Attributes can be captured and organized by type – demographic, physical, psychological, functional, professional, aspirational, etc. Each attribute then can be mapped on to a product, service, or piece of communication related to the original query/interaction.
Attribute Analysis has become simpler and more reliable with the growth in social listening technologies. This means when a customer today says she is ‘eco-friendly’, retailers can translate that interest into energy efficient products or a bias towards stores that don’t use plastic bags or proactively look towards reducing their personal carbon footprint by shopping online.
2. EVENT SEQUENCE ANALYSIS: This technique observes the sequence of events a customer goes through until the buy (or don’t buy) decision is reached. The objective of event sequence analysis is to understand the lead indicators for certain positive action (for example buy) or negative action (attrite).
For an e-tailer, the relevant events could be:
1. Method used for login (if it is via a Facebook ID or a Google ID, reasonably rich details about the customer become available)
2. Search terms used (example: refrigerator, power bank, LED lamps)
3. Adding items to basket or the wish list
4. Liking the Facebook page of the product
5. Crowdsourcing opinion by posting on Facebook (i.e. Apple vs Samsung)
Every event offers an opportunity for hyper personalization. These can be done by email, a chat bot, an immediate offer on the web page, providing discount coupons for select products and displaying items of interest.
This is achieved through a combination of Attribute Analysis and Event Sequence Analysis. Fundamentally, the goal is to make the right offer at the right time to ensure three things:
1. Making the shopping cycle easier and faster
2. Not losing upsell opportunities
3. Ensuring that the customer does not drop away at any stage
Attribute Analysis and Event Sequence Analysis make a powerful combination in businesses other than retail as well.
A bank can, for instance, use them to make sure a loan repayment does not lapse or a loan does not get cancelled by a customer. The bank can observe late credit card payments or an ‘unlike’ for the bank on a Facebook page to signal a customer’s lapse in loan repayment. Early intervention, at each event, can ensure the customer doesn’t lapse or move away.