In the era of cognitive marketing, decision-making and problem-solving will be aided by smart machines that sense, learn, infer, and even think on behalf of humans. Such machines outperform humans in several areas, especially those that involve uncovering patterns that can be used to predict human behavior.
For an automotive client, we used behavioral segmentation to help accelerate their customer journey. This kind of segmentation groups buyers by what they actually do, which creates a tailored, relevant, uncluttered, direct path to purchase. Our behavioral approach extracted raw clickstream data to perform feature engineering. A similar graph was built for clustering to reveal distinct website behaviors. These clusters have a natural interpretability with website interaction and the customer journey. As a result, five distinct customers segments were extracted, with each segment having specific intent that can be mapped in the path to the purchase funnel. For each segment, focused content and product recommendations accelerated the journey path towards conversion.
The ability of smart machines to manage new oceans of data generated by a hyperconnected economy has become increasingly viable, given advances in hardware, data science, advanced analytics, artificial intelligence and smart machines. Their greatest value lies in their ability to identify trends that their developers never imagined.
