Metrics for early pooled model?

Sam Davis
Sam Davis Member Posts: 1 Newcomer
Hi all!

My company, a series A startup, is working towards implementing our scaled customer segment. One of the questions we're continuously asked (rightfully so) are what our metrics will look like. If you're company is currently operating with a successful pooled customer model, would you be open to sharing what metrics you're tracking and the numbers attached?

Appreciate your help!
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  • Brian Hansen
    Brian Hansen Member Posts: 75 Expert
    5 Insightfuls First Anniversary Name Dropper
    Hello, Sam. Preface to say that we are not operational on a Scaled CS model, but I'd like to join the conversation to share the data points we're looking to track. Those are below. I'm curious how those match to what you're thinking.

    - User engagement with content (emails and in-app messaging)
    - Participation in 1:many trainings
    - Increased product adoption
    - Increased number of qualified leads for upsell and cross-sell - for BDRs to work and close with AEs
    - Increased NRR
    - Increased NPS responses with usable feedback 
  • Ed Powers
    Ed Powers Member Posts: 173 Expert
    Photogenic 5 Insightfuls First Anniversary 5 Likes
    I recommend you use metrics that track the behaviors of your customers, which is what you're trying to influence regardless of the tiering and tactics you use. Unfortunately, most in Customer Success use highly aggregated financial outcomes along with well-intended, but subjective and irrelevant KPIs. While it's helpful to get ideas from others, copying is problematic. 

    I suggest you follow a process to determine the metrics that work for your business: 

    1. Interview customers to learn why some leave and why others stay and buy more. 
    2. Quantify those reasons by broadly collecting data and using Pareto analysis to focus your efforts on improvement. 
    3. Look upstream in your processes for variables that might predict those behaviors, collecting any new data you aren't already collecting. 
    4. Use factor analysis and regression to narrow your list to those critical few KPIs that predict behaviors in your particular case. 
    5. Track those KPIs and launch process improvement projects to improve your results.

    Happy to discuss this approach along with the appropriate statistical tools (survival charts, control charts, Pareto, factor analysis, regression, AI/ML) any time. 
    Shaun Porcar
  • Brian O'Keeffe
    Brian O'Keeffe Member Posts: 181 Expert
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    Do you have metrics applied to other sectors? NPS, renewal rate etc...? If so, apply those to your tech touch sector. I would add Advocacy (how many members from that sector VS others) and posts and engagements per week, month etc.... If you use SF and post to track engagements that started with community posts. If done well, watch as Tech Touch equals or exceeds all other sectors. It is pretty amazing to see! 
  • kmulhalljr
    kmulhalljr Member Posts: 40 Navigator
    5 Likes First Comment Name Dropper 2023 Success Network - Supporter
    For RGCs (revenue generating orgs) we've defined 4 customer categories: tech touch (<10mil budgets), major markets (orgs with 10+ branches), strategic (80+mil budgets) and strategic-cloud. We use the following metrics for each...

    tech touch: NPS, CSAT and or CES (depending on engagement flow) as well as CAC (we focus exclusively on measuring time x employee wage / revenue of goods sold)

    major markets: NPS, LTV and TCPE (time cost per expansion)

    strategic: NPS, CSAT and or CES, LTV and Health Score (these accounts aren't fully managed by our Customer Success team so there may be additional metrics)

    strategic-cloud: NPS, MRR, ARR

    For NRGCs (non-revenue generating customers) we use NPS and what we call 'Brand Ambassador Score' (we use things like referrals and track social media mentions...then pull the analytics from them, eg. # number of impressions on a post). Our marketing team is very fond of this and tracks this last bit of info and reports back the value they estimate based on things like platform ad rates.