Wednesday, 5 October 2016

Digital Marketing Segmentation on the basis of purchase behavior

Frequency, Recency, Amount, Categories, FRAC Analysis

Purchase behavior in the online world is a very different entity when compared with the traditional world. With the rise in social and digital media platforms, consumers are constantly evolving and changing the ways in which they research and purchase online. New shopping paths are emerging depending on behavior, device, location, and intent. It’s not just what consumers do that is important; it is also how, when and why they do it.

Consumers are increasingly distracted, but smarter. Marketers don't need to lag behind! Digital marketers need to take a hard look into the data trail that consumers leave behind. Analysis of this behavior can provide actionable insight into how consumers arrive at their purchase decision.

One of the chief ways in which this can be done is in terms of the purchase behavior of the consumers. In order to implement some key questions need to be answered. They include, what does your consumer buy online? How frequently? Each time they buy, how much do they spend? Do they buy products only from a particular category? Or do they often buy from a variety of categories? The answers to these questions will enable you to do what is commonly known as a FRAC Analysis in the digital marketing world.

Simply put, FRAC Analysis involves:
  • Frequency = the number of transactions the customer has made in a fixed time period
  • Recency = interval between the times when the latest consuming activity happened and the present
  • Amount = monetary value of each purchase action
  • Category = types of product purchased, singly or together



This is an excellent way to segment your existing customer base and slot them into buckets. Some buckets will respond better to offers and promotions than others, so your email marketing or App marketing efforts can be concentrated on them for best results. Not only that, over time, the FRAC Analysis can also begin to help you predict how the customer lifetime value changes over time and to spot trends that help you maintain/retain the hold you have on your most profitable customers.

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