BACK / How Lumana increased its lead-to-SQL submission rate by 46% from Q2 to Q3
Location: California, United States Content type: Performance Marketing
46%
Increase in lead-to-SQL submission rate
CHALLENGE
- Hackmamba joined Lumana’s performance marketing program on August 12, with paid campaigns already running across Google, Meta, LinkedIn, and other channels.
- Google Search carried the largest share of paid media spend, but informational searches and irrelevant queries were consuming budget without producing enough qualified pipeline.
- Lumana’s Brand campaign was matching searches for “Luna,” while camera-related keywords were attracting people looking for hardware instead of Lumana’s software.
- LinkedIn campaigns were reaching smaller companies and junior job functions with limited buying authority.
- Meta cold-audience campaigns were spending without generating enough qualified leads.
- Campaign reporting focused on CPL and lead volume, which gave the team limited visibility into which campaigns, audiences, and keywords progressed into SQLs, opportunities, and closed business.
SOLUTION
- Hackmamba took over the performance marketing program and connected campaign decisions to CRM outcomes.
- We started mapping Google Ads keywords through lead, SQL submission, SQL acceptance, opportunity, closed-lost, and closed-won.
- We grouped keywords based on whether they produced closed business, generated leads that stalled, or failed to contribute to closed revenue.
- We added negative keywords, removed weak search terms, fixed the Brand campaign, and excluded camera-related searches with poor software-buying intent.
- We moved more Google Ads budget into the Top Keywords and Use Cases campaigns that were producing stronger downstream results.
- We tightened LinkedIn targeting by excluding existing converters, competitor companies, and job functions without enough buying authority.
- We launched SQL-based lookalike audiences and native Lead Gen campaigns across LinkedIn and Meta.
- We consolidated Meta retargeting campaigns, paused weak ads, and reduced spend on cold audiences that were failing to generate leads.
- We launched Reddit as a paid experiment and used engagement data to evaluate audiences and topics.
- We tested ChatGPT Ads with traffic and conversion campaigns and tracked the leads coming from the channel.
- Weekly reporting included CPL, SQL submissions, SQL acceptance, pipeline, and CRM outcomes so budget changes reflected sales performance.
RESULTS
- Lead-to-SQL submission increased from 14.6% in Q2 to 21.25% in Q3, a 46% increase.
- Lead-to-SQL acceptance increased from 7.6% to 10.65%, a 40% increase.
- Cost per accepted SQL decreased 20% to approximately $4,400.
- SQL submission-to-acceptance remained around 50%, with the increase in SQL volume continuing to meet Lumana’s sales acceptance criteria.
- Pipeline generated during the second half of Q3 was 300% higher than pipeline generated during the first half of the quarter.
- ARR generated per lead increased from approximately $1,340 in Q2 to $2,759 in Q3, a 106% increase.
- Paid media spend decreased 67% from Q2 to Q3.
- Total revenue increased 138% from Q2 to Q3 during the same period.
- Inbound closed-won revenue increased from approximately $69,000 in Q2 to $145,000 in Q3, a 110% increase.
- Opportunities created and closed within the quarter increased from approximately $16,000 to $22,000, a 38% increase.
Hackmamba took over Lumana’s performance marketing program in August and connected campaign decisions to CRM outcomes across Google, Meta, LinkedIn, Reddit, and ChatGPT Ads. From Q2 to Q3, lead-to-SQL submission increased 46%, lead-to-SQL acceptance increased 40%, and cost per accepted SQL fell 20%. During the same period, paid media spend decreased 67%, ARR per lead increased 106%, and inbound closed-won revenue increased 110%.
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