Lookalike Modeling

Find lookalike companies matching your best customers. The difference between good and bad lookalike modeling is almost always the data underneath it.

91% Of CRM data is incomplete

40% Of goals fail from bad data

$15M Avg cost of poor data yearly

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Why Your Lookalike Modeling Produces Wrong Answers

Analysis is only as good as the data feeding it. When your CRM data is 91% incomplete (Salesforce) and 40% inaccurate (Experian), every model, report, and recommendation built on that data is unreliable. You're not making data-driven decisions. You're making bad-data-driven decisions.

Garbage In, Strategy Out

Your ICP analysis says your best customers are mid-market SaaS companies. But the employee count data is wrong on 30% of accounts, the industry classification is inconsistent, and 25% of accounts are duplicated. That ICP might be right. Or it might be an artifact of dirty data. You can't tell.

Market Sizing on Incomplete Data

Calculating TAM requires accurate firmographic data across your target market. When company revenue estimates vary by 50% between sources, employee counts are missing for a third of accounts, and industry codes are unstandardized, your market size calculation has such wide error bars that it's barely useful.

Customer Insights Require Customer Data

Segmentation, CLV analysis, churn prediction, and lookalike modeling all require complete customer records. When your customer database has gaps in firmographics, missing contact data, and inconsistent classifications, every analytical output is compromised.

Leadership Loses Confidence

When your analysis consistently conflicts with operational reality, leadership stops trusting the numbers. The board sees a TAM that doesn't match revenue trajectory. The VP of Sales sees lead scores that don't predict close rates. Trust in data-driven decision-making erodes.

CRM data quality before and after Verum enrichment showing improved email coverage, phone connectivity, and record accuracy — Before vs after: how Verum transforms your CRM data quality.

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How Clean Data Transforms Lookalike Modeling

Clean, enriched data transforms lookalike modeling from a struggle into a strength. We handle the cleanup and enrichment so your team focuses on execution, not data problems.

Complete Records From 50+ Sources

We fill in the missing fields that lookalike modeling depends on. Emails, phones, titles, company size, industry, tech stack, and social profiles. All verified from 50+ sources and cross-referenced for accuracy.

For your team: Instead of working around data gaps, your team works with complete records that make every lookalike modeling decision more confident.

Ongoing Quality Maintenance

Data decays at 30% per year. We offer quarterly re-enrichment and validation to keep your records current so your processes don't degrade over time.

Human QA on Everything

Every project gets human review before delivery. We don't just run your data through APIs. Our team validates edge cases, reviews match quality, and ensures accuracy.

Diagram showing 50+ data sources converging into a single enriched record through Verum's multi-source enrichment engine — How Verum cross-references 50+ sources for every record.

93% Deliverability guarantee

24‑48hr Typical turnaround

50+ Data sources

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What You Can Do With Clean Data for Lookalike Modeling

Reliable ICP analysis. Build your Ideal Customer Profile on clean, complete data so the analysis reflects reality, not data artifacts.
Accurate market sizing. Calculate TAM, SAM, and SOM with verified firmographic data that produces trustworthy estimates.
Customer segmentation. Segment customers by verified attributes to identify your most valuable cohorts and their shared characteristics.
Churn prediction. Model churn on complete customer records so your predictions are actionable, not noise.
Board-ready analytics. Produce analyses that leadership trusts because the underlying data has been cleaned and verified.

CRM integration flow showing data exported from Salesforce or HubSpot, enriched by Verum, and imported back with improved field completeness — Your CRM data, enriched and returned with 90%+ completeness.

Getting Started Takes Less Time Than Your Average Meeting

Step 1: Free Assessment (5 minutes)
Upload a sample file or tell us what you need. We'll review your data and tell you exactly what we can do, with expected match rates and timelines for lookalike modeling.

Step 2: Discovery Call (30 minutes)
We'll walk through your current stack, data sources, and goals. No sales pitch. Just a technical conversation about your data.

Step 3: Data Analysis (on us)
We run a free analysis on a sample of your records so you can see results before committing to anything.

Step 4: Full Engagement
Once you approve the sample results, we process your full dataset. Most projects complete in 24‑48 hours.

Step 5: Ongoing (if you want it)
Data decays at 30% per year. We offer quarterly or monthly re‑enrichment to keep your records current. No long‑term contracts required.

Timeline showing 30% annual data decay from 95% accuracy at month 1 to 70% at month 12, with job title changes, email bounces, and phone disconnects — Why ongoing enrichment matters: 30% of your data goes stale every year.

Why Teams Choose Verum for Lookalike Modeling

We do the work. Send us your data. We clean, enrich, and return it. You don't manage another tool.
Fast turnaround. 24-48 hours for most projects.
Human verification. Every project reviewed by our data team before delivery.
No long-term contracts. Per-project pricing. No annual lock-in.
We understand lookalike modeling. We've helped dozens of teams improve their lookalike modeling through better data. We know what matters.

The Old Way vs. With Verum

The Old Way	With Verum
Working with 91% incomplete CRM data	Every record enriched from 50+ verified sources
30% of data decayed and outdated	Quarterly refresh keeps records current
Manual data research eats selling time	Pre‑enriched records ready for immediate use
Reports nobody trusts	Analytics built on verified, complete data
Multiple tools, same data problems	One vendor for cleaning, enrichment, and maintenance

Data enrichment visual showing Verum's approach to why your lookalike modeling produces wrong answers — Visual guide to how Verum solves B2B data challenges.

Common Questions About Lookalike Modeling

How does clean data improve lookalike modeling?

Clean data eliminates the errors, gaps, and inconsistencies that cause lookalike modeling to underperform. When your CRM data is accurate and complete, every process built on it works better: routing, scoring, segmentation, outreach, and reporting.

How long does it take to see results?

Most data projects complete in 24-48 hours. You'll see the impact on your lookalike modeling immediately because the underlying data quality improves overnight, not over months.

Do we need to change our existing tools or processes?

No. We clean and enrich the data inside your existing CRM. Your current tools and processes stay the same. They just work better because the data feeding them is better.

How is this different from buying a ZoomInfo license?

Three differences. First, different problem: ZoomInfo sells net-new contacts, Verum enriches your existing records. Second, different pricing: ZoomInfo runs $15K-$50K+ per year, Verum charges per project. Third, different ownership: ZoomInfo requires data deletion when you cancel. Verum data is yours forever.

Ready to Improve Your Lookalike Modeling?

Not sure yet? Upload a sample file and we'll run a free data quality assessment. See exactly what we can improve before committing.

Ready to fix this? Tell us what you need. Clean data in your CRM within 24-48 hours.

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