Companies are under pressure to consistently get it right when it comes to product development and market adoption. They are not only coping with internal pressures such as supply chain management and labor issues, but also ever-increasing competition in a volatile global economy. In order to effectively manage these issues, executives are turning to forecasting at every stage of product development and the market adoption process to help make the right decisions.
Generating a product sales forecast involves two important precursors; understanding what customers really need in a new or updated product, and determining who will be most likely to purchase it. Of the marketing research processes that are most useful to generating an accurate forecast, two that are most important to get your project from the drawing board and into the hands of your customers are product development research and adoption modeling.
Product Development Research
There are many methods to test how well consumers will respond to a new product or concept. A particularly useful tool is conjoint analysis, which uses statistical techniques to determine what combination of product attributes are most influential to a customer’s buying decision. In conjoint analysis, a customer is shown a set of concepts for a product with different attributes and associated levels, then the customer is asked to either rate which is most favorable to them (standard conjoint) or pick one option or the other they would choose (discrete choice) on the basis of preference.
For example, consider a hypothetical product, described through set of concepts for an educational toy robot, PAM (Playtime Automated Machine). Children interact with PAM via a touchscreen. For the concept test, PAM is represented as a series of different attributes: touchscreen size, types of game apps, brand and price. Each of PAM’s attributes is then further rendered by different levels for each attribute. For the attribute types of game apps, PAM has four levels: reading, math, music and science. Customers would then be shown various concepts for PAM via an online survey, and are then asked to decide which configuration of the concept they favor or would choose, depending on the type of conjoint method used. From their choices, researchers would create models to understand which attributes are the most important to consumers, and would create market simulations to show what percentage of the market would purchase PAM at different price levels. The overall idea is to give mangers a better idea of consumer acceptance of PAM before it goes to market.
Conjoint analysis is a popular technique in the product development stage, which adds value to the product design process by giving insight to the consumer decision-making, understanding the acceptance rate for potential products.
Even accounting for all its benefits, conjoint analysis is not enough alone to get a product from the concept stage to market. While new product insights are necessary to design the best product possible, and to know how to best price the product, it does do not tell you everything you need to know about at what rate and by whom your concept will be accepted in the market place. Since all consumers of your products are different, some individuals will accept the product right away, while others will choose to wait until later for a variety of reasons, or will never purchase the product at all. To better round out the knowledge necessary to properly introduce a new product, adoption modeling is a must.
Adoption Modeling
Adoption modeling is next step in the pre-market forecasting process for new product introduction. Studies that examine how new ideas and products are adopted show a fairly predictable pattern as seen below in Figure 1. If we circle back to the robot toy example, PAM, we may see that it will be first adopted by a group known as Innovators. This group generally adopts a new concept very early and will prove that PAM works, with a varying degree of influence over other potential adopters of the product. For example, this might be a small group of very dedicated toy robot aficionados.
The next group to pick up PAM would be Early Adopters, who generally have more influence, are a much larger group and may include opinion leaders. For example, at the Early Majority stage of adoption, a staff writer for Toy Robot Monthly may review PAM favorably, which may cause a larger percentage of people to begin buying it and posting on social media how great it is. These early adopters may then be influential enough to effect the early majority in time for the Christmas toy rush. After Christmas, PAM remains popular has received enough notoriety to be acceptable to the late majority. Eventually, the late adopters and laggards (aka, kids whose parents finally got around to purchasing their children “the coolest educational toy robot on the market”.
Adoption modeling is essential for estimating how quickly your new product might spread through the market, and how it will spread. In the case of PAM, executives might know that their potential market consists of 10 million kids in the US under the age of 8, and their company has 80% of market share in the toy robot industry. What they need to know (at least some what they need to know) to put this to optimal use is the following:
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Who are the innovators and early adopters in terms of demographics and past purchasing habits?
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What are these groups’ habits with respect to networking with others?
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What is the criteria for early majority buyers to purchase?
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How big are these groups, and how should I reach them with marketing communications?
With the above knowledge in hand, PAM’s creators would have the raw materials for a very powerful and effective marketing plan for the new robot. In addition, if this information is coupled with historical market adoption data and customer profiles for each group, they can infer the length of time it will take for them to reach their milestones. Such information is very valuable as input to volumetric forecasting they would be able to perform prior to product launch.
Actionable Research
While adoption modeling must make assumptions (overall economy, seasonality, etc.), if the conjoint analysis reveals potential customers like the concept, executives can then use adoption modeling to estimate how long it would take to reach milestones for unit sales and properly resource not only their launch, but the stages that follow of their product’s tenure in the market. Product development research, including conjoint based concept tests and adoption modeling, are primary marketing research components, both of which are a significant focus at Actionable Research. Following the decision to perform these research efforts, knowing which questions to ask and how to ask them is the most important next step along the path to delivering a quality forecast and successful new products.
To learn more about how these methodologies can help to improve your product development, contact our researchers today
This article was originally published in April of 2016 and has been updated to reflect the changing market.
