Debunking a Market Research Myth

What customers say they will do, and what they actually do, can be two completely different things

As all businesses know, when it comes to customers, what they say they will do (in market research), and what they actually do, are two completely different things. All too often, I see revenue forecasts or sales projections that fall into this trap.

The day after Apple launched the iPad Mini,  I stumbled across some research[1] (obviously completed in record time!) that suggested that 14% of respondents ‘would definitely buy’ the product, and 32% said they ‘probably would’. Add the two numbers together and you’ve got 46% take-up. Fantastic!

The Urban and Hauser scale tells us that, of the 14% who said they would definitely buy, you can be reasonably sure that 90% of them will actually buy, while 40% of those who said they ‘probably would’ will actually buy, Do the sums, and your take-up forecast becomes 25.4%.

Later that week, I was discussing with a Pricing Manager, the importance of having a decoy product. When asked if we could model the impact of a decoy product, I remembered some forecasts made in an experiment conducted by the Behavioural Economist, Dan Ariely.

In his talk at the London School of Economics in March 2008 (which is also described in his book Predictably Irrational), Professor Ariely described an experiment where 16% of participants would take up a digital-only subscription to The Economist at $US59, none would take up a print only subscription (the decoy) priced at $US125, but 84% would take up a print and digital subscription at $US125.

When the experiment was repeated without the decoy, the 16% became 68% and the 84% became 32%. A quick calculation, assuming 1mill subscribers at the above-mentioned prices, reveals that revenue would be nearly 43% higher with the decoy product than without.

Following a quick search on Google, I discovered that The Economist (which doesn’t appear to report subscriber numbers) had digital-only circulation of 100,000[2], out of a total circulation of 1,574,803. This implies a digital-only circulation of 6.35%, significantly lower than Professor Ariely’s number. Could this be another example of market research not catering for the difference between what customers say they will do, and what they actually do?

In a previous post Are you Pricing Like Dennis Denuto?” , I talked about why scenario analysis was one of the pricing traps companies often fell into (liking a set of number from one scenario without reality-checking the assumptions the scenario is built upon). You no longer have an excuse for falling into this trap with revenue or sales volume forecasts.

 

https://www.linkedin.com/pulse/debunking-market-research-myth-jon-manning?trk=hb_ntf_MEGAPHONE_ARTICLE_POST

 

Need Better Price Volume Mix Analysis? It’s Easier Than You Think.

Most Price Volume Mix analyses are “top-down” analyses.  They focus on certain buckets, typically price, cost, and volume, and then assign everything else to a plug labeled “mix.” While this approach can supply a quick-and-dirty view of the big picture, it usually raises more questions than it answers. As soon as you share results, someone wants to identify the driver of those results. The top-down approach doesn’t provide answers to that, because you cannot drill down into a plug.  You return to your desk and run a deeper set of cuts just to uncover yet another set of questions.

In contrast, “bottom-up” Price Volume Mix analysis calculates the exact impact of price, cost, and volume at the specific levels of unique customer, product and even transaction.  By building calculations from the ground up — with no plugs — a bottom-up approach instantly identifies which areas of business are driving each area of change. This empowers you to find actionable insights for margin improvement at any level in your business.  A top-down approach raises more questions and requires more analysis; a bottom-up approach answers questions and allows focus on taking action.

price volume mix analysis

Five Situations Requiring Bottom-Up Price Volume Mix Analysis

1. Measuring the Success of Price Increases

Eliminating the effects of customer mix shift is critical to understanding the effect of price increases. Top-down Price Volume Mix analysis, which simply compares the change in overall average selling price by product, can be misleading. Customer mix shift can drive average selling price down even if you successfully increased prices for every individual customer (and vice versa).

In contrast, bottom-up Price Volume Mix analysis isolates the impact of price changes at the customer level, providing true visibility into the success of your price increase implementation.

Even if a price increase did achieve its overall goal, it likely did not succeed with every customer and product. By providing insight into price changes for individual customers and products, or any combination thereof, a bottom-up approach to Price Volume Mix allows you to measure success at any level of granularity to identify individual pockets of opportunity for margin improvement.

2. Identifying Opportunities to Pass Cost Changes on to Customers

Many businesses compare price change to cost change to determine how effectively they’ve passed cost increases through to customers. Top-down Price Volume Mix analysis measures overall average selling price, which is a product of both customer by customer price change and customer mix shift. It may appear as though you’ve passed costs through effectively, when in reality, you have merely benefited from positive customer mix shift.

Bottom-up analysis provides a true measure of price change and is therefore a better yardstick for gauging how effectively you’ve passed through cost changes. It also enables you to measure price changes customer by customer and product by product to identify specific areas where cost changes haven’t been passed through and take corrective action.

3. Measuring the Impact of Initiatives Across a Business

Businesses undertake many initiatives in any given year. This often requires the development of different methodologies to measure different initiatives, which can lead to time-consuming debates around methodology and often results in double-counting impact across multiple initiatives. The inflexible nature of top-down Price Volume Mix analysis means it does little to resolve this problem.

Bottom-up Price Volume Mix analysis, on the other hand, serves as a consistent basis for measurement. By isolating the effect of each driver of margin change at the level of individual customers and product, it provides a congruous framework for measuring the impact of almost any initiative across the business. Whether the goal is to increase prices in a particular region, reduce costs on a specific set of products, or increase marketing to a targeted segment, bottom-up Price Volume Mix analysis isolates and measures the exact impact of initiatives.

4. Understanding Drivers of Product and Customer Mix Shift

A significant drawback to top-down Price Volume Mix analysis is that it “plugs” customer and/or product mix by calculating the buckets such as price and volume and lumping the remainder into an amorphous bucket of “mix.” This makes it difficult, if not impossible, to understand exactly which customers and products are driving mix shift and the direct these effects take.

Bottom-up Price Volume Mix, however, calculates customer and product mix for every individual customer and SKU, empowering you to identify exactly which customers and products are driving results and take action accordingly. Moreover, while a top-down approach simply provides visibility into overall performance, a bottom-up approach provides a means to identify individual pockets of opportunity trending in a different direction than overall mix shift.

5. Measuring Impact of Innovation on the Bottom Line

Adding new products and culling others is often a significant impact driver of margin performance. Yet, by using a plug for mix shift, top-down Price Volume Mix analysis provides no means of isolating the mix shift impact of new and discontinued products. Bottom-up analysis, however, allows you to measure the exact impact of such actions as well as the impact of new or lost customers, market segments, or any other aspect of your business.

The Bottom Line

By building calculations from the ground up — with no plugs — a bottom-up approach instantly identifies which areas of business are driving each area of change. This empowers you to find actionable insights for margin improvement at any level in your business, like it has for our customers on the KiniMetrix platform. For one industry leading customer in the distribution business, measuring the impact of specific initiatives, pinpointing drivers of product/customer mix, and understanding impact of new/discontinued products on mix shift has enabled this company to closely manage mix to optimize margins—and ultimately their bottom line—in what is traditionally a thin-margin industry.

 

Need Better Price Volume Mix Analysis? It’s Easier Than You Think.