White Papers

[CASE STUDY] How Leger Analytics Used Discrete Choice Models to Project Market Share for a New Vision Product


Executive Summary

A vision care company was deciding whether to launch a new product. Using discrete choice and price elasticity models, Leger’s analytics and research teams identified the product features that are most appealing to consumers and eye care professionals (ECPs), recommended a price for the product, and produced two market simulators, enabling the company to project the impact of market changes on the probability of their product being chosen over competing products.


Over time, the healthcare market in the United States has evolved drastically. Seemingly endless product options are available for consumers, and competition is fierce. Another piece of the puzzle is the role of healthcare professionals in deciding what to recommend to their patients, which can be a make-or-break moment for new products.

THE CHALLENGE: WHETHER TO LAUNCH A NEW PRODUCT

In 2019, a successful American vision care company was deciding whether they should launch a version of their existing product line featuring a new-to-market innovation. As with any new product launch, the product managers had several key questions:

  • This investment will cost $1 million…is it worth it?
  • Which combination of features and options will consumers and eye care professionals (ECPs) find most appealing?
  • What should the price of the product be?
  • How will the introduction of the product impact our market share?
  • Will we gain new clients, or will this new product only cannibalize our existing customers?

In the past, the company used focus groups to answer these questions. Although the groups were informative, conducting them was very expensive. Furthermore, they could not extrapolate the insights to the American population, due to the qualitative nature of the data collected.

THE SOLUTION: ONLINE SURVEYS FEATURING DISCRETE CHOICE MODELS

Based on the company’s objectives, we conducted two different quantitative online surveys:

  • One among American consumers who already use a similar product, or are willing to try using the product
  • One among American ECPs who are responsible for recommending products in the same category to their patients

Each of these surveys featured a discrete choice model customized for each audience.

WHAT ARE DISCRETE CHOICE MODELS, AND HOW DID WE USE THEM?

A discrete choice model is an advanced analytics tool that can be used to help companies understand which set of features their consumers prefer most and how much more they are willing to pay for features they want. In this case, we also used a discrete choice model to understand which product ECPs were most likely to recommend to their patients.

Using discrete choice models allowed us to simulate a real-life buying experience among consumers and a real-life recommending experience among ECPs.

As noted by Mico Perreault, Data Scientist and leader of the analytics component, “Interestingly, in this case, consumers’ product choices do not rely only on their preferences and the supply of products, but also their eye care professional’s recommendations. Therefore, we needed to measure this influence and capture the healthcare professionals’ preferences in the equation.”

“Using discrete choice models gave us the flexibility to show over 100 price points depending on the product, the format, the quantity, and multiple pricing factors. With this many combinations, we were able to break down what is really driving choice for both consumers and eye care professionals, giving us confidence in the results,” added Colette M. Faust, Account Manager and leader of the research component.

The discrete choice models showed each respondent a series of screens with different product options (from screen to screen, each product varied in terms of price, format, supply, and rebates available). Each screen featured four products, and respondents were asked to choose the one they preferred most (a “none” option was also available). One of the options the company was considering was bundling the new product with one of their existing products. Therefore, we also incorporated product options with bundles into the models. For illustrative purposes, here is an example of what the screens the consumers saw looked like:*

Sample Discrete Choice Model Screen

*To maintain client confidentiality, specific information about the products tested has been omitted. Click on the image to see a larger version.

The Key Takeaways

We provided the company with a detailed overall report which included key insights and recommendations based on the research. We also provided two market simulators, one for consumers and one for ECPs.

Using the data collected through the discrete choice models and online surveys, we…

1. IDENTIFIED WHICH FEATURES ARE DRIVING CONSUMERS’ PURCHASING DECISIONS, AND BY HOW MUCH

We were able to let the company know which features (price, format, supply, or rebates available) drive consumers’ purchasing decisions and the relative impact of each feature on the overall purchasing decision.

Our analytics team also used the discrete choice model results to infer the price elasticity of the products tested. Our analysis enabled us to project the price at which consumers begin to be interested in the company’s new product. We were also able to project what percentage of consumers would be interested in purchasing the product at their manufacturer’s suggested retail price (MSRP) and how many consumers would be interested if they discounted (or increased) the MSRP by 15%, 30%, etc.*

Share of Preference by Price Chart
*To maintain client confidentiality, specific information about the products tested has been omitted. Click on the image to see a larger version.

The pricing data from this analysis greatly factored into the company’s decision about whether launching the new product would be advisable.

3. PRODUCED TWO MARKET SIMULATORS WHICH ENABLE THE COMPANY TO SIMULATE DIFFERENT MARKET SCENARIOS AND PROJECT HOW MARKET CHANGES WOULD IMPACT THEIR SHARE OF PREFERENCE (FOR NEW AND EXISTING PRODUCTS)

In addition to a full report detailing the results of the quantitative surveys, we provided the company with two user-friendly market simulator dashboards: one for consumers and one for ECPs. By clicking a few buttons, the company can easily manipulate the dashboards to help them understand what would happen to their share of preference if they or their competitors modified the price, format, supply, and/or rebates available for their product(s). With the dashboards, the company can modify the options they select for each feature independently, enabling them to answer questions such as, “What happens if I change the price of my product to x, but my competitor decides to offer a rebate of y?”

Using the dashboards, the company can also test their new product against their existing product line, which enables them to project whether introducing the new product is advisable or would risk cannibalizing their existing market share.

Here is an example of what our market simulator dashboards look like:*

Sample Market Simulator
*To maintain client confidentiality, specific information about the products tested has been omitted. Click on the image to see a larger version.

THE OUTCOME

Is the new product the company was testing available on the market? Not yet: of course, big decisions like these take time. However, the data gleaned from Leger’s online surveys, especially the discrete choice models, has been used as a key input for the product team’s business model.

As with any new product launch, there is a long road ahead, but based on the data, the product team can proceed with solid evidence about which format of the product is most preferred among consumers and eye care professionals.

Leger is currently collaborating with this company on another project.


ARE YOU INTERESTED IN A CUSTOMIZED ANALYTICS SOLUTION?

Please contact us by filling in the form below.