Charlie Grinnell writes and speaks about how brands can understand audience behavior beyond their own data, use creator and community insights, and make marketing decisions based on evidence rather than internal assumptions.
Charlie Grinnell is most useful for talks and workshops on audience research beyond a brand's own data.
Best for
Financial-services marketing teams seeking a practical session on customer trust outside the CRM.
Not for
Consumer brands wanting a paid creator-led social campaign with sponsored posts and usage rights.
Key takeaways
Every brand has a dark market its own data cannot see.
Influence is whoever the audience listens to when deciding, not follower count.
A real audience signal appears in more than one place and is big enough to matter.
Check first: Confirm recent fintech or financial-services session recording, deck, post-event feedback, and audience roles.
Main ideas
Every brand has a "dark market" its own data cannot see · Influence is whoever the audience listens to when deciding, not follower count · A real audience signal shows up in more than one place and is big enough to matter
Charlie Grinnell writes and speaks about how brands can understand audience behavior beyond their own data—and turn what they learn into better marketing decisions. Follow Grinnell for practical ways to find overlooked customer voices, test assumptions against evidence, and adapt when that evidence challenges the plan.
Grinnell’s distinctive contribution is connecting audience research to decisions teams can act on.
In a talk recap about the “dark market”, skincare conversations and small YouTube travel reviews illustrate how buyer behavior can differ from the audience or journey a brand assumes.
A story from Grinnell’s time leading social at Aritzia adds a useful discipline: look for signals that appear in multiple places and matter at meaningful scale, rather than building a plan around one striking data point.
That same outside-in approach shapes Grinnell’s advice on creator selection.
A post challenging follower-count shortlists asks brands to find the voices customers already trust—which could be creators, communities, newsletters, or other sources of influence.
Grinnell also argues for letting audience behavior settle creative debates: in a post on testing video variations, watch time becomes evidence instead of relying on the most senior person’s preference.
The work also examines where marketing systems fall short.
A monthly consumer-culture roundup connects platform changes and brand campaigns to the enduring importance of memorable human ideas.
In a post about AI and “contextual texture”, Grinnell shows why transcripts alone can miss jokes and shared references, and why AI-generated records should flag uncertainty for human review rather than guess.
Charlie Grinnell's recurring argument is that brands make marketing decisions from the data they already own — CRM records, focus groups, their own social listening — and miss the larger conversation happening outside those walls.
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They push teams toward outside-in research: find who the audience actually listens to when deciding, require more than one signal before moving budget, and settle creative disputes with audience behaviour rather than seniority.
A second thread runs through the work on AI: tools collect words but miss shared references and cultural knowledge, so a useful system has to say when it is unsure and keep a person in the loop.
In financial services, Grinnell frames creator trust as a competing relationship the CRM cannot see.
The posts mix conference talks, client-facing arguments, a monthly culture roundup, and product work at RightMetric.
Every brand has a "dark market" its own data cannot see
Grinnell argues that the behaviour happening around a category is bigger than what the brand measures, and that it never appears in CRM records, focus groups, or the brand's own social listening.
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The buyer is often there rather than in the tracked funnel. The fix they propose is not simply collecting more internal data but building a loop: monitor behaviour outside the brand's walls, measure it so it becomes more than a feeling, then adapt the plan even when the findings contradict the plan already made.
A skincare brand believes its audience is women aged 35–50, premium and aspirational, while the real category conversation is often 22–32 year olds doing ingredient deep-dives and dupe comparisons. Luxury travel brands map Instagram to website to booking, but bookings often come from 15-minute "honest stay" reviews on small YouTube channels with a few thousand subscribers, not the destination photography absorbing the budget.
Influence is whoever the audience listens to when deciding, not follower count
Grinnell argues that creator shortlists sorted by follower count systematically exclude the voices customers actually follow, and that brands overpay for the least attention.
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The supporting claim is that influence is not a person at all — it is whoever the audience already listens to at the moment of decision, which can be a creator, a subreddit, a newsletter, a news outlet, or a relative.
Instead of a follower filter, they propose three questions: who does our audience already listen to when deciding, is anyone in our category actually winning with creators or are we assuming, and which voices could mention us without it reading like an ad.
None of those answers appear in a platform report.
Gymshark sent free gear to smaller fitness YouTubers instead of betting on big fitness celebrities. For a bank, the voice moving a newcomer toward their first Canadian credit card is probably someone with a few thousand followers explaining credit scores in their first language — someone who would never appear on a celebrity shortlist.
