Prolego is an AI strategy firm advising executives on applied AI. The database was mature. The infrastructure wasn't. This is how iExcel built the acquisition foundation underneath it.
Applied AI advisory doesn't sell on a landing-page CTA. The buyer is an executive weighing whether to deploy AI inside a live business — one who wants to know the firm's thinking, watch the point of view develop across a few months of content, and make a considered decision to open a conversation. The sales cycle is patient. The buyer is senior. The evaluation is slow, honest, and thorough.
Prolego builds into that world. Applied AI strategy for executives — engagements that begin as thinking partnerships and land as deployment roadmaps. Content is the primary evidence: how the firm reasons, what it publishes, how it frames what's changing.
When iExcel picked up the engagement, the audience was there. The content was there. What was missing was the infrastructure to turn attention into a segmentable, measurable pipeline. Contacts sat in the CRM without job titles or company data. The lifecycle stages didn't reflect how a senior buyer actually moves. The dashboards didn't cross-reference channel spend with contact quality. What the business needed wasn't more content. It was an operating layer underneath the content it already had.
The first meaningful lever wasn't a new campaign — it was subtraction. A legacy database carries silent tax: non-email records, hard bounces, unsubscribes, and non-marketing contacts that quietly distort every dashboard leadership looks at. Cleaner reporting starts with cleaner inputs.
iExcel ran a systematic pass through the HubSpot database. Non-email records were separated. Bounces were flagged and removed from marketing-eligible lists. Historical unsubscribes were honored across every property. Anyone who wasn't a marketing contact — internal, vendor, or otherwise out-of-scope — was excluded from send lists so open rates, click rates, and channel dashboards reflected the real audience instead of the noise.
The output was a defensible marketing-eligible base: roughly a third of the legacy list pruned, honestly counted and stably reported. Not a bigger number to brag about — the right one to plan against.
An advisory pipeline lives or dies on segmentation. If you can't tell which contacts are senior enough to matter, which are still anonymous, and which are ready for a nurture sequence, the CRM is just an inbox. iExcel built a three-stage enrichment model across the entire Prolego database so every contact carried a clear position on the ladder — and every contact could be moved up it.
On top of the automated rungs, iExcel ran a manual enrichment sample against 300 contacts — LinkedIn URL, job title, hierarchy, company, personal-vs-business email split, Twitter handle, website URL, birthday. The point wasn't just the extra fields. It was the resolution: every enriched record dropped straight into the right segment, the right nurture stream, and the right report — no cleanup on the far side.
The enrichment ladder is only useful if the CRM knows what to do with a contact once it reaches the top. We wired the two systems together with a lifecycle model that treats enrichment stage as the trigger — not a nice-to-have field, but the ignition for movement through the pipeline.
The workflow: any contact whose enrichment stage flips to Potential Lead — meaning full profile, verified business email, seniority resolved — is automatically promoted to a HubSpot Lifecycle Stage = Lead. That single automated move connects the identity layer to the sales-facing pipeline. Enrichment doesn't sit in a spreadsheet anymore. It shows up as pipeline the sales side can actually pick up.
On top of that: lead scoring calibrated against title, industry, and engagement. Forms rebuilt and QA'd so every submission carried a source, medium, and campaign tag intact. List architecture rewritten so segmentation was rule-driven, not manual. And a HubSpot–Zapier integration to catch the last-mile inputs the CRM didn't ingest natively.
Form submission, imported list, or content download. Source, medium, and campaign tags land on the record. Enrichment stage starts at Random.
Automated + manual passes lift the contact through the three-rung ladder. Job title, seniority, company, and business email get resolved on the record.
The moment the enrichment stage flips to Potential Lead, HubSpot auto-promotes the record to Lifecycle Stage = Lead. Sales sees pipeline. Marketing sees attribution.
With enrichment stage wired to lifecycle stage, the automation layer had a real segmentation surface to fire against. iExcel built the Prolego marketing engine across both HubSpot and ActiveCampaign — each play scoped, tagged, and tied back to a specific stage transition so no send fired in a vacuum.
