{"id":23503,"date":"2024-09-24T15:45:53","date_gmt":"2024-09-24T14:45:53","guid":{"rendered":"https:\/\/www.dataiq.global\/?post_type=award-winner&p=23503"},"modified":"2024-09-27T15:28:55","modified_gmt":"2024-09-27T14:28:55","slug":"2024-dataiq-awards-breakthrough-with-data-or-ai-brand","status":"publish","type":"award-winner","link":"https:\/\/www.dataiq.global\/devstage\/award-winner\/2024-dataiq-awards-breakthrough-with-data-or-ai-brand\/","title":{"rendered":"2024 DataIQ Awards – Breakthrough with Data or AI (Brand): Lebara"},"content":{"rendered":"

Lebara \u2013 a mobile-virtual-network-operator \u2013 is a small telecommunications company operating in five countries and it has faced typical challenges of small telecommunications companies, such as struggles with the adoption of new technologies due to limited resources and budget constraints.\u00a0<\/span>\u00a0<\/span><\/p>\n

Lebara underwent a true data transformation in under two years, shifting the entire business strategy from offline retail stores, to an online, digital-first, AI driven customer experience. From no data science team and a rudimentary KPI reporting warehouse, Lebara overhauled its tech stack and data culture, delivering five times as much data in 12 months, empowering machine learning, personalisation, and lifetime value-based relationships with customers. This has driven a 44% increase in customer base, with 66% now active online versus 40% pre-transformation. Churn has reduced by up to 15% and Lebara now has a market leading Trust Pilot score.\u00a0<\/span>\u00a0<\/span><\/p>\n

Lebara deployed a state-of-the-art technology stack, enabling targeted campaigns, natural language processing, and an AI driven customer experience. These changes created a 5.3% uplift in active customers, generating nearly \u20ac500,000 in additional value.<\/span>\u00a0<\/span><\/p>\n

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Why a datalake was needed\u00a0<\/strong><\/p>\n

Lebara previously acquired customers through offline retail stores and had no ability to personalise engagement with customers. There was a limited understanding of consumer needs, and no tailored offers to reward loyalty, creating shallow customer relationships. Customer dissatisfaction was reflected in a dismal 1.9 out of 5 Trust Pilot score, and sector-high churn rates in France, causing considerable revenue loss.\u00a0<\/span>\u00a0<\/span><\/p>\n

Prior to migration, the on-premises data warehouse consisted of siloed, outdated technologies that had not changed in ten years \u2013 its sole purpose was reporting high-level KPIs. Data pipelines lacked automation, meaning business decisions were based on out-of-date data \u2013 up to 11 days late. Furthermore, this legacy platform had no way to measure profitability, restricting our ability to identify or retain on high value customers.\u00a0<\/span>\u00a0<\/span><\/p>\n

With no data science team, customer communications were one-size-fits-all. No personalisation, no machine learning, and no AI.\u00a0<\/span>\u00a0<\/span><\/p>\n

Lebara migrated from data warehouse to Lakehouse, overhauling their entire technology stack, bringing both data and applications to Azure, with Databricks as the unified engine for data processing, and MLflow to for the machine learning lifecycle.\u00a0<\/span>\u00a0<\/span><\/p>\n

The new Lakehouse architecture allows access to nearly five times the volume of data to be ready for analytics. Decisions are based on previous day\u2019s trading, compared with the 11-day lag prior to migration.\u00a0<\/span>\u00a0<\/span><\/p>\n

Within just 18 months, a dedicated Analytics team was formed consisting of 15 members including Data Analysts and Scientists, to build machine learning models and lead the adoption of generative AI (genAI).\u00a0<\/span>\u00a0<\/span><\/p>\n

GenAI has been deployed as a suite of intelligent digital workers, increase capabilities in customer experience. <\/span>\u00a0<\/span><\/p>\n

AI Driven Chat-Bot services:\u00a0<\/span>\u00a0<\/span><\/p>\n