Work Your Promotional Data Harder: Drive More Trips & Bigger Baskets

Everyone loves a good deal. For decades, printed circular and coupon-based promotions have been an integral part of the retail strategy to boost sales and acquire new customers. While print advertising is still alive and well, many retailers and brands now leverage digital technology and channels to offer customers an alternative way to engage, browse, and shop. Black Friday has evolved to encompass both Black Friday and Cyber Monday, and many retailers now additionally have a website, a mobile site, and an app as well as their own digital circular. With this shift towards a multi-channel environment, many different types of granular promotional data are being generated more quickly than ever.

In today’s retail world, retailers need to be able to leverage all of this promotional data and measure a promotion’s full impact on the total business. As fundamental as it is, however, this is more challenging than meets the eye:

  • Promotional data sit in silos, preventing access to a comprehensive view of detailed data
  • Item and basket-level detail is necessary for understanding promotional effectiveness, but disaggregating data is often a time-consuming, manual process

Retailers should look at three key focus areas to improve promotional analytics:

STOP using data in silos and having a fragmented understanding of a promotion;

START using all relevant data to understand every element surrounding a promotion.

Promotional data often sits in silos, and bringing it all together can be a manual task – especially if analysts lack the means to consolidate everything efficiently. Look for a more efficient and automated way to unify the disparate data sources. With a comprehensive view of detailed data, you can understand everything about a promotion from depth of discount to margin impact to trips driven.


STOP using summarized data and inaccurately measuring promotional performance;

START leveraging basket-level details to drive better promotional offers.

With data often available in aggregated or summarized form, promotional details are lumped together into one bucket, regardless of the type of promotion involved (eg. in-store circular and direct mailers are often both tagged as features). It’s important to disaggregate and measure these separately – what works for a shopper via in-store circular may not work via a direct mailer. By accurately measuring the performance of different offers, you can reach the right customer with the right promotional offer. 


STOP limiting promotional analysis to just the featured item;

START measuring the full store impact to see what drives more total dollars.

With countless promotion types, time periods, and metrics, it’s highly time-consuming to analyze multiple inputs and dimensions using a spreadsheet. As a result, retailers often can’t see the impact beyond the item or even the immediate category. With a broader and more flexible view of data, you can investigate the full performance of promotions to identify the ones that drove the most trips or largest baskets and make better decisions about future promotions.



In the ever-evolving retail landscape, retailers need to be able to quickly adapt and get better at conducting promotional analytics to survive. Download this guide to learn more about:

  • The real barriers to effectively measuring promotional performance
  • How to use the granularity of data to drive better offers
  • How to account for total store metrics in your promotional strategy


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