Data Analytics

Information is not Knowledge

In marketing today, there is a lot of talk about big data and analytics to generate insight out of the mass of data and translate it into actionable recommendations. In market research we collect masses of data, much of which is ignored. iReach has built an Analytics Practices to inspire knowledge from more detailed data analysis and modelling to uncover more insights for sales and marketing specialists in 4 key areas:

Marketing Segmentation

Successful segmentation depends on understanding what consumers need, how groups of consumers differ from one another, and how consumers decide among products. Identify those consumers that are most likely to buy your product and ensure your messaging and promotions are talking to them directly.

Choice Modelling

Experimental designs that are tailored to the specific objectives, constraints, and variables of the project to predict consumer preferences and purchasing behaviours. In every New Product Development, product owners are challenged with making the right choices. ‘Gut feel’ is not enough in the competitive environment that every brand in every category faces.

Marketing Mix Modelling

Marketing mix modelling measures the potential value of all marketing inputs and identifies marketing investments that are most likely to produce long-term revenue growth. Simulation of such market opportunity will ensure brands launch products with the winning mix of attributes and features.

Predictive Analytics

Forward looking data science increases the returns on marketing investments by implementing predictive models. Blending Market Research data with internal data such as a CRM can uncover new opportunities for brands.

Key Benefits: