Real success stories

A company identified its customer churn patterns so as to generate alerts and thus activate loyalty campaigns for these potential customers.

After having obtained a detailed profile of the shopper’s behavior, the manager of the online area at a retail company easily recognized “proximity” sales segments within seconds. Taking these segments as a basis, he selected a sample of the customers who were delivering better response and readjusted the sample’s profile. Finally, this profile was applied on the universe of customers and prospects and in the end, the process was automated into bimonthly cycles.

A CRM manager on an ecommerce company crossed data coming from the website, from already-made transactions and from campaigns, and additionally he tracked the path to purchase in real time. Through predictive techniques, he quickly identified the best product to recommend to each customer and immediately launched cross selling campaigns.

A marketing director used Quiterian’s visual data mining techniques to forecast the profile of respondents to marketing actions, and thus increased 20% the effectiveness in customers acquisition campaigns.

A sales manager used Quiterian DDWeb both to develop a first purchase matrix to get to know activations and average expenditure per shopper, and also to predict the customers’ base churn. Not only did he improve effectiveness in retention campaigns, but he also managed to spread the customers value and lifecycle.

A telecommunications operator could state that 30% of the customers who had cancelled their telephone service were under 35 years old and had been using the service for less than 2 years. More than a half of them decided to move from one company to another because they were offered more advantages. Analyze in depth your customers’ behavior with Quiterian DDWeb and obtain from them a 360º customers view. Identify soon which active contracts have reduced expenses and anticipate to their attrition. Increase your customers’ value and secure their loyalty by working out the optimum consumption per contract and by offering them complementary products.

A hospital brought together data from various transactional subsystems. They found and were able to clean up duplicate medical records, bouts of illness with no patient, patients with no medical histories, patients aged over 120, treatments for children being given to senior citizens, etc.

A pharmacoepidemiology service successfully analysed the profile of patients on multiple drugs (for instance, people who have been prescribed more than 5 different drugs within 30 consecutive days)

A consumer credit card company saved over 20% of the time it spent on segmenting its best customers for new campaigns.

The marketing chief of a telecommunications company could get to know which mobile phones had answered to a certain campaign and which results had been parallel obtained through the web site, in order to quantify the impact caused by that campaign. Campaign Workflow ensures an integrated campaign management: targeted campaigns launching, real-time campaigns monitoring, assessing and finally modifying campaigns on the fly.

A regional healthcare service unified data from various transactional subsystems. Among them: health cards, waiting lists, blood and tissues banks, analytical accounting, registers of misscarriages, deaths and births, etc. Professionals in the sector integrated data from HIS (hospital information system) with other sources (laboratory, emergencies, pharmacy, etc.) and performed a process of data audit and hygiene, verifying coherence of information.

Two important Spanish blood and tissues banks unified data from different information sources, and carried out the testing and standardization of formats and codes depending on the institution of origin. This, together with a multi-annual treatment of information and a 360º donor’s view, enabled them to draw a profile through relevant variables (how the typical donor is and how he/she is not). They could identify the profile of new donors, the profile of recurring and usual donors, as well as the profile of donors who stop from donating.

A pharma-epidemiology service identified and analyzed simultaneous use of various drugs (patients, doctors and profile of doctors who prescribe drugs “too much”). The same service analyzed the use of risperidone and Olanzapine by senior people (+65 years old), as well as simultaneous use of trimetadizine and antiparkinsonians by general population. Through integrating data from heterogeneous sources and by putting predictive analytical techniques into practice, they made an accurate prediction of drugs consumption and of the evolution in the prescription of genertic drugs.

Using Quiterian DDWeb’s advanced analytical techniques, the pharma area in a regional hospital could get to know early the use of active principles by different medical areas. And, furthermore, its professionals analyzed the pharma expenditure per unit, disease and patient in real time, as well as the effectiveness of the active principles in specific treatments or the adherence of external patients. They could also investigate patients who had received treatments within the same medical case with these three products: Afotericina B Liposomal, Voriconazol and Caspofungina

Two regional hospitals generated content of different fields in the Integrated Scorecard (welfare, hospitalization, operating rooms, budgeting, consumption, economic-financial, human resources) and submitted it as a dynamic reporting solution. They could also generate the content of a scorecard for the radiology department and for the corporate RIS (radiology information system), while the repository that had been generated remained available for its exploitation.

An insurance company analysed benefits paid to its insured customers and detected unusual combinations that turned out to be cases of fraud.

A company identified the most appropriate products to recommend to each of its customers.

A health service discovered the causes of death among women on weight' loss diets.

A regional government ministry identified savings of 1,022,388 USD on the cost of mobile telephony.

A trading company identified the spending patterns of its best customers. New campaigns were adjusted to these patterns to achieve better outcomes.

A multinational in the telecommunications sector designed and automated a system to early detect defaults and thus prevent frauds. Additionally, the company could adjust the prices of its products and services up to the risk level. Perform optimal pricing analyses and prevent frauds through Quiterian DDWeb’s visual data mining techniques. Reduce duplicities and costs through process automation, and improve your operations and competitive position in the market.

A bank validates tens of millions of transactions every day (in total several hundred million transactions). It checks that the data comply with business rules and approves them in order to file its report with the central bank.

A phone company modified its target client to be contacted based on the responses received to its initial mail shots.

A pharmaceutical company analyses the efficiency of its sales force, how to optimise sales territories and simulates various route scenarios.

A public transport service profiled its vehicle breakdowns to implement preventive maintenance which prevented more than 80% of them.

A water utility company noticed that water reserves were dwindling while the weather forecasts were not predicting rain. They loaded 30 Gb of information from the various subsystems and in two and a half hours they had a forecast of how many days supply they had left if it did not rain.

A public service found where and when counterfeit money was being collected. It then identified the characteristics which determined this situation (the profile) and implemented appropriate policies.