Clay has become the go-to tool for revenue teams that want to enrich, score, and route leads without writing code. Buska captures social buying signals in real time. Put them together, and you get a pipeline where every social mention gets enriched with company data, scored for fit, and pushed to your CRM or outreach tool automatically. No spreadsheets, no manual lookup, no context switching. In this guide, I'll walk you through how to build this workflow from scratch.
Why Clay + Buska work well together
Buska is good at one thing: finding social signals that indicate someone is ready to buy. It monitors Twitter, Reddit, LinkedIn, and other platforms for mentions that match your keywords, then scores each one for buying intent. What Buska doesn't do is enrich those signals with company data or push them into your sales stack.
That's where Clay comes in. Clay takes a raw data point (like a Twitter handle or LinkedIn URL from a Buska mention) and runs it through dozens of enrichment sources to find the person's email, company, role, funding stage, tech stack, and more. Then it scores the lead based on your ICP criteria and exports qualified leads wherever you need them.
The combination means you go from "someone posted about needing a tool like ours" to "here's their email, they're a VP at a Series B company in our ICP, and they've been added to our Lemlist campaign" without touching a spreadsheet.
Setting up the Clay table
Start by creating a new table in Clay. This will be the central hub for your social signal pipeline. Add the following columns to match the data Buska sends via webhook:
- mention_text (text) - the original social post content
- platform (text) - Twitter, Reddit, LinkedIn, etc.
- author_username (text) - the handle or username of the author
- post_url (URL) - direct link to the original post
- intent_score (number) - Buska's AI-generated intent score (0-100)
- keyword_matched (text) - which Buska keyword triggered the capture
- detected_at (date) - when Buska detected the mention
In Clay, go to the Sources tab and select "Webhook" as the data source. Clay will generate a unique webhook URL. Copy this URL because you'll need it for the next step.
Connecting Buska's webhook to Clay
In your Buska dashboard, navigate to Settings, then Integrations, then Webhooks. Paste the Clay webhook URL you copied in the previous step. Click Save. Buska will now send a JSON payload to Clay every time it detects a new mention matching your keywords.
Test the connection by triggering a test webhook from Buska. You should see a new row appear in your Clay table within a few seconds. If the columns don't map automatically, use Clay's field mapping interface to match the JSON keys to your table columns.
Adding enrichment columns
Now comes the powerful part. Add enrichment columns to your Clay table that automatically look up additional data for each new row. Here's a recommended enrichment stack:
- Person lookup: Use Clay's "Find Person" enrichment with the author_username and platform fields as input. This will attempt to find a full profile, including email, LinkedIn URL, and current company.
- Company lookup: Chain a company enrichment off the person lookup result. This gives you company size, industry, funding, revenue, and tech stack.
- Email finder: If the person lookup doesn't return an email, add an email finder column (Apollo, Hunter, or Clearbit) as a fallback.
- ICP scoring: Create a formula column that scores the lead based on your ideal customer profile. Weight factors like company size, industry, role seniority, and funding stage.
Clay runs these enrichments automatically for each new row, so every time Buska sends a new mention, the full enrichment pipeline runs without any manual intervention.
Scoring and filtering leads
You now have two scores for each lead: Buska's intent score (how strong the buying signal is) and your ICP score from Clay (how well the lead fits your ideal customer profile). Combine them for a composite score.
A simple formula works well: (intent_score x 0.6) + (icp_score x 0.4). This weights buying intent slightly higher than fit, which makes sense because a perfectly-fitting lead with no intent is less valuable than a slightly off-ICP lead who is actively looking for a solution.
Add a filter view in Clay that only shows leads above your composite score threshold. Start with the top 20% and adjust based on results. You can also create separate views for different lead tiers (hot, warm, cold) to route them to different follow-up workflows.
Exporting to your sales stack
The final step is pushing qualified leads out of Clay and into the tools your team actually uses. Clay supports native exports to most major platforms:
- HubSpot or Salesforce: Push enriched contacts directly into your CRM with all the enrichment data mapped to contact properties.
- Lemlist or Instantly: Export to cold outreach tools with the signal text included as a personalization variable.
- Slack: Send a notification to a team channel for the highest-scoring leads that need a personal response.
- Google Sheets: For teams that want a simple review step before leads enter the CRM.
Set up Clay automations to trigger these exports based on your composite score. For example: leads scoring above 80 get pushed to your CRM and trigger a Slack alert. Leads scoring 60-80 go into a Lemlist nurture campaign. Leads below 60 stay in Clay for manual review.
Optimizing the workflow over time
After running this pipeline for a week or two, review the results. Which keywords generate the highest-converting leads? Which platforms deliver the best ICP fit? Which enrichment sources have the highest match rate? Use these insights to refine your Buska keywords, adjust your ICP scoring weights in Clay, and tighten your export filters.
The beauty of this setup is that every component is modular. You can swap enrichment providers, add new scoring criteria, or change export destinations without rebuilding the entire pipeline. Start simple, measure what works, and iterate.
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