Decoding what consumers really want: How to accelerate innovation with AI-enabled consumer insights

Decoding what consumers really want: How to accelerate innovation with AI-enabled consumer insights

An unprecedented opportunity exists to equip innovation teams directly with consumer insights. Using AI in product development, consumer brands can bring new products to market faster and more cost-effectively. In this Intelligence Brief, we illustrate how companies can harness the power of AI to enable consumer-centric brand development using the mental health wellness space as an applied example.

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Decoding what consumers really want: How to accelerate innovation with AI-enabled consumer insights

Providing market feedback to technical innovation teams via a market research team can be cumbersome, ultimately increasing the time and cost required to launch products. An opportunity exists to equip product development teams with AI-enabled consumer insights (AICI), providing data-driven feedback on consumer behaviors, needs, and preferences to quickly inform technical product development decisions as they craft champion products.

How AI-enabled consumer insights work:

AICI platforms harness data from multiple sources (social, search, survey, and more) and apply advanced AI and data-mining algorithms to uncover predictive and prescriptive insights. These solutions operationalize AI and extend its value beyond market research and customer insights groups, which include product development and innovation.

Currently, shopping activities are moving online and emerging technologies such as AI, chatbots, and virtual reality are disrupting antiquated data collection processes enabling new ways to gather and analyze consumer data. Thus, market research is reimagined by tapping into new datasets of consumer behavior that are vast, high-quality, and updated in real-time.

AICI is good, but not great without human expertise:

AI is great in concept, but it is difficult to gain meaningful insights from generic models, and training a custom model requires a significant investment of time and money. PreScouter simplifies this process by combining AI analysis with our proven approach to quickly and efficiently achieving actionable insights.

Here’s what PreScouter does differently:

  • We ask the right questions: PreScouter has the capability and skills to research the space beforehand, assessing both technical and market data, before deciding what consumer data we are looking for.
  • We make building the AI model a conversation: As with all our work, we do not simply deliver results to the client but engage them in iteratively developing the questions to be addressed by the analysis.
  • We have the right resources to fine-tune the model: Our PhD-level analysts use their expertise to refine the results to the desired level of accuracy and precision.

Using AI-enabled consumer insights to find “the next big thing” in mental wellness supplements:

In this Intelligence Brief, we showcase the combination of PreScouter’s custom AI-Enabled Consumer Insights (AICI) analysis with PreScouter’s technical analysis capabilities to inform early-stage product development. This process provides innovation teams with answers to the following product development questions:

  • Our marketing team found an opportunity to launch a mental wellness supplement, but they don’t have the bandwidth to support the prototyping process for another 6 months, how do we keep this project moving forward?
  • We found several efficacious ingredients aligning with our “backed by science” brand: which ingredients are popular amongst consumers? Which other ingredients should we should consider? What time of day do people use these products? Are there consumer behaviors that we should consider?

Science meets AICI:

We built an AI model trained to find answers to the following questions.

  • What active ingredients could be used in a consumer product to tackle anxiety, depression, stress and support mental resilience, improve mood, and contribute overall positively to overall mental & brain health?
  • Which ingredients have the highest potential to achieve beneficial outcomes?
  • For the most promising ingredients with clinical efficacy, which are most popular amongst consumers?
  • What are the specific mental health categories should we target?
  • What co-ingredients should we consider formulating with?
  • What product format and dosages are typically discussed by consumers?
  • Are there consumer behaviors providing an opportunity for additional products for a line of mental health products?
  • How could the timing of product launch be optimized?

Key findings:

There are 22 active ingredients that can help tackle anxiety, depression, and stress, and supporting mental resilience, mood improvement, and overall mental & brain health.

  • Three of these were shown to have the strongest clinical efficacy amongst ingredients associated with the mental wellness areas of interest and were selected for AICI analysis.
  • One of these three was shown to be the most consistently discussed for over 3 years straight.
  • PreScouter’s interactive retrieval-augmented generation (RAG) tool rapidly assessed answers to specific questions using the social platform discussions which we also validated with quantitative machine learning analysis.
  • We provide five targeted product development recommendations on formulation, market focus, and format.

The full details regarding these key findings and more are presented in the Intelligence Brief.

At PreScouter, we are already working with clients in areas such as cosmetics, fashion, and cannabis to build custom AICI solutions, helping our clients save time, make better decisions, and get products to market faster.

Reach out here to learn more about how you can leverage our AI capabilities.

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