We offer analytical services in the area of CRM and marketing operations. Our solutions provide individual treatment of customers, the identification of their typical behavior and purchasing preferences.

We have been helping companies to accomplish these goals for many years, by providing the means to effectively use the available customer information. Some of this information can only be obtained by applying advanced Data Mining techniques to various available data sources.

When a company has access to historical data about customer behavior, it is possible to model many areas of customer activity.

Our services also support the management of marketing campaigns, providing the means to reduce their costs and increase effectiveness.

Optimization of marketing campaigns

We offer a choice of analyses for the purposes of increasing the efficiency of various marketing initiatives. These analyses proved to be very precise and effective because they rely on the available customer information or on the data about the results of similar campaigns in the past. Our services help in choosing the target groups of marketing campaigns and analyzing the effectiveness of these campaigns.

For example, assume that the goal of the analysis is to choose a group of clients for the target of a direct mailing campaign. One of the possible solutions is to build a statistical model which evaluates the probability of a positive response to the offer.

Additionally, the analysis of the performed marketing initiatives and their effects make possible the construction of complex models, which predict not only the probability of a positive response, but also the expected profit.

The analytical solutions offered by StatConsulting in the field of marketing campaign optimization provide the means to:

• rank the customer according to the probability of positive response to the conducted campaign,
• identify the characteristics of customers which significantly influence the probability of a positive response,
• select a control group for the purpose of determining the profit from the campaign,
• lower campaign costs due to more accurate targeting of offers and smaller size of target group.

Cross Selling & Up Selling analytical support

Our solutions, based on statistical data analyses and Data Mining techniques provide the means to offer optimal product combinations for particular customers in ways that best match their current needs.

One of the analytical methods for discovering the dependencies between purchased products is Market Basket analysis. It provides the information which products or services are most frequently purchased together and which product basket should be offered to customers. In order to select the customers most likely to purchase a given product group, Cross/Up Selling can also be supported by customer segmentation methods or classification models.

The benefits of using our analytical solutions aimed at Cross/Up Selling support are:

• identification of product or services baskets which are frequently purchased together,
• selection of target groups for Cross Selling & Up Selling campaigns,
• increasing customer loyalty and decreasing the risk of defection, by offering the customers appropriate products fitting their needs,
• increase in sales.

Retention campaigns analysis

The planning of retention campaigns can be supported by analyzing the history of customer behavior. StatConsulting supports the selection of target groups for retention campaigns with the use of Data Mining techniques based on multinomial variable modeling.

The constructed retention models allow to determine groups of customers interested in buying various retention offers and to rank the customers according to their tendency to buy a product or service.

We also provide the analyses of retention campaign costs and effectiveness.

The benefits of using our solutions are:

• decreased campaign servicing costs,
• increased sales of various offers,
• increased customer satisfaction and loyalty,
• extended period of cooperation with customers due to better identification of their needs.

Market Basket analysis

As a part of CRM, markets basket analysis is used primarily for:

• planning of Cross Selling & Up Selling campaigns,
• planning of churn prevention campaigns,
• optimization of product and services packages,
• planning of loyalty campaigns.

We have developed proprietary software for the purposes of basket analysis. Our analytical solution provides the means to answer the following questions:

• Which products or services are purchased together?
• Which products or services are likely to be purchased in the future?
• What is the profile of customers using a given services basket?

Churn / Attrition analysis

The goal of churn analysis is to identify customers who are likely to stop using the company's products, as well as those customers, whose churn is likely to bring about the biggest losses.

Customer churn can be the result of formal actions, when contracts are officially terminated, as well as informal ones, when customers discontinue their payments without terminating the contract. Churn analysis is one of the fundamental methods in CRM.

Churn analysis profiles the customers who are likely to cease using the company's services. Identification of groups of customers characterized by high probability of defection allows the company to take preventative measures, such as attractive retention programs.

StatConsulting constructs analytical models which asses the customers' churn tendency and the loss generated by their attrition.

