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For this iconic American jeans brand, increasing online sales wasn’t just about driving conversions but about making the shopping experience feel more personal. They wanted to engage shoppers in a way that felt relevant and intuitive, guiding them to the right products while fostering long-term loyalty.
The challenge? Identifying which visitors were most likely to buy, which were interested in signing up for a website account, and which could be nudged into increasing their basket size.
Without real-time behavioral insights, their existing strategies relied on broad promotions that didn’t always reach the right audience, leading to wasted marketing spend.
By analyzing real-time visitor behavior, Quin AI accurately predicted each shopper’s next move, allowing the brand to present relevant incentives at precisely the right moments. This predictive approach ensured offers reached the right shoppers when they were most likely to act.
The results? A 23% boost in conversion rates for pants (these are jeans if you’re reading this in the UK), a 21% increase for t-shirts, a 27% uptake in daily account sign-ups, and a 1.64X increase in average basket size.
Here’s how they did it.
Headline results:
- 23% increase in conversion rate for the pants product category
- 1.64X increase in average basket size
- 21% increase in conversion rate in the t-shirt product category
- 27% increase in daily average account sign-ups
For this iconic American jeans brand, increasing online sales wasn’t just about driving conversions but about making the shopping experience feel more personal. They wanted to engage shoppers in a way that felt relevant and intuitive, guiding them to the right products while fostering long-term loyalty.
The challenge? Identifying which visitors were most likely to buy, which were interested in signing up for a website account, and which could be nudged into increasing their basket size.
Without real-time behavioral insights, their existing strategies relied on broad promotions that didn’t always reach the right audience, leading to wasted marketing spend.
By analyzing real-time visitor behavior, Quin AI accurately predicted each shopper’s next move, allowing the brand to present relevant incentives at precisely the right moments. This predictive approach ensured offers reached the right shoppers when they were most likely to act.
The results? A 23% boost in conversion rates for pants (these are jeans if you’re reading this in the UK), a 21% increase for t-shirts, a 27% uptake in daily account sign-ups, and a 1.64X increase in average basket size.
Here’s how they did it.
Headline results:
- 23% increase in conversion rate for the pants product category
- 1.64X increase in average basket size
- 21% increase in conversion rate in the t-shirt product category
- 27% increase in daily average account sign-ups
Challenge #1: Creating a shopping experience that feels personal
This renowned US denim brand knew that to increase their conversions and minimize drop-offs, they required a more tailored shopping experience.
So, instead of relying on broad discounts, they wanted to engage visitors with product offers that genuinely interested them.
To do this effectively, they needed real-time insights to:
- Identify what captured their customers' interest
- Differentiate casual browsers from serious buyers
Armed with this information, they could craft a shopping experience that guided buyers to relevant products and delivered timely offers to minimize website abandonment and encourage purchases.
How Quin AI helped
Quin AI identified potential website abandoners in real-time by analyzing their on-site behavior to predict their next move. Quin AI then pinpointed the products and categories these shoppers engaged with to gain a clear understanding of their preferences during that session.
With these insights, Quin AI strategically highlighted key product benefits, ensuring shoppers received relevant incentives at the right moment for maximum engagement.
This well-timed, personalized approach kept them engaged and led to more completed purchases, driving a 23% increase in "Pants" sales and a 21% boost in "T-shirt" sales.
Challenge #2: Turning website visitors into account holders
The same leading apparel brand wanted to increase website account sign-ups as part of a broader effort to strengthen customer loyalty.
They introduced an incentive to encourage registrations, but without deep insights into new visitors, they couldn’t identify those most likely to sign up. This lack of targeting meant their offers weren’t always reaching the right audience, reducing the effectiveness of their membership campaign.
How Quin AI helped
Quin AI leveraged first-party data to develop a clear understanding of the brand's first-time visitors. By continuously monitoring their live interactions, its algorithm identified key behavioral signals that revealed each visitor’s likelihood to register for an account.
Then, when potential subscribers were detected, they received an incentive showcasing membership benefits at the optimal moment to encourage sign-ups. This approach led to a 27% increase in daily average account sign-ups, strengthening customer loyalty and driving long-term engagement.
Challenge #3: Increasing basket value without discounting
This premium jeans brand also aimed to increase revenue by boosting sales in its "Upper Body Apparel" category. However, instead of relying on discounts, they wanted to encourage shoppers to add higher-value items to their baskets.
A key part of this strategy was nudging customers interested in lower-priced items, such as t-shirts, toward more premium purchases, ultimately increasing average basket value.
Identifying the price ranges shoppers were considering – and whether they were open to upgrading – was a challenge. Their existing methods couldn’t accurately assess buying intent in real-time, making it harder to guide customers toward higher-value purchases.
How Quin AI helped
Quin AI analyzed shopper behavior in real-time, identifying users based on their price sensitivity and likelihood to complete a purchase or increase their basket size.
