Enabling sales effectiveness with tailored cross-sell and up-sell recommendations to customers
Benefits & Results
Background
Reed Exhibitions, part of RELX Group, is a global event organizer hosting over 500 events in 30 countries annually. They connect professionals from various industries, including technology, healthcare, and real estate, to foster business opportunities, innovation, and networking. Their events include trade shows, conferences, and digital forums. Reed Exhibitions aims to leverage cutting-edge technology, foster industry connections, and expand their global footprint to deliver unparalleled experiences for exhibitors and attendees.
Challenges
Issue Identification: Reed Exhibitions struggled to maintain ongoing customer engagement after events and lacked a comprehensive customer view, including demographic, geographic, and historical transaction data. This impeded their ability to identify and pursue revenue enhancement opportunities based on customers' past purchase history.
Issue Impact: The inability to capitalize on revenue opportunities from existing customers hindered business growth.
Solution
NowVertical implemented the "you might also like..." feature to recommend movies and content to channel publishers and IP buyers based on their specific needs, interests, behaviors, and purchasing patterns. This solution is powered by a recommendation engine that extracts purchase history and other demographic and geographic parameters of the customers, providing personalized product and show recommendations for each individual.
Implementation
- Complete Engagement: NowVertical handled the entire delivery process from business analysis to design, implementation, and support.
- Business-Led Delivery: Achieved through business engagement, a BI Working Group, and benefits realization.
- Agile Delivery: Enhanced business engagement and achieved early benefits.
- Flexible Data Warehouse: Utilized industry best practice Kimball data marts to support country-specific needs.
- Data Science Model: Developed using Python scripts, these models ingested historical transactional and behavioral data to generate product and show recommendations.
- Dashboards: High-performance dashboards provided actionable insights for CRM and marketing teams to develop effective marketing strategies and deliver exceptional customer experiences.