A pipeline no one can measure is a pipeline no one can trust. Once the CRM was structured and the automation was running, iExcel built the reporting layer that let leadership actually read what was happening — one place to look, one set of numbers that didn't disagree with each other.
GTM handled the event layer. Google Analytics carried the traffic story. Google Optimize ran the on-site tests. HubSpot's native reporting held the CRM view. Databox consolidated the cross-channel picture — LinkedIn Ads, HubSpot pipeline, GA traffic, blog performance — into a single live dashboard the marketing and executive sides could open together.
Three purpose-built HubSpot dashboards anchored the day-to-day: an Email Overview, a Lead Generation view, and a Marketing Channel Performance board. UTM tracking, form-submission tracking, and goal-conversion tracking were rebuilt underneath them so every source line was defensible.
Marketing hub + reporting. Lifecycle stages, enrichment properties, lead scoring, and the automated Potential-Lead → Lead promotion workflow.
Drip infrastructure — onboarding, AI-content nurture, prospect outreach, content confirmations, RSS-triggered blog sends against tagged segments.
Every conversion event fires through GTM. Form submissions, downloads, and outbound clicks land in analytics with a defensible source tag.
Traffic, source attribution, and conversion tracking wired to the contact record. UTM discipline enforced at the campaign level so no report has to guess.
On-site experiments against the highest-intent pages. Winners moved into the production template. Losers documented and archived.
Live cross-channel dashboard — LinkedIn Ads, HubSpot pipeline, GA traffic, blog performance in one view. The dashboard leadership actually opens.
The right channel for a senior-buyer audience. Wired to HubSpot and Databox so contact quality is measurable against spend, not asserted against it.
Last-mile inputs the CRM doesn't ingest natively. Form fills, event confirmations, and outside-tool events land on the contact record without operator lift.
Weekly visibility on the applied-AI cluster. Site audits, content-gap analysis, and competitor keyword footprint benchmarked and re-run each cycle.
An advisory site that reads well but ranks poorly is a pipeline leak. The Prolego content library was substantive — the kind of thinking a senior buyer actually wants to read. What it needed was for the machine layer underneath it to stop fighting the reading experience.
SEMrush audits mapped the technical debt. 301 redirects were drafted against high-value URLs whose slugs had drifted. Broken links across the blog were caught and fixed. Blog titles and meta descriptions were rewritten against the queries executives were actually running. H1 and H2 hierarchy was normalized so search engines and screen readers agreed on what each page was about. UI-element cleanup on the article template made the read cleaner without ripping the design.
The sitemap and site-structure recommendations went to the developer side with checklists — no ambiguous asks, no "make it better" tickets. Every change had a reason, a benchmark, and a way to verify it landed.
With the database enriched and tracking honest, paid social had a foundation worth spending against. March retargeting ran at a 0.71% click-through rate. April's restructured campaigns hit 1.41% in the first half of the month — a +98% jump against the program's own baseline, achieved on creative and audience changes rather than added budget.
Published LinkedIn sponsored-content averages sit in the 0.44–0.65% band. The rebuilt campaigns ran at more than double the top of it.
If you're running an advisory firm — AI, strategy, technical, executive — and you're staring at a database that behaves more like an address book than a pipeline, ad accounts spending against a fuzzy audience, and content that gets read but doesn't get attributed, the Prolego engagement is the shape of what to do about it.
Cleanup first. Enrichment second. Lifecycle third. Automation only when the segmentation surface underneath it can support the send. Reporting the whole way through — because leadership needs a place to look, not a hunch to trust.
Most agencies sell the campaign. iExcel builds the operating layer underneath it — the enrichment ladder, the lifecycle workflow, the dashboards that don't disagree with each other — and stays through the phases that make the campaigns work when they finally run.
A CRM that segments. An enrichment ladder every contact sits on. Lifecycle promotion tied to real signal. Dashboards that agree with each other. Book a 15-minute sanity check on your acquisition setup — we'll tell you what's under-built and what to do about it.
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