A multi-channel, casual apparel retailer wanted to improve consumer engagement and increase ecommerce revenue through personalization on their website. Their previous model standardized product recommendations across all audiences on all digital platforms, but they weren’t seeing the results they wanted.
To begin, Sophelle analyzed consumer behavioral data at every digital touchpoint on both web and mobile interfaces. This objectively determined who clicked on what items in any given platform. Despite standardizing product recommendations, customer data found that customers were actually interested in different products across the various touchpoints.
Sophelle built data models to customize new AI algorithms to improve the consumer experience. Mobile-specific optimization opportunities were identified, then run through A/B tests.
The creation of a new personalization strategy optimizing mobile user experience gave the apparel retailer a 7.96% lift in revenue in only 4 weeks.