The client, a US based market research agency were developing a Software-as-a-Service market research solution, for their clients in the Consumer Goods industry.
They wanted to be able to combined multiple data sources, including unstructured eCommerce product listings and reviews, to large consumer surveys and social media data. This aim was for this platform to provide clients such as General Mills, Nestle and the Food & Drug Administration transformative insights across areas such as consumer trends, brand health, product distribution and pricing.
We designed and delivered an insights platform with a range of syndicated solutions to provide targeted insights directly to the fingertips of Consumer Goods brands in near real-time. Our automated solutions captured consumer data from online sources such as large-scale quantitative and qualitative surveys, social media and eCommerce product listings, and applies advanced Large Language Models (LLMs) to identify and analyse this data across core attributes such as brands, product categories, claims and ingredients.
We produced tailored solutions around Consumer Insights, Brand Health tracking, Product Distribution &Pricing Trends and Social Listening, to enable marketing executives to identify opportunities for new product development, optimize their marketing spend or product branding and positioning. Our solutions were delivered and rolled out on time and under budget and are frequently used by over hundreds of Consumer Goods companies within the US & Canada.
New solutions & increased revenue
Together with the client we designed and developed a range of brand new syndicated solutions for the market research platform. These became a key part of their offering and made up a large proportion of the solutions' revenue.
New AI models to identify trends and consumer segments
We build advanced NLP models to identify consumer personas from their social profiles and detect emerging consumer trends, which brands used to improve their product portfolio. We also developed consumer segmentation models using advanced machine learning, enabling brands to optimize and target their marketing spend.
Automation to reduce time on support & maintenance
Through a concerted effort to automate the solution, from automation of data pipelines, through to automation of manual annotation and testing, we were able to significantly reduce wasted time and resource.
This led to efficiencies of over 70% which equated to over $1m in annual savings.