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Industry: Travel, Logistics & Infrastructure
+92%
customer retention
+49%
customer conversion
+70M
yearly sales uplift
Our client is a leading European carrier, which, over the past three years, has been invested in providing to their customers a better experience with personalized offers and product recommendations.
The client utilized Aliz’s two models to recommend ancillary products. The first one is serving real-time recommendations when the customer is in a booking session. The second one is serving batches of recommendations a posteriori of the booking session, to reach back customers within email campaigns.
Industry: Travel, Logistics & Infrastructure
+10%
in up sales
Our client, a group active in the Asian market, launched an initiative to diversify its portfolio of activities. Originally a carrier and cargo group, it opened up various new lines of business such as offering hotels and packaged deals, entertainment activities, insurance contracts, and food & grocery deliveries.
Aliz first suggested analyzing the client’s main line of business to see how potential customer needs may be fuzzily matched towards other LOBs. The client’s operational team used Aliz’s customer segmentation model to create different buyer profiles to categorize the airline’s customers.
Industry: Media, Electricity
+20%
conversion rate
Our customer, a media company, used Aliz’s propensity model to predict the willingness of users to fill out a contact form to get in touch about a specific service. With this model, we were able to assign individual users a propensity score to help measure the likelihood of subscription.
This information was used to target customers more precisely in order to improve the performance of marketing campaigns.
Maximize engagement by recommending specific product versions in real-time. Provide truly personalized recommendations that combine historical user behavior and metadata (e.g. location).
Improve campaign targeting by identifying consumer groups with similar preferences. Use customer segmentation backed by machine learning to reduce waste and save money on new marketing initiatives.
Improve marketing decision-making by understanding the future actions of visitors, leads, or customers. Propensity modeling attempts to predict the likelihood that users will fill out a form or sign up for a service to help you make informed decisions on marketing channels and messages.
FIRST
Limited scalability
Finding an experienced data scientist is no easy task. The lack of in-house competence can limit scalability. MaaS helps overcome this challenge.
1
SECOND
Uncertainty
AI projects are experimental research projects. Will you succeed eventually? Without the right quality and quantity of data, you never know. MaaS provides a solid basis for your AI endeavors.
2
THIRD
Instability
Once you managed to finalize model, it is hard to deploy it into a production-ready environment. MaaS solutions are ready for action.
3
Our MaaS solutions are pre-assembled tech capabilities deployed in a microservice architecture. This offering includes all the features required to efficiently maintain and operate your services on Google Cloud, without the hassle. Based on a cloud-native ecosystem, our solutions package key business capabilities together to enable a Composable Enterprise. Want to know more?
Ready to improve your digital business performance by offering customers exactly what they need?
Istvan Boscha
CEO DACH
Balazs Molnar
CEO APAC