SAS is behind a multifold increase in the number of clients with whom Generali communicates using targeted campaigns

Today, regional insurance company branches can quickly and flexibly prepare product campaigns precisely matching the local specifics.

The professional career of Ladislav Prekop has been tied to data ever since he began working as a business analyst in the insurance business. He realised how valuable data is even more once he became a manager of the Reporting and Analysis Department and responsible for analysing customer data and preparing campaigns. This is why he has such an excellent understanding of customer relationship management. “If CRM is to work, it needs to be built around data,” he says.

This was his motto when he began working for Generali as the CRM and B2B manager. In the past, Generali was not one of the insurance market leaders when it comes to analysing data for customer relationship management. Customer samples had been selected by IT staff according to certain selection criteria on the basis of requests from other departments. This process, however, was very labour intensive and it could take up to several weeks till the database was ready. If the requesting department then discovered the data did not match its original idea, they had to wait once again for the new sample.

A clear idea

First and foremost, L. Prekop wanted to speed up and improve the quality of preparing campaigns for the internal sales specialist network. Speeding up the process would aid individual Generali branches in preparing their own campaigns in a simple way. The improved quality would make the sales specialists’ work more efficient and improve their confidence in the headquarters. Of course, behind both parameters there's an effort to improve our business results. “At the same time I was aware that we cannot achieve a significant improvement without quality software,” he adds.

To analyse customer data, Generali chose the SAS Enterprise Guide software solution. Not only because the staff at the CRM and B2B department were used to working with SAS tools. “One of the deciding factors was that this software allows us to prepare interesting analytical projects without a
knowledge of programing,” notes L. Prekop. Because of this, even if the employee responsible for campaigns should leave the company, we don’t have to discard ongoing projects. Even a complete novice can understand them. “If an analyst leaves us, he/she does not take all the know-how with them, which would be the case if we prepared similar projects using programing,” he adds.

Maximum automation

The first thing the SAS software did at Generali was to remove inconsistencies and improve the quality of the data used to target campaigns and analyse the portfolio. Having linked the system to our data warehouse, we started a process of data unification and seeking of the so-called one version of truth about our customers.

In the next step, the responsible team made sure that the SAS software works well with the central information system of the insurance company. Our objective was to automate the entire process of campaign preparation, thus making it much faster.

Today, when a regional manager requests a sample of potential clients for a micro-campaign, he/she just needs to fill out the prepared form. From the form, the analytical tool automatically ‘reads’ individual criteria, analyses the data in the data warehouse and within several hours uploads to the campaign tool leads which a sales specialist can immediately work with.

Diminishing scepticism

After a year and a half, L. Prekop managed to reach the first goal he set for himself - make the internal network work with campaigns and use lead management. “I consider it a great achievement that we were able to overcome the initial scepticism and persuade even those sales specialists who in the past were used to working in a different way,” he says.

At present the insurance company is running multiple cross-selling and up-selling campaigns. Using the new SAS software-based system and its connection to the campaign tool, the company managed to reach out to about a quarter of its clients in the past year. For comparison, previously it was just 2 to 3% a year. Of course, L. Prekop understands that using analytics is similar to a long-distance run. His objective is to gradually contact up to half of all clients each year using campaigns built around data. At the same time, he wants to expand what analytics can do both in terms of volume and quality.

After the launch of cross-selling and up-selling campaigns, the CRM and B2B department at Generali began preparing the best offers the insurance company can offer its clients based on data analysis. It is also working to improve segmentation. “In the future we also want to use predictive modelling, but before we can do that we need to further improve the quality of the data in our data warehouse,” explains L. Prekop.

Predictive modelling can tell the insurance company what is the likelihood of the selected clients reacting to the offered deal. Because of this, the company will be able to select a smaller group of targeted clients who are most likely to find the offer interesting. This not only saves costs but also eliminates unnecessary client communication.