Pricing as a Growth Strategy in a Downturn

Guest Article by John Griffin, Co-founder and CRO at M3ter, a metering and pricing engine for SaaS companies.

One of the biggest headwinds faced by SaaS businesses in 2022 is the slowdown of ‘easy’ customer acquisition that had been driven by Covid-19.    

The pandemic only accelerated the long-term trend towards the cloud and SaaS. Specific challenges such as business resilience and remote working acted as a catalyst for more general reappraisal of value and flexibility, and an associated enthusiasm for digital transformation. The result was that businesses took on a whole host of new tools and platforms, leading to a surge of new customers for SaaS businesses, and an industry boom.   

But now, the hangover. After a period of enthusiasm, businesses are taking stock and streamlining their tech stack. This is further encouraged by an uncertain economic outlook, with a risk of recession, declining stock market valuations (in some sectors), and uncertainties around fundraising all contributing to the international belt-tightening.   

In this environment, SaaS businesses are turning their attention to new strategies to sustain growth. One of these is pricing and, in particular, deploying usage-based pricing (UBP) combined with Product-led Growth (PLG). Using these strategies, the barriers to customer acquisition are lowered because initial commitments are limited and users can test out products more easily.

Therefore, revenue expansion requires fewer sales effort and logo churn is lower because costs are directly associated with usage, which both implies value and provides an easy release valve (simply use less rather than give up the service entirely).   

But whether this strategy is right for your company will depend on the data.   

Start with the data

Businesses can analyse their usage and billing data to work out where and how customers derive value from their product – such as how and when they use it, and the circumstances in which they stop using it. This kind of insight enables a company to focus their product development on what matters most, and design new pricing strategies that better align usage and value.   

But where to look first? With so many streams of data, and product and finance teams finding themselves increasingly stretched, sifting through usage and billing data can be a daunting and time-consuming undertaking.  

Be organised and keep a good record

In 2020, the average person generated 1.7 megabytes of data per second online, adding up to a total of 2.5 million terabytes created each day. Companies are no different and now find themselves dealing with huge quantities of data, some of which is completely unstructured.  

Good data infrastructure should be the starting point for any business wishing to understand and harness the power of their information streams. Since smart product development and flexible pricing rely on data, getting this right is crucial.  

Whatever your situation, it makes sense to start with an audit, mapping out your data pipelines at the enterprise level. The aim is to build a clear understanding of where your data is coming from, where it is going, and why. Is it being stored in one place, or are you starting to see silos pop up across the business where data is duplicated and potentially divergent?  

With a robust map of data flows, you can better understand where there are inefficiencies in how you collect and store data. You’ll also know just what a goldmine of information you’re sitting on, and that probably isn’t yet being harnessed to its full potential. 

Make sure your data is clean

Once you have a reliable understanding of the way data is flowing through your organisation, you need to make sure it’s consistent, accurate and useful.  

Unsurprisingly, given the sheer quantity of incoming streams, data hygiene is a common issue for modern tech businesses. According to a recent IBM report, 83% of companies suffer from serious data inconsistencies. The impact of this can be significant and cost businesses anywhere between $9.7 million and $14.2 million each year.  

 Data inaccuracy is most often caused by disparate data streams flowing into different pockets of the business, without any central organisation, labelling or monitoring. To avoid this, consider implementing a centralised data repository to collect, process, and store raw data – creating a single source of truth that can support various applications.  

Invest time in developing data governance policies to make the management and monitoring of your data more streamlined. These policies should clearly define ownership of data streams and outline data sharing practices throughout the business, to avoid siloing between departments.  

Take aim at the right pricing goal

Once you have your data in order, it’s time to reflect on your business goals. To do this, ask yourself a few key questions. Firstly, who is buying your product, and (if different) who is using it? Familiarise yourself with your key personas and understand their behaviours, use cases, buying power, and priorities.  

Next, think about your product: which feature is driving the most engagement, and how much does this cost to run? Do different constituencies use different features? The goal here is to get a good sense of where the value lies, so you can create a pricing strategy that aligns with this. 

One of the shortcomings of traditional SaaS pricing, which involves recurring fees based on feature access or the number of seats, is that it takes no account of actual usage. This means that customers can pay for something they don’t use, or conversely, pay not much for something they use heavily. The opportunity of usage-based pricing is in aligning value and usage more clearly. But in terms of what type of usage you attach pricing to, there is no one-size-fits-all type of approach – it depends on your business and what the data tells you.   

Using data to drive pricing, to drive growth

Pricing will be core to SaaS growth in the coming years, 45% of SaaS companies say they have already implemented some form of complex pricing strategy based on their data. Snowflake, for example, has attributed its continued success to intelligent pricing, as it helps it appeal to CIOs and tech leaders looking to optimise their newly-squeezed spend.  

Aligning pricing with usage habits is the ideal long-term strategy to increase efficiency and scale alongside your customers using their own requirements, and the proper use of data is absolutely core to making this work.