Case Study
GTM Sales Intelligence
How a B2B sales team turned scattered data across calls, CRM, email, and docs into a working AI intelligence system
Discovery summaries in <30 seconds — down from 30+ minutes of manual prep
Key Achievements
Built context layer across Salesforce, Gong, Gmail, Google Drive, and HubSpot in 5 weeks
Automated discovery summaries cutting prep time from 30+ minutes to under 30 seconds
Achieved 85%+ classification accuracy for pipeline stage and deal health
The Challenge
Sales context is scattered across call transcripts, CRM records, email threads, and internal docs. Reps waste time searching instead of selling. Follow-ups are inconsistent. Pipeline visibility is poor. Every sales org has this data. Almost none of them can actually use it. The information exists — it just isn't connected, structured, or accessible when it matters. For this B2B sales org with 40+ reps and an enterprise pipeline, that meant 30+ minutes of manual prep per follow-up, inconsistent outreach across the team, and pipeline surprises every week.
Our Approach
Our approach centered on a context layer — a structured system that connects all customer data sources, normalizes the signal, and makes it retrievable at the moment it's needed. Rather than building another dashboard, we focused on the underlying infrastructure: connecting the systems where the data lives, defining retrieval logic that prioritizes recency and relevance, and automating the outputs the team already needed. The result was a working system in 5 weeks, not a pilot.
Our Solution
We built a context layer across all five data sources, plus retrieval logic and automated outputs for the workflows that mattered most.
Context Layer
Connected Salesforce, Gong, Gmail, Google Drive, and HubSpot into a single structured context layer — one source of truth for every deal.
Retrieval Logic
Built retrieval logic with recency weighting and query expansion so the right context surfaces at the right time, not just the most recent record.
Automated Summaries
Automated discovery call summaries and follow-up drafts — ready in under 30 seconds, consistently formatted across the team.
Pipeline Classification
Implemented AI-driven pipeline classification with 85%+ accuracy, giving managers real-time visibility instead of weekly manual updates.
Measurable Results
The system shipped in 5 weeks. The sales team went from 30-minute manual prep to automated summaries in under 30 seconds, with consistent follow-ups and real-time pipeline visibility.
85%+ Classification Accuracy
Pipeline stage and deal health classified automatically — up from ~60% baseline with manual tagging.
Under 30 Seconds
Time to discovery summary dropped from 30+ minutes of manual call review to automated output in seconds.
3× Follow-Up Consistency
Measured by manager review — drafted follow-ups from a single system replaced five-tool searching.
Real-Time Pipeline Visibility
Pipeline health surfaced continuously, replacing weekly manual update cycles.
What Users Say
The client credited the speed of delivery and the team's ability to understand a complex sales process quickly.
"MetaCTO stood out for their ability to quickly grasp the intricacies of our product and translate that into clean, scalable solutions."
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