A real audience signal shows up in more than one place and is big enough to matter
Drawing on time as head of social at Aritzia, Grinnell describes teams pulling a behavioural dataset, finding the first place a segment looks distinctive, and building a media plan without asking whether the finding is real.
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Two tests decide it: the signal appears in more than one place at once — interests, brands and creators pointing the same direction — and it is big enough to matter, because a tiny over-indexed niche is a trap even when the pull is genuine. What survives both tests is worth budget; what does not is a chart that looked interesting in a meeting.
A newcomer banking segment over-indexes on a remittance app.
That is one signal.
If the same people also over-index on money-transfer creators, settlement subreddits, and the grocery chains that stock food from home, Grinnell treats it as worth sizing up.
Their practical advice: take an important segment, find where two or three signals point to a place where nothing is being spent, and bring that gap to the next budget meeting.
Trust is moving from institutions to creators, and the CRM cannot see it
In a short event post aimed at financial services, Grinnell argues that a client may already trust a fintech app more than the brand, and that relationship-tracking systems were never built to see trust move that way.
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A CRM can flag a renewal call; it cannot see that the client has started trusting someone else more. The claim is that creators win that attention with content built for how people actually behave online rather than what a client profile says about them.
Grinnell says they were digging into exactly this at Digital Marketing for Financial Services Midwest in Chicago on September 22, presenting the trust shift as a core financial-services issue rather than a brand-awareness extra.
Creative decisions should be settled by audience behaviour, not by who is most senior
Grinnell treats notes like "can we make the font bigger" and "can we add loud music" as guesses, and observes that without evidence in the room, rank becomes the tiebreaker — so good ideas die because the loudest or most senior person did not like them.
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Their argument is that testing moves the argument out of the meeting entirely: make variations, put them on the platform, and let retention decide, because choosing to keep watching is the audience choosing to spend time with the brand.
YouTube announced it would let advertisers upload up to three cuts of the same video, starting with Shorts, and show which one people kept watching.
Grinnell's advice for when the feature lands: take footage already planned, get two or three edits made, and test simple variables first, such as how soon the product appears and how long the video runs.
At the time of the post the feature was not live and YouTube had given no firm date.
AI can collect words but not meaning, so a good system admits what it does not know
Grinnell separates context — what was said — from what the post credits their friend Jared Henriques with calling "contextual texture": the inside jokes, shared references and cultural knowledge nobody ever wrote down.
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The risk is that an AI tool confidently summarises something it never understood, and never signals the gap. Their proposed standard for AI-assisted research is honesty about uncertainty: source what you can, mark what you cannot, and keep a person in the loop.
A call transcript mentioning the line "I'm all sweaty, I was watching Cops" reads as a Step Brothers reference to anyone who knows the film, and as nothing to a tool that would summarise it anyway with total confidence.
Grinnell describes what RightMetric is building: Google Drive as the filing cabinet plus a map that updates daily, checking recorded calls, Basecamp threads and Drive for what was decided and why, linking back to the original call, asking a person when context only the team has is needed, marking unsourceable dates and dollar figures as missing instead of guessing, labelling output "proposed" until a person reviews it, and marking superseded decisions rather than deleting them.
The ask at the end is a single test question: what does the system do when it isn't sure?
Hand the platforms the mechanics; the memorable part still has to come from the brand
In a recurring monthly roundup format, Grinnell scans platform and consumer-culture changes and draws one conclusion: as platforms absorb targeting, creative and even checkout, what remains a brand's own job is the part people remember.
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The format itself is a stated priority — pattern-spotting across several shifts at once rather than one announcement at a time — and it doubles as a platform-risk briefing for marketing teams.
The roundup covers TikTok Buy Direct moving one-tap checkout into the For You feed; ChatGPT testing visual ads while people wait for an image to generate; Meta opening Customer Lifecycle Strategy to all advertisers with a spend-only-on-new-customers toggle; updated Meta ad terms making advertisers responsible for AI changes from October 30; ŌURA hand-building a miniature city with 35 modelmakers in Prague rather than using AI; Liberty Mutual's Jim Henson Creature Shop mascot with 40–50% of marketing dollars behind it; Popeyes biscuit mix and sauces on Canadian grocery shelves; and Amex Canada saying referrals drive customer acquisition.
Grinnell closes: "Hand the platforms the targeting, the creative, even the checkout.
