AI & Intelligence · Case Study 03

Untapped
Revenue
Uncovered.

Client

Lotus Lens Studio

Event Photography · $6.2M

Duration

14 Weeks

Technical RevOps & CRM

Database

1800+ Contacts

8 Years of History

$18.5K
Upsell Revenue in 90 Days
61%
CRM Data Accuracy Lift
3.8×
Database Reactivation ROI
22%
Premium Package Attach Rate

The Problem

A Profitable
Database Ignored

Lotus Lens had a CRM with ~1800 contacts spanning 8 years. Contacts weren't segmented, deal stages stale, zero automation. Premium upsells sold entirely by chance — dependent on whether a rep mentioned them on a call. Highest-margin offerings had no systematic path to market.

CRM at 34% duplicate rate — suppressing deliverability

Premium package attach rate <9% — no systematic upsell path

850 dormant contacts with zero re-engagement logic

Database Segments at Audit

SegmentContactsLast ActiveReactivated
Past Corporate Clients7406–18 mo31%
Single-Event Bookers97512–36 mo18%
Warm Leads — Never Closed2253–9 mo44%

Our Approach

AI-Powered
Reactivation Engine

01

CRM Rebuild & Data Hygiene

New 11-signal behavioral scoring model. Clay-powered deduplication resolved 34% duplicate rate and appended data to 1800+ contacts.

02

Private AI Recommendation Model

Fine-tuned on 8 years of booking data to predict premium package likelihood. Powers automated upsell sequences at key milestones.

03

3-Track Reactivation System

Distinct campaigns for corporate clients, single-event bookers, and cold warm leads — each with custom messaging and offer logic.

04

Upsell Trigger Architecture

Sequences fire at 21-day, 7-day, and 48-hour pre-event milestones with AI-predicted package recommendations per profile.

Engagement Timeline

14 Weeks, 4 Phases

CRM Audit

Wk 1–2

850 dormant contacts, zero re-engagement logic. 34% duplicate rate suppressing deliverability and score accuracy.

Data Architecture

Wk 3–4

Clay deduplication pass. 11-signal scoring model built. Historical deal data migrated and re-categorized.

AI & Automation

Wk 5–9

AI model fine-tuned on booking history. Three reactivation tracks launched. Upsell triggers at 21-day, 7-day, and 48-hour milestones.

Optimization

Wk 10–14

Weekly campaign reviews. AI model retrained on early closed-won data for improved recommendation accuracy.

Tech Stack

Tools & Why

HubSpot CRM

CRM

Rebuilt with new pipeline stages, lifecycle scoring, and behavioral properties driving AI inputs.

OpenAI API

AI

Private package recommendation model fine-tuned on 8 years of booking data.

Clay

Data

Enrichment and dedup engine. Resolved 34% duplicate rate, appended data to 1800+ contacts.

ActiveCampaign

Email

3-track reactivation system with behavioral triggers on HubSpot data.

Retool

Analytics

Internal dashboard: reactivation performance, AI accuracy, and CRM health in real time.

Segment

Tracking

Captures revisits, gallery downloads, and events to feed the AI scoring model.

Outcomes

What
Changed

$18,500 in upsell revenue within 90 days from AI-powered package recommendation sequences.

CRM data accuracy improved 61% — a reliable revenue asset instead of a liability.

Database reactivation generated 3.8× ROI across all three campaign tracks.

Premium attach rate: 9% → 22% within 60 days of behavior-triggered upsell launch.

44% reactivation rate on cold warm leads — the highest-performing segment.

"

We were sitting on years of client data and doing absolutely nothing with it. Within three months, the AI-driven system had surfaced $18,500 in upsells we would have never captured manually. It changed how we think about our database entirely.

L

Studio Director

Lotus Lens Studio · Event Photography