Built a small free plugin to run cohort-analysis on your pipeline - looking for feedback :)

[jonojeff]

Hi all! 

Just please let mek now if this isn't allowed here and I'll remove. 

I've been working in HS on sales/rev-ops for quite a few yeras now and running cohort-analysis has always been something I've found tremendous value from, especially since the deals I've worked with were always varied and had long sales cycles. 

Cohort analysis allows you to batch the deals into buckets based on shared characteristics (such as create date) and see how those deals evolve over time, far more revealing than 'snapshot' analytics. 

Anyway, I've built this small (free) tool - https://sales.studio/ (you can see a live demo with dummy data here: https://my.sales.studio/demo) and would love some community wisdom on how I can improve it! 

Thanks so much! 

Jonathan 

[DanielZarick]

This looks nice, @jonojeff !  Are you able to do cohort analysis on contacts as well? Ideally want to see time from when a contact became a marketing contact to when they created a deal in sales pipeline... as a cohort broken down by month.

[jonojeff]

Thanks, @DanielZarick !

Right now, we've built this for deals, but an interesting idea to have on a contact basis. I see the value in that. If this is something that you're genuinely interested in, we may be able to add this quite quickly. Feel free to DM me if that's the case. 

I know some of our beta testers have a pipeline where it only becomes an opportunity mid-way through (such as having zero-dollar weighted deals created for every lead) and that's very easy to setup using our tool. But indeed, we don't have it for all contacts. I need to think about how this would work to avoid data overload (and everyone tags MQLs differently). 

Thanks for the thoughts - really interesting! 

[PamCotton]

Hey @jonojeff, 

Thank you for sharing Sales Studio with us! It sounds like you've put a lot of effort into creating a useful tool for the Community. 

We're always excited to see innovative solutions like yours.

Kindly,

Pam