Last spring, a Series B SaaS company (let’s call them Latchwork, because the real name is under NDA and the founders are British enough to find that funny) sat across from me with a problem that’s becoming depressingly common. Their funnel was working. Their business wasn’t.
What follows is the engagement, more or less as it happened. I’ve composited a few details from two other clients facing the same pattern, but the numbers are real and the decision points are unedited. Treat this as the conversation we’d have if you’d brought the same dashboard to my table.
The SaaS client that broke our funnel
Latchwork sells workflow software to operations teams at mid-market manufacturers. GBP 14M ARR, 38% YoY growth, the kind of company that looks healthy on a board deck and panicked in a Slack DM.
Lead volume up, revenue flat
The dashboard told a tidy story. MQLs up 41% year-over-year. Cost per lead down 18%. Form fills, demo requests, gated content downloads, all green arrows. The CMO had a slide deck she was rightly proud of.
Revenue, meanwhile, had been flat for two quarters.
Sales were closing the same number of deals from a much larger pile of leads. Conversion from MQL to SQL had fallen from 22% to 11%. The pipeline was getting fatter and slower at the same time, a sort of metabolic disorder for go-to-market teams.
The first uncomfortable diagnostic
I asked the SDR team a single question: when a deal closes, what do buyers say convinced them? The answers had nothing to do with the funnel we’d built.
“Saw you in a Reddit thread about ERP integrations.” “My peer at [competitor’s customer] mentioned you on a call.” “Heard the founder on the Operations Leaders podcast.” “Someone in our Pavilion Slack said you were the only tool that didn’t need a six-month implementation.”
Not one buyer cited a webinar. Not one cited a gated PDF. The marketing team had spent GBP 180,000 in the previous quarter producing assets that, when you interrogated them, weren’t moving the deals that closed.
Did you know? According to trust and thought leadership stage of the funnel, the ideal marketing funnel would actually be a marketing cylinder where every lead converted, but this is famously not a reality for any real business. The shape of the leak matters more than the size of the top.
Why attribution stopped making sense
Here’s the bit that broke me. We ran a multi-touch attribution model, the proper one, with Bizible feeding into Salesforce, weighted touchpoints, the works, and it credited paid search with 47% of pipeline influence.
Then we asked closed-won customers directly. Paid search showed up in roughly 12% of stories, and almost always as the last touch, the moment someone, already convinced, typed the brand name into Google to find the demo button.
Attribution was measuring the doormat, not the journey. The funnel diagram assumed buyers entered at a defined top and progressed in measurable stages. Latchwork’s actual buyers had been marinating in mentions for months before they ever showed up in a CRM.
Myth: Multi-touch attribution captures the real buyer journey. Reality: It captures only the journey that touches your trackable properties. Every Slack DM, podcast download, and overheard meeting comment is invisible to your model, and those are often the touches that actually decide the deal.
Mapping where buyers actually decided
Once you accept that the funnel is a partial map, the next question is uncomfortable: where are the conversations? You can’t optimise what you can’t see, but you can at least catalogue it.
Reddit threads, Slack groups, podcast clips
We spent six weeks doing what I now call a “presence audit.” It’s not glamorous. Two analysts, a shared Notion doc, and a lot of search operators.
For Latchwork’s category, we identified 23 communities that mattered. Three subreddits with serious operational depth (r/manufacturing, r/ERP, and a smaller one I won’t name because it’s still half-pristine). Eleven Slack and Discord groups: Pavilion, RevGenius, two industry-specific ones, a few CFO peer groups. Nine podcasts, ranging from 4,000 listeners to 80,000.
Then we counted. How often did Latchwork come up? How often did each of their three main competitors? In what context: recommendation, complaint, comparison, neutral mention?
The results were brutal. Latchwork’s largest competitor was mentioned 4.3 times more often, and 71% of those mentions were unprompted recommendations. Latchwork appeared in 60% fewer threads, and when they did, the tone was neutral or mildly confused (“anyone tried these guys?”). Nobody was advocating. Nobody was warning others off them either, which is almost worse.
The dark social audit we ran
The harder layer was dark social, the stuff that never appears in any analytics tool. WhatsApp threads. Internal company Slacks. Conference hallways. We couldn’t measure these directly, but we could proxy.
The proxy: a “How did you hear about us?” field on the demo form, replacing the useless drop-down with an open text box. (Drop-downs lie. They funnel people into “Google” because it’s first.) Within a month, 38% of respondents wrote something that contained a person’s name or a community name. “Mark from Acme told me.” “Saw it in the Pavilion #tools channel.” “Lukas’s podcast.”
