Corpus Loop
AI Store Builder
Case study · Sales & RevOps Automation

Up to 1,500 leads a month went untouched. Then the system stopped forgetting.

We rebuilt the RevOps backbone behind AI Store Builder — 20,000+ monthly leads routed into a monitored sales cadence, with setter-to-closer handoffs, AI call coaching, onboarding automation, and conversion feedback to advertising platforms.

Leads left without a contact attempt — monthly
Before1,000-1,500
missed entirely
After0
left without an automated next step
An unanswered lead is re-surfaced after 5 minutes, then kept inside later follow-up windows instead of disappearing from the team’s day.
Client
AI Store Builder
Sector
AI eCommerce SaaS
Market
Global
Reach
250,000+ users
Scale
20,000+ leads / month
Role
RevOps & Sales Automation Architect
Engagement
Aug 2025 – ongoing
Team
Sole technical owner + CEO + sales manager
01 · The client

A 250,000-user platform whose growth lives between an opt-in and a phone call.

AI Store Builder helps aspiring entrepreneurs launch and run AI-powered eCommerce stores. Its acquisition engine spans paid campaigns, organic audiences, affiliates, and partner funnels — creating more than 20,000 leads each month for a distributed setter and closer operation.

That scale makes the space between lead capture and human contact the real product. A lead has to be identified, routed, claimed, called, followed up, booked, handed to the right closer, and eventually connected back to the campaign that created it. One broken handoff turns paid demand into a silent CRM record.

Corpus Loop has served as the sole technical owner of the sales automation layer since August 2025, translating operating decisions made with the CEO and sales manager into production workflows.

02 · The problem

Lead intake existed. The revenue system did not.

When we inherited the stack, one unstable intake workflow was doing most of the work. Everything after capture depended on people remembering what came next.

First contact could take several minutes or stretch into hours. If the first rep missed the lead, there was no dependable cadence to bring it back. Follow-ups lived in memory, ownership changed informally, and an estimated 1,000-1,500 leads every month were never contacted once.

Management had the same blind spot on calls. Recordings existed, but review was inconsistent, so leaders could not see qualification quality, objection patterns, handoff risk, or where setters and closers needed coaching. Purchase outcomes also stopped inside the CRM instead of consistently informing ad decisions.

1,000-1,500
leads per month estimated to receive no contact attempt
minutes to hours
before a new lead might receive its first attempt
0
automated safety nets after a rep missed the first opportunity
03 · Our approach

Make every sales state explicit. Then automate the next one.

We did not patch the intake workflow and call it done. We rebuilt the full operating layer around three rules agreed with leadership.

Rule 01

Every lead has a next action

Claimed, called, re-surfaced, booked, nurtured, activated, or excluded — never simply forgotten.

Rule 02

Ownership moves with the lifecycle

Setter, closer, and onboarding handoffs are written into Close, Calendly, Slack, and the dialer instead of living in chat.

Rule 03

Every useful call becomes data

Connected setter and closer calls produce structured outcomes and coaching signals that management can review without replaying every recording.

04 · How it works

One revenue loop. From opt-in to feedback.

The system joins acquisition, sales execution, call intelligence, onboarding, and ad feedback without asking reps to operate another dashboard.

AI Store Builder revenue operations automationPaid, organic, partner, and affiliate leads enter a central intake and identity layer, move through Close CRM into claiming, calling, booking, and onboarding. Trellus and Fathom calls are analyzed into coaching data, while activation events feed Meta and historical Google Ads reporting.ACQUISITIONCORE REVOPSSALES EXECUTIONINTELLIGENCE + FEEDBACKLead Sourcespaid - organic - YouTubepartners - affiliatesopt-inCentral Intakenormalize - enrich - detect regiondedupe + attribution identityClose CRMsingle lead recordstatus + owner + cadenceClaim + CadenceSlack - Close - Trellus5-minute re-opt safety netSetter to CloserCalendly handoffsales + onboarding sequencesTrellus + Fathomsetter + closer transcriptsconnected calls onlyAI Call Analysisoutcome + qualificationcoaching + risk signalsManagement VisibilityGoogle Sheets + Slackstructured, searchable feedbackactivation / purchaseAd FeedbackMeta Conversion APIGoogle Ads loop - historicalclosed-loop campaign learning
The rep still works in Close, Slack, the dialer, and Calendly. The automation handles state, timing, routing, and feedback behind those familiar tools.
Five-minute rescue loop

If the first lead is not contacted, it is re-surfaced after five minutes and again through later age and disposition windows.

Stateful regional cadence

Attempts, cadence days, call outcomes, and regional windows stay synchronized across Close and Trellus.

Clean identity and routing

Duplicate detection, attribution fields, country logic, and lifecycle tags prevent split records and conflicting journeys.

Setter to closer handoff

Calendly events update ownership, opportunity state, Sheets, Slack, and follow-up sequences without manual reassignment.

AI coaching layer

Setter and closer calls become high-level qualification, objection, discovery, trust, closing, and appointment-quality signals.

Closed-loop attribution

Activation events are deduplicated and sent back to Meta; a Google Ads feedback loop also ran before that channel was paused.

05 · The results

The pipeline stopped depending on memory. And started behaving like infrastructure.

The largest change was operational certainty: every new lead now enters a visible sequence, every missed first attempt has a recovery path, and management has a structured view of calls that previously lived inside recordings.

1,000-1,500 untouched / month->Every lead gets a next step
No-contact leads are automatically re-surfaced rather than relying on a rep to remember them.
100,000+
workflow executions each week across the sales automation layer
20,000+
leads handled each month across inbound and re-engagement paths
99.9%+
lead capture rate across the production intake system
<0.1%
workflow failure rate at production scale

Follow-up became system behavior

Reps no longer need to hold every callback and retry window in their heads. The workflow owns the clock and brings the lead back.

Calls became management data

More than 60 connected setter and closer calls are currently analyzed each month into structured notes and coaching signals.

Ad decisions gained a feedback layer

Activated sales flow back into advertising reports, giving leadership outcome data to use alongside campaign performance.

Measurement note: operating volume, capture, and failure rates reflect production monitoring. The missed-lead baseline is the client’s operational estimate. Revenue, CPA, show-rate, and close-rate improvements are intentionally not claimed because those outcomes were not isolated from wider sales and marketing changes.

07 · What’s next

One sales playbook. Not eleven disconnected tools.

The repeatable pattern is not specific to AI Store Builder. Leadership defines how leads should move, when ownership should change, what a qualified appointment looks like, and which outcomes matter. We translate that operating model into reliable automation, AI visibility, and feedback loops your team can actually run.