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GAP is an iconic global retailer that needs no introduction. Famed for their timeless apparel and ability to adapt to changing trends, GAP has long been a staple in wardrobes and shopping centers worldwide.
However, they had a big question to tackle: how could they level up their digital customer experience to keep up with the demands of today’s tech-savvy shoppers?
The answer: A partnership with Quin AI.
Working together, GAP leveraged Quin AI's advanced predictive technology to create personalized shopping experiences that delighted customers and increased conversions – all while protecting their profit margins.
Let's take a closer look:
GAP's results
- 3.16X increase in average basket size
- 30% of shoppers added a second product to their purchase
- 89% boost in conversions
GAP is an iconic global retailer that needs no introduction. Famed for their timeless apparel and ability to adapt to changing trends, GAP has long been a staple in wardrobes and shopping centers worldwide.
However, they had a big question to tackle: how could they level up their digital customer experience to keep up with the demands of today’s tech-savvy shoppers?
The answer: A partnership with Quin AI.
Working together, GAP leveraged Quin AI's advanced predictive technology to create personalized shopping experiences that delighted customers and increased conversions – all while protecting their profit margins.
Let's take a closer look:
GAP's results
- 3.16X increase in average basket size
- 30% of shoppers added a second product to their purchase
- 89% boost in conversions
Challenge #1: Nighttime conversion slumps
While GAP's website saw thriving sales during the day, conversion rates took a sharp dip during nighttime hours. With their physical stores closed, these off-peak hours were a golden opportunity to boost their overall revenue.
However, they didn’t have the insights to figure out what their visitors were looking for or how to keep them engaged. Without a clear picture of their customer’s behavior, delivering personalized experiences that would turn browsers into buyers was nearly impossible.
Determined to turn things around, GAP set out to find a smarter way to understand their nighttime shoppers and deliver customer experiences that would truly resonate.
How Quin AI helped
Quin AI, with its ability to dive into GAP's real-time website data, pinpointed the exact hours when conversion rates took a nosedive: 22:00–08:00. This precision allowed GAP to understand when their website visitors would likely abandon their shopping journeys.
However, Quin AI's insights didn't stop there – they also revealed that many nighttime visitors showed clear intent to purchase but ultimately abandoned their transactions.
Armed with this knowledge, GAP leveraged Quin AI to deliver offers aimed at nighttime visitors on the verge of abandoning their carts. These perfectly timed nudges gave these shoppers the little push they needed to finish their purchases.
The result? A 33% rise in conversion rate, turning low-performing sales hours into a major revenue driver.
Challenge #2: Declining basket sizes
Although GAP's customers were adding items to their carts, the total value of those baskets – and the number of items per transaction – was steadily declining.
To tackle this, GAP needed a way to get shoppers to add more to their carts without relying on impersonal, blanket discounts that could eat into profits. Instead, they wanted a more tailored solution – one that could spot high-potential buyers in real-time and offer the right incentives to encourage them to add more to their baskets.
How Quin AI helped
Quin AI used its advanced in-session data analysis to get a real-time read on how visitors were shopping. This made it possible to predict their behavior without relying on preset rules or waiting for them to add something to their cart.
More specifically, Quin AI helped GAP uncover two key shopper groups:
- Customers interested in products within a specific price range with the potential to increase their basket size
- Shoppers with just one item in their cart who also showed a high likelihood of increasing their basket size.
With these insights, GAP was able to move beyond generic, one-size-fits-all strategies. They offered tailored incentives designed to match each shopper’s preferences:
- Customers shopping within specific price ranges were encouraged to explore higher-value purchases.
- Shoppers with a single item in their cart received personalized offers, prompting them to add another product and increase their overall spend.
By meeting shoppers where they were and offering incentives that resonated, GAP created a more engaging shopping experience – and saw some pretty impressive results in the process.
Namely, a 3.16X increase in average basket size, with as many as 30% of the target audience adding a second item to their cart.
Challenge #3: Enhancing campaign efficiency
GAP kicked off their summer discounts with bold, eye-catching banners across their website. But as the campaign unfolded, they soon realized that just putting the offers out there wasn’t cutting it. To really make a difference, they needed to get those discounts in front of the right people – the ones who would be excited to take advantage of them. That’s when they set out to bridge the gap between their deals and the customers who would love them most.
How Quin AI helped
Quin AI’s behavior prediction capabilities allowed GAP to figure out exactly who was most likely to respond to their promotions and when to reach out for the biggest impact.
With this enhanced understanding, Quin transformed GAP’s summer discount campaign by tailoring it to each shopper’s journey. Instead of relying on broad promotion, Quin used its advanced algorithm to identify the right audience and deliver personalized incentives at the ideal moment. This approach didn’t require any additional discounts – proving that precision, not more promotions, drives real results.
The impact was significant: GAP saw a 1.89X increase in conversion rates.
Challenge #1: Nighttime conversion slumps
While GAP's website saw thriving sales during the day, conversion rates took a sharp dip during nighttime hours. With their physical stores closed, these off-peak hours were a golden opportunity to boost their overall revenue.
However, they didn’t have the insights to figure out what their visitors were looking for or how to keep them engaged. Without a clear picture of their customer’s behavior, delivering personalized experiences that would turn browsers into buyers was nearly impossible.
