From “too hard to measure” to cross-stack answers in minutes

Structify gives Merge’s RevOps and post-sales teams a single place to ask questions across Salesforce, Gong, Pylon, Slack, and Google Sheets, so they can surface insights and support cross-functional decisions in minutes instead of days.

We used to put cross-stack analyses in the 'too hard' bucket because they'd take longer to run than the payoff was worth. Structify dropped that from days to minutes. Now we answer the hardest questions across our data stack while they're still fresh, keeping momentum and exec focus on what matters most.

About Merge

Merge is the leading provider of agentic tools and customer-facing integrations for the largest banks (e.g., U.S. Bank and Mastercard), AI companies (e.g., OpenAI, and Perplexity), HR technology providers (e.g., BambooHR and Carta), and more.

With a fast-moving product org and a broad customer base, RevOps sits at the center of go-to-market, customer success, finance, and recurring revenue operations.

Alex oversees RevOps at Merge, a cross-functional role that also touches internal AI efforts alongside the heads of product and engineering. His team fields data requests from across the org, often involving systems that don’t talk to each other.

What Structify Does for Merge

Merge’s RevOps and post-sales teams operate across a wide surface area: CRM data in Salesforce, standard reporting in Google Sheets, customer conversations in Gong, support and ticketing in Pylon, and internal coordination in Slack. Before Structify, getting a cross-system answer meant pulling from each tool individually, stitching things together manually, and hoping nothing fell through the cracks.

Structify connects all of it. The team can ask operational questions across systems in plain language: no SQL, no manual exports, no dedicated analyst required.

Ad hoc data pulls and internal reporting. When leadership wants a quick read on product performance or needs to understand a trend across customer segments, the team delivers structured, sourced answers through Structify’s RevOps channel, fast enough to drive decisions in real time.

Product feedback analysis. Structify pulls from Pylon, Gong, and Slack into a single view, automatically deduplicating customer requests and categorizing them into priority tiers (1–3). In a head-to-head test, the VP of RevOps ran the same exercise both manually and in Structify. The results were identical, but what took 12 people two hours each (24 total hours) took roughly 30 minutes in Structify.

Ticketing and support intelligence. Pylon had no connection to GTM data, which meant RevOps had zero easy visibility into support-side patterns that could inform sales or CS motions. Structify bridged that gap, enabling ticket queries, resolution trend tracking, and connecting engineering activity back to customer outcomes.

Cross-team context sharing. When someone from product, sales, or CS needs context on a customer issue or feedback trend, they get answers in minutes instead of scheduling a meeting or waiting for a report. Alex pointed to this as one of the less obvious but most meaningful benefits: removing the friction that slows cross-functional collaboration.

• 0124 hours of manual work replaced in one exercise — A feedback analysis requiring 12 people × 2 hours each completed in ~30 minutes with identical results, validated head-to-head by the VP of RevOps
• 02Cross-system visibility where none existed — Salesforce, Gong, Pylon, Slack, and Sheets unified into a single queryable layer with no data warehouse required
• 03Ad hoc answers in minutes, not days — Leadership requests, trend analysis, and cross-functional questions answered on the spot instead of becoming multi-day projects
• 04Expanding across the organization — Finance (RAMP API for spend tracking and ROI), pre-sales (API documentation verification), engineering (codebase Q&A, debugging via chat session analysis)

Before Structify

Merge's RevOps team had good standard reporting in Salesforce and Google Sheets, but their actual day-to-day was dominated by ad hoc requests that didn't fit existing reports.

Their CSP had no connection to go-to-market data. Gong transcripts lived in their own silo. Support data couldn't be cross-referenced with Slack without manual effort.

Every cross-system question became a mini-project: export, clean, merge, analyze, present. The drag added up fast.

They'd tried off-the-shelf LLMs but found them slower and less reliable than expected. Token limits caused timeouts and too much context diluted prompts, causing hallucinations.

The gap felt like an accepted cost of operating at their stage.

With Structify

Structify changed the economics of every ad hoc request. Instead of a multi-hour manual pull, the team asks a question and gets a structured, cross-system answer.

Questions that previously weren't worth asking became easy to answer.

A key factor in adoption was Structify's wiki feature, which lets the team provide rich operational context without the token limit or context dilution tradeoffs Alex saw in other tools.

He sees the difference as architectural: meaningful RevOps results require robust, chained AI agents with routing and evaluation logic, not a simple LLM bolted onto a data connector. That precision is what turns a tool teams try into one they trust.

Merge is already expanding beyond RevOps: Finance is exploring RAMP integration for spend tracking and ROI analysis, pre-sales uses it to verify API documentation currency, and Engineering sees potential for codebase Q&A and internal debugging. What started as a RevOps tool is becoming cross-functional infrastructure.

RevOps sits in the middle of GTM with a dozen stakeholders, all processing and understanding the business in their own way. Through tailored, scheduled reporting and significantly faster ad hoc data requests answered, Structify minimizes time spent on reporting so operations can maximize process, strategy, and scaling the business.