Deriving Actionable Insights from Big Data to Enhance Customer Experiences Across the Consumer Journey

Abstract

This research article explores how big data analytics can be leveraged across the different touchpoints of the consumer journey to derive actionable insights that lead to enhanced customer experiences. The massive amounts of data generated from multiple sources represent an invaluable asset for brands to understand audiences. This study examines current data sources like transactions, website behavior, social media, IOT devices etc. as well as analytical techniques spanning descriptive, predictive, prescriptive, and diagnostic methods. Using big data analytics contextually enables greater personalization, optimization and predictive interaction triggering across key stages of awareness, consideration, purchase, post-purchase, and loyalty. These techniques power use cases around defining lookalike segments for proactive engagement or determining channel mix influence across the journey to create seamless omnichannel experiences. However, brands need to focus on critical factors like data integration across systems, veracity and governance, evolving specialist skills in analytics/storytelling and cultural adoption to translate this potential into superior lifetime value across segments. Though data privacy and strategy misalignment remain ongoing challenges, benefits outweigh risks for brands bold enough to become insight-led across the customer journey. This research serves both as an approach guide and playbook for data-driven journeys.