Our Churn analysis provides the means to:

• identify the clients who are likely to churn and select target groups for retention campaigns,
• undertake the appropriate retentive measures and diversify the preventative actions according to customer segments,
• predict losses caused by customer churn.

Survival analysis

The main purposes of Survival analysis in CRM are to estimate the time a customer will subscribe to a service or to estimate the probability of customer's defection in subsequent life cycles. This information allows the company to determine the predicted period of retaining the customer and to introduce an appropriate loyalty policy.

The constructed survival models provide the means to estimate the distribution of customer survival time with respect to various customer groups as well as to identify the most important attributes affecting the expected customer survival time.

The benefits of using our Survival Analysis solutions are:

• estimating the survival time distribution for particular customers or whole customer groups,
• the ability to monitor the changes in survival time distribution as it is affected by various factors (such as marketing campaigns),
• better understanding of customer behavior by analyzing the factors which determine customer survival function.

Customer lifetime value and value at risk analysis

Lifetime value (LTV) analysis is used for assessing the current value of future customer profits. LTV analysis serves to estimate the magnitude of expected profit (discounted on the day the analysis is performed) a customer will generate during the whole period of using the company's services.

In order to calculate the LTV index for customers it is necessary to predict their future behavior, what actions they will take, and how long they will remain the company's customers. LTV is calculated on the basis of the size of the profit generated by the customer and the estimated time of using the services. We offer LTV models which not only are based on financial indices, but also take into account behavioral information (e.g. how frequently a customer actually uses the services).

Value at Risk (VaR) analysis asses the value at risk of a customer over a short time period. It is predominantly used for selecting target groups for retention campaigns.

StatConsulting has broad experience in performing LTV and VaR analyses. We also offer analytical tools for assessing customer value.

Our LTV and VaR solutions provide the means to:

• estimate the potential value a customer has for the company,
• determine the factors affecting customer value,
• segment the customer population with respect to the magnitude of future profits,
• choose target groups for marketing campaigns.

Customer segmentation and profiling

For customer segmentation in CRM one uses, among other means, financial indices such as LTV, which can predict the future profit from customer.

The application of a dynamic segment updating mechanism provides the means to observe the changes in costumer profiles over given periods of time.

The analytical CRM solutions offered by StatConsulting in the area of customer segmentation and profiling provide the means to:

• select target groups for marketing campaigns,
• determine the product or services profile for particular segments,
• define characteristic groups of customers,
• determine the profile of a given segment,
• discover niche customer groups, which can remain unnoticed in the case of segmentation which does not use Data Mining techniques,
• analyze the migration of customers between various segments,
• increase the accuracy of analyses by diversifying them on a segment-by-segment basis.

Data exploration and visualization

Data analyses and the construction of scoring models for CRM purposes should be proceeded by the exploration of the utilized data sets and visualization of the obtained results. In this way it is possible to formulate preliminary statements about, for example, the exclusion of some of the observations from the analysis, or the necessity to extend the available data with information from other periods of time.

The problem of the visualization of data exploration results is significant especially from the perspective of CRM, where one usually deals with very large data sets containing customer information.

The software offered by StatConsulting is capable of creating transparent data visualizations, which provide the means to:

• discover the dependencies between different attributes,
• discover incorrect values attained by various attributes,
• verify the stability of attributes over time,
• estimate the basic statistics describing the distributions of various attributes,
• automatically create a report describing the exploration results.

Data Quality analysis

Quality analysis of data for CRM is especially important because of the constant changes of customer information databases. These changes are due to:

• acquisition of new customers,
• changes of terms of contracts for existing customers, as the results of loyalty programs,
• changes of offered products and services,
• a growing history of customer relations in the context of changing economic conditions.

Data quality analysis is a fundamental part of any analytical project carried out for the purposes of CRM.

StatConsulting offers data quality solutions such as data profiling, deduplication, standardization and data enrichment.

Feel free to contact us with any questions you may have. We will be glad to answer any inquiries about our products and services.