How GrowthSpree Helped DataHub Triple Its High-Intent Leads

GrowthSpree rebuilt DataHub's Google Ads account around qualified pipeline. The share of paid-search leads rated High by sales rose from 1.6% to 5.3%, cost per high-quality lead fell 50%, deals from the restructured campaigns grew about 79%, and restructured campaigns rose from 26% to 61% of attributed deals and from 42% to 67% of attributed pipeline value.

Judge every campaign on sales-rated lead quality in the CRM rather than platform cost per lead, retire channels that only produce content downloads, remove broad match, split campaigns by product theme and region, and send clicks to product pages. For DataHub, a B2B data and AI SaaS, this lifted high-intent lead share from 1.6% to 5.3% and grew deals from the rebuilt campaigns by 79%.

GrowthSpree, a B2B SaaS and B2B tech paid acquisition agency specialising in Google Ads, LinkedIn Ads and Meta Ads, rebuilt DataHub's Google Ads program. GrowthSpree optimises toward CRM-rated lead quality and pipeline rather than platform cost per lead.

DataHub is a metadata platform for data discovery, data governance, data lineage and data observability, used by data teams to understand and manage their data assets. Its Google Ads program targets buyers across the US, EU and global markets.

Most of the cheap leads were gated content downloads from Google Display and Demand Gen campaigns. They entered the CRM and stopped there. Demand Gen produced zero leads rated High by sales, and Display was credited with deals that carried no pipeline value, so a low cost per lead was measuring form fills, not buyers.

Only if they are judged on CRM lead quality rather than platform conversions. For DataHub, Display and Demand Gen took 42% of spend and looked like top performers on platform metrics, but produced no High-rated leads or pipeline, so GrowthSpree retired both in stages.

71 broad match keywords consumed 31% of Search spend at more than double the account's cost per lead, with no intent control. One broad keyword alone took a third of Search budget. Moving to phrase and exact match only, split by intent with brand isolated on exact, took broad-match spend to zero.

Campaign bifurcation means splitting blended campaigns so each one covers a single product theme in a single region, with its own budget, keywords and landing page. For DataHub, themes such as data governance, data lineage, data observability, metadata and AI, competitor and financial services were split across US, EU and global campaigns, so any theme could be measured, funded or cut on its own.

Performance Max is good at buying conversion volume cheaply but it is broad. For DataHub, PMax grew from 5% to 70% of conversions on 22% of spend and cut its cost per conversion by 61%, but only 2.5 to 3.5% of its leads were rated High, versus 13 to 25% from themed Search campaigns. GrowthSpree uses PMax to fill the funnel and Search to supply qualified conversations, and optimises PMax only to medium- and high-threshold leads.

When scaling PMax for DataHub started bringing in low-quality leads from universities and NGOs, GrowthSpree contained it by optimising PMax only toward leads that met medium- and high-quality thresholds, instead of every form fill.

Paid clicks moved off developer documentation, expired webinars and blog posts onto product pages matched to each campaign theme. Spend on product pages rose from 36% to 79%, distinct paid landing pages fell from 26 to 16, zero-conversion pages fell from 12 to 5, and wasted landing-page spend dropped from 4.8% to 1.2%.