Alright, so I’ve been absolutely loving Fathom for call recording and note-taking—it’s become a core part of our sales workflow. But as someone who lives in Looker Studio for our revenue reporting, I kept hitting a wall: I really wanted to blend our call analytics (like call volume, duration, no-shows) with our CRM pipeline data to see the real impact of outreach.
The official API is great for raw data, but I wanted something more dashboard-friendly and refreshed automatically. Since a native connector doesn’t exist (yet 🤞), I decided to roll up my sleeves and build a makeshift one over the weekend.
Here’s the general approach I took—it’s definitely a bit hacky, but it’s working in production for us now:
* **Core Components:** I used a lightweight cloud function (Google Cloud Functions) as the “middleware.” It’s scheduled to run daily.
* **Data Flow:** The function calls the Fathom API, pulls the call data (filtering for our team’s users), and does some basic transformations—things like categorizing call outcomes based on keywords in the summary and calculating averages.
* **The “Connector” Part:** This is the hacky bit. Instead of a proper Looker Studio Community Connector, I write the cleaned-up data to a BigQuery table (you could use Sheets, but BQ handles our volume better). Then, I use Looker Studio’s native BigQuery connector to visualize it.
* **Key Transformations I Found Useful:**
* Bucketing call durations for quick analysis.
* Merging Fathom’s “meeting title” with our internal deal IDs for easier joins to CRM data.
* Flagging calls where the summary is empty (a nudge for the team to update notes).
The biggest win so far has been correlating high call activity with deal stage progression. The main drawbacks are the added complexity (now I “own” this pipeline) and the slight delay since it’s a daily batch job, not real-time.
I’m curious if anyone else has tackled this? Would love to compare notes or hear if there’s a more elegant solution brewing out there. Particularly around:
* Handling authentication more securely for a team-wide view.
* Whether to try and build a proper Community Connector (steep learning curve for me).
* Any other Fathom data points you’ve found super valuable for sales forecasting?
TIL that sometimes a little duct-tape integration can unlock a whole new layer of insight.
Pipeline is king.
Interesting approach. The cloud function as middleware is a solid pattern. I'm curious about the transformation logic you're running before sending data to Looker Studio. Are you doing any pre-aggregation there, or just cleaning and reshaping?
I've found that even with hacky connectors, pushing basic aggregates (daily counts, average durations) at the function level can drastically improve dashboard load times, especially when blending with large CRM datasets. It reduces the computation Looker Studio has to do on the fly. The trade-off is losing some drill-down granularity unless you maintain a separate detail table.