Can you double your promotion ROI?

Running a promotion is a big deal. It may involve creating tailored displays, marketing communication and setting aside a substantial investment to fund discounts.

Producers and Retailers have relied on promotions to create uplift, drive margin or share or introduce a new offering. Over the last decade, the overall promo pressure (volume x depth) has steadily increased, making it the single largest commercial investment that that producers make up, going up to 18% of their P&L in fast-moving or luxury consumer goods. In total, producers spend about billions on their promotions every year.

Getting it right is therefore important and producers and retailers a alike put a lot of effort in their promotion strategy and tactics of designing effective promotions. There’s an increasing offering of support to add insight with optimization tools that capture elasticity, cannibalization, forward buying, category effects and more. This approach suggest that you can simply forecast uplift and optimize your promotion for success.

Practice has proven this wrong.

Even best-in-class models, with deep understanding of consumer and shopper behavior, can still get it wrong. The reality is that many promotions miss their mark, show mixed results, many with net negative ROI or create a very different response than anticipated.

Overall promotion effectiveness might even look fine, but under the hood, there are great differences in the traction that that a promotion gets. What might work in one place for one audience, does not necessarily work across the board. Differentiated approach can superior to the search for the best average approach to serve all.

In addition, it is unclear how good the promotion could have been. Could it have achieved similar results with less discount or a different phasing? Finding and doubling down on what shows superior results can be far more effective than good promotions.

The online world has already come to terms with this and replaced the one-shot general approach for a promotion, with a system to test & learn what works. Launch several versions, pick-up what works and then double-down on the successful elements. This could be anything related to the promotion mechanics (depth, offering), communication (visual, message, style, etc) or ways to approach the target audiences (direct, referral, omni-offering, linked to loyalty or personalization, etc). A lot of ROI potential for a promotion event is discovered, rather than planned.

Imagine that you could bring this ability to a real-world setting of promotions.

This could unlock a pathway towards promo ROIs, which are at least double compared to traditional offline variants.

How to emulate the online promotion approach in a real-world setting?

There are two major hurdles to get iterative testing & learning in a real-world setting anywhere close to the system that we know online:

• Granular, real-time measurement of performance. The performance of the promotional display, its individual shelves, products and associated comms, all get lost in PoS data.

• Responsive system to redeploy the display with certain improvements. This is difficult in (traditional) retail operations and would require a significantly easier way to launch waves of displays, each with improvements that can tap into higher ROI

The critical enabler would ultimately be is a promotion display that could measure critical success metrics, like the rotation of individual products, linked to various attributes of the display location, planogram, promotional price and offer.

These could, in turn, be used to identify pathways for ROI improvement with feedback from the live display, e.g.

-Differentiated depth & mechanism, avoiding going too deep (too soon)

• Display deployment optimization (location in the store)

• Planogram optimization (which assortment, how many slots)

• Ensure compliance (was the display really in the store)

• Ensure timely replenishment (avoid running out

• And, if linked to shopper/loyalty data, ways to personalize & engage shoppers

Then, a next wave of improved displays and promotion characteristics are launched – perhaps even with differentiated approached for different stores or target segments. Think of this a multi-shot approach, where there might be 2 or 3 waves of displays. The only real requirement to achieve this would be displays that can be easily rotated with a new set, at minimal cost. Traditional displays cannot do this, but there are emerging alternatives with pooled display systems, that can rapidly be deployed, recovered and redeployed.

Here’s the interesting part. Like the online equivalent, this does not mean that you have to measure all promotion locations, all displays and all products, but create a smart sample. Have a few connected displays as ‘probes’ in your overall fleet and you can create all the intel that you would need. If these are deployed smartly, e.g. stratified and randomized, you would need a sample of about 10-15% of your display fleet.

MOOS to disrupt the promo display space

MOOS is partnering with leading display vendors to create a fleet of smart displays. These displays measure the transaction and can create the required feedback loop to improve the deployment of the displays and thereby the overall promo ROI.

First test showing the principle are very promising and our dev team is working on an integrated solutions. Stay tuned for our joint offering in this space.

If you can’t wait, then get in touch for a sneak peek.