Health and Beauty Ingredient Selection: Familiarity-Desire Analysis

Understanding consumer desire for product ingredients is important, but ingredient familiarity is also important to consider. Consumers may have low desire for an ingredient because they are not familiar with it, despite the ingredient providing excellent benefits.

Hit Laboratories developed the “Familiarity-Desire” (F-D) ingredient analysis to help health and beauty product developers with their ingredient selection and marketing.

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Ingredient desire results. Results based on a target market survey.

 

Familiarity and desire scores are calculated from several survey responses. The results are different for each product tested, since ingredient desirability depends on the specific application.

The chart below shows familiarity and desire scores plotted across four quadrants. For this product, Aloe vera is both highly desirable and familiar to consumer respondents. Corn oil is the least desirable ingredient, and it’s familiarity in this application is also poor.

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F-D Analysis results determine which ingredients to feature in the tested beauty product

 

Which quadrant an ingredient falls into determines how it can be treated for marketing purposes. This helps answer the question of which ingredient should be positioned as the “hero ingredient”, which ingredients should be featured, and which may hurt a product’s marketability.

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The F-D Ingredient Analysis is a standard component of the Cosmetics Assessment Standard (CAS) study, which assesses the appeal of new health and beauty products and provides actionable product improvement and marketing insights.

How to Test Your Product Idea Using Concept Validation Surveys

Getting early market feedback is crucial for consumer product development. While this is widely known, the different available methods can be confusing for inventors and marketers.

Few things compare with concept surveys for speed, validity (statistical power), and depth of results. The main purpose of this early-stage survey is to benchmark the appeal of a new product idea against similar alternatives that are already in the market. If the product scores higher than the alternatives, it’s a good sign of potential product viability. If not, the results will show where the concept is weak, and may suggest improvement ideas.

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An excerpt from a new product concept survey report. The tested product’s viability metrics are compared against those of benchmark products. The study type shown is for testing the viability of new beauty products.

Various study configurations are common, but they all typically employ 200 or more respondents, are conducted through online questionnaires (which significantly improves speed and cost).

Respondent recruiting is an important issue, and targeting criteria will depend on the purpose and stage of the survey. A “mass-market” sample (which is representative of the general adult population) can help identify the product’s target market by reporting which segments have the greatest interest in buying the product.

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Example demographic response to a new invention idea, used to help identify the target market.

If the target market is already determined, the survey sample can be recruited from that specific population (for example, “US women age 18 to 24”, or “dog owners age 50+ in Florida”). From that population, different product variations (“concepts”) can tested to determine which has the best sales metrics.

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The purchase intent for a new product is displayed by region, indicating where the best region to launch the product may be.

Some early-stage developers choose to conduct their own informal surveys, which can help determine consumer preference or critical product flaws. Professional research can be a worthwhile investment because do-it-yourself surveys may not pass the Investor Test. If you conduct your own surveys, be sure to address these important issues:

  • Questionnaire design: it’s easy to write questions that are confusing, leading (causing bias), or can be interpreted in several ways. The manner and order in which you ask questions can also significantly affect the responses.
  • Benchmarking: if you learn 50% of respondents “like” your product, is that good or bad? Without a database of other results, or running benchmarking surveys, the results are inconclusive.
  • Sampling: finding respondents who represent your target market is always a challenge.

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An excerpt from a new product concept selection survey. The results for one concept variation are shown, which would be compared to other variations also tested.

Using the “Investor Test” to Prove New Product Ideas

Inventors face many challenges, and perhaps the most serious is the issue of marketability. After all their invested time and effort, will they be able to raise funding for manufacturing? Will they be able to get retail distribution? Will anyone actually buy it?

This issue is known as concept validation, and there are two key components for product development:

  1. Technical Validation: Proving the invention is technically possible (that it will work properly)
  2. Market Validation: Proving that people will buy the product (in sufficient quantity, at the required price)

A characteristic of inventors is that they tend to like inventing, leading them to focus on technical validation. At some points, perhaps after perfecting their prototype, or receiving their first sample batch, they must address the second and larger challenge: proving people will buy it.

An easy way to know if you’re validating your product idea sufficiently is with the “Investor Test”. Ask yourself:

If I showed the results to an investor, would it give them the confidence to invest in my product?

This is a very relevant question because many inventors eventually find themselves asking that exact question.  A good invention validation method will be:

  • Quantifiable: instead of vague observations, results should be measurable (numeric).
  • Reproducible: you could run the test again, and get similar results.
  • Trustworthy: conducted by competent people, in an unbiased manner.

While asking family and friends what they think of your new invention is a good idea, it clearly fails the “Inventor Test” of concept validation:

  • It’s not quantifiable because the results are typically qualitative responses like “that’s a good idea, can I get it in blue?” Even if you attempt to measure their responses, the results won’t be statistically significant unless you survey many hundreds of friends.
  • It’s not reproducible because you can only observe the initial reaction of your friends and family once.
  • It’s not trustworthy, because your friends and family have inherent biases not present in typical consumers.

It’s naturally a good idea to validate your invention idea in multiple ways. This will give investors more confidence to fund your product, and give you more assurance that you’re on the right track.