The part people remember still has to come from you."
A newcomer can see how Grinnell scans platform and consumer-culture changes and turns them into a monthly brief.
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It answers what this person pays attention to, and how platform change can affect brand decisions.
Grinnell runs through a month of shifts: TikTok Buy Direct moves checkout into the For You feed; ChatGPT tests visual ads while people wait for image generation; Meta opens Customer Lifecycle Strategy so an AI toggle can spend only on new customers; Meta's updated ad terms make advertisers responsible for AI changes from Oct.
30; ŌURA uses 35 Prague modelmakers to hand-build a miniature city; Liberty Mutual introduces Liberty Biberty, a Jim Henson Creature Shop puppet, with 40–50% of marketing dollars behind it; Popeyes puts biscuit mix and sauces on Canadian grocery shelves; Amex Canada says referrals drive customer acquisition.
Grinnell closes: 'Hand the platforms the targeting, the creative, even the checkout.
The part people remember still has to come from you.'
For brands planning a campaign
For a fintech team, this is a ready-made agenda for a monthly platform-risk review. It argues that as platforms absorb targeting, creative and checkout, the remaining brand job is distinctive memory—so a campaign brief should reserve budget for ideas that cannot be reduced to a platform setting.
Answers a common team problem: how to settle subjective creative arguments with audience evidence.
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It shows Grinnell translating a platform feature into a practical workflow.
Grinnell describes the familiar notes—'Can we make the font bigger?' 'Can we add loud music?'—as guesses.
YouTube announced it will let advertisers upload up to three cuts of the same video, starting with Shorts, and show which one people kept watching.
Grinnell says this moves the argument out of the meeting, where rank often becomes the tiebreaker and 'great content ideas die ... because the loudest or most senior person in the room didn't happen to like them.' The audience decides by choosing to keep watching.
The feature was not live and YouTube had no firm date.
His advice: take footage you were already going to use, get two or three edits made, and test simple variables first, like how soon the product shows up and how long the video runs.
For brands planning a campaign
A fintech creator brief can require three low-cost cuts around one core idea and let watch behavior decide. The implication is to budget for variant production and instrument the test, rather than spend the same money on one internally approved edit.
This is the clearest explanation of Grinnell's core thesis: the 'dark market.' It answers what they mean by behavior that never shows up in CRM, focus groups, or social listening.
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Grinnell tells the story of speaking with Rand Fishkin at the back of the room and explains the 'dark market': behavior around a category that never shows up in a CRM, focus group, or the brand's own social listening.
Two examples: a skincare brand that thinks its audience is women 35–50, premium and aspirational, while the real conversation is often 22–32 year olds doing ingredient deep-dives and dupe comparisons; and luxury travel brands that map Instagram to website to booking, while bookings often come from 15-minute 'honest stay' reviews on small YouTube channels with a few thousand subscribers.
Neither scenario lives in the data the brand already has.
The fix is a loop: monitor outside the walls, measure it so it is more than a feeling, and adapt even when findings contradict the existing plan.
For brands planning a campaign
Before a fintech media plan is locked, the team can fund an outside-in listening pass across communities, small creators and review formats that the CRM would miss. This post also gives the strongest raw material for a talk or workshop on dark-market trust signals.
Direct evidence for fintech relevance, and a short statement of the trust shift Grinnell speaks about.
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It answers why a fintech brand would bring this person in.
Grinnell writes that a CRM can flag a renewal call but has no idea the client has already started trusting someone else more.
Wealth is shifting to people who trust a creator over an institution, and creators are winning attention with content built for how people actually behave online rather than what a client profile says.
Grinnell says they are digging into exactly this at Digital Marketing for Financial Services Midwest in Chicago on September 22.
For brands planning a campaign
Use this as the anchor for a financial-services workshop: it frames creator trust as a retention and acquisition issue, not a brand-awareness extra. The speaking date also shows a live market where the talk can be positioned.
A practical guide to rethinking creator selection.
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It answers how Grinnell wants brands to choose voices, and what to use instead of follower count.
Grinnell opens by betting that a next creator shortlist will be sorted by follower count and that the voices customers actually listen to will not be on it.
They cite nano and micro creators near 17% engagement versus mega and celebrity creators around 6%, and say nano creators now land 43% of all brand partnerships.
The argument: 'Influence isn't a person.
