JourneyTree is a light-weight and efficient Customer Analytics tool for retail business of any domain, based on the state-of-the-art Machine Learning (ML) algorithms.
Almost every company possesses data about their customers to be learned from. JourneyTree is intended for companies/brands that are not ready to hire an in-house data-science team, or pay for the extremely expensive (and complex) customer analytics software. By using JourneyTree, brands can benefit from ML without huge investments – they can quickly and easily analyze their proprietary data in order to extract actionable information from it. It is a way with the lowest risk to explore the data, estimate its value (knowledge that can be extracted) and decide on the future strategy regarding customer analytics.
Doesn’t matter what and where you sell
→ retail, electronics, events , e-commerce, services…
Doesn’t matter to whom you sell
→ B2B or B2C
JourneyTree can be used either as stand-alone software or as a plug-in for existing systems.
The output can be delivered as a visual report or ingested by other systems via API.
Easily usable by Teams from all of your departments (Marketing, Sales, Product Development, Customer Success)
Our goal is to keep your investment at the minimum (time, money, effort) while providing as many benefits as possible. How is this achievable? We can work with transactional data ONLY but any additional data is welcome. JourneyTree puts Customer Revenue Optimisation above everything else throughout Customer Lifecycle.
The system will calculate top-scored recommendations for our clients, according to their customers’ journeys, as well as perform analytics on emerging trends in customers’ interests.
Customer behavior segmentation for personalized messaging
Automatic, data-driven customer segmentation which enables you to understand different profiles of behavior and tailor personalized messaging and offers. Increase brand loyalty by addressing customers in a way they like it.
Per-customer churn prediction
Prevent churn by quick reaction to early signs of customer's decrease of activity.
Get recommendation of actionable which still maximizes your margin.
Expected lifetime value calculation
Calculate per customer expected lifetime value. Understand who are your most relevant segments and manage your resources accordingly.
Per-customer product recommendation
Get ahead of your customers by knowing in advance which product they are most likely to be interested in. Understand future demand and navigate your sales.
Co-founder & Project Coordinator
Co-founder & Chief Data Scientist
Huge international research and consulting experience (Italy, USA, Canada, Germany, Belgium, Serbia, etc.). Expert in Risk and Resilience Management of complex Socio-Technical systems. Holds a PhD in Industrial Engineering and Management from Politecnico di Milano, Italy.
Data scientist with 10 years of experience in bridging the gap between ML models in laboratory and ML models in real life applications. Firm believer that good data science solutions are simple yet artistic. Holds a PhD in Applied Data Science from EPFL, Switzerland.
CTO & Software Architect
Software architect with 9+ years experience in industrial projects and team leading. Assistant professor. Scientist and lecturer at Ecole polytechnique fédérale de Lausanne EPFL, Switzerland. Holds a PhD in Applied Computer Science.