Verified Enterprise Testimonial
This funnel is a booking machine, generating over 100+ qualified meetings for our sales team.
Shelly Brown
VP of Prudent Technologies
A 26+ year cybersecurity and IT consulting firm with deep credentials, recognizable enterprise clients, and a sales pipeline that depended on cold calls. We built the AI outbound layer plus an inbound engine on top. The pipeline doubled. CPL landed at $93 on a $100M target market.
Prudent is a 26+ year IT consulting firm. Cybersecurity, Salesforce, data platforms, Splunk implementations. The kind of firm that wins enterprise mandates because they have done the work before, not because they have the loudest marketing.
When we walked in, the picture was familiar to anyone who has run a long-cycle B2B services business: deep credentials, real Fortune-list logos in the case study deck, and a pipeline that depended almost entirely on cold calls and referrals. Strong relationships, weak system.
The bottleneck was not capability. It was reach.
Enterprise B2B services have a specific math problem. Average deal size is $250-300K. Lifetime value is $750K. Sales cycle is 3 to 9 months. That math gives you a generous allowable cost per qualified meeting, but only if you can find the right buyers in the first place. Inside a $100M target market, that means reaching the 3,000 or so accounts where the deal makes sense, not the 30 you happen to know.
The job was to build a system that would surface those accounts predictably, qualify them before a salesperson got involved, and feed the existing closing team enough warm conversations to keep them busy.
Before we walked in, the picture looked like this:
Sales cycles started cold. The pipeline was almost entirely outbound from a small team of senior salespeople. Every enquiry was the result of someone picking up the phone, sending an introduction email, or working a referral. There was no system feeding warmer conversations into the funnel.
The website was a brochure. Strong on credentials. Weak on conversion. No clear next step for a buyer who landed on the site after seeing the firm in a procurement shortlist or a peer recommendation. The most-visited pages did the least work.
The buyer was not where the firm was looking. Most enterprise buyers in cybersecurity and IT services research quietly for months before reaching out. The firm had no presence in those quiet research moments. By the time a prospect was ready to talk, the conversation was happening with three vendors, not one.
AI outbound was not in the stack. The closest thing to scaled prospecting was a rented data list and a junior BDR sending generic templates. Reply rates were in the low single digits. The senior team had to redo most of the work to make it presentable to enterprise contacts.
This is the picture every long-cycle B2B services firm eventually sees: deep expertise, real wins, real referrals, and a ceiling that comes from depending on humans to do work that ought to be systemized.
Every GetNos engagement runs the 7-Phase Revenue Funnel System. We do not skip phases. We do not build creative before we know who it is talking to. We do not ship offers before they pass The Crucible.
The target market was finite and addressable: roughly 3,000 enterprise accounts in India and adjacent markets where the firm's services made commercial sense. We worked backwards from that universe to land on the monthly account-touch volume, the qualified meeting target per week, and the cost structure each layer needed to clear.
Enterprise unit economics gave us room. With $250-300K average deal size and $750K LTV, the allowable cost per qualified meeting was high. The math told us: spend more to qualify well, less to fill the top of the funnel. That inverted the prior approach.
The Spy went into the field on day one. We did not target "IT decision makers". We mapped the actual buying committee on enterprise cybersecurity and Salesforce engagements: the technical buyer (CISO, Head of IT, Salesforce admin), the economic buyer (CFO, VP Finance), the user buyer (the team who would live with the deployment), and the coach (the internal champion who pushes the deal forward).
The PONI built off that intel. Every persona got their own message. The CISO cares about risk reduction and compliance posture. The CFO cares about TCO and capex versus opex. The Salesforce admin cares about implementation speed and not being stuck with consultants who disappear post-go-live. Same firm, same offer, four different conversations.
Buying-committee mapping 21-layer pyramid · 4 personas CISO · CFO · admin · coachThe Trojan replaced one generic "IT services" pitch with three vertical-specific offers. Each one had its own diagnostic, its own promise, its own price band, and its own qualification criteria. The Crucible (New, Unique, Exciting, Easy, Predictable, Huge) was applied to each before any of them shipped.
The diagnostic call did the qualification work. Buyers showed up with a real problem, walked away with a written assessment, and self-selected into the right vertical conversation. Sales calls stopped being discovery and started being scoping.
The Bait was a vertical-specific diagnostic. For cybersecurity, a 12-question security posture self-audit that returned a written assessment in 48 hours. For Salesforce, an admin-readiness scorecard. For data, a Splunk health-check questionnaire. Each one was useful enough to be worth filling out for its own sake. The buyer got value before any sales conversation.
The Genie ran the nurture. Email plus LinkedIn DM sequences, segmented by vertical, by buying-committee role, and by where the buyer entered. CISO got security-leader content. CFO got TCO modeling. Each touch reinforced the diagnostic finding from The Bait.
Vertical diagnostics · 3 verticals 48-hour written assessment Email + LinkedIn Genie Segmented by role + verticalThe traffic stack split two ways. The Strike on the inbound side ran LinkedIn and Google Ads aimed at intent keywords ("Splunk implementation cost", "Salesforce admin handover", "cybersecurity audit India"). Identity-led creative pointed at the buying-committee role on the other end of the click.
On the outbound side, AI-led prospecting changed the math. We built sequences that researched each account before sending, opened with a specific, public, recent signal from that company, and asked one calibrated question. Reply rates climbed from low single digits to the high teens. Cost per booked meeting landed at $4.
LinkedIn intent ads AI outbound · per-account research $4 per booked meeting 30% of leads from AIThe diagnostic call playbook was rebuilt around the buyer's own data. Not a generic intro. A walkthrough of the assessment they had already completed.
Pre-call. Sales received a one-page brief with the buyer's diagnostic answers, vertical signal, and the highest-impact recommendation already drafted by a senior consultant.
On the call. The salesperson opened by walking through the buyer's own findings. The conversation focused on the buyer's specific risk or opportunity, not on the firm's services. By minute fifteen, the question shifted from "what do you do" to "when can we start".
Post-call. A scoped statement of work landed in the buyer's inbox within 48 hours, signed off by the senior consultant who had reviewed the diagnostic. Time from first call to signed engagement compressed sharply.
By month four, AI outbound was producing 30% of new leads at $4 per booked meeting. By month six, the inbound diagnostic engine had matched outbound on volume and beat it on close rate. By month eight, total enquiries had cleared 674, against the 243 from the prior comparable window. Same ad spend, two engines.
The rate-limiting step stopped being prospecting and started being delivery. With $750K LTV per client and $250-300K deals closing inside the engagement window, the firm could afford to be selective on which engagements to take. That is the right problem to have.
243 → 674 in 8 months $93 CPL on $100M TAM 30% from AI outboundSame firm. Same expertise. Same ad spend. Different system. Two engines feeding one closing team. AI outbound + inbound diagnostic doubled the pipeline on a $100M target market.
If your audience is real and your offer is solid but the funnel is the bottleneck, book a 30-minute Revenue Math Audit. We work backwards from your revenue target, not forwards from your product. We will tell you what we'd build, what we wouldn't, and whether it makes sense for either side.
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