It's whoever your audience already listens to when they're making a decision.' That can be a creator, subreddit, newsletter, news outlet, or sister-in-law.
Gymshark sent free gear to smaller fitness YouTubers rather than betting on big celebrities.
A bank's decisive voice might be someone with a few thousand followers explaining credit scores in their first language.
Grinnell swaps the follower filter for three questions: Who does our audience already listen to when deciding?
Is anyone in our category actually winning with creators, or are we assuming?
Which voices could mention us without it reading like an ad?
For brands planning a campaign
A fintech team can replace a follower-count shortlist with those three questions and then look for decision-stage voices in credit, budgeting, remittance and newcomer communities. The campaign brief should ask for the names of five voices customers listened to last month, not a list of platform metrics.
Explains Grinnell's operating philosophy on AI and context, which matters for any brand using transcripts, call recordings or automated research.
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It answers what good AI-assisted research should do when it is unsure.
Grinnell uses a Step Brothers reference to show the gap: an AI tool reading a call transcript would not get the joke but would summarize it with total confidence.
A transcript gives AI the words, not necessarily the meaning.
Their friend Jared Henriques calls the missing layer 'contextual texture': inside jokes, shared references and cultural knowledge nobody wrote down.
At RightMetric, Grinnell says they are building it with Google Drive as the filing cabinet and a daily-updating map on top: the system checks recorded calls, Basecamp threads and Drive, writes down what was decided and why, links back to the call, asks a person in Basecamp when it needs context only the team has, marks unsourceable dates and dollar figures as missing instead of guessing, labels everything 'proposed' until a person reviews it, and marks superseded decisions rather than deleting them.
The closing question: 'what does it do when it isn't sure?' If it guesses, it thinks the person was actually watching Cops.
For brands planning a campaign
For a fintech brand evaluating AI research or call-analysis tools, this post supplies a concrete test: ask what the system does when it lacks context. The campaign or workshop can use it to argue for reviewable, sourced, status-labelled AI outputs in regulated financial marketing.
Gives a concrete method for validating audience signals.
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It answers how to tell a real behavioral insight from an interesting chart before spending next year's budget on it.
Grinnell recalls a senior leader trying to kill an influencer partnership with three words—'She's not cool.' That was one signal from one person's taste; the data pointed the other way.
Grinnell did not know who was right, but remembers neither side had enough to know.
The pattern Grinnell sees: teams pull a behavioral dataset, find the first place a segment looks distinctive, build a media plan, and never ask whether it is real.
A real signal passes two tests.
It shows up in more than one place at once—interests, brands and creators pointing the same direction—because one spiky data point is usually a false positive.
It is also big enough to matter, since a tiny over-indexed niche is a trap even when the pull is real.
Example: a newcomer banking segment over-indexes on a remittance app; if the same people also over-index on money-transfer creators, settlement subreddits and grocery chains that stock food from home, the signal is worth sizing.
The data itself is a commodity, but most competitors never turn it into a decision.
Grinnell's advice: take an important segment, find where two or three signals point to the same place where nothing is being spent, and bring that gap to the next budget meeting.
For brands planning a campaign
A fintech team can run this two-test cross-signal exercise before committing budget: require at least two or three independent signals—interests, creators, communities and spending behavior—to converge before funding a new segment. It also gives a simple diagnostic for why a campaign plan built on one over-indexed chart should not proceed.
Who your audience already listens to, not follower count
Charlie Grinnell argues creator shortlists default to follower count and miss the voices customers actually follow.
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They cite nano and micro creators near 17% engagement versus mega and celebrity creators around 6%, and nano creators taking 43% of brand partnerships, then point to Gymshark sending free gear to smaller fitness YouTubers and a bank example where someone with a few thousand followers explaining credit scores in their first language may move newcomers more than a celebrity. The core claim is that influence is not a person but whoever the audience listens to when making a decision, including subreddits, newsletters, outlets, and family.
Before a brief, ask who the audience listens to when deciding, whether anyone in the category is winning with creators, and which voices could mention the brand naturally.
Those answers do not show up in a platform report; they require watching what the audience reads, watches, and shares outside the brand's view.
For brands planning a campaign
For a fintech brief, build shortlists around audience listening behavior and community trust rather than tier size, then pressure-test whether a creator can mention the product without it reading like an ad.
Charlie Grinnell describes every brand having a dark market: behavior around its category that never appears in CRM, focus groups, or social listening.
