So you're thinking about a pricing project, but you're concerned your data isn't clean enough. You're almost certainly right. However, that's no reason to worry. Your data will never be 100% clean—yet that should not stand in the way of starting a pricing project, or any software project, for that matter. In fact, when done correctly, one of the benefits of implementing pricing software is the opportunity to see your data in a new way, uncovering inconsistencies, errors, and opportunities for refinement. As you get deeper into using the software, you will be able to provide valuable corrections to your data management team, improving your overall pricing strategy. In other words, if you go about the data cleansing process in the right way, you can greatly improve the veracity of your pricing business intelligence.

Our pricing solution implementation experts have extensive experience helping enterprises source and clean data. We have encountered all the most prominent challenges and opportunities this process presents. To help you get a leg up before your pricing solution implementation, here's a guide to cleansing your data:

Why Data Cleaning Matters

Data and pricing requirements go hand in hand—you cannot effectively discuss one without considering the other. Data forms the backbone of pricing activities, and having a well-structured plan for delivering that data to the application is a foundational element of a successful project.

High-quality data yields better pricing and business decisions. On the other hand, inaccurate insights as a result of structural errors, duplicate values, missing external sources, or a number of other common data hygiene issues will generate irrelevant observations and faulty decision-making. For example, if your pricing analytics process is leveraging data riddled with typographical errors and missing values, an accurate analysis of data is impossible.

At the same time, getting data right—or at least mostly right—during the initial cleaning process saves time and effort later. While it's important to remain flexible enough to adjust your data strategy during the project if an unexpected roadblock arises, being thorough with your initial data cleaning effort will save you time down the line. If you must adjust data inputs later in the process, you risk reworking elements already developed, causing delays and additional effort. By finalizing data requirements early, the rest of the project progresses more smoothly and efficiently.

Finding The Data You Need for a Pricing Solution Implementation

In our experience, most organizations store pricing-related data in an ERP system such as SAP, Oracle, or another enterprise software. Alternatively, this information is occasionally housed in a dedicated data warehouse. However, pricing-relevant data can also reside in other systems, including CRM platforms and external data sources.

Identifying and extracting this data to supply it to pricing software is a crucial early step. Your organization's data is unique, so there is no one-size-fits-all blueprint for sourcing pricing data. You may have to do some digging to uncover all the relevant information during the cleansing process. 

The Different Types of Data You Should Look For

When structuring a data plan, it is useful to start with what we call "The Big Three": customer data, product data, and sales transactions. However, these aren't the only sources you will need to investigate. External data sources like competitive data or offline information like an Excel spreadsheet may need to be cleansed, structured into a standard format, and integrated.

Let's examine the different types of pricing data in greater detail.

Customer Data

Customer data includes customer names, numbers, segments, and geography. Additionally, other relevant attributes—such as industry, purchase history, or customer lifetime value—can help refine pricing strategies. The more precise the segmentation and classification of customers, the better the pricing recommendations will be, facilitating more informed decisions.

Product Data

Product information includes product numbers, descriptions, segments, and hierarchy details. Understanding the business rules guiding how products are grouped and sold—whether by category, region, or market—is the key to effective pricing decisions. Having this information clearly defined within the pricing software ensures better statistical methods.

Sales Transactions

Sales transactions help identify pricing leakages and opportunities for optimization. By analyzing pricing from the wholesale or list price all the way down to the pocket price (the actual revenue after all discounts and deductions), businesses can visualize their price waterfall.

Contracts, quotes, and overrides at the point of sale influence the final invoice price, and breaking these out within invoice data allows organizations to identify inefficiencies and refine pricing strategies.

Other Potential Data Types

Beyond the Big Three, other valuable data sources may contribute to a comprehensive pricing strategy:

• Currency and Exchange Rates – Essential for international businesses dealing with multiple currencies.
• Competitive Data – Market pricing and competitor benchmarks provide context for pricing adjustments.
• Pricing Conditions (SAP Users) – Individual pricing condition records stored in SAP should be inventoried to determine what the pricing software will manage.
• Offline Data (Excel Spreadsheets, Non-Integrated Databases) – Some companies store critical pricing information in standalone documents. Integrating this data ensures consistency across the organization.

This is by no means a comprehensive list of every source of potential pricing data. Sourcing your data is an essential step, but it can also be a challenging one. However, if you are working with a pricing solution implementation partner, they can help you through each of the cleaning steps.

How a Pricing Solution Implementation Partner Helps

Partnering with an experienced pricing solution team simplifies data identification and integration. For example, before becoming a client, our team works with prospects to determine where pricing data resides and what should be integrated into the pricing software.

Our team has an established process, incorporating cleaning tools and effective data management strategies. Using a standardized data specification template, we capture metadata for all necessary fields, ensuring proper formatting and compatibility with the pricing system. This foundational work runs parallel to business and pricing requirements gathering, ensuring seamless integration between pricing strategies and system capabilities.

Expert Project Management Tips for Pricing Solution Data Cleaning

Engaging IT teams early is critical for successful data integration. Once the necessary data elements are identified, you and your SI partner should begin planning outbound integrations from internal systems into the pricing software. This way, you can ensure proactive collaboration to facilitate a smooth data transfer that minimizes implementation delays.

It's also important to note that while the data cleaning process is vital, pricing software's flexibility allows for adjustments after the fact. In other words, pricing software allows for ongoing data improvement. As your users engage with the system, inconsistencies become more apparent and can be corrected in the source system. Once corrected, changes flow automatically into the pricing software through periodic integrations, improving data accuracy and maintaining data integrity.

Data Cleaning for a Solid Pricing Solution Foundation

Accurate, well-structured data free of integration issues, inconsistent formats, or syntax errors ensures pricing strategies are based on reliable information, preventing costly errors and poor business decisions. Without clean data, you may struggle with misclassified customers, incomplete product information, or inconsistent sales transactions, leading to suboptimal pricing decisions. For example, if a company has duplicate customer records in its ERP system—one listing a client as a wholesale buyer and another as a retail buyer—the pricing software may apply incorrect discounts, causing revenue leakage. 

By cleaning and consolidating this data before implementation, you can ensure that pricing models reflect the true nature of your customer base, leading to better pricing optimization and more profitable outcomes.

The Step-By-Step Guide to Successfully Implementing Pricing Software Series

This article is the sixth installment of our ongoing pricing project series.

These articles are designed to meticulously unfold the complexities of pricing software implementations. Our approach provides a clear roadmap from the project's outset, introducing each crucial phase in detail and making it easier to absorb and apply the information effectively. 

• Part 1: How to Make Your Pricing Software Project Successful
• Part 2: How to Set Successful Pricing Software Goals
• Part 3: Identifying Your Product Pricing Strategy: 4 Examples
• Part 4: Why You Need to Involve Executive Stakeholders in Software Implementations
• Part 5: When to Use Agile Vs. Waterfall Workflows: A Point-By-Point Comparison

Over the course of this series, we will cover the following topics: