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Case Study · Agent 01

Growth Ops Agents in Production.

A leading Indian consumer health platform.

Same team, same paid budget. Nine points more D30 retention, ₹4.2 cr in CAC efficiency reclaimed in a single quarter, and the analyst queue is empty by 10 a.m.
At A Glance
Client
A leading Indian consumer health platform
Industry
Consumer healthtech, diagnostics, telehealth
Scale
6M registered users · 1.4M MAU · 80+ cities · ~₹220 cr ARR
Paid spend
~₹28 cr/year across Meta, Google, affiliates
Agents deployed
Growth Ops Agents
Deployment
6 weeks from kickoff to all workflows live
Headline Numbers
+6pp
D30 retention lift on reactivated cohorts (41% → 47%)
₹4.2cr
CAC efficiency reclaimed in Q1
<1hr
Median time-to-insight on funnel questions, down from 3–5 days
The Situation

The data was there. The operating tempo was not.

The growth team ran a data-rich operation: Mixpanel for product, Branch and AppsFlyer for attribution, Snowflake as the warehouse, and eight ad accounts across Meta, Google, and three affiliate networks. The team was 14-strong, including three embedded analysts.

Despite that, the gap between a growth question being asked on Monday and a defensible answer landing was three to five days. Decisions that should have been weekly slipped to monthly.

It wasn’t a tooling gap. It was a workflow gap.

What Was Breaking

Four places the team was losing days every week.

  1. 01

    Funnel diagnosis lagged the business.

    When checkout conversion dipped, the analyst cycle to find the cause took the better part of a week. By the time the answer arrived, the team was already debugging the next thing.

  2. 02

    Creative fatigue was always called too late.

    ROAS would dip for 7–10 days before anyone noticed. By then, real budget had been burned.

  3. 03

    Reactivation was a generic email blast.

    Dormant users all got the same offer. Conversion sat at 0.4%, and the team had no reliable way to score who was actually reactivatable.

  4. 04

    Analysts were the bottleneck on everything.

    Every campaign waited on a custom audience cut. Every funnel question waited on a query.

The Deployment

Six weeks. Fourteen hours of client engineering.

Six weeks from kickoff to all three workflows live, read-only. No data left the client warehouse.

Engineering effort on the client side: 14 hours, mostly access provisioning and one workshop on definitions.

Systems connected
Snowflake, Mixpanel, Branch, AppsFlyer, Meta Ads, Google Ads, internal booking DB, CRM (Customer.io).
Workflows live
3 workflows, including 1 voice-led workflow.
Engagement model
Embedded growth ops support for the first 90 days, then platform-only.
The Workflows

Three workflows. One voice-led.

01

Funnel Drop-Off Diagnosis

Root cause by morning.

Trigger
Daily at 7:30 a.m., plus on-demand via Slack
Data sources
Mixpanel events, Branch attribution, internal booking DB, payment processor
How it runs
Pulls the last 24 hours of funnel and compares to 7-day and 30-day baselines. Flags drop-offs >3σ from baseline. Traces flagged steps to source: channel, creative ID, device, city, time-of-day. Writes a 4-sentence root-cause summary.
Human in the loop
Growth lead reviews in the 9 a.m. standup. One click expands the underlying SQL trace.
Output
Slack #growth-daily by 7:45 a.m., plus a saved analysis link.
Before

Three-to-five day analyst cycle, often arriving after the next dip had started.

After

Same-morning answer with a named root cause. Standups now lead with action, not investigation.

02

ROAS & Creative-Fatigue Detection

Always-on, with significance testing built in.

Trigger
Continuous on Meta and Google, with 4-hour Slack-cadence alerts
Data sources
Meta Ads, Google Ads, post-impression conversion data, Mixpanel
How it runs
Calculates rolling ROAS per ad set and creative. Detects when CTR or CVR has dropped >15% over a 5-day rolling window, with a 95% significance test before firing. Separates creative fatigue from audience fatigue. Suggests next-best lookalike cohorts.
Human in the loop
Performance marketer reviews the alert, confirms a pause or creative refresh.
Output
Slack alert with one-click pause. Daily creative-fatigue digest to the head of growth.
Before

Weekly creative review, often a week behind the actual fatigue signal.

After

Fatigue called within 48 hours of statistically significant signal, with the next creative already briefed.

03

Reactivation Voice Agent

Voice

Personalised voice outreach to dormant users.

Trigger
Weekly batch every Monday morning
Data sources
User behavioural data, last test booked, propensity model (rebuilt monthly), CRM communication history
How it runs
Identifies dormant users (no booking 90–180 days). Scores reactivation probability. Top decile (~2,400 users/week) is routed to the voice agent; rest go to email and WhatsApp. Voice agent dials with personalised openings, surfaces incentives, books appointments if intent is detected. Conversations are transcribed and tagged.
Human in the loop
Growth ops reviews a 5% sample of voice calls weekly for quality and compliance.
Output
Direct booking, follow-up call tagged in CRM, model retrain signal.
Before

Generic reactivation email at 0.4% conversion.

After

Voice-led top decile at 4.2% conversion. Roughly 180 incremental bookings per week from a population that previously did nothing.

The Numbers

Audited against pre-pilot baseline.

₹4.2cr
CAC Efficiency Reclaimed in Q1

Net savings from ROAS reallocation and creative-fatigue avoidance, audited against pre-pilot baseline.

+6pp
D30 Retention on Reactivated Cohorts

41% to 47%, sustained across three monthly cohorts.

<1hr
Median Time-To-Insight on Funnel Questions

Down from 3–5 days. Measured across 90+ tracked questions in Q1.

4.2%
Conversion on Voice-Led Reactivation

Up from 0.4% on the prior email-only baseline. Roughly 180 incremental bookings per week.

“Our growth team stopped being the bottleneck. The decisions we used to make on Friday based on Monday data, we now make on Tuesday morning. The compounding from that is real.”

Deployment Timeline

From kickoff to all three workflows live.

  1. 01Week 1

    Scoping workshop with growth leadership. Three workflows and the voice agent locked.

  2. 02Weeks 2–3

    Read-only connections to Snowflake, Mixpanel, Branch, ad accounts. Definition layer built with the analyst lead.

  3. 03Week 4

    Funnel Diagnosis and ROAS workflows live.

  4. 04Week 6

    Voice agent live for reactivation. All three workflows in production.

Frequently Asked

Common questions about this deployment.

Six weeks for this engagement. Most growth-team deployments land in the four-to-eight week range, depending on the number of workflows and the state of the underlying data definitions.
Fourteen hours total for the Growth Ops deployment, mostly access provisioning and one workshop. The Actioneer team handles the build.
No. Actioneer connects read-only to the systems already in place. Nothing is ingested, copied, or relocated.
The voice agent dials the top decile of reactivatable users with personalised openings, surfaces a relevant incentive, and books a return appointment if intent is detected. Conversations are transcribed and tagged; a 5% sample is reviewed weekly for quality and compliance.
Against a pre-deployment baseline agreed with the client. All headline numbers ship with traceable underlying queries.
Yes. Workflows are continuously refined post-launch. Triggers, thresholds, and approval gates can all be edited without re-deployment.

Illustrative case based on representative Actioneer deployments. Client identity, figures, and quote are synthetic. The workflows reflect real Actioneer deployment patterns.

Begin The Engagement

Identify The Workflows Where AI Agents
Would Deliver Immediate Impact.

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