Filter Out the Noise with Data Science Driven Price Optimization

June 9, 2023

At a glance

  • Main takeaway: Price optimization can provide you with a better understanding of how your customers interact with you, your products and services to help you develop an effective pricing strategy.
  • Impact on your business: Increasing the price of your products and services may sound simple, but it can cost you money and your customer base if not done correctly.
  • Next steps: Aprio’s Data Management & Insights services team can perform a price optimization assessment and analysis to provide data-based recommendations so you can make business decisions with confidence.
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The full story:

Have you thought about increasing the price of your products and/or services to drive revenue, but are unsure how to do it without potentially alienating your customers? Well, you’re not alone. If done smartly, you can increase your prices, drive revenue and keep your customer base by performing a price optimization analysis.

Filter out the noise and get down to the real data

Price optimization removes the ambiguity so you can make pricing decisions with confidence because you have the data to back it up. By using price optimization to analyze your customers, a sliding scale model can be created that captures multiple data points on the behavior of each customer, the market and how they interact with your products and/or services. The advantage of creating a sliding scale model is to find the delicate balance between increasing your prices without churning your customers.

However, the key is to treat each customer as an individual so you can fully understand how they act and accurately predict their stickiness. In other words, the likelihood that your customers will stay with your company if you increase the price of your products and/or services.

This is determined by first collecting a series of data to give you a multidimensional view of each individual customer. The types of data collected and analyzed to create the sliding scale model, include:

  • Historical transaction sales
  • Financial history
  • Performance in the market
  • Brand reputation
  • Service calls activity
  • Relationship with customers (i.e., Have you conducted customer surveys?)

Another area to carefully analyze is any potential contractual obligations. What does this mean? Review and identify any possible key blockers (i.e., terms and conditions) that are laid out in the contract between your company and each individual customer that may contain contractual price restrictions, such as providing a customer with a 90-day or more notice prior to issuing a price increase.

Calculating data to determine a risk category

Once the data is collected and a sliding scale model is developed, you can calculate a rating that puts each customer into a risk category — low, medium, and high — to determine what is the percentage level that you can increase your prices without making your customers churn.

And because you collected data on each customer as an individual, you can use the sliding scale to identify the cross section between the percent of increase (whether that be 5%, 10%, or more) and the percent of churn. This cross section is crucial because if you get too much churn, you can lose your customer base. After all, the point is to increase revenue and keep your customers, not lose money and give your customers a reason to leave.

The bottom line

Price optimization can provide you with a better understanding of your pricing line and most importantly the impact on your customer base. By analyzing the financial and sales history, performance in the market and brand reputation you can create customer price lists, a discounting approach and an effective price strategy with positive business outcomes you can expect.

Aprio’s Data Management & Insights services team can perform a price optimization assessment and analysis to provide you with data-based recommendations to give you the confidence to make informative business decisions.

Upon delivery, the price optimization models are yours to continue the price optimization analysis on your own cadence. And Aprio is available to support or conduct future price optimization analysis using your new models.

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About the Author

Greg Levins

Greg Levins is a Director of the Aprio Digital Transformation & Cybersecurity Advisory Services and leads the Aprio Data Management & Insights practice. He has more than 40 years of experience in the business of IT, focused on program management, enterprise architecture and methodologies, with a microfocus in data management. He has led successful digital strategies and implementations for clients operating in vertical markets, including: Aerospace, Manufacturing, US Military, US Federal, Retail, Healthcare, Travel, Utilities, Oil & Gas and Banking. Greg is a certified facilitator who excels at aligning stakeholders and team members at every level of an organization to deliver scalable, secure solutions that deliver speed to value.