In our scenario the fencing metric follows seasonal cycles which aren't particularly spikey. Rather, if our features are delivering on the value prop, the metric should grow over time. We do have other feature-specific usage metrics that would be much more spikey but we're less concerned about making those predictable - won't dive in unless people want to! Would like to hear more, Akshay. High spikes might increase the need for predictability but also make it harder to "smooth out" or require more precision on measurement cadence. But I'm interested to see if folks are doing anything novel to address the lack of predictability of UBP in cases where that's a concern for their customer base.

Almost a mini-pricing project! Not sure I can do justice to all that info here. I'll DM at some point when I free up. 😀

Casual stroll vlogs - love it. Do we need to be on a treadmill to co-analyze?

Just curious, why only prospects? Don't feel existing customers have insights on how value scales and which metrics might better capture that? They're WTP answers might be anchored by what they pay today but still usually helpful to contrast prospect WTP to existing customer responses and to consider where divergence comes from.

@Alexa Gjonca All comes down to how the questions are asked, sequenced and the extent to which you can derive directional sense from a qualitative discussion (e.g., asking preference on a scale of 1 to 5 where possible). So like you said, once you've drafted survey, easier to comment on that.

When you interview your next set of customers, don't "share pricing with them", ask them directly how they think the course should be priced (price model) and possibly even what their WTP is (price level). I agree with @Michael Narkiewicz though, it isn't clear how your 8 courses continue to deliver value over time. Hard to say without more details but you should consider what you need to continue to create and provide to this audience to make the platform more sticky. What makes them keep coming back? And for all founders, we need to believe in what we're building but a healthy dose of skepticism in understanding our customers' value perception goes a long way. Your software is much better than the competition. 100% true. But the office managers typically using it are from a past generation, not familiar with modern UI and not able to properly benefit from the improvements. Value perception = zero. Just an example.

Ah got it! That's really cool. So wins in this case would be what these sites are reporting or choosing based on these tests? Either way, a lot of value in understanding "what works" for the success stories. I am personally finding there are critical scale considerations for those of us still making the climb.

@Ashish Gupta I haven't actually watched them but look in the classroom section of PricingSaaS and you'll find Ulrik's primers on pricing fundamentals. Bound to be some basics on how you design tiers there. Depending on what stage you're in, this may not be such a small deep dive if you want to do it right. But at its core, you want to identify clear segments within your customer base (could be based on a lot of things but most likely: how they engage with your products / features). So, segment A has a clear set of ways in which they use features differently than segment B. Obviously the features need not be mutually exclusive; segment B could need most of the same features but also need an additional set that segment A does not. Accordingly you should find how the willingness to pay differs across these segments based on the value they derive from the different sets of features they use and price accordingly. I'm using SaaS lingo here but applies to other industries / delivery models as well. The key is to really understand how these segments differ across dimensions that are most meaningful and not default to small, medium, large type, conventional segmentation from the get go. More conventional segments may end up being the proxy or the nomenclature you use but the magic happens in fully exploring your customer's use cases, business behaviors, collaboration criteria and a whole host of possible dimensions that affect how they engage with your product / service. It can sound intimidating but it doesn't have to be. Much of this should be the diligence any business is engaged in when refining their own business (let alone monetization) models. That scratches the surface but so much more to consider once you really get under the hood. And more knowledgeable folks will have different / better takes than this, I'm sure. Good luck!