Just finished a 90-day pilot with the Gemini meeting scheduler across our sales team. Main result: each rep saved an average of 2 hours per week previously spent on manual back-and-forth scheduling.
We integrated it with our existing CRM and email system. The time saved is clear, but I have questions about scaling and edge cases.
* Is the 2-hour savings typical, or are we an outlier?
* What are the hard limits on daily scheduled meetings per user before performance degrades?
* We hit a sync delay with our CRM once. Is the API rate limiting documented anywhere?
* For revops, how does it handle complex round-robin assignment rules based on lead source?
Looking for concrete data on long-term reliability, not just initial setup.
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2 hours/week per rep is in line with what we saw, but the savings plateaued after about 6 months. The reps just filled the time with other low-value tasks. Automation only helps if the freed-up capacity is redirected.
On scaling: we hit API bottlenecks around 150 scheduled meetings per user per day. The sync to our CRM would lag by 3-4 hours at that volume. The rate limits are in the API docs, but they're buried. Look for the section on "throttling tiers".
For complex round-robin, it can't handle lead source weighting natively. You'll need to manage that logic upstream in your CRM and push the assignment to Gemini. We built a middleware service for that.
YAML all the things.
That 2-hour saving tracks with what I've seen in implementation studies, but there's a key detail. Was the saved time audited and reallocated? If not, you might not see that benefit on your bottom line after the pilot glow fades.
For your scaling questions, the 150 daily meeting bottleneck is real, but performance degradation starts earlier, around 120, with calendar syncs becoming less instant. The API docs are a mess - search for "concurrent request limits," not just throttling.
On round-robin, user1046 is right that native handling is limited. The better UX pattern is to use your CRM as the single source of truth for assignment logic and have Gemini act as the execution layer. Trying to build complex rules inside the scheduler itself creates a maintenance headache. Have your revops team mapped out those lead source workflows yet?
Exactly. The real metric isn't hours saved, it's what those hours are converted into. If you're not tracking the output from that freed-up time, the reported savings are just vanity.
On the API docs, they're not just a mess, they're wrong half the time. The "concurrent request limits" you found are for the v2 API. If you're still on v1, which a lot of legacy integrations are, the behavior is completely different and not documented at all. We had to reverse-engineer it from network logs.
Building rules inside the scheduler is a trap. It turns your scheduling config into a second, worse CRM. Every time marketing adds a new lead source, you're now updating two systems.
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