Business Intelligence

Business intelligence or doing intelligent business? Are you wondering which method you should choose in order to achieve the desired economic results? Can one fifth of costs generate four-fifths of the profit? But, most importantly, how to define the fifth according to Pareto? It is clear that an informed decision-making process cannot do without good quality materials and outputs from internal and external analyses. Use customer data to maximise profits and to ensure a stable development of your business. We will give you the right tools for you to understand the business context.

What is business intelligence?

• Knowledge, technology, applications and processes used in business for the understanding of the market environment and business context. In other words, they are tools designed to analyse the customer’s behaviour and to define marketing objectives.
• Converting data into information that is presented to end users in a comprehensive way and subsequently evaluated as knowledge. They serve as support to efficient decision-making in business.
• Business intelligence applications process data from sales, production, financial operations and other sources, analyse business trends and results and in this way prepare key indicators for business performance management.
• The applications can show business operations as historical, real or predictive data, mostly using existing data in the data warehouse or, occasionally, using data obtained directly from operational systems. The common features of applications include data cubes, reporting, support to analyses, overview display, data mining, performance management and predictive analysis.

What can we do for you?

• We can carry out analyses and develop appropriate models from available data consolidated in the data warehouse and we also propose suitable tools.
• We are good at working with analytical means; we use sophisticated analytical and statistical functions:
  • Customer segmentation according to predefined parameters, such as service level, relationships management and working with customers (retention, acquisition, up-sell and cross-sell), targeted product offers, risk management based on various input data, behavioural segmentation based on behaviour patterns, value segmentation defined in line with the expected or current profitability, and static segmentation working with statistical data.
  • Prediction – design, testing and calibration of prediction models for various purposes. For example propensity-to-buy (PTB); churn: customer departure predictions; value predictions: life-time value; risk prediction: probability of default (PD), and loss given default (LGD).
  • Behavioural scoring – generally used as an input in the process of approving and defining credit exposure.
  • Profitability of individual commercial transactions and individual customers – allocation of realised revenues and expenses to cost centres, activities, business units, etc.; by employing a correct method this can be used as a stand-alone analytical information for management decisions or as an input in the segmentation and other processes.
• We know that ensuring operational outputs is not the only goal. The long-term goal is to use all these resources to retain customers, build relationships and increase loyalty, to optimise the product offer, disseminate the good reputation of the business and penetrate new markets whilst maintaining profitability, financial prudence and risk management.