- Determine the best price for your product or service
- Learn which features are most important to include in your product, and which you should develop first
- Understand the incremental value of product feature changes
- Quantify the price premium associated with your brand
- Gauge demand change of price changes
- Learn how your product with compete in the current (and future) competitive landscape
- Measure cannibalization of share from existing products/ see how you could steal share from competitors
- Determine the price/feature combinations that lead to the ideal product mix
- Conduct strategic pricing – test novel price ranges for current or new products
- Understand which features or offerings should be bundled together to reach the greatest number of people
- Measure preference for bundled versus a la carte purchases
Below are some tools/methods elucidate uses in product development research.
We have conducted dozen of conjoint projects, from straightforward product optimization to complex product line-up configuration and pricing. Conjoint is a great tool that forces respondents to make difficult trade-offs, just like real-world buyers have to do. When we force them to make these trade-offs, we get a much better picture of the values of the product attributes; we get better discrimination.
We are particularly skilled in complex applications of conjoint, including highly customized versions of Adaptive Choice-Based Conjoint.
What-if Simulator (a component of conjoint projects)
A market simulator allows visibility into future product/feature/price preferences even when the market changes in the near term. Testing “what if” scenarios can guide many aspects of product development and positioning. A simulator provides a number of advantages: Lengthens the shelf life of the data Many research projects end with answering the primary research question. A simulator, when done correctly, allows for clients to go back to the research and ask “what if” questions that may not have even occurred to them during the study. This is especially useful in product development when a project is designed to see product preferences in the context of competition. When the market changes- the simulator can be used to see impacts Shifts within a given market occur all the time; a simulator can be used to see potential impacts. One example is price decreases. With a competitive market simulator, prices can simply be adjusted down (even for competitive products) and share of preference can be re-measured. Elucidate has developed a proprietary simulator that clients rave about. One client said “In my role in product development, I have used dozens of conjoint simulators, this is the best one I have ever used.” Features and advantages of the elucidate market simulator include:
- Filter / Banner capability: Can use simulator on entire dataset or sub-cuts of data
- Multiple product client share of preference: Can see preference scores for a single product or multiple products stacked on top of each other
- Competitor share of preference: Can see competitor share of preference
- Price elasticity calculator: Can see how a range of price points impacts share of preference
- Multi-view Results: can see summarized or detailed results with one click
Other advantages include:
- Very user-friendly: Takes less than 15 minutes to understand all features
- No Licensing: The product is delivered to clients and they can continue to use the simulator an unlimited number of times on as many computers as needed.
MaxDiff (Maximum Difference Scaling) is an approach for obtaining preference/importance scores for multiple items (brand preferences, brand images, product features, messages, advertising claims, etc.). MaxDiff is also known as “best-worst scaling”. Today, beyond standard MaxDiff, there are numerous ways to improve results to better answer business questions. Anchored MaxDiff takes the best of MaxDiff (valid gauging of relative preference or importance) and adds a threshold value above which absolute importance is identified. Sparse MaxDiff and Express MaxDiff allow study of 100 or more items. We are well-versed in all varieties of MaxDiff. MaxDiff scores are easy to interpret. When you see a “10” it has twice as much value as a “5” – something you can’t do with rating scale results.
Total Unduplicated Reach and Frequency (TURF) examines a variety of possible subsets of items to find the bundle that reaches the most people possible. We commonly use MaxDiff data as the input for TURF, which introduces the ability to conduct simulations similar to conjoint-style market simulations. You select which items are to be made available to respondents (as if they were in competition with one another within a marketplace). The percent of respondents projected to “choose” each item as “best in market” is computed. We are also well-versed in advances in TURF methodology that allow for the examination of very large subsets from very large total sets of items.