Promotion optimization: How to incentivize conversions and reduce margin loss

By Ian Nadeau on March 10, 2023

Subway’s five-dollar footlong deal launched in 2008 — at the beginning of a recession — and became one of the most successful campaigns in food history. Accompanied by an unforgettable jingle, the five-dollar footlong brought customers in droves ($3.8 billion of attributed revenue within its first year) and saw Subway turn into the largest fast food chain globally. 

However, despite its success, the campaign was abruptly discontinued. Why? Because even with the increase in customers, the margin loss for Subway franchisees proved too costly. Further, giving everyone access to the deal — even those who previously paid higher prices for footlong subs — removed the underlying strategy of all promotions: incentivizing on-the-fence shoppers. Later incarnations of the five-dollar footlong deal came and quickly went, further proving that even large spikes in sales volume can be negative when done at the wrong price point. This is a key example of why it’s important to not just rely on past promotions success, but to focus on optimizing promotions that will lead to revenue growth today.

With a recession on the horizon, many brands are reevaluating their promotion plans as shoppers are becoming more spending conscious. After two years of prosperity, ecommerce sales growth in 2022 is projected to fall below 10%, which would be its lowest rate in over a decade. 

Now that companies are competing for attention by lowering prices, how can you acquire consumers without selling at a loss, or — more importantly — devaluing the brand? 

Optimize your discounts so that promotion budgets are being saved for the right consumers — increasing conversions and protecting margins — by incorporating the following into your ecommerce strategy.

9 Strategies for Retail Promotion Optimization

What Is Promotion Optimization?

Promotion optimization is the process of maximizing the effectiveness of promotions and retiring underperforming promotions to achieve specific goals such as increased sales, brand awareness, or customer engagement.

A study conducted by found that those who receive an offer experience a 38% rise in oxytocin levels and are 11% happier than those who did not receive a coupon. Additionally, VoucherCloud statistics tell us that 57% of first-time shoppers are more motivated to complete a purchase if they’re able to redeem a coupon. 

What does this mean for ecommerce brands? Greater conversion rates, increased site traffic, reduced inventory, and less cart abandonment are the main benefits of promotions. While these key performance indicators (KPIs) can help define ecommerce performance, they don’t paint the entire picture. As a result, retailers need to rethink their future promotions.

Avoid sitewide offers

Just because an offer performs well doesn’t mean it’s benefiting the brand. Many businesses deploy discounts at a loss in the hopes that gains will be realized through add-on products and services, as well as repeat visits. However, not every consumer is looking to tack on additional items. Many simply see a sitewide offer in-session and take advantage of the discount to buy the product they already intended to purchase, but at a cheaper price. Just like Subway discovered in the aftermath of their five-dollar footlong promo, discounts without a strategy only end in margin loss.

Further, sitewide offers create the following issues for brands:

  • Trains customers to search out discounts
  • Discounts are easily shareable across the web
  • Causes confusion for consumers who are excluded from the promo (e.g., only first-time shoppers are eligible)
  • Impacts the bottom line by cutting revenue from sales and depleting the promotion budget

Use case: Less is more

A leading clothier needed a solution that went above the one-size-fits-all approach to their site offers.

This required something capable of: 

  • Suppressing offers to those identified as likely purchasers; 
  • Determining the optimal offer to show based on the visitor’s in-session behaviors;
  • Identifying site visitors who might be influenced with the right offer to make a purchase;
  • And only showing offers to those who are on-the-fence, while they are still on the site.

The clothier found this solution with Session AI’s early purchase prediction (EPP) machine learning model. The dynamic segmentation of EPP allowed them to identify which visitors are likely or unlikely to buy, as well as those who are on-the-fence — meaning they’re influenceable — in real-time. This level of insight enabled the retailer to target those who may not have completed a purchase otherwise while they were still on the site. Further, the data suppressed more than 870,000 offers to ineligible consumers in the first quarter of implementing Session AI — helping them achieve promotion optimization.

This data-driven approach to promotions resulted in: 

  • 4.8% conversion rate lift
  • 8.9% increase in revenue per visitor
  • 3.9% average order lift
  • Millions saved in promotional budget

More than discounts

Price-cutting incentives attract consumer attention, especially during an economic downturn. But, discounting items isn’t the only promo at a brand’s disposal. Free shipping, rewards points, gifts, and more can be promotion optimization tactics to help turn an on-the-fence shopper into a new customer. 

What if you can unify all these offers and customize their deployment depending on the user? 

Offers are content and the majority of your visitors (67%) want dynamic content that adjusts to the current context of their visit. Even more shoppers (74%) would find value in “living profiles” if that enabled curated experiences, offers, and products. Do they have a big ticket item? Offer free shipping. Are they buying in bulk? Tack off 10% if they have X amount in their cart. 

