How to choose the right pricing model with Stormly
Product managers are responsible for developing and managing pricing models, which is a very important part of the product development life cycle.
For this reason, it’s critical that you choose the right pricing model in order to maximize revenue and satisfy customers’ needs.
There are many different pricing models and choosing the right one comes down to matching the usage pattern, perceived value of your product, and the way users pay for your product.
It can be difficult to determine which model will work best for your specific organization, but luckily, with Stormy’s Power Usage Insight and our few tips, it will be super easy for you to make that decision.
For starters, it would be good to consider what type of product you have and how often it gets used by customers. For example, is your subscription service, or an app more valuable than something like gym membership? Can you provide exactly the same or better value for less? The answers will help guide your decision when choosing between different types of pricing.
But most importantly, we need to figure out the usage pattern of your product. The L30 and metrics are Facebook’s way of measuring how active your users were over the last 30 days.
We used that metric while creating this Insight, so by using L30, we will be able to know what percentage of users were active all of those 30 days, or less. With Stormly, you can see that right away!
|Fig 1. Usage pattern with mostly one-off usage — relatively little power users
|Fig 2. Usage pattern with lots of repeat usage — many power users
Above we see two different power usage patterns. On the left, we see relatively few power users, as not many of them come back to use the product more than once over the last 30 days.
On the right, we see an interesting pattern, where we have relatively a lot of users that used the product for 20 or more days over the last 30 days. That’s great news! That this product has a decent amount of power users.
It’s important to note that not all users will have used your product for an entire 30 days period. That’s because some people might have only downloaded your app in those last few days. So there’s no way they could’ve had enough time to use the app or website as much as everyone else already has done.
Since many business apps and products are most active during the workweek, it makes sense to measure usage only for weekdays. Luckily, we’ve added a possibility to pick that option from our Power Users insight, to make the results as relevant as possible.
It’s also good to keep in mind that we do recommend doing power user analysis when working with SaaS, social apps, and apps with frequent usage. However,iIf you have an app that’s only used once every few months, then running this analysis would not really be helpful.
Now with those results, let’s look at three most common pricing models and see which one fits best based on how your chart looks like.
Per usage, or one-time payment
The less power users you have, and thus more one time usage, the more it makes sense to charge per usage. If people use your service only once or twice in total, it’s very unlikely that they will convert to a subscription. Overall revenue in this case could be higher if you stick to a usage based pricing model. This corresponds with the left power user chart shown at the beginning.
Paying a recurring subscription fee per user or a seat
On the other hand, if you have a high percentage of power users, it’s most likely that they will want to have a subscription-based price. Charging them for usage could mean that they’ll not use it as much as they could, resulting in lower overall revenue. Another danger of misalignment between the usage pattern and pricing model is that they could look for cheaper alternatives, which do offer a subscription. This corresponds with the power user chart on the right side, shown at the beginning.
A combination of the two, so a fixed subscription component
If your power user chart looks like it has most usage on the left and right, but much less in the middle, your best choice might be a combination of a user based pricing model, with a per-usage component. An example could be an email marketing tool, where you pay a monthly fee plus a part that depends on the volume of emails sent. With this pricing model, you can serve companies of different sizes and different usage patterns.
If you have a free product, or depend mostly on advertisements, then you could add a one-off payment component to make sure you become less dependent on ads.
If your power-usage pattern doesn’t match your pricing model, you may want to rethink your product strategy. Once you decide to relaunch an improved product that triggers a different usage pattern, and enough data is collected, you should run a power users analysis again. This way, you can keep testing suggested pricing models until you get to the usage pattern you’re after.
Or you could simply change the pricing model and make it fit your usage pattern, which is usually easier to implement, but may not get you the revenue potential that you could be going for.
The Power Users insight from Stormly is an easy way to get started with analyzing the power usage pattern for your own product. With just a few clicks, you’ll be able to see your chart and make a decision that could skyrocket your revenue and amount of power users! Isn’t that amazing?