Ad Library Signal Detection — End-to-End Pipeline

One signal channel. Fully wired. Scrape to outreach in one flow.

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Pricing

$500 flat. Done in 48 hours.

I build a complete signal detection pipeline for one channel: Google Ad Library. Restaurants running event-related ads get scraped, cleaned, enriched with verified decision-maker contacts, and delivered into your Email Bison outreach flow. Not a proof-of-concept — a working pipeline you run on repeat.

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What You Get

• Google Ad Library scraper built on your Apify infrastructure: Detects restaurants actively spending ad budget on event promotion. Integrated with your existing Apify setup so it fits into how you already work.
• Cleaning and dedup layer: Raw scraped URLs normalized, chains and cafes filtered out using your exclusion criteria, duplicates removed against your existing prospect list.
• Contact enrichment through your Clay flow: Each flagged restaurant enriched with a verified contact at the right title — event director, event manager, owner, or ops lead. Formatted to match your existing Clay output.
• Email Bison delivery: Final output pushed into your outreach flow, ready to send. No manual reformatting or CSV gymnastics.
• Validation run: I test the full pipeline against your list of 10-20 known event-heavy restaurants before delivering. You see it catch the ones you already know about before trusting it on unknowns.

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How It Works

1. You share your Apify setup, Clay enrichment flow, and Email Bison config. I also need your restaurant exclusion list and 10-20 known event-heavy restaurants for validation.
2. I build the scraper, wire it to your cleaning logic, connect to Clay for enrichment, and format for Email Bison. One pipeline, end to end.
3. I run the validation pass against your known positives, then run a broader scrape.
4. I deliver the working pipeline with a walkthrough. You and your co-founder can run it, tweak filters, and scale volume.

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Success Criteria

• End-to-end flow works: You hit run, it scrapes, cleans, enriches, and delivers contacts into Email Bison. No manual steps in between.
• Signal accuracy: 70%+ of flagged restaurants are genuinely running event-related ads.
• Known-positive hit rate: The pipeline catches at least 60% of your validation list.

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What the Monthly Engagement Looks Like

Once this channel is running and you see the signal quality in real outreach, I add the remaining channels and automate the full motion:

• Facebook Ad Library + Reddit: Same pipeline pattern applied to two more ad platforms.
• Job posting signal: Scraping culinary job boards for restaurants hiring event roles — different signal, same pipeline structure.
• Social media signals: Instagram and LinkedIn monitoring for event-related posts.
• Multi-signal scoring: Weight and combine signals so the hottest prospects surface first.
• Full outbound automation: Signal-triggered sequences with copy tailored to each signal type.

Minimum commitment: 90 days. After that, month-to-month.

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What I Need From You

• Access to your Apify scraping scripts and Clay enrichment flow
• Your restaurant filter criteria (zip code radius, chain/cafe exclusion list)
• 10-20 restaurants you already know are event-heavy (validation set)
• Email Bison config so I can format output to match

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Next Step

Send me your Apify setup and validation list. I will have the full pipeline built and validated within 48 hours. Pay the $500 here to kick it off, or grab 30 minutes if you want to walk through your pipeline first.

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Ryan Murphy | UpfrontOps | rmurphy@upfrontoperations.com

How We Connected

You and I connected around go-to-market engineering and signal-based prospecting. You came in already running Apify, Clay, and Email Bison with custom scripting. That put us ahead of the typical first call where I am explaining what these tools are.

What Team Dexter Does

Team Dexter built an inquiry tool for the hospitality industry that replaces static contact forms with an interactive, context-rich booking experience. When a restaurant gets 20 event inquiries a week, the event team needs structured, qualified briefs, not generic form submissions. Your tool gives customers photos of each space, asks for backup dates, surfaces other properties in the portfolio, and delivers a qualified lead to the event team so they can respond with precision instead of sending a generic deck.

Your Current Prospecting Stack

You are scraping Google Maps via Apify by zip code within a 20-mile radius of major cities, filtering out cafes, pizza spots, and chains. Those URLs go into Clay for normalization and web scraping. Clay agents check each restaurant site for event-related content and multi-property footprints. From there, your team segments by title (event directors, owners, CEOs, ops leads) and runs outreach through Email Bison.

The Signal Gap

You know your ICP at both the business and person level. The missing piece is buying signals. Three channels came up:

• Ad library scraping: Restaurants running event ads on Google, Facebook, or Reddit. If they are spending money to promote events, events are a priority for that business.
• Job posting monitoring: Restaurants hiring event directors or event managers on LinkedIn, culinary job boards, or industry marketplaces.
• Social media event posts: Instagram and LinkedIn posts showing event photos or event recaps, confirming the restaurant actively hosts events.

What You Want From This

You want the flow built, not just a list. Signal in, data cleaned, contacts enriched, email out. Scalable and repeatable. You also want a sparring partner on GTM strategy: someone to pressure-test signal ideas and identify what you might be missing.

Agreed Next Step

I proposed a $500 quick win to build one signal channel (ad library scraping) end-to-end. If the signal proves out, we stack job postings and social media on top using the same pipeline pattern. You confirmed that chunking it this way makes sense and that you want to move fast.

Your Company

Team Dexter is a three-person, bootstrapped hospitality tech startup. You and your co-founder built it from the ground up. You handle go-to-market. Your co-founder handles the more technical side. You are profitable but reinvesting everything until revenue and GTM are proven out. That discipline tells me you think in terms of ROI, not vanity spend.

Your Product

You built an inquiry tool that transforms how restaurants handle inbound event bookings. Instead of a generic contact form that dumps unqualified leads into an inbox, your tool gives the customer an interactive experience: photos of each space, floor plans, backup date prompts, and visibility into the full property portfolio. The event team gets a structured brief they can act on immediately instead of starting from scratch on every inquiry.

For multi-property restaurant groups, the cross-sell value is significant. A customer who comes in for one venue sees the entire portfolio upfront. That keeps revenue inside the brand instead of losing it to a competitor because the event team sent a generic "not available, try somewhere else" reply.

Your GTM Challenge

You know exactly who your customers are: restaurants and restaurant groups with high event volume, staffed by event directors, event managers, owners, and operations leads. You have the tools (Apify, Clay, Email Bison, custom scripts) and the technical chops to run a real prospecting operation. What you do not have yet is signal precision. You can find restaurants. You cannot yet identify which restaurants are actively prioritizing events right now.

That is the difference between cold outreach and timed outreach. Ad spend on event promotion, job postings for event staff, and social media posts showcasing recent events are all proof that a restaurant is investing in events today, not six months ago.

What Matters to You

You said precision is the moat when it comes to go-to-market. I agree. You are not looking for a vendor to run a generic playbook. You want a sparring partner who understands your industry context and can help you figure out which signals actually move the needle, then build the infrastructure to act on them at scale.