Rather than having a sitewide banner atop the page, brands should strategically suppress or deploy offers on a user level as a part of their promotion optimization strategy

Anonymous traffic targeting 

Due to privacy laws, moves by the walled gardens (deprecation of 3rd party cookies, IDFA), and changes in consumer behavior, more than 90% of website traffic is anonymous. How can brands adjust their promotion planning when traditional identifiers are no longer an option? Session AI accurately predicts purchase propensity for anonymous and known shoppers based on their real-time clickstream data. This insight then directs whether to deploy or suppress an offer (even the discount amount) depending on whether that visit is likely to result in a purchase.

Real-time offers

Today’s technology empowers ecommerce with AI decisoning and machine learning. These two advanced tools can monitor customer behavior on a momentary basis and compare their micro behaviors to historic use cases — allowing real-time offers based on relevant information.   

Use case: Eligible visitors only 

A top U.S. retailer incorporated Session AI in-session marketing to automatically identify anonymous influenceable visitors and segment them by whether or not they’re eligible for offers.

In order to be offers eligible, visitors had to meet the following criteria: 

  • Determined to be an on-the-fence shopper 
  • Have a cart value between $30 and $200
  • Margin positive (total margin of all cart items had to be higher than the value of the offer)
  • Did not already receive a current campaign offer

Using this criteria, the retailer was able to trigger coupons in real-time and incentivize those who would have otherwise abandoned the site without converting. Offers included: 

  • A 30-minute time-bound offer for 10% off was served up to anonymous visitors who were on-the-fence;
  • A future coupon to return if they provided their email for visitors who were unlikely to buy in that session;
  • And for anonymous visitors who were predicted as highly likely to buy in that session, they simply allowed them to complete their transaction uninterrupted – thus not giving away unnecessary margin.

Employing a triggered approach to promotions increased the retailer’s average lift in revenue per visitor by 4% – 15%, overall providing a 12x ROI within the first year of using Session AI. 

In-session rewards notifications

Did you know that 83% of shoppers are more likely to buy again from a company with a loyalty program? Many of us are members of such programs, yet few routinely monitor point redemptions, expirations, and further rewards opportunities. Notifying a shopper about expiring points, exclusive discounts for loyalty members, and redeemable coupons can help brands further tailor their offers around those particular points. 

In-cart recommendations

Seeing what the consumer has added to their cart allows brands to take further action: free shipping if they spend X amount, accessories that others who bought this product purchased, and protection plans (if applicable). In-cart recommendations are especially effective as they apply to likely shoppers who can be influenced to buy ancillary products or services, as well as help brands avoid cart abandonment with incentivized actions. 

Intent analysis and activity-based offers

What your customer is doing directly correlates with why they’re on your site. Using early prediction modeling, it’s possible to identify consumer intent in as little as five clicks. This level of analysis unlocks activity-based offers that are determined by the likelihood of purchase; likely to buy: no offer; unlikely to buy: showcase social proof around your product or service; on-the-fence shopper: 10% off. You can even take it a step further by deploying a discount on all items related to the visitor’s specific search query (e.g., outdoor gear).  

In-app offers

The Starbucks Reward Loyalty Program has more than 31.2 million users, giving the brand a giant audience to market to with upcoming releases and seasonal products. Being able to target this segment with personalized offers proved so profitable that 52% of sales in U.S. stores during the second quarter of 2021 came from program members. That’s because Starbucks is able to drop discount codes to those who haven’t visited in a while, give gifts to members on their birthdays, and let shoppers know when new drinks are available and where. Take a note from Starbucks and leverage your app to assist with promotion optimization. 

Targeted offers at point of sale

Every time you check out at the grocery store a list of coupons are printed based on what you purchased. That’s to help incentivize you to not only get that item again, but return to that store to purchase the product. Digital brands can do the same by sending discounted coupons with an expiration date to consumers following a purchase to help bring them back in a timely manner. 

The key to promotion optimization is learning from the results. Use advanced analytics to improve the offer and adjust based on the returns. At the core, promotions are intended to improve short-term sales with the hope that the same shoppers will turn into long-term buyers. Unfortunately, this hope is seldom realized as discount shoppers are more likely to take advantage of your deals — and drain profit margins — than they are to become lifelong customers. This is especially true of brands with frequent promotions, as they train consumers to wait until a discount is available to purchase.

With promotion optimization, brands can benefit from short-term conversions and eliminate margin loss by deploying or suppressing offers based on in-session intent that’s determined by the unprecedented accuracy and unparalleled speed of AI and ML. It’s important to consider all of these strategies if you are revamping your promotion process or kicking off promotion planning for the new year.

Rethinking your promotion plans? Learn how you can optimize your promotions with Session AI in-session marketing.

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