Your pricing needs to be optimized to avoid leaving money on the table. And to optimize pricing, your sales process needs to be digital and data-driven.
The pandemic accelerated a shift to digital buying and selling—and it’s change that is here to stay: In a recent Forrester study, 38% of survey respondents believe the pandemic permanently altered buyer requirements.
High-tech and software organizations feel this change as much as any sector. As XaaS and perpetual licensing models mature, buyers are becoming more selective. Increasingly, they don’t want a product their organization can grow into—they want to buy a la carte, adding the features they want and when they want them.
This brings a new level of complexity to pricing strategy and configuration. To drive growth and value in today’s market, software and high-tech organizations need to understand how buyers are buying at the moment, be able to test pricing hypotheses for particular customer segments, and adjust strategies rapidly and continuously.
That requires good data. The problem? Many organizations can’t use data to optimize pricing due to outdated technology and processes. This leaves not only money on the table but also limits the ability to take advantage of emerging revenue intelligence capabilities.
Mature sales organizations have robust capabilities that enable them to act both strategically and proactively. They use abundant historical sales and order data, as well as competitive data to segment customers and test, optimize, and manage pricing for each segment. They can also model price elasticity to test pricing hypotheses and fuel new marketing strategies. As a result, they enjoy competitive advantages in margin, upselling/cross-selling, order conversion, customer experience, customer lifetime value, and other key sales metrics. Their maturity also drives a better internal experience, aiding in retention.
Immature sales organizations |
Mature sales organizations |
Make pricing decisions based on “gut feel” |
Make pricing decisions based on data-driven analysis |
Use various systems and tools support the sales process, but there is little to no integration |
Have integrated systems and tools across the sales process |
Enter data multiple times in different systems, increasing the chance of errors and inconsistency |
Gather normalized data from all connected systems and use it for analysis |
Have differing customer engagement strategies across sales teams |
Design experiences intentionally for customers and employees |
Leverage Excel and or CRM for trend and analysis reporting because that’s “what they know” |
Hire for data analytics skillsets and invest in business intelligence tools |
Here’s a closer look at the characteristics of mature sales organizations that enable them to optimize and manage pricing.
It’s not sufficient to develop a pricing strategy, implement it once, and then use inflation as the reason for setting annual price increases or exchange rates as the sole input for price variances in different countries. Mature sales organizations have moved beyond this “analog” pricing approach. They can update pricing in near real time, based on frequent—even quarterly—analysis of historical and competitive data and customer segmentation exercises. They develop pricing hypotheses based on analysis, then test them, collect feedback, learn, and repeat.
While there’s plenty of talk about artificial intelligence and machine learning, today’s mature sales organizations have focused on maximizing the capabilities of CRM, CPQ, and other technologies that support the sales process. They’ve also integrated these systems and tools, enabling greater process automation. Through integration, activity in one system can activate follow-on steps in other systems without manual intervention.
It’s impossible to learn from bad data; therefore, clean, normalized data collected from all key customer touchpoints and used across all sales systems and tools is a critical prerequisite for price optimization and management. Because they’ve fully integrated sales/quote-to-cash technologies, automated data process flows, and a business intelligence repository that feeds normalized data across systems, mature digital sales organizations are able to limit unstructured or duplicate data that can lead to accuracy issues later on, during analysis.
These characteristics also position them to begin looking at high-value technology in the next wave of digital sales—revenue intelligence capabilities that will certainly create competitive advantage. Gartner research estimated that at the end of 2020, only about 1,800 companies employed some sort of machine learning-based pricing optimization management tool—but that more than 10,000 business-to-business companies globally would benefit from such a tool.
Mature digital sales organizations don’t just employ technology—they intentionally design the business processes that influence price optimization and management capabilities, including lead-to-opportunity, opportunity-to-quote, quote-to-order, order-to-cash, and order-to-fulfill/software provisioning processes. They also use human-centered approaches to ensure that new capabilities resonate with and address the needs of users, both customers and employees. Examples of how an organization may intentionally design processes to improve customer experience include:
Changing to a usage-based pricing model that allows for lower points of entry
For employees, this could involve:
A digital sales process isn’t just about the technology. It also requires people who can create strategies for using digital tools within the business and who are able to analyze the data outputs from those tools and use that insight to recommend strategic business decisions. Certainly, there are options for upskilling existing workers, but companies may also need to look outside for experienced talent in areas such as data science and revenue operations.
It will be impossible to move forward without a clear picture of where you currently stand. Analysis should look at current systems and processes that drive price optimization and management, gauge maturity against the maturity spectrum depicted earlier, and identify critical gaps and maturity issues. You can then begin to home in on areas of focus.
A useful technique for prioritizing initiatives is to use a 2x2 matrix, with value and cost/effort as the axes. This helps focus on investments that have few dependencies and can be beneficial in terms of reduced cost or top-line revenue growth.
As noted earlier, mature digital sales organizations get that way by designing processes intentionally, using human-centered design principles and approaches. For example, design should seek to significantly reduce operational support from other teams in order to complete order entry or manual price adjustments in the ERP system. This will require working in new ways. So, think critically about how the identified changes will affect your current organization: Which teams will need new skills? What type of training will that require? Where will you need to acquire skills?
Modern technology will enable pricing optimization, but it will not deliver meaningful change on its own. It will be necessary to integrate technologies so systems can talk to each other and eliminate the need for duplicate manual entry. This process, along with cleansing historical data and normalizing it across systems, will take time. Here, it is useful to pursue incremental change that can begin delivering some benefits sooner than later.
Additionally, don’t underestimate—or under-invest in—the people side of change. Sufficient focus should include both employees and customers. For example, portals can support both customers and the sales team.
One of the hallmarks of digital organizations is their willingness to implement quickly and then build on it over time. They don’t wait to introduce change until everything is “perfect”—they look for ways to expedite new capabilities and then use them to learn and enhance their pricing approaches. These organizations continuously test and re-evaluate pricing hypotheses: Was our hypothesis correct? If not, what does the data say we got wrong? What does the data suggest we could do better? For example, data may show that large customers want automated renewals while smaller customers prefer an online/ecommerce experience, or that managers are receiving too many or too few approval notifications, meaning that thresholds must be raised or lowered. This is insight that the organization should be prepared to act on in a timely manner.
Stay laser-focused on creating a digital sales organization
These price optimization and management principles are particularly applicable to the high-tech and software sector, where they enable RevOps and growth opportunities—at the heart of the industry’s strategy. But they are relevant across industries. The key to building this capability is to maintain focus on becoming a truly digital sales organization. You’ll be able to leverage pricing optimization and management as a key part of your strategy to drive business growth and value.