How Well Does Your Pricing Organization Learn From the Field?

Unlock latent potential with price experimentation

With every price quote or posted price, there is an opportunity to learn about the market, and in turn, improve pricing. Yet, a tremendous amount of the information is not captured, systemized or utilized, neither by people in pricing nor the algorithms they employ. The potential in learning from the untapped sources of field information can be tremendous.

To learn from the field, there are two kinds of tools that can be utilized: surveys and experiments. Let’s focus on the latter tool – price experimentation. Any time a price change is executed, there is a chance to observe results and learn. While any price change can be considered an experiment, price experimentation specifically refers to the changing of prices in an intelligent manner designed to yield as much information as possible at an acceptable level of risk. Price experimentation provides an opportunity to gain critical knowledge, learn from that knowledge and act to optimize price and ultimately impact margin and revenue.

However, price experimentation is vastly underutilized, and many organizations are missing out on the opportunity to unlock a lot of latent potential.

Learn by Example: Price experimentation success

To truly understand its potential, let’s examine a real-world example. Vistaar had the pleasure of working on a highly successful project with a producer of digital media where price experimentation was used to learn about market willingness-to-pay and ultimately resulted in tremendous revenue and margin growth.

The company’s pricing team utilized a pricing solution from Vistaar that inherently provides the ability to execute price experimentation and learn from it. The intelligent software helped to segment products to model price sensitivity and price and identify noticeable outliers based on peer groups. It established a preliminary price elasticity model, then mathematically calculated optimal price increases to balance volume and margin. The software executed the suggested price changes and tracked the results in the market. Based on what was learned, the system updated elasticity models and reverted price on any underperforming products. From there, its rinsed and repeated!

Price experimentation delivered not only a twelve percent increase in gross profits in a short period, but the pricing organization achieved improved predictive accuracy in their machine learning models, enhanced pricing manager expertise, increased stakeholder buy-in and collaboration, and captured all price change and result data to build database richness.

The project took place in what can be considered the ideal platform for price experimentation, e-commerce consumer goods, due to factors such as easy price execution, available competitor intel data, quick clean feedback data and low risk to get buy-in from stakeholders. It typified the ease of experimentation in the e-commerce channel.

If you are in B2B negotiated pricing, you may be thinking how can price experimentation work for me?

Results are closer than they may appear (with pricing software)

Yes, B2B negotiated pricing is different and can be viewed as a more difficult place for price experimentation. B2B pricing can lack elements such as competitive intel, easy ways to execute price changes, feedback data on orders or quotes, advanced measurement tools, and stakeholder buy-in. However, successful price experimentation is possible in the B2B domain! The apparent challenges are surmountable and more feasible to address than you might think.

Capturing lost bid data and competitive intelligence is often quite feasible. For example, one U.S. chemical company has a routine process for calling and visiting field sales offices to extract and systematize lost quote and competitive data. This is conducted by talking with reps and rifling through emails and paperwork. This kind of investigation leads to the development of a sustainable business process that provides necessary intel. In addition to internal investigation, businesses can utilize syndicated data from trade associations, if available. After some initial work to gather missing data, today’s pricing software takes care of the rest:

  • Easily Execute Change – Modern pricing software enables the quick execution of price experiments through easy communication of price changes to the field, targeted pricing for test markets, approval workflows to enforce test prices, and real-time tracking of price performance.
  • A System of Record – One of the main reasons that lost bid data is missing is the fact that quote data is not linked to order data in a systemized way. Pricing software implements user workflow and enables the linkage of quotes-to-orders. The software can serve as the system of record and a repository of valuable data.
  • Advanced Measurement – In most pricing initiatives, a 1-3% revenue increase is a definitive victory. However, detecting 1-3% revenue increments takes sensitivity to separate the signal from the noise. Pricing software’s advanced algorithms measure the impact of a pricing strategy change with a much greater degree of clarity and accuracy than standard BI reporting tools typically used by pricing organizations.
  • Stakeholders Want In – Thanks to the ease of execution and quick result detection provided by pricing software, price experimentation risk is generally considered low. The lower the risk, the easier it is to get stakeholders to participate in price experimentation.
  • Machines Learn Better – With the right data, powerful machine learning techniques can estimate willingness-to-pay and predict win probabilities and volumes. Facilitating price experiments through pricing software helps these models to become more accurate and precise over time.

Ultimately, pricing software enables the execution of price experiments and the retention of learnings to continually optimize price and deliver on margin, revenue and volume. Not only does price experimentation through pricing software advance machine learning, but it enhances people and organizational learning. Pricing teams gain more expertise about their sales markets and strengthen skills for advanced analytics. Communication channels open and more collaboration across stakeholders takes place to improve processes. At Vistaar, we believe that no matter the industry, learning from the field and acting on that data through pricing software, powered by advanced analytics, differentiates the winners from the rest.

For more information on how to unlock latent potential with pricing software, please click here.

This article was authored by:
Kelly Capizzi, Associate Director, Marketing
Graduate from Millersville University of Pennsylvania

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