Usage-based pricing: How to lay the foundations for success

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This article was provided by Griffin Perry, CEO and co-founder of m3ter.

Use-based pricing is rapidly becoming popular among software companies. Why it’s easy to see: Software-as-a-service (SaaS) businesses with usage-based pricing have experienced 29.9% year-over-year revenue growth compared to those who don’t, 21.7%. What’s more, OpenView Partners estimates that seven of the recent nine software IPOs have the best net revenue retention with operated use-based pricing.

But implementation-based pricing is surprisingly difficult to implement, and the biggest hurdle is the quality of the company’s consumption data. After all, intelligent pricing can only work if it is built on good data.

Here’s how companies can find the right foundation for a successful, intelligent pricing strategy.

Select the appropriate usage data to measure

Avoid limiting your attention. The temptation is only to measure the consumption vectors that drive your current price, but you should spread the net and measure all the consumption vectors that you have To be able to Against the potential cost, and it drives all variable costs. Ultimately, price improvements depend on the behavior observed, so it is better to measure first and then decide what is important, not the other way around.

To illustrate, imagine running a backend-a-service for video games (which, in a previous life, I did). You are currently charging based on API calls, but it looks like you’re probably leaving money on the table. You decide to start differentiating between different API calls so you can break usage by type.

You also consider measuring other use vectors that may be a good basis for values, such as the number of active players or items in your virtual goods catalog, and you know the drive costs, such as total storage and data aggregation. After observing the results for three months, you begin to see patterns in the data that indicate that price changes can lead to significant bottom-line improvements.

Make sure your usage data is clean

Do you believe that the data you use is clean, complete and accurate? Or will it push? For many businesses, there is room for improvement. In fact, a recent IBM report found that 83% of companies suffer from data inaccuracies.

There is an old saying, “Inside the trash, take out the trash.” If your usage is riddled with data duplication, errors and missing information, there is no way you can expect to run a sophisticated usage-based pricing model. Check that your quality assurance processes are adequate, and if you have any doubts, consider adding a dedicated data QA engineer to your team who can help design and implement a robust test regime.

Be able to apply values ​​flexibly

Consumption-based pricing models can quickly become complex. You almost always want to offer a volume discount mechanism to reward more usage, but there are different options. Volume-based, tiered and CD prices are the most common. You might also consider a mechanic who trades discounted rates for a minimum cost level commitment, as this reduces the perceived risk from the customer and helps bring cash forward for you.

On top of that, you might also consider hybrid models that introduce feature-based layers or usage-based components in per-seat models. Consumption Allowance is a good example: when a customer reaches their allowance, they are either throttleed or pay a usage-based extra.

You need to combine pricing, usage data, and account details to store these complex pricing settings, deal with custom terms for specific accounts, and then calculate the cost amount so that this can be passed through your invoicing system.

You also need flexibility to develop your values. As mentioned above, the ideal choice for your business may not be immediately obvious – you may be surprised by customer behaviors that you haven’t yet discovered, and if you can’t adapt to their emerging potential, it will be a missed opportunity.

Remember that there are multiple users of usage and cost data

Use usage and cost data to run billing on a monthly cycle. But in other usage cases other parts of the stack such as Sales CRM, Customer Success Platform and SaaS Platform need to have more frequent, usage and cost data available.

You need to decide whether there should be a single source of truth that centralizes usage and spends data in one place, or design a data governance strategy that can fit data in different places and evaluate concerns about duplication, inaccuracies and manual data management. Does. For human error.

The canonical mapping attached to this vs. Point-to-point mapping when designing your strategy for data sharing between different systems. Canonical mapping involves a significant commitment of time and resources, and implementation is risky. But if successfully deployed, standardization allows different systems to easily communicate with each other – each application can translate its data into a single, common model that understands all other applications as well.

Don’t forget your margins

Optimizing usage-based pricing is about understanding the relationship between basic consumption, cost (how use is converted into revenue) and margin (total profitability of that consumption).

To understand the margin by the customer, you need to record the cost and, if it is shared among the customers, allocate it. An example is Cloud Cost – you may have a large cloud service bill that is driven by resources that support multiple customers (such as computer instances, databases, and storage). If you can allocate this to individual customers based on their usage, you can identify low-margin customers and take steps to improve overall profitability (usually with a change in prices).

Be customer obsessed

The good news is that with consumer-based pricing, your customers won’t have to worry about shelfware, trash, or failing to get the full value out of their investment. They can only measure their consumption and spend up or down depending on their needs.

Also, if you choose the right pricing metrics that align with the customer’s target results, their value will only increase if they succeed themselves. It is excellent for customer relationship and builds a cycle of lasting loyalty.

But remember that customers can be right with consumption-based prices in principle, if they underestimate their consumption or have an unexpected spike, they may get a nasty surprise in their monthly bill – a dangerous moment that marked the end of your relationship. Can. You need to be able to actively manage these situations by responding to usage indicators.

Also remember that in a consumption-based world, pricing is a part of the product experience. Consumers want to know how much they are spending and how their consumption costs. Make sure you have that data always available as close to real-time as possible, so they can easily check their running total at any time and see their next bill forecast.

Making use-based values ​​successful

Ultimately, software companies turn to use-based pricing to get their true value, particularly driven by trends in automation and product-led growth.

The model works because it enables value-based pricing that is easily measured with customer success – but it is not easy to implement, it needs to be well-designed, and cannot get off the ground without reliable, trustworthy data base. .

Choosing to invest meaningfully in your data infrastructure is a good place to start, which gives you the foundation, while both you and your customers can count on intelligent pricing and navigating the complexities of billing.

Griffin is the CEO and co-founder of Perry m3ter,


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