Addressing Inconsistencies in Clay Data for SDR Outreach Team

Hi Clay S. - We've been currently rolling out Clay data to our SDR outreach team and theres been some flagged inconsistencies which i want to check with.

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As a company we deal with only eCommerce websites, so I’ve been running a AI prompt to scrap the website and if there is sign of a eCommerce presence (basket on site etc.) to put a tick. This hasn’t been working as there has been noticed non-commerce businesses coming through.

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We’ve noticed on a contact level that people have moved business with a different job title to what is getting pulled into the table. How often do you scrape LinkedIn? There Is instances of their LinkedIn being different to what is pulled.

2 comments

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For your AI prompt issue, the accuracy depends on the prompt's quality and website indicators you're using. Not all eCommerce sites display obvious elements like shopping carts - some use subtle indicators or third-party checkout systems that might be missed by your prompt. Regarding LinkedIn data, we don't scrape LinkedIn in real-time. Our data providers collect information without using your active session or cookies, which means they can only access publicly visible information. This explains why you're seeing outdated job titles for people who have changed positions. To track job changes more accurately, you can use our "Track Job Changes" feature by providing LinkedIn profile URLs. For better company identification, using LinkedIn URLs rather than domains will yield higher accuracy.
Sources: 11 AI Prompts to Automate Prospect Research with Claygent [Automated Outbound] - Clay University Track Job Changes
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