That number, 38% person-or-community mentions, became our north-star reading. It told us how much of inbound demand was carried by other people’s voices versus our paid channels.
Counting mentions instead of clicks
We built a weekly tracker. Not a dashboard, just a spreadsheet, because dashboards make people defensive about the numbers. Columns: source, date, sentiment, audience size, was it solicited or organic, and did we have a relationship with the speaker.
Did you know? Atlassian’s guide to funnel analysis notes that funnel charts cannot tell you why drop-offs occur. They’re “best used as a high-level visualisation before moving into a deeper investigation.” Most teams treat the funnel as the investigation rather than the prompt for one.
Rebuilding the budget around presence
This is where it got political. You don’t move marketing budget without somebody’s quarterly bonus getting nervous.
Pulling 40% from paid search
Latchwork was spending GBP 62,000 a month on paid search. About GBP 24,000 of that was on bottom-funnel terms, branded plus high-intent category keywords, that genuinely did capture demand. The other GBP 38,000 was on broad-match category terms that drove volume, looked good in the Google Ads dashboard, and converted to MQLs that didn’t close.
We pulled GBP 25,000 a month, roughly 40% of total search spend, and reallocated it. Not all at once; over a six-week taper, watching pipeline like a hawk. Branded search stayed untouched. We protected the doormat.
Where that money went instead
The new allocation, monthly:
- GBP 8,000 to podcast sponsorships in three of the nine relevant shows, flat fee, full-episode reads by the host
- GBP 6,000 to a community manager (fractional, three days a week) whose job was being genuinely useful in those 23 communities
- GBP 5,000 to customer story production: short video, written case studies, quotable data points customers could use
- GBP 3,000 to directory and citation listings in operations-focused B2B catalogues, including a curated entry in the Web Directory under the workflow software category, where we’d noticed buyers cross-checking vendors before booking demos
- GBP 3,000 to a quarterly research report we’d produce and seed
That last one mattered more than it looks. Original data is the single most-mentioned content type. Nobody quotes your blog post about “5 Tips for Better Workflows.” They quote your survey of 400 operations managers because they can use the number in their own slide.
The internal pushback we worked through
The paid search manager was furious. Predictably. Her dashboard was about to look worse, through no fault of her own, and her quarterly review was tied to MQL volume.
The fix wasn’t to argue with her. It was to change her metric. We moved her bonus from MQL volume to MQL-to-SQL conversion rate and pipeline contribution. She immediately started killing her own bad keywords, the ones she’d been protecting because they hit her targets, and her remaining campaigns got 30% more efficient within two months. Compensation drives behaviour more than strategy decks ever will.
Myth: Marketers resist budget shifts because they don’t understand strategy. Reality: They resist because they’re being paid against metrics that punish the new strategy. Fix the comp plan first; the strategy fight gets a lot shorter.
Six months of mention-first execution
The plan looked clean on a slide. Reality, as ever, was messier.
Seeding conversations without astroturfing
The line between “participating in community” and “astroturfing” is thinner than agencies pretend, and audiences sniff it out within weeks. We had three rules.
One: the community manager always identified herself as working at Latchwork. No sock puppets, no “long-time lurker” nonsense. The transparency cost us nothing because she was actually helpful.
Two: she answered questions about competitors honestly, including recommending them when they were the better fit. This sounds insane until you watch what happens. A recommendation against your own interest is the single most credibility-building thing a brand representative can do. Three months in, two competitor recommendations had circled back as Latchwork deals because the asker remembered who’d been straight with them.
Three: she never posted in a thread we’d seeded ourselves. If a customer asked us to write something they could share, fine, but they posted it. The goal was earned presence, not theatre.
Quick tip: When you join a community as a brand, set a public ratio: for every one mention of your product, contribute ten genuinely useful answers that have nothing to do with you. Track it. The communities that matter will notice the ratio before they notice your product.
Equipping customers as narrators
Customers will tell your story. Most don’t because you’ve made it inconvenient. We rebuilt the customer marketing motion around making advocacy frictionless.
Every quarter, we shipped customers a “narrator pack”: three short data points specific to their account (“you saved 340 hours of ops time this quarter”), two quotable statistics from our research report, and one ready-to-post LinkedIn draft they could edit. About 22% of recipients posted something. That’s not viral, but at 90 customers, it meant roughly 20 organic LinkedIn posts a quarter from credible practitioner accounts. Worth more than any sponsored post.
