Case Study · 6 months
342% MQL Increase Through RevOps Architecture and CRM Integration
CRM integration and RevOps architecture that increased marketing qualified leads by 342%.
342%
MQL Increase
12,000
Records Migrated
6 days
Migration Time
Client
B2B technology, India
Challenge
Disconnected systems, 5-7% leakage
Solution
HubSpot + RevOps
Timeline
6 months
Key Result
342% MQL increase
Tools
HubSpot, Salesforce, Zapier
Technix Infotech increased marketing qualified leads by 342% for a B2B technology company by implementing HubSpot CRM, migrating 12,000 records from Salesforce in 6 days, building a 14 criteria lead scoring model, and connecting marketing automation to the sales pipeline. Revenue leakage of 5 to 7% was eliminated through automated handoffs.
The Challenge
Marketing and sales operated in completely separate systems. Marketing ran campaigns in Mailchimp. Sales tracked deals in Salesforce. Neither team could see what the other was doing. Leads generated by marketing were manually forwarded via email, and 30% were never followed up.
The company was losing 5 to 7% of revenue to operational inefficiency: missed follow ups, duplicate records, broken integrations, and reports that took 2 days per week to compile. The CEO wanted a number for 'cost of marketing' and nobody could provide it.
Average time from marketing lead generation to first sales follow up. By the time sales called, the lead had already talked to 2 competitors.
Why This Was Not a Standard Project
12,000 records across Salesforce, Google Sheets, and a custom Access database with no standardized data model. Contact, company, and deal relationships were inconsistent. Duplicate records accounted for 15% of the database.
The sales team had zero trust in any CRM data because it had been wrong for years. Any new system had to be provably accurate from day one or the team would reject it, just like they rejected the last 2 CRM attempts.
The deduplication process used a 4 field matching algorithm: email, company domain, phone number, and fuzzy name matching. 1,800 duplicate records were identified and merged with rules preserving the most recent activity data. The migration ran in 6 stages over 6 days with automated validation scripts at each stage.
What We Did
Audit and Architecture
Month 1Audited existing systems, mapped data flows, identified revenue leakage points. Designed the RevOps architecture blueprint with HubSpot as the central hub.
Data Migration
Month 2 (6 days)Migrated 12,000 records from 3 sources. Custom deduplication with 4 field matching. 6 stage migration: contacts, companies, deals, activities, custom objects, validation.
Automation Build
Months 3-4Built 25+ workflows: lead scoring (14 criteria), lead assignment, follow up sequences, deal stage automation, marketing attribution tracking, and automated reporting.
Optimization
Months 5-6Refined lead scoring based on closed/won data. Optimized workflows based on adoption metrics. Built executive dashboards showing pipeline, attribution, and revenue.
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The Technical Deep Dive
The lead scoring model was built from historical closed/won data: 14 scoring criteria across firmographic fit (5 criteria: company size, industry, location, technology stack, funding stage) and behavioral engagement (9 criteria: website visits, email opens, content downloads, webinar attendance, pricing page visits, demo requests, and more).
Workflow automation connected marketing attribution to deal creation, eliminating the manual handoff that had been causing 48 hour follow up delays. When a marketing contact hit a score threshold, HubSpot automatically created a deal, assigned the appropriate sales rep based on territory rules, sent an internal notification via Slack, and started a 7 touchpoint nurture sequence.
Within 30 days of go live, the sales team was using HubSpot voluntarily (not mandated) because the lead scores were accurate. The first month showed 89% correlation between high scoring leads and actual deals closed. Trust was earned through data accuracy, not executive mandate.
The Results
| Metric | Before | After |
|---|---|---|
| MQLs per month | ~40 | ~177 (342% increase) |
| Follow up time | 48 hours | Under 2 hours |
| Revenue leakage | 5-7% | Near zero |
| Reporting time | 2 days/week | Real time dashboards |
342%
MQL Increase
12,000
Records Migrated
6 days
Migration Time
<2 hrs
Follow Up Time
The 342% MQL increase was not from generating more leads. It was from properly identifying, scoring, and routing the leads that already existed. The marketing team was generating leads all along, but without scoring and automated handoff, 60% of qualified leads were never reaching the sales team.
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Book a Free Consultation“Technix connected our entire revenue stack in 6 months. Our MQLs increased 342%, our sales team follows up in under 2 hours instead of 2 days, and for the first time we can see which campaigns actually drive revenue. The lead scoring model was accurate from week one.”
Head of Revenue
B2B Technology Company, India
Tools and Technologies Used
HubSpot CRM
Salesforce (source)
Zapier
Looker Studio
n8n
SlackWhat We Learned
01
Clean data before migrating
15% of the database was duplicates. Moving dirty data to a new CRM just creates a more expensive version of the same problem. The 6 day migration included 2 days of deduplication and cleaning.
02
Lead scoring needs real data
The scoring model was built from actual closed/won deals, not assumptions. This made sales trust the scores within the first month. Trust earned through accuracy, not executive mandate.
03
Speed of follow up is everything
Reducing follow up time from 48 hours to under 2 hours was the single biggest driver of the 342% MQL increase. The leads were always there. They were just going cold before anyone called.
Frequently Asked Questions
Questions About This Type of Project
The full migration of 12,000 records from 3 sources (Salesforce, Google Sheets, Access database) was completed in 6 days. This included deduplication of 1,800 records, field mapping, and automated validation at each stage.
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