Are you asking your team the right questions? Are they questions that are driven by business impact? As this Forbes article rightly suggests – you cannot answer questions with the data you did not collect!
We live in a world today where data is everywhere, and there are more sources to collect them from, than ever before. Leveraging the right sources will effectively help with better business decisions. A PWC survey indicates that data-driven organizations were three times as likely to achieve major improvements in their decision-making capabilities. The importance of cohesive, granular data, in the development of pricing strategies can never be over-emphasized, according to this whitepaper. It says that if a predictive pricing strategy is your “weapon for managing profitability,” the “ammunition” to power that weapon is solid data.
As a SaaS company, you typically need the following types of data:
- Demographic data to know who you are selling to
- Data on what feature/s are actually driving engagement
- Data to track conversion rates, and to understand what your average customer acquisition cost is
- Data from analyzed support/refund calls, and to identify if you are losing customers and prospects in the sales funnel
In my book, Price To Scale, Pricing Guru and former Director, Product Marketing at Gainsight, Johnny Cheng simplifies these considerations and clearly illustrates the 3 essential data sources to tap into for analysis and research, during your pricing journey. He says,
“ The only three things I do are:
- Talk to customers or prospects.
- Look at historical data.
- Look at competitive data.
I’ve seen a lot of McKinsey-like studies where they do a lot more, but at the end of the day, as a pricing professional, you just have to be really flexible and organic with your pricing. You can’t get stuck at a figure.
You have to be able to look into analysis and optimize. A lot of pricing professionals don’t like the optimization part. It’s all about just tuning, tuning, and tuning. I’m a strong believer in optimization and changing my price curves, especially for newly launched products once a month. It then becomes once a quarter, then maybe once a year, and finally maybe never. But you have to keep tweaking.”
The important consideration is to curate the data sets that will determine, and throw light on value propositions, how the competition is doing, and most importantly on what the customer wants. Speaking to customers and analysts provides on-ground insights. Knowing the pulse of the buyer can help you be on track, or better still - even ahead of the curve, by providing value at a price point that is amenable to the customer.
Historical data is a window into trends, preferences and on some occasions a reminder of what not to do. It helps with evolving and transforming organically by optimizing best practices.
With competitive data, you are armed with the necessary information, research and insights on the competitors’ landscape. This helps you understand how similar organizations are providing value, how they are approaching pricing, and how their customer acquisition and retention strategies are formulated. These insights can better enable you to package, position and price your offering well enough to edge them out.
In line with these considerations, your ability to adapt and respond to market fluctuations and willingness to adopt emerging technology and research tools, all while keeping the customer at the core of your business model, will help you define, and refine your pricing strategy as you go.