When your CRM starts to grow fast, duplicates follow even faster.
For one global organization, that meant 30,000+ duplicate records clogging HubSpot — breaking reports, confusing reps, and making automation unreliable.
In this episode of How I Fixed Your Data, I spoke with Hazel Johnson, Head of Operations at ProsperoHub — an Elite HubSpot Partner based in the UK — about how her team tackled a massive data optimization project using Koalify 🐨.
The result?
✅ 99% reduction in high-priority duplicates
✅ 35% improvement in data formatting
✅ A global client who now trusts their HubSpot data again.
🎥 Watch the full conversation with Hazel Johnson from ProsperoHub:
ProsperoHub’s client, a global enterprise with multiple teams and regions, had been scaling fast in HubSpot — but without a structured data quality process in place.
When Hazel’s team ran a full portal audit, the results were clear:
Nearly 30% of company records had no domain
Key fields like region, industry, and persona were missing
Over 10,000 duplicates flagged by HubSpot’s Data Quality Center (and it only counts up to 10,000!)
Poor ownership and inconsistent data entry across departments
“We had all the right data — it was just spread across multiple records,” Hazel explained.
“The client’s sales and marketing teams were struggling to trust what they saw in HubSpot.”
Without consistent data, lead routing failed, campaigns hit the wrong segments, and reports showed inflated numbers.
Something had to change.
After presenting a full audit, ProsperoHub and the client agreed to start with two core priorities:
1️⃣ Fixing duplicate records
2️⃣ Rebuilding data consistency at the company level
Hazel’s team evaluated several deduplication solutions — including HubSpot’s native tools — but quickly realized they needed something more powerful and flexible.
“HubSpot’s tools could get us part of the way,” Hazel said. “But Koalify took us the rest of the way — seamlessly integrated, easy to use, and cost-effective.”
ProsperoHub compared Koalify with two other market alternatives using three criteria:
Cost: Fair pricing for a global-scale cleanup
Ease of Use: Clean interface that clients could self-manage later
Integration: Deep HubSpot embedding for workflows and automation
Koalify won on all three fronts — hands down.
Once Koalify was implemented, ProsperoHub mapped out a phased deduplication strategy:
High-priority duplicates were those affecting:
Lead routing and sales assignments
Company data enrichment (missing domains, industries)
Reporting accuracy
Mid- and low-priority duplicates were scheduled for review later.
For the top tier, the team built workflow-driven merges directly in HubSpot via Koalify’s native actions.
“It took maybe 20 minutes to configure,” Hazel shared. “That’s the beauty of the UI — simple, fast, and safe.”
ProsperoHub exported mid-tier duplicate lists, grouped them by region, and handed them to local managers.
That allowed each region to verify records before merges — ensuring nothing was lost across territories.
After just three months, the results were dramatic:
High-priority duplicates: reduced from ~10,000 to fewer than 100 (–99%)
Total duplicates: dropped from around 30,000 to 10,000 (–66%)
Formatting issues: decreased by 35%
Regional accuracy: improved from inconsistent to fully verified per region ✅
Client satisfaction: went from “frustrated” to “over the moon” ❤️
“It was a breath of fresh air,” Hazel said.
“For the first time, data optimization felt easy. The right tools saved everyone time — and restored trust in the CRM.”
Hazel’s biggest takeaway?
You don’t have to wait for a crisis to fix your data.
“Every client — whether they have 1,000 or 100,000 records — can benefit from using Koalify. The usability, cost, and seamless HubSpot integration make it a no-brainer.”
And the client? They were so happy with the results that they extended ProsperoHub’s contract to continue managing data health long-term.
Clean data → Confident teams → Continuous growth.
That’s how you fix your data.
Run a full audit before you start deduplicating
Prioritize merges by business impact
Automate what’s safe, review what’s ambiguous
Split large cleanup projects by region or team
Keep the client involved — data trust builds adoption