6 June, 2024

Predictive Market Research , Market research

Concept Testing in Action: 3 Practical Concept Testing Examples

From new product variants and service offerings, to creative territories, concept testing is vital to mitigate risk, identify winning ideas, and ensure data-driven decision-making when bringing something new to market.

In this article, we’re going to be taking a closer look at concept testing, including some real-world concept testing examples to help inspire your pre-launch testing strategies.

Let’s dive in!

Why is concept testing important?

Concept testing refers to the process of evaluating and validating ideas from early-stage to later-stage to determine how they are likely to perform in-market once launched. Through concept testing, companies can gain a clearer understanding of how a target audience is likely to respond to new products, services, campaigns, or other ideas while gathering valuable feedback to refine and improve the ideas under testing.

Concept testing optimizes the development process by ensuring that resources are directed toward ideas with the greatest potential, greatly improving the chances that a new launch will succeed.

Concept testing can be applied to every individual step of the development process, helping to identify not only the most viable products or services, but the most resonant logo ideas, messaging, naming ideas, and more.

Some concept testing examples include:

Test the viability of multiple concepts to narrow the field
Test new product packaging
Test claims or the prominence of claims on packaging
Understand consumer reactions to new product forms or flavors
Evaluate product repositionings or line extensions relative to your competition
Gauge consumer reaction to promotions
Identify product attribute importance, including drivers and barriers
Evaluate ads and messages

Concept testing is vital for providing companies with the data they need to make informed strategic decisions throughout the development of something new, mitigating risk and maximizing the chances of in-market success.

For the past decade, CRG Predictive Intelligence has validated its innovation success by comparing our concept testing results against Circana’s in-market retail sales data. The result of this research-on-research has yielded a 90% prediction accuracy on product concepts year after year.

Additionally, we have validated our method against more traditional monadic concept testing approaches and MaxDiff techniques.

CRG’s research initiatives have revealed several reasons to consider prediction markets for your next breakthrough innovation need:

Prediction markets have been shown to identify disruptive or breakthrough concept potential better than traditional survey testing
The further out from an event, the more accurate prediction markets become versus “claimed” self-reported future consumer behavior
Truly disruptive concept probabilities will diverge, while concept diagnostics for less disruptive, or closer-in ideas, will be highly correlated
Prediction markets deliver proven accuracy when key measures are framed in a targeted or Job-to-be-done specific context
Extensive normative database

Predicting the Growth of Plant-Based Proteins

Learn how HUUNU predicted key consumer trends in the plant-based protein market.

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3 real-world examples of concept testing

CRG Predictive Intelligence applies an industry-leading prediction market methodology to the concept testing process, helping companies measure metrics like “purchase likelihood”, ”relevance”, “advantage”, “solves a problem” and “job-to-be-done”. Combined with qualitative rationale, the result is a crystal-clear picture of the likely success of the concept under testing, including valuable feedback on how it might be refined or improved.

Here’s how three CRG Predictive Intelligence customers tested their concepts using the HUUNU platform:

Concept testing example 1: New product innovation viability for an allergy/cold medication manufacturer

As previously noted, prediction markets have been proven to identify disruptive or breakthrough concept potential much better than traditional survey methodologies. Simply put, truly disruptive ideas are easily missed using traditional survey techniques because the idea may be considered too high risk or the appeal may not hit certain thresholds for success if it was intentionally developed for a niche audience.

One CRG client, a cold and allergy medicine manufacturer, used CRG’s prediction market methodology to test new product forms and flavors for viability, while managing to surface breakthrough ideas, successfully identifying numerous truly disruptive product concepts that went on to achieve significant in-market success.

Concept testing example 2: High-risk/non-starter use case for a top health and beauty brand

A health and beauty brand approached CRG after traditional survey methods reported a new acne product to be high-risk. The brand felt there was merit to the idea and wanted to be absolutely sure it was a non-starter before pulling it from development. They wanted to give it a fair shot by testing the concept using CRG’s alternative methodology.

CRG tested the product among the target audience it was designed for, and results showed it was worthy of greater consideration – it was neither high-risk nor a non-starter. Upon launch, it became a number one-selling acne treatment product on the market and won Allure Magazine’s Best Beauty Award – neither of which would have happened without CRG’s prediction market concept testing approach.

Concept testing example 3: Frozen novelty testing for a popular ice cream brand

A popular ice cream band was looking to expand its product offering to include new frozen novelty forms. There were seven concepts on the table, and the objective was to use concept testing to understand each variant’s likelihood of success quantitatively while understanding the key themes associated with each concept for consumers at a qualitative level. CRG’s concept testing revealed that one concept clearly outperformed the others on each of the key measures, so this concept was prioritized for full development.

Expertly test concepts and early-stage ideas with CRG

For the last decade, CRG has been helping companies optimize their development processes with industry-leading insights, delivered via the cutting-edge HUUNU platform. In the HUUNU prediction market methodology, participants are challenged to participate in a betting game, where they bet virtual currency on how they believe a concept will perform among a certain target market. How much and how quickly they bet gives companies deep insights into the emotive response, tacit knowledge, and collective judgment of the market participants. Each quantitative bet is backed up by a qualitative rationale at no additional cost, delivering important insights into what drives and motivates the target audience.

With HUUNU, brands can gain access to the following concept testing deliverables:

Prediction Likelihood Index: A summary overall prediction score on key success metrics, reported on a 0-100% certainty scale (e.g.: new mothers are 89% likely to buy this product, etc.).
Preference Prediction: A metric showing the proportion of participants betting for and against each outcome in the prediction market betting game.
Strength Meter: A summary of the intensity of positive or negative betting activity on each outcome or answer.
Verbatim Explorer: A pivot table that provides detailed qualitative rationale on all positive or negative predictions, with a summary of highlights from all feedback.

The result? An unprecedented strategic advantage and accurate decision-making at every stage of the development lifecycle.

Learn more about CRG’s Advanced Concept Testing solution today.

FAQs

What metrics or data are typically collected during concept testing?

This depends on the partner you’ve chosen to carry out concept testing. With CRG, an example of concept testing metrics typically included are:

Purchase likelihood
Uniqueness
Relevance
Advantage
Solves a Problem
Job-to-be-done

How do you analyze and interpret the results of a concept test?

In a prediction market, concept testing questions are designed to measure the likelihood or probability (0-100%) of an event happening. Participants are not asked to report their own preferences or opinions, but rather to predict how they feel a target audience might respond to the concept under testing. Leveraging a validated prediction algorithm, HUUNU quantifies a Prediction Likelihood Index for each question based on the collective judgment of the participants. The analysis would then be presented as a probability, for example, “dog owners are 87% likely to buy this product”.

What are some best practices for communicating concept test findings to stakeholders?

Numbers and facts are not all stakeholders want to know when carrying out concept testing. The qualitative rationale is equally, if not more, important. Stakeholders want to understand things like, why was this concept so well received? Conversely, why did this concept bomb? Can this idea be refined or salvaged? Qualitative rationale on each quantitative measure is absolutely invaluable for stakeholders and should be part of any concept testing methodology.