Decoding & Predicting Brand Love

“Explore how Actnable Predictive AI helped a plastic goods manufacturer decode brand love and enhance brand visibility.

The Case

A leading plastic goods manufacturer wanted to understand the strength of its brand in people’s minds, perceptions, attitudes, and key drivers behind their decision-making—moreover, the key components that go into building a brand everyone loves. They commissioned a detailed market research study in major centres, and predictive modelling was performed on the survey data to understand the key drivers, perceptions and what goes behind a truly loved brand.

Approach

Based on the client’s research objectives, primary research was conducted using a survey method, and data was collected using a structured questionnaire. The raw data includes variables on demographics, psychographics, awareness, usage and preference, and perceptions.

An analysis framework was developed to unlock the insights from the data, and basic statistical modelling, such as driver analysis, brand image profile, and PCA (Principal Component Analysis), was performed. Key building blocks such as saliency, preference, and strong perception attributes (e.g., Trust, and brand love) were identified as independent variables.

Various predictive modelling algorithms, including Logit and Random Forest, were tested. Random forest brought the best performance and variable importance.

Impact

The model unleashed the key components or drivers behind brand love. The score can easily be predicted by adjusting the value of independent variables for scenario planning. This gave our client a robust understanding of brand building blocks and a scientific method to predict future insights based on available inputs. It also helped them take action to increase brand visibility, affinity, and, ultimately, brand preference.

Actnable Predictive AI

Actnable Predictive AI is a suite of advanced analytics-powered AI algorithms which empower data-driven decision-making to drive business growth.

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