Dynamic pricing, demand-related pricing, hyper-personalized pricing: leading firms such as Amazon and Uber show us how successful pricing strategies can be implemented using digital tools and services. Digital pricing techniques have the potential to generate sustainable profits for a wide range of businesses.
Digitalization isn’t just about technology; it’s fundamentally about how businesses make money, and therefore it has a significant impact on pricing strategies. Digitalization affects pricing in two ways:
- New digital solutions and business models call for new pricing models, and
- Digital tools offer companies ways to make faster and more differentiated pricing decisions within their existing business models.
New digital pricing models for new digital products
Using traditional pricing models is not an effective method for monetizing innovative solutions based on digital technology. This applies to numerous IoT devices (objects and machines connected via the “Internet of Things”). These networked objects have built-in software solutions that use machine data and usage information to boost productivity and predict when maintenance will be needed. This leads to less downtime and lower costs for customers. For its drilling machines, GE used to set a sale price per machine; however, this didn’t fully tap the “value in use” of its new digital solutions. Instead, GE implemented a usage-based model, charging per day of drilling, and incorporated additional services into its offer. As a result, the manufacturer now profits from digitalization.
Another example is Ecolab, which offers a real-time data-driven water management process rather than simply selling water chemicals. Using gathered data and benchmarks, Ecolab identifies ways for water treatment providers to operate their plants more effectively and efficiently over the long term. A pricing model based on volume of water chemicals sold doesn’t reflect the added value provided to the customer. A better approach is to install the necessary hardware more economically and use a subscription pricing model to generate recurring revenue streams. Such models are highly customer-centric, putting customer relationships at the core of business strategy.
How relevant are existing pricing approaches for today’s companies and their new digital solutions?
At a recent industry conference, participants were asked if they were currently working on new digital solutions and pricing models. The good news is that most companies are. Overall, 72 percent said they were in the process of developing new digital solutions, and 16 percent said their solutions had already been launched.
However, these firms must make sure their monetizing strategies are tailored to their specific offerings and the value they provide.
Supporting existing pricing processes through digitalization
Even companies without innovative digital products can benefit considerably from digital pricing. With the help of digital tools, existing processes can be made much more efficient. For example, Excel spreadsheets are still used in countless pricing departments. While Excel is a good starting point, it has a number of weaknesses that hinder the use of digital pricing, such as the need to enter and transfer data manually, difficulties in sharing insights with colleagues, compatibility issues due to multiple versions of the software, the inability to conduct real-time reporting and price management, and the fact that there is no “single source of truth” when it comes to data.
More evolved software solutions for digital pricing have many benefits. They support price optimization based on a large number of data sets, generate better and more granular price differentiation, and increase process efficiency, leading to fewer mistakes. Plenty of software providers offer this kind of solution; however, companies should bear in mind that the software they use should reflect their pricing requirements and be able to manage interfaces with existing systems, such as ERP or CRM systems. Selecting modular solutions for specific needs or customized solutions has often proven to be a smarter approach than opting for huge, all-inclusive pricing machines. Furthermore, there are many easy-to-use, standalone solutions for very specific pricing tasks.
Apart from these tools, there are also more extensive solutions based on big data analytics, artificial intelligence (AI), and machine learning (ML). Implementing such technologies can be highly beneficial but require a word of caution: they are not suitable for every pricing decision. Furthermore, they rely heavily on broad and reliable data input and are still often “black-box” models with little transparency regarding accuracy of results. At times, they may also conflict with the company’s pricing strategy as pricing is completely automated. Having in-depth knowledge and applying these technologies carefully are key to success.
Technology and pricing software will never replace sound pricing skills and pricing fundamentals, such as having in place clear pricing structures, well-functioning systems for price steering and control, effective price-increase processes, and a set of common pricing principles. Solid data management and governance are needed, but discipline, harmonization, and standardization are also important aspects of pricing. A building material company, for example, streamlined 99 SAP pricing procedures into a single global one, while still reflecting the specifics of the business. This was an enormous effort, but a necessary step in order to be ready to tackle digitalization.
How proficient do companies think they are at digital pricing?
They rate the importance of digital pricing much higher than their actual digital pricing capabilities. More than 50 percent of the participants at the industry conference said that digital pricing was highly important in their day-to-day business. In contrast, more than 70 percent ranked their company’s digital pricing capabilities as not important.
However, there are pragmatic solutions to help these firms transform their data into information and knowledge, and consequently into better and faster pricing decisions.