Skechers personalizes marketing campaigns by integrating Uniphore CDP with Databricks
Skechers integrated Uniphore's Customer Data Platform with the Databricks Data + AI Platform and Delta Lake to unify customer data across 180+ countries for AI-driven audience segmentation and omnichannel marketing, reducing campaign lead time from 2-8 weeks to 4-10 days and achieving a 324% increase in click-through rate, 68% reduction in cost per click, and 28% boost in return on ad spend.
Overview
Skechers integrated Uniphore's Customer Data Platform with the Databricks Data + AI Platform and Delta Lake to unify customer data across 180+ countries for AI-driven audience segmentation and omnichannel marketing, reducing campaign lead time from 2-8 weeks to 4-10 days and achieving a 324% increase in click-through rate, 68% reduction in cost per click, and 28% boost in return on ad spend.
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Inspect the highlighted sourceThe challenge
Skechers' legacy data warehousing environment was not designed for its post-pandemic scale, making it increasingly challenging to manage vast volumes of customer data in real time across 180+ countries; the retailer needed to shift from a channel-centric to a customer-centric approach and lacked a comprehensive customer data platform to power targeted, omnichannel marketing.
The solution
Skechers integrated Uniphore's Customer Data Platform with the Databricks Data + AI Platform, using Kafka for batch and real-time data ingestion and Delta Lake to manage upserts and build reliable pipelines, giving marketers a 360-degree view of the customer to orchestrate omnichannel journeys and deliver targeted product recommendations and incentives.
Reported business value
Skechers cut campaign lead time from 2-8 weeks to 4-10 days and, on live campaigns, saw a 324% increase in click-through rate, a 68% reduction in cost per click and a 28% improvement in return on ad spend; its At-Risk email campaign saw a 65% increase in conversion rate, a 65% lift in click-through rate and a 55% boost in revenue per mille.
Sources
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