We also identified the eleven customers who already posted publicly about operations work and gave them earlier access to product, more founder time, and an invitation to a small advisory group. Two of them went from occasional posters to consistent advocates. One started a podcast that now mentions Latchwork in nearly every episode, not as a sponsor, just as a tool they use.
The LLM citation experiment
Halfway through the engagement, we noticed something in customer interviews: a fair number of buyers had asked ChatGPT or Perplexity to recommend tools in the category before talking to us. By month four, this was 19% of new opportunities and climbing.
So we ran an experiment. We tracked which sources LLMs cited when asked “what’s the best workflow tool for mid-market manufacturers” and similar prompts. The citations were dominated by G2 reviews, a few specific publications, Reddit threads, and, surprisingly, well-structured directory listings and category pages.
We did three things. We doubled down on getting reviews on G2 and a smaller industry review site. We pitched stories to the publications that LLMs were actually pulling from (not the ones with the biggest brand names, the ones with the deepest topical archives). And we made sure our directory listings were complete, accurate, and used the language buyers used.
By month six, when we re-ran the LLM prompts, Latchwork was appearing in 4 of 7 recommended-tool lists across ChatGPT, Perplexity, and Claude. It had been in zero at the start.
Did you know? ClickFunnels’ beginner guide describes a sales funnel as “the simplest way to turn someone who’s never heard of you into someone who buys from you.” That definition still holds. The question is whether the simplest path still runs through your owned channels, or through someone else’s mouth first.
Numbers that convinced the CFO
I have a rule with CFOs: never lead with the philosophy. They’ve heard it. Lead with the cohort.
Pipeline quality shifts
Six months in, MQL volume was down 23%. That number lived on a slide we showed nobody outside marketing.
The numbers we did show: SQL conversion rate had moved from 11% to 27%. Average deal size up 18%, because bigger companies were now showing up, since peer recommendations travel up-market more easily than Google ads do. Sales cycle down from 94 days to 71 days, because buyers were arriving pre-convinced rather than pre-curious.
Net new pipeline was actually 14% higher than the previous half despite the volume drop. Fewer leads, better leads, faster close.
CAC payback from 14 to 9 months
The CFO’s favourite metric. CAC payback period, the months of gross margin needed to recover the cost of acquiring a customer, moved from 14 months to 9. That’s the kind of shift that changes how a board talks about your unit economics.
Two things drove it. The mix of larger deals at similar acquisition cost, and the compounding effect of mentions: a podcast episode from month two was still driving demos in month six, while a paid search click was dead the moment it converted or didn’t.
| Metric | Month 0 (baseline) | Month 6 |
|---|---|---|
| MQL -> SQL conversion | 11% | 27% |
| Avg sales cycle | 94 days | 71 days |
| CAC payback | 14 months | 9 months |
| “Person/community” demo source mentions | not tracked | 52% |
| LLM tool-list inclusion rate | 0/7 prompts | 4/7 prompts |
What we couldn’t measure (and accepted)
The honest part. We never built a clean attribution story for the new approach. We couldn’t tell the CFO “podcast X drove GBP Y in pipeline” with the precision the old dashboard pretended to offer.
What we could say: the only variable that changed was the budget reallocation, and these are the cohort outcomes. That’s a worse measurement story and a better business story. The CFO, to her credit, accepted it. Not all CFOs would. If yours wouldn’t, the political battle is yours to fight before the strategy battle.
Myth: If you can’t attribute it cleanly, you can’t justify it. Reality: The most valuable marketing activities in B2B have always been hardest to attribute: relationships, reputation, word-of-mouth. The dashboards that promised to fix this have been quietly wrong for a decade. Better to admit the measurement gap than to optimise toward the bits you can see.
Translating this to other constraints
Latchwork had budget, a competent team, and a category with active communities. Most engagements don’t have all three. Here’s how the playbook bends.
The $5K/month version
Cut everything except two things: the customer narrator programme and presence in three communities. That’s it.
The community work is one good person, two days a week. Could be a contractor, could be the founder for the first six months. (Founders, in fact, do this better than anyone, and it doesn’t scale, which is fine because nothing about early-stage marketing should.) The narrator programme costs almost nothing in cash; it costs the discipline to actually package data for customers every quarter.
Skip the podcast sponsorships at this budget. Skip the research report. Pitch yourself as a guest on smaller podcasts instead, free, and the clip lives forever. Make sure your directory listings and category pages are tight, because LLM citations are the cheapest distribution you’ll ever get and most teams ignore them.
