Setting up a Data-Driven Pricing Strategy: Sales Data to Use

In any data-driven pricing strategy, your pricing data is the guiding compass for making informed pricing decisions – and sales data undoubtedly plays a vital role. By harnessing sales data effectively, businesses can unlock hidden patterns that point to opportunities for boosting profitability and competitiveness in the long term.  

Pricefx, the G2-recognized leader in enterprise pricing software, joined forces with Venkat Vaidyanathan, Managing Partner EMEA, and Stuart Ball, Founding Partner, from SPMG Global, a pricing strategy and consultancy firm with over 20 years’ experience in pricing guidance, to discuss the importance of sales data in pricing and how pricing partners like SPMG Global help companies unlock more targeted, revenue-driving pricing decisions.  

In this article, we’ll explore sales data types that support pricing decision-making, strategies to effectively prepare sales data for pricing software implementation, and the support offered by pricing partners in this process. 

So, let’s dive in.  

Which Sales Data is Important for Pricing?  

Sales data is the catch-all term for what you get from a mix of customer and material master data, transaction data, and the prospect data from CRM systems. Let’s briefly go over each of those subtypes now and their role in data-driven pricing: 

Customer and prospect master data  

Customer master data contains customer identifying information, such as contact details, related or hierarchical information (for instance, a parent company and its subsidiaries), and the attributes that justify different price points.  

Prospect data is an extension of the customer data with a focus on prospects, capturing their company information and segmentation criteria for pricing (such as size, purchasing history, and location). By leveraging this type of CRM data, businesses can target would-be customers with the right pricing strategy for their unique segmentation group. 

Material master data  

Material master data involves a company’s products or materials, including their unique identifiers and position in the product hierarchy. Not only is this data type crucial for invoice approvals and sales order processing, it’s also an essential input for pricing analytics and optimization, helping companies set the right prices at the product line or individual SKU level.  

Transaction data  

Transaction data involves financial transactions between entities, such as orders and invoices, and is needed to analyze historic performance, understand pricing trends, and ultimately, make the right pricing decisions in the future.  

What Your Sales Data Needs to Have to Support Data-Driven Pricing 

Good sales data – whether at the customer, product, or transaction level – has a few key qualities in common that support data-driven pricing, including quality, consistency, granularity, and clarity. 

Your company’s sales data should have the following qualities to ensure a successful implementation of data-driven pricing:  

1. It’s clean and well defined   

Poor quality or inconsistently defined data leads to frustrating errors and delays during implementation, particularly in testing. At worst, uncleaned data may lead to inaccurate conclusions from your pricing engine that erode margins. Putting in adequate time upfront to cleanse and classify your production-level data ensures your solution gets off the ground quickly and produces outcomes your business can trust.  

2. Its customer segmentation variables are identified and consistent  

Building and refining customer segmentation attributes, and more important still, ensuring they are consistently captured across key datasets, are critical to any pricing strategy. The more gaps there are in your segmentation criteria across customers, the more error-ridden your segmentation will be, negatively impacting your targeted pricing and ultimately leading to missed revenue opportunities.  

3. It contains transactional information 

Sales data can be a weak point for businesses in part because it’s missing critical information at the transaction level, which is essential for identifying and fixing margin leakage. Ensuring your sales data is complete at this level of granularity is a prerequisite to monitoring and optimizing price performance with accuracy.  

4. It’s machine readable  

In contrast to manual pricing tools like Excel, pricing software lacks a human element to intuitively understand data based on certain cues we take for granted. For example, while we can quickly grasp the meaning of color coding in a spreadsheet, a machine learning algorithm’s pattern recognition may exclude this capability. 

For this reason, your sales data should be structured in a machine-readable format to enable a more seamless integration of pricing information and avoid costly misinterpretations by the pricing engine.  

How Pricefx Software Partners Help With Data Preparation   

A common question software partners hear from companies is how to gauge when their data is ready for effective pricing strategies. It’s a good one, as data preparation can be a complex undertaking, and often, those involved are unaware of the potential unknowns in the process.  

In response, here are some ways a Pricefx software partner can help ensure your data is in good shape for implementation: 

• Diagnose the state of your data: Partners can conduct short diagnostic projects to assess the current state of a company’s pricing infrastructure, including its data, and illuminate critical areas that will need to be addressed prior to implementation, such as quality and formatting issues. 
• Provide integration guidance: Partners can also provide guidance when integrating data between CRM and ERP systems through pricing software, helping to define which customer attributes are critical for their pricing strategies.  
• Evaluate data readiness: While it is ultimately up to your company to take the appropriate measures concerning its data preparedness, partners can support them in the process by providing a comprehensive evaluation of your data readiness for pricing software implementation.  
• Support pricing strategy implementation: Pricing partners with consulting and strategic expertise can review the company’s current pricing strategies, including pricing models and discount structures, and suggest customer segmentation to optimize revenue and margins. They can then help design optimal pricing processes and provide support in their implementation using the right tools (such as pricing software).  

Overall, pricing partners assist companies in their data preparedness efforts by identifying their data needs, aligning their data with their pricing strategies, and creating a sustainable foundation to enable smarter data-driven pricing decisions in the long term.

How Else Can Pricing Partners Drive Value for Your Business? 

In this article, we’ve outlined sales data’s pivotal role in driving smarter, more gratifying pricing decisions, and how pricing partners support businesses like yours in ensuring that data is in an optimal state to achieve those outcomes.  

Moving forward, it’s important to recognize that data preparedness is just one type of support you can expect from a pricing software partner. To learn more about how our partners work with your business to implement and maintain your pricing solution to enable data-driven pricing success, consider checking out our article below: