies that just raised, champion or job-change tracking, lookalike companies, first lines or icebreakers, account research or call prep, or our first 100 customers. LinkedIn content and social selling go to linkedin, rivals to competitor-intel, client work to agency.

paid-ads

When the user wants to plan, research or brief paid ads on Meta, Google, LinkedIn, TikTok or ChatGPT. Holds dated, sourced findings a model would not know from training (Meta's Andromeda and why creative diversity now does the targeting, Performance Max controls and AI Max results, ads in Google AI Overviews, AI Mode and ChatGPT with reported prices, CPC and CPM benchmarks from large datasets, brand bidding law) and how to read ad library data without overclaiming. Also use when the user mentions a paid ads strategy, Meta or Google ads, where to spend an ad budget, PPC, paid social, whether LinkedIn ads are worth it, the Meta, TikTok or LinkedIn ad library, the Google Ads Transparency Center, a swipe file, winning ads in a niche, competitors' ads, PPC or negative keywords, CPC, who bids on our brand, conquesting, an ad creative brief, ad fatigue, Advantage+ or Performance Max. Creators who make the ads go to creators, a competitor beyond its ads to competitor-intel, which channels at all to growth-strategy.

reddit

When the user wants to market on Reddit, or asks what works there now. Holds dated, sourced findings a model lacks (ChatGPT stopped citing Reddit in August 2026 while Perplexity and Google kept it, member counts gave way to weekly visitors, how subreddits now ban promotion and AI-written text, karma and account-age filters, silent removals) and how to read Manifold's Reddit tools without miscounting. Also use when the user mentions a Reddit strategy or marketing plan, should we be on Reddit, the founder on Reddit without getting banned, Reddit threads to reply to, posts asking for a tool like ours, where to comment this week, Reddit pain points, what Redditors complain about, customer language from subreddits, which subreddits to post in, subreddit rules, is self promotion allowed there, can I post my product in r/SaaS, Reddit threads that Google or AI answers show, Reddit SEO, or Reddit ads. Pains across every source go to voice-of-customer, AI answers as a whole to ai-search, paid campaigns to paid-ads.

seo

When the user wants more organic traffic from Google, or asks what works in SEO now. Holds dated, sourced findings a model lacks (what the 2025 and 2026 updates rewarded and punished, CTR by position with and without AI Overviews, what the September 2025 num=100 change did to Search Console, how far keyword volumes and traffic estimates miss) and how to read that data without being fooled. Also use when the user mentions an SEO strategy or roadmap, keyword research, a content plan, topic clusters, pillar pages, an SEO brief or outline, quick wins, striking distance keywords, low-hanging fruit, title tags and meta descriptions, optimize this page, on-page SEO, content decay, refreshing or pruning old posts, keyword cannibalization, two pages competing, vs pages, alternatives pages, rank tracking, where do we rank, watching Search Console, or traffic drop alerts. Crawling, indexing, diagnosing a drop and migrations go to technical-seo, AI answers to ai-search, backlinks to link-building.

technical-seo

When the user wants to know if Google can crawl, render and index their site, why organic traffic fell, or how to move a site without losing rankings. Holds dated, sourced findings a model lacks (the September 2025 num=100 change that cut Search Console impressions with no real loss, the 2MB fetch limit, 2025 and 2026 update dates, how JavaScript, noindex and canonicals are handled now, how little Core Web Vitals weigh, how slowly domain migrations recover) and how to read crawl and Search Console data right. Also use when the user mentions technical SEO, an SEO audit or health check, crawl our site, broken links, duplicate titles, noindex or canonical problems, redirect chains, crawled currently not indexed, indexing problems, Core Web Vitals or INP, our traffic dropped, we lost rankings, was it a Google update, clicks down but impressions flat, a site migration, changing domains, a redirect map, a replatform, redesign or subdomain merge. Content and rankings go to seo, AI crawlers and llms.txt to ai-search.

tiktok

When the user wants organic growth on TikTok or asks what works there now. Holds dated, sourced findings a model would not know from training (what the 2026 US joint venture changed, what TikTok documents about For You and search, length, watch time and posting frequency from studies of millions of posts, engagement benchmarks by follower tier, the music limits that get brands sued) and how to read Manifold's TikTok data without fooling yourself. Also use when the user mentions a TikTok strategy or 90-day TikTok plan, starting a TikTok account for a brand, how often to post on TikTok, a TikTok audit, what a competitor does on TikTok, TikTok engagement rate, best performing TikToks, TikTok hooks or opening lines, what is trending on TikTok, trending formats or sounds, mining TikTok comments, objections or customer language from TikTok, why a TikTok went viral, TikTok SEO or search, or the TikTok algorithm. TikTok creators go to creators, TikTok ads to paid-ads, Reels to instagram, Shorts to youtube.

voice-of-customer

When the user wants to know what customers actually say on Reddit, in reviews, social comments, LinkedIn and search, turned into ranked pain points, objections, evidence-based personas or positioning. Holds dated, sourced findings a model lacks (posts against interviews, why mention counts miss the needs that matter, interview saturation, how far AI-simulated customers match people, how much of a 2026 sample is vendors and ads) and what mining each source costs. Also use when the user mentions pain points, voice of the customer (VOC), jobs to be done, what people struggle with, objections, why people hesitate to buy, is X worth it, buyer personas, our ideal customer, which roles buy, synthetic personas, an AI focus group, customer interviews or surveys, customer language for copy, how to position against X, what makes us different, a positioning statement or which category to claim. Reddit as a channel goes to reddit, a named rival's complaints to competitor-intel, demand and market size to market-research.

x-twitter

When the user wants to know what works on X (Twitter) now, audit an X account (their own, a founder's or a competitor's), or decide whether and how to post there. Holds what a model would not know from training (what X's published ranking code weighs since January 2026, what X has said and others have measured about link posts and Premium, why engagement benchmarks disagree by a factor of a hundred, who is on X in 2025-2026) and how to read Manifold's X tools, which see one account's feed and nothing else. Also use when the user mentions an X or Twitter audit, audit our Twitter, how does our Twitter compare to a competitor's, what a founder or brand posts on X, which tweets get the views, the X algorithm, the link penalty, links in replies, whether to pay for X Premium or a blue check, threads, why our reach dropped on X, shadowbanned, or an X strategy. LinkedIn goes to linkedin, finding and paying creators to creators, mentions of the brand by others to brand-monitoring.

youtube

When the user wants to grow on YouTube organically. Holds dated, sourced findings a model would not know (how YouTube says it recommends videos, Test and Compare picking thumbnails by watch time, views counted from the first frame since August 2026, the inauthentic content and Shorts originality rules, the 2027 Partner Program thresholds, YouTube as the domain Google's AI answers cite most) and how to read channel, video, comment and transcript data. Also use when the user mentions a YouTube strategy or 90-day plan, should we start a YouTube channel, YouTube SEO, a channel audit or teardown, most viewed videos, YouTube video ideas or keyword research, underserved topics, mining YouTube comments, objections in reviews, why a video blew up, replicating a video, Shorts, thumbnails, CTR, average view duration, or demonetisation. TikTok, Instagram, sponsoring creators and AI answers on every engine go to tiktok, instagram, creators and ai-search.