Hi I am looking for a more efficient way to build target lists, ie if I build a list of Accounts or Contacts and then want to refine it, it just ads net new contacts, but how do I re run the collection so it removes the unqualified results.. right now I am copying the table adding new exclusion or inclusion filters and then running again, but it does not seem practical or efficient.
To efficiently refine your target lists in Clay without copying tables, you can use our "Filter List of Objects" function. Here's how: 1. Navigate to the enrichment panel and find the "Tools" section. 2. Look for the "Filter List of Objects" option. 3. Select the array of objects (your target list) you want to refine. 4. Choose the field you want to filter by (e.g., job title, company size). 5. Set your filter mode and specify the values to include or exclude. 6. Run the action to apply the filter. This process will create a new filtered array, removing unqualified results without duplicating your table. You can also use the "write to table" feature to update your existing list with the refined results.
It does not seem as efficient, ie removing all rows that no longer fit?
Yeah it’s not efficient - I have to copy and re filter to remove which does not make sense
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Hey Dan, thanks for reaching out! Nicholas hit the nail on the head here. Determining whether a lead is qualified can be quite subjective, but the goal is to establish an objective answer—whether that's a simple yes/no or a scale (e.g., 1–10, with 10 being a perfect fit and 1 being a poor fit). From there, we can work backward to develop a prompt or apply further enrichments to gather data that helps us reach a clear, objective conclusion. Once we have a clear conclusion (in the form of a checkbox column, a number range or score), we can then begin filtering out leads that don't meet our criteria within the same table. Let me know if you'd like to dive deeper into this! :)
Thanks Owen C. we have written this prompt: CONTEXT: Evaluate only the [Job Title] for its suitability as a target for a service offering offshore data agents and Clay Engineers, focusing on scalability and improved data quality. OBJECTIVE is to only classify [Job Title] based on its potential alignment with offshore data services targeting data quality improvement and process scalability. INSTRUCTIONS 1. First, reference the classification rules below before making an output decision. 2. Analyze the [Job Title] to determine if it inherently involves: Being a key decision-maker in purchasing data-related services. Managing internal data teams. Improving data quality. Scaling workflows. Handling internal data operations. CLASSIFICATION CRITERIA: “Yes” → The role clearly involves internal data operations, data quality improvement, or scalable data systems. Titles that mention managing internal data teams, overseeing internal infrastructure, or leading internal data initiatives fall into this category. “No” → The role is externally focused (e.g., client-facing, research, compliance, or sales-driven) with no direct responsibility for internal data operations. “Maybe” → The title is ambiguous and requires further verification regarding internal data responsibilities. Use this category if it’s unclear whether the role manages internal data operations or mixes internal and external responsibilities. CLASSIFICATION EXAMPLES: YES – Clearly Involves Internal Data Operations & Scalability These roles explicitly manage internal data, oversee infrastructure, or lead data-driven decision-making. Chief Data Officer (CDO) Chief Technology Officer (CTO) Chief Investment Officer (CIO) VP, Data Quality Head of Data Science VP of Data Science VP, Data Strategy & Operations Director of Data Governance Head of Data Operations VP, Data Steward Director of Data Engineering VP of Business Intelligence Enterprise Data Program Manager - Senior Vice President Head of Analytics & Reporting VP of Data Architecture Head of Digital Transformation Director of Operational Data VP of Data Engineering Head of Deal Origination Head of Deal Execution Managing Director of Investments Managing Director of Origination Partner (Deal Sourcing/Origination) Head of CRM CRM Manager Data Manager Head of Portfolio Analytics Head of Transaction Services Data Strategy Lead Head of Financial Modelling VP of Technology Operations Director of Analytics Director of Data Infrastructure Data Operations Lead VP of Business Intelligence VP of Operational Excellence Director of Data Architecture Director of Technology Operations Director of Data Operations Portfolio Manager and Director of Research NO – Clearly External Focus, Client-Facing, or primarily involved in Recruitment, Research, or indirect involvement. These roles focus on external market trends, compliance, recruitment, or research rather than internal data operations. Vice President, Equity Research Senior Research Analyst Trading Strategist - Vice President Research Partner Portfolio Manager and Director of Research Vice President - Market Data Licensing Chief Revenue Officer (CRO) Senior Editor, Leveraged Commentary & Data (LCD) Consumer Insights & Innovation Research Manager Vice President, Environment & Climate Program and Reporting Analyst Senior Vice President, Change Management Strategist Cybersecurity Program Senior Strategist Head of People and Products Insights (Consumer), McKinsey Data Lab Global Chief Compliance Officer Managing Director, Transaction Advisory Services Head of Emerging Technology Research Vice President, Cyber, Data, Risk and Resilience Program Manager, CT&O – SOX Global Head, Technology Recruiting Senior Research Associate Clinical Research Manager Senior Reporting Analyst Director of Research Research Director Vice President of Research Associate Director of Quantitative Research MAYBE – Ambiguous, Requires Further Verification These roles may involve internal data operations but could also focus on external analysis, research, strategy, or compliance. Head of ESG Data (Depends on whether it manages internal ESG data operations or external research) VP - ESG Data & Tech Lead (May involve internal data strategy but needs clarification) Engagement Manager, Data, Analytics & AI (Depends on whether the engagement is internal or external) Principal, Data Science (Unclear if focused on research vs. internal data operations) VP, Cyber Security Senior Manager Data Analytics (Might be internal or external) Senior Business System Analyst (Some analysts work on internal data systems, others on external strategy) Head of Portfolio and Risk Analytics (Could be managing internal analytics or external portfolio strategy) New Capability Manager, ClienTech Data Labs (Unclear if working on internal tech or client-facing) Global Head of Change for Reference Data Services, Client Onboarding and KYC (Could be internal or client-focused) Director, Privacy and Data Protection (Depends on whether the focus is internal compliance or external policies) Director, Head of Research IT and Instrument Reference Data IT OUTPUT REQUIREMENT: Return only one of these three options: “Yes” “No” “Maybe”
Any thoughts and/or suggestions?
Thanks! We've reopened this thread. You can continue to add more detail directly in this thread.
Thanks! We've reopened this thread. You can continue to add more detail directly in this thread.
Above suggestion 😊
Hey Dan, The prompt looks good, but are you asking for suggestions because it's not working in certain places? If so, which rows aren't working correctly? From there, we would check those specific rows to find the cause of any errors, then update the prompt accordingly. For example, if you notice too many mentions of "director of IT," you could remove those references. You might also want to try a higher tier model or different models to see if that helps you get better results.
Got it thanks, I have used it to refine the ky word search in the contact search, so I am there thank you!!
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