Case Studies
Learn how companies are hyper-personalizing their communication
Current cases
industry
service
Retail
How Predictive Analytics Helped a Furniture Retailer Save €529K
A Swiss furniture retailer spent €667,000 annually on direct mail campaigns. Using predictive analytics, this budget was reduced by 79%. Sales remained the same.
retail
How predictive analytics helped an electronics retailer detect bonus abuse
A major electronics retailer lost money through the misuse of its loyalty program. Cashiers charged purchases to their own cards to collect bonuses. Manually reviewing videos and receipts was slow and inefficient.
telecommunications
A telecommunications provider now sees the risk of customer churn 3 months in advance.
A major telecom provider was losing 15 % subscribers annually. The customer retention team only reacted after a customer expressed a desire to cancel. Using predictive analytics, the company now identifies at-risk customers three months earlier.
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Frequently Asked Questions
Where does the data for training the models come from?
The models learn exclusively from the behavioral history of your own customers. We do not use general market data. The predictions relate specifically to how your customers interact with your company.
How does the integration with my current tools work?
We can connect to many types of software, including medical systems and warehouse management programs. We send messages via SMS, Viber, Telegram, or website chats.
Do I need programmers to use the platform?
No programming knowledge is required. An analyst can train and test models via a simple interface with buttons.
How is the pricing model structured?
Billing is based on the number of predictions per month. One prediction per customer per run counts as one unit. This keeps costs directly tied to usage, simplifying budgeting.