Multi-Brand Retailer Increases Revenue From Anonymous Visitors

A major US clothing retailer operating multiple brands realized between 4% and 15% average revenue lift per visitor by using ZineOne’s in-session marketing platform. Real-time intelligence allows their premier retail brands to personalize anonymous site visits, in the moment, at scale.

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The retailer’s goal was to move away from sitewide offers that erode margin by using intelligence to make real-time buying predictions and segment according to visitors’ propensity to buy.

The retailer achieved between 4% and 15% average increase in revenue per visitor across multiple use cases.

The Challenge

Sitewide promotions were not only diluting their brands but also eroding profit margins. The retailer wanted a more strategic way to deliver (and withhold) offers to their consumers.

The Solution

Using patented intelligence models from ZineOne, the retailer can predict who may be influenced by a real-time offer. For all other visitors, they do not share discount offers. Visitors who show strong buying propensity in that session, they will present a “complete the look” upsell product recommendation.

They have been able to unlock new segments for their anonymous web and mobile web traffic in the moment they are on their site. The platform then uses these predictive insights to increase conversions and save margin in real-time.

The Result

By leveraging ZineOne’s in-session marketing platform, the Multi-Brand Retailer was able to identify influenceable visitors and improve conversion rates across a dozen use cases.

The Retailer realized 12X ROI within the first year by working with ZineOne.

An example of one of the Retailers’ use cases included the following:

A 30-minute time-bound offer for 10% off was served up to anonymous visitors who were on-the-fence.
For visitors who were unlikely to buy in that session, they offered them a future coupon to return if they provided their email.
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.

Reserve time-bound offers only for visitors who need them to complete their transaction.

Prediction-Based Segments

In summary, the U.S. Retailer uncovered unique segments based on early purchase predictions, especially for those who would have abandoned the website without making a purchase. In a privacy-first world where retargeting is getting increasingly more complex, this is key. The retailer achieved a 4% – 15% average lift in revenue per visitor.

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