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One example is a skincare brand that thinks its audience is women 35 to 50, premium and aspirational, while the real conversation is often 22 to 32 year olds doing ingredient deep-dives and dupe comparisons.
Another is luxury travel brands mapping Instagram to website to booking while bookings come from 15-minute honest stay reviews on small YouTube channels with a few thousand subscribers.
The fix is not more internal data but a loop: monitor outside the walls, measure it so it is more than a feeling, and adapt even when findings contradict the plan.
Build an outside-in loop that monitors category behavior the brand does not own, turns it into measurement, and adapts the plan when the data contradicts internal assumptions.
For brands planning a campaign
A fintech team should look outside CRM and owned social listening for where trust actually shifts. Small YouTube channels, communities, and creator reviews can be more decision-relevant than polished brand content.
How to tell a real audience signal from an interesting chart
Drawing on time as head of social at Aritzia, Charlie Grinnell recalls a senior leader trying to kill an influencer partnership with 'She's not cool' while the data pointed the other way, and neither side had enough to know.
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Many teams pull a behavioral dataset, find the first distinctive segment, and build a media plan without asking whether it is real.
A real signal must show up in more than one place at once, such as interests, brands, and creators pointing the same direction, and be big enough to matter.
In a banking example, a newcomer segment over-indexes on a remittance app; if the same people also over-index on money-transfer creators, settlement subreddits, and grocery chains stocking food from home, the bet is worth sizing up.
Two tests: the signal appears in more than one place at once, and it is big enough to matter.
One spiky data point on its own is usually a false positive, and a tiny over-indexed niche is a trap even when the pull is real.
For brands planning a campaign
For fintech and banking campaigns, require multiple corroborating signals and size before moving budget. Look for places where two or three signals point to the same underfunded gap.
Charlie Grinnell says notes like 'Can we make the font bigger?' and 'Can we add loud music?' are guesses, and rank becomes the tiebreaker when no evidence is in the room.
Read more
They point to YouTube's plan to let creators upload up to three cuts of the same video, starting with Shorts, and show which one people kept watching.
Charlie Grinnell calls it a great equalizer for marketing teams because social managers, brand managers, CMOs, and people in the video often disagree.
The audience is the boss, and retention is the evidence.
Make as many variations as practical, put them on the platform, and let audience performance decide.
At the time of the post, the YouTube feature was not live and had no firm date.
For brands planning a campaign
For organic video, ship multiple edits and test simple variables first, such as how soon the product appears and how long the video runs; use retention to settle creative disputes.
AI needs context and texture, not just transcripts
Charlie Grinnell distinguishes context, or what was said, from what the post credits Jared Henriques with calling contextual texture: inside jokes, shared references, and cultural knowledge that was never written down.
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An AI tool reading a call transcript might confidently summarize a Step Brothers reference it does not understand.
Charlie Grinnell says RightMetric is building a system that checks recorded calls, Basecamp threads, and Google Drive for new decisions, writes down what changed and why with links back to the call, asks a person when it needs context only the team has, marks dates and dollar figures as missing instead of guessing, and labels outputs 'proposed' until a person reviews them.
Old decisions are marked superseded, not deleted.
Build an updating map over the filing cabinet, with missing-data flags and proposed labels, and let people supply context the system cannot source.
Charlie Grinnell says the system is not perfect, which is why a person still reads what it writes.
For brands planning a campaign
For brands using AI for creator or community research, demand systems that show uncertainty, cite sources, and keep a human review step. A fluent summary of a transcript is not the same as understanding an audience.
Charlie Grinnell publishes a 60-second roundup of platform and consumer-culture shifts.
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Examples include TikTok Buy Direct one-tap checkout in the For You feed, ChatGPT testing visual ads while people wait for an image, Meta opening Customer Lifecycle Strategy to all advertisers with a new-customer toggle, updated Meta ad terms making advertisers responsible for AI changes from October 30, ŌURA hand-building a miniature city with 35 modelmakers in Prague instead of using AI, Liberty Mutual's Jim Henson Creature Shop mascot getting roasted by John Oliver with 40 to 50 percent of marketing dollars behind it, Popeyes biscuit mix and dipping sauces on Canadian grocery shelves, and Amex Canada saying referrals are key to acquisition. The takeaway is to hand platforms targeting, creative, even checkout, but the memorable part still has to come from the brand.
A short monthly briefing format that groups several platform and culture changes into one scannable update.
