Case Study: Making the Go/No Go Decision for a New Product

Energy Market Solutions was asked to determine the viability of a commercial surge protection product aimed at small to mid-sized businesses and to optimize its’ features and price. There was some urgency to the research because a pilot test was underway and a decision was needed in the near future about going to a full market introduction or eliminating the product.

Clients questioned the viability of the product due to its low price (and resulting low margins) and mediocre penetration. There were also serious concerns (and resistance) to potential upfront investments in new equipment.

The client wanted to know what the optimal product features, optimal pricing, projected take rates, and promotional positioning would be, and whether we thought the product should be fully launched.

The client provided financial spreadsheets containing internal cost data, target population estimates, pilot test results, and access to personnel involved with the pilot test.

The primary objectives of the research were to:

1. Assess the optimum pricing and attribute package for small to mid-size commercial customers for each of 2 regions. The product attributes of the commercial surge protection product to optimize were (ranges are undisclosed):
   • Monthly Fee
   • Warranty
   • Installation fee
   • Contract Terms
2. Determine what product attributes are most important to all customers. Determine if there are differences across the 2 regions.
3. Gauge customer perception of the product and penetration estimates for the product
   

The secondary objectives of the research included:

• Identifying potential communication opportunities (i.e. what are the most appropriate promotion channels for this product?), and
• Determining interest and need for point-of-use surge protection and/or small UPS devices (e.g. for PCs and cash registers). Do customers want to purchase these as part of a product bundle?

Respondents were recruited by telephone to participate in the internet-based survey. The utility was identified as the sponsor and an incentive was paid. Respondents were pre-qualified on the basis of: SIC, potential interest in product, and non-participation in pilot test. The study was completed in 10 weeks.

Feature Optimization
The feature optimization exercise used a modified conjoint (trade-off) design. This exercise helped us identify the optimum mix of price, warranty, installation fee and contract terms for all customers as well as for each region. The exercise assessed the importance that prospective users places on the various individual features of the product. Respondents were also asked to rate potential combinations of features of the product.

The Pricing Model
In addition to the modified conjoint exercise, respondents participated in a pricing exercise that allowed us to develop market-based pricing and penetration estimates.

We used a van Westendorp Price Sensitivity Meter, combined with a purchase probability extension, as the primary tool for the pricing analysis. The van Westendorp model was developed by Dutch economist Peter H. van Westendorp to examine patterns of price-consciousness. The survey included four questions for each product profile, including respondent’s prices for the product:

1. for a bargain – a great value for the money,
2. starting to get expensive, but still worth considering,
3. so cheap that quality is doubted, and
4. so expensive that it would not be considered.

In addition, we asked two additional purchase-intent questions in order to examine the likely effect of price on receptivity (willingness to buy) and on total sales revenue. The net result of adding these two purchase intent measures to the traditional van Westendorp model is to substantially increase the understanding of the prices at which receptivity (share) and revenue can be optimized.

An extended market simulator with market penetration, sales diffusion, and revenue projections was delivered to the client. This tool allowed the client to create a version of the product with specific product features and prices and see the effect on a variety of projections. The output gave purchase probability (including sales diffusion estimates) details in total, by size of company, and by region, along with revenue projections for the product with the features as the user defined them. The client can run what-if scenarios with any combination of product features and price in order to see the net result on penetration and revenue.

Results
With the interactive tool, we delivered recommendations on product configuration and price for three scenarios:

• maximizing revenue,
• maximizing market penetration, and
• the best combination of maximum revenue and penetration.
  

We also presented the following significant findings:

1. There is, in fact, a healthy market for the product, and money to be made (the prices we recommended for all scenarios were higher than the current pilot price).
2. There is a product feature (undisclosed) that significantly increased the value of the product from the customer’s perspective, allowing the company to more than double the price with very little incremental cost.
3. The two company legends (undisclosed) that were being used to position and price the product were false.
4. Installation fees could, in fact, be part of the product mix, substantially reducing the additional internal financial investment issue.
5. Some groups of customers were quite insensitive to price and others were very sensitive. We identified them and explained how the price sensitivity could be managed (by altering the other features).