DATA SCIENCE.

Increasing call center efficiency

BEFORE

Contact with clients conducted ad hoc/without a fixed schedule, on random days and hours.

AFTER

Contact days and time have been defined for each customer group.

EFFECT

Increased efficiency by up to 2 times for certain segments.

Identification of insurance agents generating transactions with an elevated risk of loss

BEFORE

A simple decision-making model, identifying transactions posing a high operational risk, using basic data on a single transaction.

AFTER

Automatic process of assessing the agency’s quality on the basis of its current behavior and sales portfolio, based on a complex algorithm identifying the risk of high operating costs.

EFFECT

Operating costs reduced by 30%.

Analysis of the impact of competition on turnover in own stores

BEFORE

A significant drop in sales after the opening of competitor stores. Lack of information on which product groups it affected. Lack of information on how the distance of the competitor's outlet affects turnover.

AFTER

Comparison of the level of impact of competition by store category. Determination of expected decrease in sellings on specific product groups.

EFFECT

The opportunity to plan a strategy to avoid a decrease in turnover for a single shop.

Reduction of debt collection costs in a telecom company

BEFORE

Manual selection of one of 4 debt collection strategies for a given client, based on 2 simple criteria (amount and time of arrears) and the intuition of the decision-maker

AFTER

Automated process for selecting a debt collection strategy based on different criteria and maximizing profit.

EFFECT

For 40% of customers, internal debt collection turned out to be unnecessary and ineffective. Profits from collection recovery increased by 20%.

Increasing sales on the smart shopping platform

BEFORE

Random selection of several products on the screen viewed by the customer, with no hints at the global level.

AFTER

Automatic product selection based on customer profile.

EFFECT

Conversion of recommended products at 30%

Credit risk assessment model for a financial institution

BEFORE

A simple decision model

AFTER

Automatic monitoring of the quality of the scoring model. Automatic analysis of model quality

EFFECT

A more efficient model was developed using advanced modeling methodologies.

Price sensitivity model

BEFORE

A simple decision-making model based on expert rules, using basic customer data.

AFTER

A simple decision-making model based on expert rules, using basic customer data.

EFFECT

Increase in profit by 8-12% depending on the product group.

Increasing the effectiveness of additional sales in a financial institution

BEFORE

A simple decision model based on a statistical linear model using monthly data, based on data available in only one department.

AFTER

An automated process that identifies customers with the highest propensity to buy at any given time, maximizing conversion.

EFFECT

10-20% increase in conversion depending on the customer group.

BUSINESS CONSULTING.

Revitalization of the bank's sales call center

BEFORE

Contact with clients conducted ad hoc/without a fixed schedule, on random days and hours.

AFTER

Contact days and time have been defined for each customer group.

EFFECT

Increased efficiency by up to 2 times for certain segments.

Implementation of context-specific sales at a financial institution

BEFORE

Contact with clients conducted ad hoc/without a fixed schedule, on random days and hours.

AFTER

Contact days and time have been defined for each customer group.

EFFECT

Increased efficiency by up to 2 times for certain segments.

Reorganization of a midsize service company

BEFORE

Contact with clients conducted ad hoc/without a fixed schedule, on random days and hours.

AFTER

Contact days and time have been defined for each customer group.

EFFECT

Increased efficiency by up to 2 times for certain segments.

Automated evaluation of subcontractors' financial credibility

BEFORE

Contact with clients conducted ad hoc/without a fixed schedule, on random days and hours.

AFTER

Contact days and time have been defined for each customer group.

EFFECT

Increased efficiency by up to 2 times for certain segments.