For brands planning a campaign
Use these roundups to spot platform shifts and budget implications quickly. For a fintech brief, note how referral and AI-driven lifecycle tools change acquisition but do not replace a distinctive brand memory.
In a short event post, Charlie Grinnell says a client may already trust a fintech app more than the brand, and the CRM cannot see it.
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The CRM can flag a renewal call; it cannot see that the client has started trusting someone else more.
Charlie Grinnell says wealth is shifting to people who trust a creator over an institution, and creators win attention with content built for how people behave online, not what a client profile says.
They were digging into this at Digital Marketing for Financial Services Midwest in Chicago on September 22.
A conference talk or workshop format focused on trust movement and dark-market behavior in financial services.
For brands planning a campaign
Fintech marketers should treat creator and community trust as a competing relationship signal, not just a campaign channel. A talk or workshop can map where trust is moving outside the CRM.
Charlie Grinnell's posts name a handful of organisations he is personally attached to: a past in-house role at Aritzia, work on AI context tooling at RightMetric, and two speaking appearances.
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The month-in-review posts cite platforms and consumer brands as news items — TikTok, Meta, ChatGPT, ŌURA, Liberty Mutual, Popeyes, Amex Canada, YouTube — but those are commentary, not clients, sponsors, or partners, and are not listed here.
Aritzia
Employment
Grinnell writes that eight years before the post he was head of social at Aritzia, and recounts a senior leader trying to kill an influencer partnership with the words "She's not cool."
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The role is stated in his own words; the post does not describe an ongoing relationship with the company.
Describing a system that reads recorded calls, Basecamp threads and Google Drive files to record what was decided and why, Grinnell writes in the first person — "We're building for it at RightMetric right now" and "Our Google Drive is the filing cabinet" — which places him inside the company.
Grinnell thanks SocialPacific for hosting a talk where he presented his "dark market" argument about audience behaviour that never appears in a brand's CRM or social listening.
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The post records the appearance but no commercial terms.
Grinnell says he is speaking at this conference in Chicago on September 22 about clients who trust a fintech app more than the institution holding their account.
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The post is an appearance notice with a registration link, and states no sponsor or client arrangement.
Charlie Grinnell's posts are easiest to explore in two passes.
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Start with the monthly consumer-culture roundups for a fast scan of platform shifts, then move to the longer arguments on audience research, where the recurring move is to look outside CRM records, focus groups, and owned social listening for behavior a brand is not measuring.
The creator-marketing posts apply that to shortlists and follower counts; the signal-validation post sets out two tests for deciding whether an audience finding is real.
A separate thread on AI and context explains why a transcript alone misses shared references and inside jokes.
For financial-services readers, the fintech posts connect creator trust to acquisition and to blind spots in relationship systems.
Both treat channel choice as a question of where the audience already spends attention: Moylan watches premium DTC brands move into LinkedIn for consideration-stage content, while Grinnell argues in a fintech context that influence sits with whoever the audience listens to when deciding, not with follower count.
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Moylan writes as a fractional growth operator for DTC and B2B clients, with campaign results such as traffic and lead figures; Grinnell's posts are frameworks for audience research, signal validation, and platform shifts rather than client performance reports.
Both use short, diagnostic LinkedIn posts that take a standard business process and show where it breaks — Dorban on fixed procurement models meeting moving accommodation requirements, Grinnell on follower-count shortlists and single-signal media plans.
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Dorban's subject is procurement and workforce accommodation spend, not marketing audiences, and his posts run a few sentences rather than Grinnell's framework-length arguments.
Both write for marketers about how content should be planned and distributed: Macey on repurposing video across channels and running YouTube like an SEO programme, Grinnell on testing multiple cuts and letting retention decide.
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Macey's work is hands-on client execution for content marketing, SEO, and YouTube channels, with subscriber and traffic figures; Grinnell writes more about research and decision frameworks than channel operations.
Charlie Grinnell is a plausible fit for the fintech brief at the topic level so far: the supplied posts show they write and speak about audience trust, creator selection, dark-market behaviour, and measurement beyond CRM data.
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The evidence does not establish that Grinnell’s audience contains the financial-services marketers, creators, or decision-makers the brief needs.
The only measured audience figure supplied is a LinkedIn account count: 17,846 followers observed on 8 October 2026.
That is reach on one channel.
It does not show geography, age, gender, employer, occupation, job seniority, or whether followers are active buyers.
