# How does Common Room actually handle data quality? We&#39;ve been burned by enrichment vendors with 40-60% accuracy rates before.

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true"><em>We keep running into stale contacts, duplicate records, and data that looks clean but falls apart when reps use it. Trying to understand if Common Room's approach to enrichment and identity resolution is actually different before we commit.</em></p>

##### Post Metadata
- Posted at: 3 months ago
- Net upvotes: 1


## Comments
### Comment 1

Completely fair concern! Bad enrichment is one of the most common reasons AI-assisted GTM falls flat. 

Here&#39;s how we approach it differently. Most enrichment vendors pull from a single data source and call it done. We run an AI-powered waterfall enrichment model, which means we sequence across multiple providers and validating results, so coverage and accuracy are meaningfully higher.

But enrichment accuracy alone isn&#39;t the full answer. The other piece is identity resolution. A lot of teams find that even &quot;accurate&quot; data fails them because the contact is matched to the wrong account, or the same person exists as three duplicate records. We solve that through what we call Context360, our identity resolution layer that connects every signal and data point to real, verified people and accounts. 

We consistently win competitive bakeoffs on data quality. 

If you want to run a side-by-side on your actual accounts, that&#39;s something we&#39;re happy to set up: https://www.commonroom.io/demo/

##### Comment Metadata
- Posted at: 3 months ago




## Related Product
[Common Room](https://www.g2.com/products/common-room/reviews)

## Related Category
[Lead Intelligence](https://www.g2.com/categories/lead-intelligence)

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