Determined to turn things around, GAP set out to find a smarter way to understand their nighttime shoppers and deliver customer experiences that would truly resonate.
How Quin AI helped
Quin AI, with its ability to dive into GAP's real-time website data, pinpointed the exact hours when conversion rates took a nosedive: 22:00–08:00. This precision allowed GAP to understand when their website visitors would likely abandon their shopping journeys.
However, Quin AI's insights didn't stop there – they also revealed that many nighttime visitors showed clear intent to purchase but ultimately abandoned their transactions.
Armed with this knowledge, GAP leveraged Quin AI to deliver offers aimed at nighttime visitors on the verge of abandoning their carts. These perfectly timed nudges gave these shoppers the little push they needed to finish their purchases.
The result? A 33% rise in conversion rate, turning low-performing sales hours into a major revenue driver.
Challenge #2: Declining basket sizes
Although GAP's customers were adding items to their carts, the total value of those baskets – and the number of items per transaction – was steadily declining.
To tackle this, GAP needed a way to get shoppers to add more to their carts without relying on impersonal, blanket discounts that could eat into profits. Instead, they wanted a more tailored solution – one that could spot high-potential buyers in real-time and offer the right incentives to encourage them to add more to their baskets.
How Quin AI helped
Quin AI used its advanced in-session data analysis to get a real-time read on how visitors were shopping. This made it possible to predict their behavior without relying on preset rules or waiting for them to add something to their cart.
More specifically, Quin AI helped GAP uncover two key shopper groups:
- Customers interested in products within a specific price range with the potential to increase their basket size
- Shoppers with just one item in their cart who also showed a high likelihood of increasing their basket size.
With these insights, GAP was able to move beyond generic, one-size-fits-all strategies. They offered tailored incentives designed to match each shopper’s preferences:
- Customers shopping within specific price ranges were encouraged to explore higher-value purchases.
- Shoppers with a single item in their cart received personalized offers, prompting them to add another product and increase their overall spend.
By meeting shoppers where they were and offering incentives that resonated, GAP created a more engaging shopping experience – and saw some pretty impressive results in the process.
Namely, a 3.16X increase in average basket size, with as many as 30% of the target audience adding a second item to their cart.
Challenge #3: Enhancing campaign efficiency
GAP kicked off their summer discounts with bold, eye-catching banners across their website. But as the campaign unfolded, they soon realized that just putting the offers out there wasn’t cutting it. To really make a difference, they needed to get those discounts in front of the right people – the ones who would be excited to take advantage of them. That’s when they set out to bridge the gap between their deals and the customers who would love them most.
How Quin AI helped
Quin AI’s behavior prediction capabilities allowed GAP to figure out exactly who was most likely to respond to their promotions and when to reach out for the biggest impact.
With this enhanced understanding, Quin transformed GAP’s summer discount campaign by tailoring it to each shopper’s journey. Instead of relying on broad promotion, Quin used its advanced algorithm to identify the right audience and deliver personalized incentives at the ideal moment. This approach didn’t require any additional discounts – proving that precision, not more promotions, drives real results.
The impact was significant: GAP saw a 1.89X increase in conversion rates.
Quin AI x GAP: What’s next?
A 3.16X increase in average basket size, 30% of shoppers adding a second product, and an 89% boost in conversions – these impressive results highlight the impact of our evolving partnership with GAP.
As GAP continues to grow its digital presence, our collaboration has moved beyond simply identifying visitors likely to abandon their shopping journey. Initially focused on identifying visitors likely to abandon their shopping journey, we’ve expanded our collaboration to pinpoint and engage with additional audience types, such as shoppers seeking product information or exploring flexible payment options.
By understanding these distinct needs, GAP now adopts highly tailored engagement strategies to cater to each group. For example, visitors interested in payment flexibility are presented with clear, actionable billing options, while information seekers are seamlessly directed to GAP’s WhatsApp chatbot for real-time personalized support.
This deeper audience understanding enables GAP to consistently deliver exceptional customer experiences that drive higher engagement and directly contribute to their bottom line. Together, we’re shaping the future of digital retail, and we’re excited to continue building on this success.
Quin AI x GAP: What’s next?
A 3.16X increase in average basket size, 30% of shoppers adding a second product, and an 89% boost in conversions – these impressive results highlight the impact of our evolving partnership with GAP.
As GAP continues to grow its digital presence, our collaboration has moved beyond simply identifying visitors likely to abandon their shopping journey. Initially focused on identifying visitors likely to abandon their shopping journey, we’ve expanded our collaboration to pinpoint and engage with additional audience types, such as shoppers seeking product information or exploring flexible payment options.
By understanding these distinct needs, GAP now adopts highly tailored engagement strategies to cater to each group. For example, visitors interested in payment flexibility are presented with clear, actionable billing options, while information seekers are seamlessly directed to GAP’s WhatsApp chatbot for real-time personalized support.
This deeper audience understanding enables GAP to consistently deliver exceptional customer experiences that drive higher engagement and directly contribute to their bottom line. Together, we’re shaping the future of digital retail, and we’re excited to continue building on this success.