The seven posts are content signals, not audience-composition data; they show the subjects that may attract an audience, not who that audience is.
Before booking a talk or workshop, ask for recent results from comparable work: a fintech or financial-services session, a creator-selection or dark-market presentation, and any audience survey showing roles, seniority, geography, or company type.
For the dark-market talk, also request the deck or a session recording and post-event feedback from a fintech audience.
That would let the buyer judge whether Grinnell’s reach converts into the specific trust-and-measurement audience the brief needs.
No sponsorship package, rate card, media kit, or published sponsor policy appears in the material reviewed here, so there is no documented paid placement format for a buyer to plan around.
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What the posts do document is Grinnell as a speaker and session presenter: he has talked through dark-market audience research at industry events, including SocialPacific and Digital Marketing for Financial Services Midwest in Chicago, and he offers his slide deck by direct message.
For a fintech team weighing a talk or workshop, that is the practical route — an invitation to present or run a working session rather than a sponsored post.
He also writes as an adviser on creator and influencer selection, arguing that influence is whoever an audience already listens to at the moment of decision, that follower-count shortlists usually miss those voices, and that a signal has to survive tests of repetition and scale before it deserves budget.
That is the subject matter he would bring to a workshop; it is not a service sold through branded placements.
Contact runs through LinkedIn, where the posts invite direct messages for the deck and for his team's approach to giving AI tools usable context.
No partnership inquiry page, email, or submission form is supplied.
This records an absence of documented offers in the reviewed posts; it is not a claim that Grinnell never accepts sponsorships.
A financial-services marketing team that needs a practical session on where customer trust is moving outside its CRM is a strong fit.
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Charlie Grinnell already speaks and writes on exactly this ground: a CRM can flag a renewal call but cannot see that a client has started trusting a creator or community more; categories have a dark market of behaviour that never appears in CRM, focus groups, or the brand's own social listening; and creator shortlists often default to follower count while the voices that move decisions sit in smaller creators, subreddits, newsletters, and local-language explainers.
The documented commercial route matches a talk or workshop better than a sponsored placement.
The posts show Charlie Grinnell presenting at industry events, including a financial-services marketing conference in Chicago, and offering a slide deck by direct message.
They bring worked examples that a financial-services team can use: a skincare brand whose assumed 35–50 audience misses the 22–32 conversation driving the category; luxury travel bookings coming from short "honest stay" reviews on small YouTube channels rather than destination photography; and a banking example where a remittance app over-index is only worth acting on when it aligns with money-transfer creators, settlement subreddits, and grocery chains stocking food from home.
The fit is topic-led and speaker-led.
The buyer should still ask for a recent fintech or financial-services session recording, the deck, and feedback from a comparable audience, because the supplied evidence does not include audience demographics or session results.
For a workshop, the practical outputs—signal validation, creator shortlist questions, and a draft brief—are supported by the material.
A paid creator sponsorship brief would need separate evidence, covered below.
When to choose a specialist
A consumer brand that wants a paid creator-led social campaign is a poor fit on the supplied evidence.
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The brief would be something like a DTC skincare or food brand asking for six sponsored posts or short videos, product integration, paid usage rights, whitelisting, and an exclusivity window at a stated rate.
The reviewed posts contain no sponsorship package, rate card, media kit, or published sponsor policy.
The partnerships material records an absence of documented paid placement formats in the reviewed posts, not a claim that Charlie Grinnell never accepts sponsorships.
A buyer should not treat an unknown commercial feature as if it exists.
There is also an audience mismatch.
The only measured audience figure supplied is 17,846 LinkedIn followers observed on 8 October 2026.
That is not enough to promise a consumer brand reach among a particular age, geography, or buying group.
The content evidence is mostly commentary and advice for marketers—creator selection, dark-market research, signal validation, creative testing, AI context, and a consumer-culture roundup—not a record of product-led lifestyle content that would support a consumer sponsorship.
The right next step for that brief is to ask directly whether paid creator work is offered, request past sponsored examples with performance data, and get audience demographics before planning any spend.
A worked campaign example
Worked campaign angle: a 90-minute workshop for a bank or fintech acquisition team, titled "Mapping trust signals outside the CRM." The reader task is to help the team find the voices, communities, and behaviours that shape decisions before the CRM sees them.
Before the session: the client picks three priority segments, shares its current CRM view and social-listening keywords, and asks each attendee to bring five voices customers listened to last month. Charlie Grinnell supplies the deck as a pre-read.
