We lead the project aiming to increase customer satisfaction through new personalized services and achieve the 'customer 360-' and 'omni' ambition. We conceptualized and tested consumer services, built analytics models to support them and we adviced on architecture and organisational structure/competencies needed to enable success.
The client wanted to understand what customers write about their services (in surveys, social media & support) as well as what drives (dis-)satisfaction. We analysed data acquisition processes, assessed data quality and built an AI model (using NLP applications) to automatically process customer text data (10 000+ texts), enabling customer driven business development.
The client needed to increase customer loyalty and prevent customers from churning. After analysing business needs and processes, we extracted, cleansed and processed data and built a machine learning model aiming to predict customers likely to churn and what drives customers to leave. Challenges included data quality and fragmentation of customer data.
The client wanted to better understand the web behavior of their customers to enable more efficient customer communication and web development. We started by holding workshops to identify business objectives and KPIs, then we analyzed and presented the insights created through the available data.
The client understood their new loyalty program needed to be based on actual customer behavior, so they asked us to help them analyze transactions to define loyal customers, campaign effect and customer journey phases, among other things.
The client asked us to help them set their analytics and data platform strategy to enable increased conversion, loyalty and engagement. We assessed how to best use analytics based on the client's conditions (business goals, IT-environment and ability to act), and put together a granular action plan, including tools and competencies, enabling a smarter future.
Business driven ✔
Quick value ✔
Made simple ✔
"Business value from day one!"
We build & implement new models or tools for advanced analytics and Artificial Intelligence
Get access to data and advanced analytics expertise to support ongoing analytics initiatives
- Ad hoc analysis
- Reoccuring insights
- AI & analytics review
To maximize value and minimize risk, Applai uses an agile approach to implement Artificial Intelligence. Step by step we help companies towards 100% smartness, through targeting the best use cases based on business objectives & conditions, focusing on quick value.