Market modelling, A/B testing, network theory and social network analysis, and spacial analysis are some of the techniques used for optimizing and analysing elements of the marketing mix, for instance, advertising on the internet.
Many theories abound in marketing on subjects like advertising, brand equity, product optimization, pricing, promotion and so on. Market models “operationalize” these theories into practical solutions using a set of predictive modelling techniques such as regression for instance, to construct models that predict the probability of an outcome.
Market modelling is extensively used in areas such as market segmentation, brand equity analysis, advertising effectiveness, price optimization, promotions evaluation, etc. (For details, refer to Chapter Market Mix Modelling).
A/B testing (aka split testing or bucket testing) is a technique where a control group is compared with one or more test groups, to determine which treatment produces the best results. Examples in marketing include controlled store tests, controlled website tests and copy testing of online advertising. When more than one variable is simultaneously tested (A/B/N testing), multiple test groups need to be formed. In such instances the use of big data helps to ensure that sample sizes are adequate to detect meaningful differences between the groups.
Network theory is a branch of computer science concerned with the relationship between discrete objects. Applications of network theory include logistical networks, gene regulatory networks, metabolic networks, social networks, epistemological networks, etc.
Social network analysis is an application of network theory to analyse social networks. For instance how information travels in a community, or the influence one individual has over others. Applications include identifying opinion leaders to target for marketing.
Spatial analysis or spatial statistics is the study of topological, geometric, or geographic properties of objects. The propagation of geographic information systems (GIS) is driving the use and application of spatial analysis in marketing and operations research, for instance, the optimization of the location of stores based on the movement and buying behaviour of target consumers.
The R language, an open source programming software environment for statistical computing and graphics, is widely used for developing statistical software and data analysis. It is part of the GNU Project, a collaboration that supports open source projects.
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Is marketing education fluffy too?
Marketing simulators impart much needed combat experiences, equipping practitioners with the skills to succeed in the consumer market battleground. They combine theory with practice, linking the classroom with the consumer marketplace.