Setting the best price

Global manufacturer transforms pricing strategy and increases profitability using IBM SPSS Modeler

Published on 21-Jun-2011

"IBM SPSS Modeler has enabled us to be sensitive to market dynamics, and to ensure the value we provide to our customers is in sync with our prices." - Strategic Pricing Manager, Global Products Manufacturer

A global manufacturer of power systems

Industrial Products

BA - Business Intelligence, Information Integration, Optimizing IT, Smarter Planet

Smarter Planet:
Smarter Manufacturing


Putting a price tag on products and services is a delicate balancing act: set the price too high and you will scare away potential customers; set it too low and you will hurt the organization’s bottom line. How do you know when the price is right?

Business need:
A global manufacturer of equipment needed to analyze vast quantities of product characteristics and pricing data in order to align its product pricing with the market segment and to predict future pricing levels.

The company implemented IBM® SPSS® Modeler to accurately and efficiently sort and analyze information about sales of millions of customized products to determine optimal pricing across multiple markets.

Enables global manufacturer to predict the elements of a winning sale, leading to improved “win rate” and greater profitability. Ability to integrate and analyze data records numbering in the millions. Reduction in time spent by employees manually creating analytic pricing reports, and improvement in other key business processes. Increase in accuracy and efficacy of analytic pricing reports and predictions. Program can be expanded to meet business needs outside of pricing.

Case Study

Putting a price tag on products and services is a delicate balancing act: set the price too high and you will scare away potential customers; set it too low and you will hurt the organization’s bottom line. How do you know when the price is right?

A global manufacturer of equipment has grappled with this question for years. With the help of IBM SPSS predictive analytics, the company is gaining the power to quickly and efficiently set optimal prices across global markets, improving both the sales force’s “win rate” and the company’s profitability.

“We were missing growth opportunities because our pricing may have been misaligned with the market,” says a pricing manager with the manufacturer. “IBM SPSS Modeler has enabled us to be sensitive to market dynamics and to ensure the value we provide to our customers is in sync with our prices.”

A more powerful pricing strategy
The manufacturer usually customizes product orders to meet the unique needs of its customers. “Each product is essentially made to order,” the pricing manager says. “The customer gives us detailed specifications on the product configuration and we customize each order. This is why pricing can be challenging.”

To set its prices, the company relies on a wealth of data from its business systems, including information about past quotes and bids, along with the customers and product configurations involved. The amount of data, however, can be staggering: analysis of a single product line can encompass more than two million combinations of prices, products, and customers. Traditional data extraction and analysis methods can be slow and rarely yield the kind of detailed output the company needs to realize a key goal: to replicate the elements of a winning bid associated with current market conditions.

So the company searched for a more powerful way to analyze the data and help set prices for its products worldwide. After considering several vendors, the company chose IBM SPSS Modeler because of its sophisticated data mining capabilities, ease-of-use, and operational flexibility. Company executives also saw the potential for using Modeler down the road to price other product lines and support additional data mining projects.

Plugging in to Modeler
Right from the start, pricing managers were pleased with the depth and utility of the new data mining platform. The pricing models were designed to statistically analyze the interplay between product configurations, initial quotes, and final selling prices – as well as the impact of geographic location on prices and sales, which the company discovered was an important differentiator. One of the most important outputs of the model was a detailed examination of the company’s “win rate,” which identified key product, customer, and pricing characteristics driving successful bids.

Within months of implementing IBM SPSS Modeler, tests showed improved outcomes in several key areas as pricing managers leveraged a more sophisticated analysis to confidently set product prices in each market and competitive situation. Previously, managers had only limited insight into whether prices were too high (sacrificing revenue) or too low (impacting profitability) for specific brands and regional markets. “Pricing is now becoming more statistically controlled,” the pricing manager explains.

Modeler’s rapid output means the manufacturer can conduct more frequent pricing analyses, helping it stay on top of market trends and allowing it to quickly fine-tune pricing structures to stay competitive. As the pricing manager explains, “with product leaders spending less time collecting and formatting data, they have more time to focus on what matters most: working with customers and our engineering departments to develop new products to meet customer and industry needs.

Already, managers say there are indications that better pricing through predictive modeling is having a positive effect on sales. “IBM SPSS Modeler has helped us improve our win rate and increase our profitability as we shift to align our products and offerings to match market-level pricing,” says a pricing analyst. “This is being accomplished not necessarily by increasing prices, but by aligning our product offerings and product pricing with what customers value and need.”

Expert help
At the start of the project, the company turned to consultants from IBM Global Business Services to help build its first set of statistical models and train company staff in model development. The expert guidance jump-started the initiative by helping structure the project effectively using industry-standard CRISP-D M methodologies, and by assisting the company with key tasks such as data preparation and model documentation. The IBM consulting team also helped deploy the modeling solution within the company’s complex IT environment.

“IBM Global Business Services has been an integral part of our data mining project,” says the pricing manager. “They serve as a valuable sounding board for our ideas and enable us to move from concept to production at a much faster rate.” Managers also took advantage of an annual training membership to attend several Modeler courses. “The combination of classroom training and hands-on work with the IBM consultants was an excellent way to get the project rolling quickly,” the pricing manager adds.

A bright future
After the company’s success in applying predictive analytics to optimize the initial product line’s prices, the company has started employing the software to improve the way it prices its other product lines. Other uses for predictive analytics are being envisioned, including setting prices based on a “customer segmentation” model that takes into account past purchases and specific customer needs, and developing “extended term contract prices”.

As Modeler proves its worth, company leaders from other divisions are considering rolling out the modeling tool set across more business sectors. “The analytics have given us insight into current business practices and steered the company toward making changes in targeted markets, driving market growth,” the manager says. “IBM SPSS Modeler has made an immediate impact and has driven positive results.”

About IBM Business Analytics
IBM Business Analytics software delivers actionable insights decision-makers need to achieve better business performance. IBM offers a comprehensive, unified portfolio of business intelligence, predictive and advanced analytics, financial performance and strategy management, governance, risk and compliance and analytic applications.

With IBM software, companies can spot trends, patterns and anomalies, compare “what if” scenarios, predict potential threats and opportunities, identify and manage key business risks and plan, budget and forecast resources. With these deep analytic capabilities our customers around the world can better understand, anticipate and shape business outcomes.

Products and services used

IBM products and services that were used in this case study.

SPSS Modeler

Legal Information

© Copyright IBM Corporation 2011. IBM Global Services, Route 100, Somers, NY 10589, U.S.A. US Government Users Restricted Rights - Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Produced in the United States of America, June 2011. All Rights Reserved. IBM, the IBM logo, and SPSS are trademarks or registered trademarks of International Business Machines Corporation in the United States, other countries, or both. If these and other IBM trademarked terms are marked on their first occurrence in this information with a trademark symbol (® or ™), these symbols indicate U.S. registered or common law trademarks owned by IBM at the time this information was published. Such trademarks may also be registered or common law trademarks in other countries. A current list of IBM trademarks is available on the Web at “Copyright and trademark information” at: Other product, company or service names may be trademarks or service marks of others. References in this publication to IBM products or services do not imply that IBM intends to make them available in all countries in which IBM operates.