With these insights, we implemented targeted strategies to increase order value. For instance, when a shopper’s cart total fell below the free shipping threshold, we sent a timely reminder that adding more items would unlock free shipping. This gentle nudge encouraged customers to either add more to their cart or explore higher-priced products to qualify for the benefit – driving a 1.64X increase in average basket size and a notable boost in revenue.
Challenge #1: Creating a shopping experience that feels personal
This renowned US denim brand knew that to increase their conversions and minimize drop-offs, they required a more tailored shopping experience.
So, instead of relying on broad discounts, they wanted to engage visitors with product offers that genuinely interested them.
To do this effectively, they needed real-time insights to:
- Identify what captured their customers' interest
- Differentiate casual browsers from serious buyers
Armed with this information, they could craft a shopping experience that guided buyers to relevant products and delivered timely offers to minimize website abandonment and encourage purchases.
How Quin AI helped
Quin AI identified potential website abandoners in real-time by analyzing their on-site behavior to predict their next move. Quin AI then pinpointed the products and categories these shoppers engaged with to gain a clear understanding of their preferences during that session.
With these insights, Quin AI strategically highlighted key product benefits, ensuring shoppers received relevant incentives at the right moment for maximum engagement.
This well-timed, personalized approach kept them engaged and led to more completed purchases, driving a 23% increase in "Pants" sales and a 21% boost in "T-shirt" sales.
Challenge #2: Turning website visitors into account holders
The same leading apparel brand wanted to increase website account sign-ups as part of a broader effort to strengthen customer loyalty.
They introduced an incentive to encourage registrations, but without deep insights into new visitors, they couldn’t identify those most likely to sign up. This lack of targeting meant their offers weren’t always reaching the right audience, reducing the effectiveness of their membership campaign.
How Quin AI helped
Quin AI leveraged first-party data to develop a clear understanding of the brand's first-time visitors. By continuously monitoring their live interactions, its algorithm identified key behavioral signals that revealed each visitor’s likelihood to register for an account.
Then, when potential subscribers were detected, they received an incentive showcasing membership benefits at the optimal moment to encourage sign-ups. This approach led to a 27% increase in daily average account sign-ups, strengthening customer loyalty and driving long-term engagement.
Challenge #3: Increasing basket value without discounting
This premium jeans brand also aimed to increase revenue by boosting sales in its "Upper Body Apparel" category. However, instead of relying on discounts, they wanted to encourage shoppers to add higher-value items to their baskets.
A key part of this strategy was nudging customers interested in lower-priced items, such as t-shirts, toward more premium purchases, ultimately increasing average basket value.
Identifying the price ranges shoppers were considering – and whether they were open to upgrading – was a challenge. Their existing methods couldn’t accurately assess buying intent in real-time, making it harder to guide customers toward higher-value purchases.
How Quin AI helped
Quin AI analyzed shopper behavior in real-time, identifying users based on their price sensitivity and likelihood to complete a purchase or increase their basket size.
With these insights, we implemented targeted strategies to increase order value. For instance, when a shopper’s cart total fell below the free shipping threshold, we sent a timely reminder that adding more items would unlock free shipping. This gentle nudge encouraged customers to either add more to their cart or explore higher-priced products to qualify for the benefit – driving a 1.64X increase in average basket size and a notable boost in revenue.
A smarter approach to personalization at scale
Real-time behavioral insights for this designer denim brand made one thing clear: personalization at scale delivers tangible results.
By understanding each visitor’s in-the-moment behavior, Quin AI enabled the brand to move beyond broad, one-size-fits-all promotions and instead deliver precisely targeted incentives that resonated with individual shoppers.
The results speak for themselves:
- 23% increase in conversion rate for the "Pants" product category
- 21% increase in conversion rate for the "T-shirt" product category
- 27% increase in daily average account sign-ups
- 1.64X increase in average basket size
For retailers looking to take their online shopping experience to the next level, Quin AI proves that when you understand your customers in real-time, you can successfully deliver hyper-personalized experiences that boost conversions and turn browsers into loyal buyers.
A smarter approach to personalization at scale
Real-time behavioral insights for this designer denim brand made one thing clear: personalization at scale delivers tangible results.
By understanding each visitor’s in-the-moment behavior, Quin AI enabled the brand to move beyond broad, one-size-fits-all promotions and instead deliver precisely targeted incentives that resonated with individual shoppers.
The results speak for themselves:
- 23% increase in conversion rate for the "Pants" product category
- 21% increase in conversion rate for the "T-shirt" product category
- 27% increase in daily average account sign-ups
- 1.64X increase in average basket size
For retailers looking to take their online shopping experience to the next level, Quin AI proves that when you understand your customers in real-time, you can successfully deliver hyper-personalized experiences that boost conversions and turn browsers into loyal buyers.
