What is Pricing Transformation?
Pricing transformation is a comprehensive revamp of how a business approaches its pricing strategy (specifically, a B2B company). It entails the adoption and integration of digital solutions to refine and enhance how a company sets and adjusts prices.
Through pricing transformation, businesses employ digital tools to bring about greater precision and flexibility when making pricing decisions. This enables them to charge appropriate prices for each transaction, considering various influencing factors like market demands, trends, and their current and historical competitive environments.
The digital aspect of pricing transformation is what allows companies to analyze extensive data sets, improve their decision-making, streamline the pricing process through automation, and tailor pricing strategies to cater to different customer segments and varying market conditions.
Put simply, pricing transformation represents a shift from traditional, more rigid pricing methods to a modern, data-driven, and technologically advanced approach. It’s a subset of digital transformation, which comprises the incorporation of digital technology into all aspects of a business and its operations.
Synonyme
- Digital pricing transformation
- Digital pricing strategy
- Pricing automation
Why Digital Pricing Transformation?
When setting product prices, four factors come into play:
- Customers’ perceived value of your product
- Their willingness to pay for it
- Your ability to either match market rates or differentiate
- How much you can afford to sell it for while keeping the company afloat
The primary goal of pricing transformation is to establish pricing that genuinely reflects customers’ value perception and price sensitivity, remains competitive in the market, and maximizes profit potential (with the help of software).
It’s closely related to price optimization, which requires companies to apply advanced analytics and predictive modelling techniques to determine the optimal price point for each product and service in their catalog.
According to McKinsey research, well-executed, digitally-enabled pricing transformation within a company can help them improve their profit margins by 2% to 7% in just 3-6 months time.
So, in short, adopting a software-driven pricing strategy makes you more agile, competitive, and profitable in the long run and the short run.
Elements of Pricing Transformation
Pricing Models
Your pricing model is the framework or overarching strategy your company uses to determine the prices of its products or services. It involves various methodologies and considerations to set prices that align with the company’s business objectives, market dynamics, and customer expectations.
The most common pricing models include:
- Cost-based pricing — Setting prices based on the cost of production or acquisition of the product or service, plus a markup for profit
- Usage-based pricing — Customers pay a fixed price per unit of usage or per user in a subscription, and their billable amount depends on how many uses they had in a billing cycle
- Value-based pricing — Determining a sale price from the perceived value of the product or service from the customer’s perspective
- Competition-based pricing — Setting a price in relation to competitors’ prices (higher, lower, or the same)
- Dynamic pricing — Using algorithms and market data to adjust prices in real-time based on demand, competition, and other external factors
- Subscription-based pricing — Customers pay a recurring price at regular intervals for access to a product or service
- Tiered pricing — Offering products or services at different price points based on various features or levels of service, allowing customers to choose based on their needs and budget
Pricing models can vary greatly depending on the industry, the type of product or service, competition, and the target market.
Most companies use a combination of multiple pricing models. For instance, SaaS companies use a combination of nearly every pricing model on this bulleted list (hence why pricing automation software is so crucial for this process).
Pricing Processes
Pricing processes are the steps you take to determine and set prices. This always includes market research, competitor analysis, data collection and analysis, and collaboration with various departments (e.g., marketing, sales).
It also involves determining the optimal pricing model or combination of models to use for your company’s products or services (normally through a series of tests). The decisions and adjustments you make to pricing processes significantly impact your bottom line.
Pricing Tools
In digital pricing transformation, you enhance your pricing models and processes with data analytics, machine learning, and AI to more accurately forecast demand, optimize pricing, and personalize pricing strategies for different customer segments. The whole premise of digital pricing transformation is to improve operations and pricing efficiency with the help of technology.
Value of Software in Pricing Transformation
Software is what makes “pricing transformation” a word in the first place. It’s key to a company’s digital transformation strategy; without it, pricing transformation is impossible.
That said, it isn’t just the tools that matter, but how you use them. Software is only as good as the processes within your organization (plus, the right mindsets and capabilities of your staff).
But having said that, accurate data and efficient processes can only achieve so much. Data-driven pricing strategies are a must in today’s market, which is why companies turn to AI-powered software.
