By creating and fine-tuning various prognosis models, we help you find answers to even the most complex business problems.
Which clients are the most likely to stop using our services? What is the sales value of a specific end product? To which client, with which price and in what way should we sell?
How to make quicker and more precise data-driven decisions? Which actions and decisions should be easily repeatable or automated?
Machine learning solutions are helpful in solving several business problems. Automated decision-making algorithms usually combine information from internal as well as external data sources. Machine learning-based decisions are reached in the blink of an eye, and as a rule they are considerably more precise. This is because they process information in a way that the human brain is usually incapable of reciprocating when making a decision.
For example, based on sales invoices and their payment data, it is possible to forecast the estimated time of receipt of the payment for a single invoice issued. This assessment can be used by the financial manager in cash flow planning, for instance.
Machine learning technologies have undergone rapid development in recent years. Another competitive advantage comes from the fact that we use the most up-to-date machine learning capabilities in our data projects.
To sum it up – among other things, machine learning helps to harness existing data to forecast unknown values.
Forecasting which clients are about to leave
This solution created by us allows its users to give the clients of a product or service an evaluation describing their likelihood of leaving within a specific time period. The evaluation is calculated based on their behaviour or any changes therein. This pays off because it is 5 times more expensive to get a new client than to keep an existing one!
More efficient maintenance of production equipment
Machine learning-based solutions allow production companies to improve the efficiency of their activities related to equipment maintenance. The forecasting model identifies the conditions upon which equipment maintenance becomes justified. This reduces maintenance costs and improves productivity (decreased maintenance volume, fewer unplanned stoppages, lower unit cost, increased equipment utilisation, more efficient maintenance work planning).
Optimal sales price
In the sales offer it is possible to forecast the most optimal sales price for a specific product based on historical sales data (using information on the client, amount, delivery conditions, etc.).
More precise targeting in marketing
This solution created by us identifies clients with similar buying behaviour, forecasts their behavioural patterns and divides them into suitable target groups. This, in turn, helps to carry out considerably more precise and cost-effective marketing activities.
How could we boost your organisation’s business?
