Are e-commerce companies discounting too much?

With over 30 million e-commerce sites vying for customer attention, one tactic dominates the battlefield: discounting.

Whether you're managing your own online store or steering strategy for someone else's, you’ve likely relied on flash sales or all-encompassing promo codes.

For brands looking to attract and retain customers, slashing prices often feels like the quickest path to success. But here’s the hard truth: many e-commerce companies are discounting too much by offering the same deals to everyone and losing money unnecessarily.

Fortunately, there's an easy fix. Let's take a closer look:

The discount trap

According to data from IMRG, over 50% of retail sales are made on discount. While this might initially sound like a success, it underscores a deeper problem. Discounts have become so pervasive that they no longer create differentiation. The outcome? Shrinking margins and a race to the bottom.

To make matters worse, blanket discounting completely ignores the nuances of customer behavior, often giving discounts to those who would have willingly paid full price. This lack of personalization leaves substantial revenue on the table and conditions customers to expect discounts from your brand.

As a result, their willingness to pay full price diminishes over time, gradually eroding the perceived value of your offerings and making it increasingly difficult to foster meaningful, profitable customer relationships.

A smarter solution: Generative behavioral AI

Thankfully, generative behavioral AI provides a smarter, more effective way to break free from the cycle of blanket discounting. In fact, data from Nibble reveals that when brands use AI to personalize offers, they can halve the percentage discounts they offer customers and still drive the same conversions.

Generative behavioral AI (the tech that powers Quin AI) enables e-commerce brands to surpass generic discounting by predicting what customers will do next and showing them hyper-personalized experiences tailored to their unique purchase intent.

Quin AI is leading the way in this space. Our platform is explicitly designed to help businesses harness the full potential of generative behavioral AI. By analyzing real-time customer data, Quin AI enables brands to predict individual needs and deliver offers that perfectly align with their journey – maximizing value for both the shopper and the business.

Here’s a closer look at how this works:

1. Set an objective

Start by clearly defining the goals of your discounting strategy. Are you aiming to:

• Increase average order value (AOV) by encouraging customers to add more to their carts?
• Improve profit margins by reducing unnecessary discounts?
• Enhance customer retention through targeted incentives that reward loyalty?

Whatever your goals, having a clear and specific objective is essential for creating a cohesive and measurable strategy. Objectives serve as benchmarks, allowing you to evaluate the success of your efforts and make data-driven adjustments when needed.

2. Tailor your approach

Not all customers are the same, so why treat them that way? By leveraging real-time first-party data, Quin AI helps you identify and categorize visitors into predictive audiences based on a combination of behaviors and contextual factors. These distinct groups enable you to create hyper-personalized, relevant experiences that drive engagement and conversion.

Here's how Quin AI helps you categorize your key audiences:

Audience types

• Abandoner: Visitors who show intent by adding items to their cart or exploring products but leave without completing a purchase. By understanding their hesitation points, you can design targeted campaigns to re-engage them.
• Buyer: Visitors browsing with high purchase intent, displaying real-time behaviors that indicate they're likely to complete a purchase. These are your high-value visitors, and nurturing them ensures repeat business.
• Demo booker: Visitors engaging with demo-related content who are likely to schedule a demo.
• Subscriber: Visitors indicating a strong likelihood of subscribing or signing up for subscriptions, newsletters, updates, or memberships.
• Info seeker: Visitors engaged in gathering product details, reviews, or specifications, showing interest but no immediate intent to purchase. Providing them with the right information at the right time can tip them toward a purchase.
• High-value product buyer: Visitors likely to purchase higher-value or premium items
• High-value product browser: visitors exploring higher-value or premium items without showing immediate intent to purchase.
• Focused buyers: Visitors browsing a narrow range of products with clear intent to make a purchase.
• Casual browsers: Visitors exploring the site or app with moderate interest, showing no intent to purchase but open to product discovery.
• Payment hesitant: Visitors showing strong purchase intent but who are delaying at the final steps, often lingering on payment or checkout pages.
• Bargain buyers: Visitors who actively look for deals, discounts, or promotional offers who also show a strong likelihood of completing a purchase. You might be able to appeal to their needs with exclusive access to sales or early bird specials to keep them engaged.

With insights like these, Quin AI can identify high-value customers who are likely to convert without discounts. These insights empower brands to reserve promotions for those customers who truly need that extra nudge, enhancing the efficiency of your marketing spend.

