December 30th, 2014 by Chance
To celebrate 2015, we’re offering a New Year’s Quick Start package, sign up for yours today. With holiday shopping fever fading, we’re taking a look at retail analytics trends for 2015. We’ve also provided a guide to basket (affinity) analytics for insights into customer purchase behavior.
* 2015 Retail Analytics Trend Report: Five trends that businesses will need to jump on for 2015.
* Basket Analytics for Retail: How you can analyze your customer data to increase sales volume.
Want to jump start your new year? Need expert consulting for your 2015 data and analytics strategy? Launching a new product or feature to kick off 2015? Looking for content development to meet client needs?
We’re starting 2015 out right with our New Year’s Quick Start!
This offer includes three days of consulting with our expert business intelligence and data analytics team. We will work with you to customize the project scope depending on your needs.
Let us get you started with a Happy New Year!
Contact us before January 15, 2015, to take advantage of this offer.
2015 Retail Analytics Trend Report
The 2014 holiday shopping season has illuminated some important consumer trends that we will see retailers leverage for 2015.
Consumers are increasingly using mobile devices to educate themselves about purchases before they make selections. Here are five analytics trends that retailers will need to capitalize on in order to stay ahead of the competition.
Basket Analytics for Retail
Understanding how to analyze customer baskets is the key to recommending relevant products and generating more revenue. Basket analysis provides evidence-based models of customer purchase behavior so that a retailer can make the right product recommendations at the right time.
Running affinity analytics on a customer purchase data set can reveal strategic insights that can jump start sales velocity and volume. Large retailers have been at the forefront of experimenting with basket analytics and recommendation engines, but any company with customer purchase data will benefit from analysis of the behavior patterns of their target consumers.