How an AI SMS Platform Generated $280K in Pipeline from AI Search

Using Rankscale to turn ChatGPT and AI search engines into a scalable B2B growth channel.

Partner agency: Spyndle · Author: Dustin Walker

$280K

Qualified Pipeline

#2

Attribution Channel

6 mo

Time to Results

The Client

The client is an AI-powered text messaging platform built for sales teams. With a complex B2B SaaS offering in a competitive market, they were looking for new channels to drive qualified demos beyond traditional paid and organic search.

The Ask

Could AI search actually generate qualified pipeline for a B2B SaaS product? The client wanted to find out whether LLMs like ChatGPT could become a meaningful, repeatable source of demo requests.

Steps Taken in Rankscale

1. Audit & Benchmark
   Audited the client's current AI visibility across problem-aware and category-level prompts (e.g., "best AI SMS platform for X"). Used Rankscale to benchmark positioning versus competitors in AI-generated answers.

2. Prompt Research
   Analyzed qualitative data including demo call transcripts to surface the exact prompts most likely to drive qualified demos. Uploaded dozens of high-intent prompts into Rankscale and organized them into themed clusters.

3. Sprint & Track
   Set benchmark metrics for a 3-month AI visibility sprint. Secured brand mentions and published targeted content aligned to prompt clusters. Shared monthly progress updates with a live Rankscale dashboard link.

Results

• $280,000 in qualified pipeline generated during the initial six months - a strong result for what started as an experimental channel.
• AI search became the #2 customer acquisition channel, surpassing several established marketing channels as results compounded month over month.
• Ongoing retainer secured. The client continues to invest in AI search visibility with Spyndle, having seen clear and measurable ROI.

“Spyndle delivered a clear ROI within a few months. Their work expanded our organic reach across Google and AI search, driving more qualified demos.”

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