Consumer-facing brands should leverage bespoke consumer feedback data to train or fine-tune AI / ML models to get ahead. These expert models can help them gain valuable insights into consumer preferences, behaviours, and sentiments, enabling them to optimise product descriptions, packaging design and advertising copy.
One application we have developed for such AI models is to assess and classify product reviews with helpful tags. Using consumer feedback as the basis, we have created proprietary measures of product reviews, such as how influential an individual review is and how strongly it reviews the product's taste or effectiveness.
By analysing these new measures, brand owners can identify their performance and patterns in consumer reviews, generate new insights, compare themselves to competition and even highlight individual reviews for a specific purpose, such as "suitable for advertising".
Using bespoke shopper data to train AI models represents a significant opportunity for consumer-facing brands to enhance their understanding of consumers and markets.
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