European Online Retailer Reduces Checkout Drop off by 48 Percent Using Online Visitor Behavior to Predict Exit Intent in Live-Time
Sunbury-on-Thames – Faced with the challenge of visitors visiting their website without making a purchase, World Wide Lighting, a leading European online retailer specializing in lighting products, looked for ways to lift its conversion rates. The brand identified potential abandoners and delivered tailored, personalized messaging by leveraging machine learning algorithms from Celebrus and OnMarc’s MarcSense Retain.
With this innovative real-time approach to predicting exit intent, World Wide Lighting experienced a 48% reduction in checkout drop-off. Incorporating live-time data from Celebrus allowed the models to detect exit intent early, at a minimum 10 times faster than the actual exit, giving the team sufficient time to engage and retain customers before they abandon.
“Since 2022, World Wide Lighting has used Celebrus data to power MarcSense Retain and gain valuable insight into customer behavior. We are thrilled with the results seen so far and look forward to continuing to help maximize the efficiency of customer marketing efforts by leveraging live-time, comprehensive data,” said Bill Bruno, CEO of Celebrus.
“With the challenge of the exiting visitor in our minds, we set out to unlock the potential of user’s movement data as well,” said Kevin van Kalkeren, Manager Product Management & Data Science at OnMarc.
“OnMarc and Celebrus help us by revealing the true needs of our customers in a unique way. This allows us to communicate much more proactively and allows us to become more relevant and proactive in our communication. This cooperation is therefore very valuable, both operationally and strategically,” said Martijn Brouns, Marketing Manager at World Wide Lighting. For full details and insights, visit the case study at (here). https://www.celebrus.com/case-studies/world-wide-lighting-reduces-drop-off-48?hs_preview=PbvkzxHo-74888324026
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