Here’s a look at the most essential tools in pricing transformation:
Configure, Price Quote (CPQ)
Configure, price, quote (CPQ) is a tool used in the quote-to-cash process. It helps companies:
- Generate quotes, proposals, contracts, and other sales documents
- Guide sales reps through the selection and customization of products/services
- Automate pricing calculations, approvals, and discounts
- Track customer orders, renewals, and cancellations
Today’s CPQ software does a lot more than its core functions, though. Depending on the exact solution you use, CPQ can support dynamic/real-time pricing, automated profit optimization, and predictive pricing for complex products.
Business Intelligence (BI)
BI tools fall into a few different categories.
- Reporting and visualization tools provide data dashboards that make sales, pricing, market, and customer data visually engaging and easier to analyze.
- Data analytics tools process vast amounts of data quickly, helping you spot trends, identify correlations, and uncover patterns that would otherwise go unnoticed.
- Predictive analytics tools take it a step further by using historical data to forecast future demand and pricing scenarios.
- Machine learning and AI tools create self-teaching data models that adjust pricing strategies based on real-time market trends.
Pricing Software
Sometimes, price optimization is built into CPQ. But you can also use pricing analytics software as a standalone tool. This type of software can help you:
- Analyze customer buying patterns and preferences
- Evaluate pricing strategies and promotions
- Determine the optimal price range for a product or service
- Monitor market trends and competitor pricing in real-time
You can also use it to create financial models and run simulations at different product price points. So, you can use it to test different product prices before bringing them to market.
How AI is Transforming Pricing Strategies
Dynamische Preisgestaltung
Dynamic pricing enables real-time price changes based on factors like demand, supply, market conditions, and consumer behavior. AI uses predictive analytics to assess how different factors influence demand and prices, enabling companies to predict market reactions and proactively adjust prices.
A good example of dynamic pricing is the travel and hospitality industry. If you’ve ever looked at plane tickets or hotel rooms, you’ve probably noticed prices can change drastically from one day to the next. That’s because these industries use AI-powered dynamic pricing to adjust prices based on demand, weather, holidays, natural phenomena, and countless other factors.
Amazon is another solid example. The ecommerce giant changes prices every 10 minutes (by up to 20%). This equates to about 2.5 million times per day across the platform.
Customized Pricing
AI also plays a crucial role in tailoring prices for different customers based on purchase/usage history, overall engagement with a product, or loyalty. Personalized pricing is especially useful for subscription-based businesses like SaaS companies, where it’s easy to track user engagement through clickstream data.
The same logic applies in industries like B2B manufacturing, where pricing software might recognize the overall profitability of a long-term client versus a one-time customer or smaller-volume orders, then adjust prices to ensure profitability and long-term customer retention.
Quoting for Complex Products and Services
In the manufacturing and construction industries, it’s incredibly difficult to understand all the factors that could influence a company’s ability to turn a profit on a particular customer or project.
The same goes for a SaaS company servicing enterprise clients, who normally need custom IT infrastructure, integrations, and functionalities the standard product doesn’t carry.
Today, AI has the ability to calculate the estimated production or development costs based on inputs. From there, it can return a quote that maximizes the company’s profit margin and helps it understand its resource allocation for the project.
Trust and Transparency with Customers
Across the board, one of the biggest challenges with AI is getting customers to trust that the algorithms are working in their best interest.
Managing customer perception and ensuring transparency are essential to maintain trust, especially in dynamic pricing scenarios. Ethical and regulatory considerations are also crucial, as companies need to avoid discriminatory or unfair pricing practices.
FAQs
Pricing modeling is the methods you use to figure out the ideal price for your products and services. It considers factors like production costs, value perception, and product/service type when helping you make pricing decisions.
At the price stage of the CPQ process, the software calculates the final price for a product or service based on the selected options, plus any discounts, promotions, and customization factors. It also ensures that pricing is in line with company policies and optimal profit margins.
Andrew ist ein professioneller Texter, der sich auf die Erstellung von Inhalten für Business-to-Business-Software (B2B) spezialisiert hat. Er recherchiert und verfasst Artikel, die seinen Lesern wertvolle Einblicke und Informationen bieten.