## Is your feature request related to a problem?

#4947 added a new query to the backend – time to convert. It works well, just one point is kind of rough: bin width and count.

## Describe the solution you'd like

Currently the number of bins is hardcoded. Ideally we should have two options:
- return a user-specified number of bins,
- otherwise infer a reasonable number of bins using some algorithm (auto option).

@alexkim205 [suggested](https://github.com/PostHog/posthog/issues/4855#issuecomment-872423877) the [Freedman-Diaconis rule](https://en.wikipedia.org/wiki/Freedman%E2%80%93Diaconis_rule) for determining bin width (and interval based on that), but unfortunately from my testing its formula would not be the most practical – it's great for keeping a pretty constant "smoothness" of the histogram esp. with normal distribution, but we face some additional constraints that make it less than ideal:
- we can't have histograms too dense visually in the UI, from my testing a practical limit is 60 bins (above that it gets too dense),
- our data generally doesn't follow much of a normal distribution.

Clamping may help though, or maybe a different formula may work better outright – I'll be testing this.

## Additional context

Issue pertaining to the experience of time to convert: #4855

#### *Thank you* for your feature request – we love each and every one!

ee/clickhouse/queries/funnels/test/test_funnel_time_to_convert.py
maxDiff = None
    def test_basic(self):
        _create_person(distinct_ids=["user a"], team=self.team)
        _create_person(distinct_ids=["user b"], team=self.team)
        _create_person(distinct_ids=["user c"], team=self.team)
        _create_event(event="step one", distinct_id="user a", team=self.team, timestamp="2021-06-08 18:00:00")
        _create_event(event="step two", distinct_id="user a", team=self.team, timestamp="2021-06-08 19:00:00")
        _create_event(event="step three", distinct_id="user a", team=self.team, timestamp="2021-06-08 21:00:00")
        _create_event(event="step one", distinct_id="user b", team=self.team, timestamp="2021-06-09 13:00:00")
        _create_event(event="step two", distinct_id="user b", team=self.team, timestamp="2021-06-09 13:37:00")
        _create_event(event="step one", distinct_id="user c", team=self.team, timestamp="2021-06-11 07:00:00")
        _create_event(event="step two", distinct_id="user c", team=self.team, timestamp="2021-06-12 06:00:00")
        filter = Filter(
            data={
                "insight": INSIGHT_FUNNELS,
                "display": TRENDS_LINEAR,
                "interval": "day",
                "date_from": "2021-06-07 00:00:00",
                "date_to": "2021-06-13 23:59:59",
                "funnel_to_step": 1,