Unlocking the Hyper-Local Market: How We Built a Precision Prospecting Engine for Runnr.ai

Runnr.ai provides a cutting-edge platform for the hospitality industry, but their growth was being throttled by a fundamental data problem. Their target market—hotels—is notoriously difficult for standard prospecting, creating critical roadblocks:

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The "Local Business" Blind Spot: Standard data enrichment tools are ineffective at finding accurate decision-makers within local and independent hotels. Their existing process was failing, delivering incomplete or incorrect contact information.‍

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Wasted Manual Effort: The sales team spent countless hours manually searching Google and LinkedIn to find the right contacts, a process that was slow, demoralizing, and impossible to scale.‍

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Generic Outreach: A lack of reliable data meant their outreach was generic. They couldn't personalize their messaging effectively, leading to low engagement rates with busy hotel managers.‍

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A Growth Ceiling: Runnr.ai had a powerful product but couldn't build a predictable pipeline. To scale their RevOps, they needed to solve this core data and prospecting challenge.

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The challenge was clear: We needed to build an automated engine that could systematically find the right, hard-to-find contacts at their target hotels and enrich them with data for meaningful personalization.

We worked directly with the Runnr.ai team to architect a robust prospecting system designed for their unique market. We didn’t just deliver a list; we built a machine they could own and operate.

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1. Fixing the Data Foundation

‍First, we diagnosed the critical error in their existing data enrichment process. We then built a new, multi-step data waterfall in Clay. This system bypasses traditional tools by using creative sources to reliably find contact information for key personnel like General Managers and F&B Managers at local businesses.

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2. Engineering a Precision Contact Finder

‍We developed a custom logic that identifies the most relevant decision-makers based on the hotel's size and characteristics. The system automatically finds and verifies these individuals, eliminating guesswork and manual verification. This step was key to the 200% increase in contact accuracy.

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3. Enriching for Hyper-Personalization

‍To power their RevOps strategy, we added four new custom data points for every single prospect. This included information like recent guest review themes, local awards, on-site amenities, and technology mentioned on their website, allowing the sales team to craft highly relevant, compelling outreach.
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4. Delivering a Fully Automated Workflow

‍The entire process—from identifying a target hotel to delivering a fully enriched, sales-ready contact into their CRM—was completely automated. This reduced their manual prospecting time to zero and provided the sales team with a predictable flow of high-quality leads.

By implementing the Prospecting Automation System, Runnr.ai turned a major bottleneck into a competitive advantage. The results were immediate and impactful.

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For Runnr.ai:

• 200% Increase in Accurate Contacts Found: The new engine successfully identified correct decision-makers where previous methods failed, massively expanding their reachable market.

• ‍Zero Manual Prospecting: The sales team was freed from manual, repetitive data tasks. They could now invest 100% of their prospecting time in high-value activities like outreach and closing deals.
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• Deeper Personalization & Higher Engagement: With 4 new data points per lead, the sales team crafted messaging that resonated with hotel managers, leading to more meetings booked and a stronger pipeline.
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• A Scalable, In-House GTM Motion: As requested, we designed the system for them to operate independently. Runnr.ai now owns a scalable asset that will fuel their growth long-term, without ongoing dependency.