Survey Predicts Big Year for Predictive Analytics in Retail

January 02, 2014

Today we announced the results of a new survey where 70 mid-market retail and e-commerce executives shared information about their use of big data and predictive marketing analytics in day-to-day marketing. The findings show that big data marketing gained traction among mid-market retailers in 2013, and there will be continued traction in 2014.

Based on the survey findings, AgilOne was able to identify ten 2014 big data marketing predictions that pertain to mid-market retailers. The findings are best summarized in this infographic below.

Or download the full report here.

How marketers will use predictive analytics in 2014.

Or alternatively, here are our main predictions in written form:

1) 80% of retailers will have a central customer data warehouse with the ability to link all data points to unique customer channels.

2) More companies will integrate offline, call center and loyalty transactions with their online customer data.

3) Nearly 70% of retailers will be using predictive analytics for at least one of their sales channels.

4) Marketers will move beyond using only likelihood to buy predictions and will begin to utilize recommendations, customer clusters and likelihood to churn predictions.

5) Predictive modeling will move beyond email and direct mail to include social media and offline transactions.

6) Nearly 70% of retailers will be doing customer segmentation.

7) Marketers will move beyond new customer welcome campaigns (and finally) launch abandoned cart campaigns, customer win-back campaigns and VIP customer appreciation programs.

8) Over two-thirds of retail marketers will decide how to invest their marketing dollars based on which channels attract the highest customers with the highest lifetime value.

9) Almost half of marketers will have tried Facebook lookalike campaigns to acquire more valuable customers.

10) Half of retailers will outsource the creation of analytics models, but most will have marketers on staff that actually know how to use analytics models.

Download the full report here.