An enterprise AI company had strong inbound interest and a warm addressable market — but deals kept stalling after one demo. A segmented ABM drip architecture, built on deep research into three very different buyers, turned pipeline that wasn't moving into pipeline that was.
A genuinely differentiated product, and a warm addressable market — broadcasters, sports federations, media rights holders already feeling the pressure to do more with their content libraries.
But despite strong inbound interest, deals were stalling. Prospects would engage once — download something, attend a demo — then drift. The sales cycle was long, the buying committee was wide, and there was no structured content system keeping the brand present and credible throughout.
The team had leads. They didn't have momentum.
The core issue wasn't awareness, or even intent. Different leads were arriving at different temperatures, with different context — and all being handled the same way. Someone who'd just raised their hand through a paid LinkedIn ad needed a different conversation than someone who'd already sat through a demo but hadn't booked a follow-up.
The second issue was content specificity. Enterprise buyers in sports media don't respond to generic AI narratives — they respond to proof the product understands their world. That meant going deeper than "sports media" as a category, into research on what each buyer inside it actually loses sleep over.
Generic "AI for media" doesn't land. A football broadcaster wants to know what it means for football content revenue — named, not implied.
Federations are archive-rich and monetisation-poor. The proof point that lands: a dormant archive turned into a searchable, licensable library.
Rights holders managing user-generated and archival footage care about moderation accuracy and speed above almost anything else.
Three buyers inside one category, each needing their own proof. So the plan became: split active, MQL-qualified leads from passive, content-driven ones — and give each a segmented journey that branches on real engagement signals.
A full multichannel ABM drip architecture was built across two lead tracks — every email, ad, and newsletter touch written with one specific job: introduce a use case, overcome an objection, or move the reader one step closer to a conversation.
A high-intent sequence focused on getting a demo scheduled, with branches handling non-responses and re-engagement through capability-led emails.
A longer awareness-to-consideration arc, content mapped to their vertical, CTAs calibrated to their stage — until they were ready for the first track.
Every ad framed around the reader's own vertical — never a generic "AI for media" line.
Vertical-specific case studies, positioned as the natural next step after the ad — never a generic whitepaper.
How one federation turned a dormant archive into a searchable, licensable content library.
Accuracy and turnaround benchmarks for rights holders fielding thousands of clips a week.
Leads who go quiet don't get dropped — they get folded into a monthly sports-media-AI newsletter until a new signal brings them back into an active track.
Hi Kabir — you downloaded our football case study a while back. No pitch here, just what's actually shipping across sports media right now, and one thing worth 5 minutes if you're still curious.
Read this month's issue →“Sales conversations improved in quality too — prospects arrived better informed, and more specific in their questions.” Quarter-one review
Within the first quarter, the same warm market started converting — because it was finally being spoken to as three different audiences, not one.
One-time downloads that went nowhere. Active and passive leads treated identically. No visibility into drop-off.
Two branching tracks, eight journeys, content mapped to vertical and funnel stage. Every drop-off point visible and actionable.
Thirty minutes. We'll map your funnel's drop-off points and what a segmented journey could look like — yours to keep either way.