Friday, 21 December 2012

What are the steps in NBO (Next Best Offer) to give Personalized Promotion

Personalized Promotion / Next Best Action (NBA) in Retail

Increased Personalization is a trend that is common in all industries , particularly, the Retail one
According to a Research, a personalized upsell or cross-sell offer is 30% more effective when delivered within two seconds of initial product selection

The steps, models or algorithms in NBO (Next Best Offer) to give Personalized Promotion are shown below:

The combination of these models would provide a great insight into the customer behaviour and his product and offer preferences, which in turn can be used to provide him context and location senstive appopriate product as the promotions

Big Data and Personalized Promotions

With the advent of Big Data - the Analysts can store huge amount of data and analyze them using Big Data Analytic tools. One such is +SAP HANA , which can be used collect personal customer information and provide optimized offers based on their individual histories and preferences

There are many open source softwares like 'R' and +Hadoop that are spear heading the personalized promotion algorithm development

With the cost of big data hardware on the decline this trend is definitely going to speed up

How Recommendation Engine Works

Recommendation engines are a craze these days. +StumbleUpon  recently fired half of their marketing staff and hired Data Analysts to build a recommendation engine that predicts accurately (or more accurately) the links that it provides to the customers

Recommendation engine work on the same principle of other statistical engines - they are sometimes called personal promotional engines. The key here is to

1) Analyze Data
2) Create Segments / Groups
3) Create Models (Statistical)
4) Send and Measure Offers
5) Re-Calibrate the Model
6) Re-Issue Offers

How to Create Personalized Direct Mail Offers based on Shopping Patterns

Kroger - one of the world's leading grocery chain creates personalized offer on individuals (not segments).
Kroger tracks each customer as an individual. The quarterly mailers it sends contain 12 coupons specific to an individual household and are carefully designed, thanks to dunnhumby's insights. Each part of the coupon is carefully popluated with product choices from the customer's previous
shopping patterns. The last two coupons are for experiments, such as adjacent products — a purchaser of baby food who doesn’t buy diapers might see an offer for diapers.
Apart from suggesting the offers for the customers, dunnhumby also provides insights on placement of these products with the help of data analysis

CVS issues weekly sales circular using a feature called myWeekly Ad

This feature uses insights generated based from customer data and transactions to arrive at appropriate offers


  1. Price Elasticity Modelling is the key for Offer Optimization. Though time and channel has some impact - the reason someone redeems/uses and offer is just for better price

  2. Next best action involving social media data is bit tricky. All the insights one has generated from transactional data might be wiped out due to soreness of social behaviour

  3. The offer is not a best offer until proven. So all offers are test offers and the best offer is the one that has achieved the goal


Related Posts Plugin for WordPress, Blogger...