The approach starts by creating micro-segments based only on certain a priori ad-hoc group of variables such as behavioral data, demographics, attitudes, drivers, barriers, etc.īy achieving the most granularity from each group of variables and ensuring that there are no variables with higher weight than others, these micro-segments ensure sample accuracy in the creation of overall segmentation. How does our unique ensemble clustering approach work? In some cases, given the nature of the data, some algorithms are not appropriate to identify the patterns of similarity, and in some others, two algorithms can lead to different segmentation results.įor instance, k-means would put consumer A and C in the same segment and B in another segment whereas latent class and hierarchical clustering would put consumer A and B in the same segment and not C.īecause of this, at SKIM, the backbone of our segmentation methodology focuses on capitalizing the strength of many of the available algorithms via a unique ensemble approach. Stage 2: Ensemble segmentationĪfter we have our final data set, we proceed to apply the clustering algorithms.
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Some of the checks performed include data recoding, data scaling, correlation plots and variable merge via principal components analysis. Additionally, given that the data might come from different sources or tackle different areas, a thorough data pre-processing stage prior to running of any algorithms is done. Stage 1: Data Reductionĭuring the data selection, based on your research objectives, budget and timeline, we align on the characteristics needed to answer your business questions. SKIM uses a two-stage process to ensure that both elements will be covered properly. We aggregate multiple data sets, such as survey and client data, for more robust and actionable recommendations.įor a good segmentation there are two important aspects: the characteristics of the data and the algorithms applied to analyze it. The SKIM segmentation solution utilizes advanced analytics and data fusion techniques to allow brands to better identify customers’ evolving preferences. To understand preferences and trends so you can target your audience with the right marketing messages.To successfully position yourself against your competitors when entering a market or launching a product.To create new products that satisfy the needs of different consumers groups in the market.Segmentation analysis supports the following: This in return gives the ability to create tailor-made and relevant advertisement campaigns, products or to optimize overall brand positioning. Segmentation analysis is a marketing technique that, based on common characteristics, allows you to split your customers or products into different groups.