How can you use value perception to shift clients’ price elasticity?
When we discuss pricing with our portfolio we typically cover three key topics: the annual price increases you put on today’s products; how you manage discounting; and how you think about evolving the pricing structure going forwards.
Crucially, all conversations should focus on the value received by the customer rather than the price paid.
Through all of these conversations, we’re trying to put a monetary value on the outcome achieved by the customer by using your product or service, rather than simply the inputs by which they purchase the product. Focusing the conversation with your customer on the business case they achieve – whether that’s through revenue enhancement or cost savings achieved, alongside any product enhancements made – is typically the best way to keep the conversation away from a cost-plus type discussion.
The second big area we usually discuss is the product range offered and how that is presented to the customer. You have a lot of freedom for how to position the way your customer understands your offering, so careful thought should be given both to how to display options, such as ‘a good, better, best’ approach; as well as if and how to present prices.
It can often be more lucrative to optimise customer lifetime value than to acquire new customers. How does data play a role in this?
Successful selling strategies are about both acquiring new customers and looking after the ones you have, so managing each customer based on their expected lifetime value is really important.
Fundamentally, maximising customer lifetime value is about trying to encourage customers to either buy more products and services, or expanding the amount of time they spend as a customer with you.
Data is at the heart of maximising customer lifetime value, and quantifying the opportunity is a crucial first step.
The start point is to understand the composition of your customer base today in a data-driven way. Think about it as creating a mini-P&L for an individual customer over a 5–10 year time horizon to understand the net present value of that customer.
Once you understand customer lifetime value, it’s then even more important that you use this data to drive business decision making. For example, at the point of sale, are you confident you are acquiring customers who are going to stay with you for many years? Are there opportunities across the year to (re)engage with your customers ahead of a contract renewal period? Many businesses use the combination of an Account Manager and a Customer Success function to really ensure these opportunities are being maximised.
Customer segmentation has also long been considered key to effective selling. How is technology supporting sales teams in doing this effectively?
Segmentation is key to understanding variations in customer performance, initially focusing on differences by geography, customer type and product. There are now a number of analytical techniques that can be used to build relatively complex model-driven approaches which can be very powerful. We’ve recently helped a number of companies in the portfolio on this journey, but in the first instance there’s a lot that can be done by focusing on understanding simple differences in behaviour by key types of customer and product.
As with customer value, make sure the learnings are embedded in all your pricing, sales and marketing processes. Start simple, think about how you can tailor existing marketing communications and sales activity to your priority segments. However, as complexity grows, technology can really help you on your journey: for example by making sure new leads are categorised in the CRM at point of qualification and assigned to the right sales team member; or through the use of web-based pricing and discounting tools to provide greater control in your pricing practices.
Ada Pham, Assistant Director, Inflexion
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