Analytics Is Getting Better
At Predicting Individual
Consumer Behavior And
Prescribing Business Actions
Written by Rob Lane.
Every time we electronically interact with a brand or its website, we leave behind a trail of data touch points. Being the creatures of habit that we are, hidden in this digital trail are insights about our buying patterns, our personal preferences for new things, and even hints as to what we are likely to buy next. Deciphering this data into information retailers can understand and act on is at the heart of analytics for ecommerce.
Many companies are utilizing various levels of descriptive analytics to learn what has happened to them in the past, and predictive analytics to predict future consumer patterns. Prescriptive analytics goes a step further, learning from consumer behaviour in order to prescribe actions designed to attract and retain customers at various points in the consumer lifecycle.
Analytics has come a long way from its humble beginnings in the late 90s, when it first appeared as a way to quickly process mundane website tracking results.
2. Google Analytics Arrives
3. Descriptive Analytics:
What Happened To Us?
Descriptive statistics can provide valuable insights for business decision makers, but are limited in that they only aggregate, summarize and display historical data. Even what many consider to be advanced analytics are really just applications of filters on the data, such as geo-location, before producing advanced descriptive analytics.
4. Predictive Analytics:
What Are My Customer Going To Do?
By segmenting their market into distinguishable groups, based on a prediction of future buying patterns and preferences, companies can more effectively pitch products, offers and messages that are more likely to resonate with specific consumer segments:
Predictive analytics is light years ahead of simple data aggregation and output, and can provide valuable insights as to what managers should do in order to appeal to certain segments; however, it still leaves lots of room for errors based on assumptions from the past, and the limits of lumping people into groups. According to the distinguished author of Big Data at Work and Competing on Analytics, Professor Thomas H. Davenport:
5. Prescriptive Analytics:
What Are We Going To Do?
The next level of analytics technology for business, prescriptive analytics, involves combining what’s been learned in the past, taking into account present consumer activities in real-time, and suggesting a course of action for business managers:
6. What's Next?
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