3. Dynamic pricing

Generative behavioral AI also facilitates pricing strategies that adapt to individual customer profiles. Below are a few examples of how that might work in practice:

• Loyal customers: You could reward commitment with loyalty points as a token of appreciation to strengthen their loyalty and make them feel valued by your brand.
• Shoppers with high-purchase intent: Instead of reducing the price, highlight something that aligns with their behavior, such as free shipping.
• Bargain hunters: Appeal to their price-sensitive nature with a customized promotion crafted to entice them while carefully balancing the offer to protect profitability.

To quickly summarize: By tailoring offers in real-time based on customer data and intent, generative behavioral AI ensures every promotion serves both the customer’s needs and the brand’s bottom line.

It doesn't always have to be a discount...

At this point, it's worth noting that by harnessing generative behavioral AI to predict visitor intent, effective customer engagement doesn't always have to hinge on discounts.

Here are some alternatives to traditional discounting that can equally drive conversions and customer loyalty:

Value-added incentives

Instead of cutting prices, try offering value-added incentives that make the customer’s experience more rewarding. Examples include:

• Free shipping
• Complimentary gift wrapping
• Free product samples from your partners
• A generous returns policy

These simple gestures increase the perceived value of your products, encouraging customers to buy while protecting your profit margins – a win-win.

For example, IKEA used Quin AI to increase bed sales by 40% without relying on discounts. Instead, they strategically addressed customer hesitations by highlighting their 90-day return policy at the perfect moment in the shopping journey. This demonstrates how timely, value-driven engagement can boost conversions while preserving profitability.

Exclusive access

Give customers a sense of exclusivity by offering early access to new products or special editions before a public sale. This approach is particularly effective for returning customers or loyalty program members, making them feel like VIPs and rewarding their dedication with no discounts required.

Kiehl's showcases the power of exclusivity in action. By leveraging Quin AI, they targeted affluent Instagram visitors with exclusive access to their newest collection. This tailored strategy boosted conversions by 1.6x, proving that unique, personalized experiences can deliver impressive results – with no discounts needed.

Personalized recommendations

Finally, generative behavioral AI can be a powerful tool for delivering personalized product recommendations. By tailoring the shopping experience to each customer's preferences, you create a sense of understanding and value that significantly increases the likelihood of conversion without cutting product prices.

For instance, Koçtaş leveraged Quin AI to tackle website abandonment by offering real-time, tailored recommendations that guided customers to the products they were searching for. This strategic use of generative AI eased customer frustrations and led to an impressive 2.7x increase in conversion rates. Such results demonstrate how personalization can drive meaningful outcomes by aligning with customer needs and expectations while preserving your profits.

4. Experiment and iterate

Experimentation is crucial to any successful marketing strategy, and discounting campaigns are no exception. By continuously testing and refining your approach, you can identify what works best for your audience to maximize the impact of your campaigns.

Here are a few pointers to help you achieve that:

Take the objective(s) we spoke about earlier and keep them at the forefront of your mind. Having a clear focus ensures your efforts are targeted and measurable.

Then, use A/B testing to experiment with different variables that can influence customer behavior, such as:

• Messaging: Test variations in tone, style, and calls-to-action to identify what drives the most engagement.
• Discount amounts: Experiment with different percentages or fixed discounts to determine the optimal offer for maximizing conversions without eroding profitability.
• Timing: Assess the impact of when offers are presented. Consider factors like time, day of the week, or seasonal trends.
• Type of offer: Compare the effectiveness of promotions like free shipping, bundle deals, or loyalty rewards to see what motivates your audience.

By systematically testing these elements, you'll uncover the combinations that resonate most with your audience and ultimately drive better results.

To ensure the accuracy of your findings, designate a control group, i.e., a segment of your audience that receives no interventions. This baseline group serves as a neutral benchmark, providing you with a clear and unbiased view of the true impact of your campaigns.

Next, evaluate the performance of your campaigns by analyzing quantitative data. Metrics such as conversion rates, average order value (AOV), and revenue per session provide clear, actionable insights into what’s working. These indicators highlight the success of your efforts and help you pinpoint areas where adjustments can further refine your approach.

The future of e-commerce product discounting

By shifting from blanket discounts to personalized engagement strategies powered by generative behavioral AI, e-commerce companies can retain profitability without compromising customer satisfaction. By understanding and catering to visitor behaviors in real-time, your brand can create meaningful, fruitful customer relationships that stand the test of time. Ready to leave the discount trap behind? With Quin AI, the smarter way forward is just a few clicks away.