Agenda: 1. 10 minutes: define the dark market, using the skincare audience mismatch and the luxury-travel honest-stay review example to show how a brand's existing data can point away from the real conversation. 2. 20 minutes: run the two signal tests. For each segment, map where interests, brands, creators, and communities point the same direction; require at least two independent signals, then size the niche. Use the remittance-app example: a single over-index is not enough; money-transfer creators, settlement subreddits, and grocery chains stocking food from home are the corroborating signals. 3. 20 minutes: replace the follower-count shortlist with three questions: who does the audience already listen to when deciding; is anyone in the category actually winning with creators; and which voices could mention the brand without it reading like an ad. Look at nano and micro creators, subreddits, newsletters, and local-language explainers, not just tier-one names. 4. 15 minutes: map trust movement. Use the fintech trust post to discuss how a client may already trust a creator or app more than the institution, and what that means for retention and acquisition. 5. 15 minutes: each team writes a one-page brief: audience, the voices worth testing, the message, and the first test. 6. 10 minutes: owners and next steps.
Outputs: a one-page campaign brief, a shortlist of ten voices with a reason for each, two low-cost test ideas, and a gap list where CRM or listening data is missing. A content team that also wants to settle creative arguments could add a short module on testing two or three cuts of the same video and letting retention decide, but that is a separate use of the material.
Caroline Moylan is the stronger choice when the team already knows who it needs to reach and wants an operator to build the campaign.
Read more
In one reviewed post, PilotShip Partners, a financial-services firm working in capital introduction, brought Caroline Moylan in as fractional head of growth; the post reports search, AI-search and website work plus a LinkedIn personal-brand push, 430% traffic growth over five to six months, 47 qualified website leads, and a number-one ranking on brand terms.
A second post argues that premium DTC brands are using LinkedIn for the consideration stage, citing creator content consumption among B2B buyers and LinkedIn influencer marketing driving direct sales.
For a fintech team that needs traffic, leads and a channel plan run for them, this is direct execution evidence.
The reviewed material is one engagement's results plus a channel argument, not a repeatable method for finding the voices and behaviours that never appear in CRM, focus groups or listening data.
A team that has not yet located those signals would still need that diagnostic work first.
The performance figures are self-reported, with no audience demographics or independent measurement.
Greg Dorban is the better choice when the brief is a procurement or operations spend review.
Read more
The two reviewed posts argue that a procurement process can run well and still produce a poor accommodation outcome when a fixed model meets a moving requirement, and that workforce accommodation is worth centralising and managing as a serious spend category with meaningful hard cost on the table. A buyer whose real question is how to control a large variable cost across sites, bookings and changing headcount is closer to this material.
These posts are about workforce accommodation procurement.
They do not cover client or consumer trust, creator selection, dark-market research or financial-services audiences.
If the campaign decision stays as stated, a trust-signal workshop for a fintech team, this material leaves the central reader task unanswered.
Bobby Macey is the stronger choice when the team needs a video-first content and search engine built and run.
Read more
The reviewed posts show the work after a video goes live: embedding it in a related blog post, linking to it from other site pages, feeding it into email journeys, and cutting five or more Shorts or Reels across Instagram, Facebook, TikTok and YouTube.
A second post describes a four-year YouTube programme for a knee-pain clinic that it says took subscribers from under 300 to more than ten times that number and raised website clicks from about 3,000 to over 60,000 a month.
A team whose buyers search for a solution and that needs someone to publish, repurpose and measure video has a concrete case to check.
The evidence is channel execution and search distribution, not analysis of where trust is moving.
The posts do not cover creator evaluation, dark-market research or financial-services audience behaviour, so they do not replace the workshop's method.
The audience example is a healthcare clinic, and no demographic detail or independently verified performance data is supplied.
This page draws on seven LinkedIn posts by Charlie Grinnell, covering audience research, creator selection, creative testing, AI-assisted research, platform roundups, and financial-services trust, plus comparator posts by three other creators used only to compare approach and format.
Individual post dates and view counts were not included with the evidence; no talk recordings, video transcripts, or audience demographics beyond a follower count observed on 8 October 2026 were available.
The material shows Grinnell's stated ideas and examples of his work; it does not establish paid sponsorship formats or employer details beyond what the posts themselves say.
Recent engagement
Across their last 8 LinkedIn posts, the median post got 11 reactions and 1 comments. Checked 2026-11-02.