Quick tip: If you have GBP 0 for paid amplification, spend a fortnight writing one piece of original research using data you already have: customer benchmarks, internal usage patterns, an industry survey of 100 people. Original numbers travel; opinions don’t.
Regulated industries and compliance walls
I’ve worked with two financial services clients and a healthcare platform where the mention-first playbook needed real surgery. You can’t have your community manager casually answering questions in a Slack group when every public statement needs compliance review.
What works instead: thought leadership from individual experts within the company, with their content pre-cleared in batches. Conference circuits over community participation. Co-authored research with academic institutions or industry bodies, slower, more credible, harder for compliance to object to. Customer references that go through proper channels but get used in many places once approved.
The principle still holds. Buyers decide via mentions and trust signals, but the channels skew toward gated, formal, and slow. That’s fine. Regulated buyers also move slow. The pace matches.
When funnels still beat mentions
I’d be lying if I said the funnel is dead. There are categories where it remains the best model.
High-volume, low-consideration purchases. SMB SaaS at $29/month where the buyer is also the user, decides in an afternoon, and never asks a peer. E-commerce, mostly. Local services where Google search intent is the entire journey. Anywhere the consideration window is shorter than 48 hours, paid acquisition into a tight funnel still wins.
The shift to mention-first matters most where deal sizes justify peer consultation, buying committees include multiple people, the category is mature enough to have communities, or the consideration cycle is long enough for trust to compound. That’s most of B2B above GBP 10k ACV. It’s not all of marketing.
What if… your category has no communities yet, no Slack groups, no active subreddits, no podcasts? Then your job changes. You don’t seed mentions in existing communities; you build the community itself. This is harder, slower, and the moat is enormous. The B2B brands that did this in 2015-2020 (Drift, Gong, Pavilion itself) own their categories now in ways no funnel could have produced.
Principles worth stealing
Strip the case study away and a few patterns hold up across every engagement I’ve seen go this direction.
Demand creation vs. demand capture
Most marketing teams are 80% demand capture and call it strategy. Paid search, retargeting, SEO for bottom-funnel keywords, all capture. All necessary. None of it creates new demand; it harvests demand someone else created.
Mentions are demand creation. So is original research, podcast appearances, customer advocacy, community participation. The healthy ratio for most B2B companies above GBP 5M ARR is roughly 60/40 creation to capture. Most teams are inverted, and the symptom is exactly what Latchwork showed: more leads, same revenue, slowly worsening unit economics. You can’t capture your way out of a creation deficit.
Did you know? The trust and thought leadership stage of the funnel is traditionally established with “events, advertising, trade shows, content, webinars, direct mail, viral campaigns, social media, search, media mentions, and more”, but the funnel model treats these as feeders into capture, not as the work itself. They are the work.
Trust compounds, clicks decay
A paid click is worth what it’s worth on the day. A mention in a high-trust community can drive demos for years. I’ve seen podcast episodes from 2021 still appearing in “how did you hear about us” forms in 2024.
This compounding is poorly captured by quarterly dashboards, which is why most marketing teams under-invest in it. You’d never run a finance department where the CFO refused to acknowledge anything beyond the current quarter’s cash. But marketing teams routinely run on metrics that ignore everything older than 30 days.
If you only steal one mental model from this article, steal this: ask of every marketing investment, “will this still be working in 18 months?” If yes, it’s probably under-funded. If no, it’s probably over-funded.
The metric your team should track Monday
One number. Not a dashboard, not a quarterly review, one number you start counting next week.
The percentage of new opportunities where the buyer mentions a person, a community, or a piece of content unprompted as part of why they took the call. Not as the only source, not as the attribution credit, just as something they say happened.
The way to capture it is brutally simple: an open text field on the demo form, plus a single SDR question on every discovery call (“before you booked this, where did you first encounter us?”). Tag the responses weekly. Watch the trend.
If that number is below 30%, you’re running on demand capture and your funnel is more fragile than your dashboard suggests. If it’s above 50%, you’re in mention territory and your job is to feed the channels that put you there. Above 70%, you’ve reached the position every category leader eventually reaches: marketing’s job is no longer to generate demand, but to deserve the demand other people generate on your behalf.
That’s the shift worth making. Not because the funnel is wrong, it isn’t, exactly, but because the funnel was always a model of the journey you could measure, never the journey buyers actually took. The teams figuring this out in 2025 will own their categories by 2028. The ones still optimising MQL volume will be wondering, six quarters from now, why their pipeline got fatter and their revenue didn’t.
Start counting mentions Monday. The dashboard you build from that number will be the one that matters next.
