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Background of the Problem

Many will remember the game show "Let´s make a Deal" from the 90ies where candidates had to choose one of three gates. Behind one gate, the prize was always hidden, and behind the other gates lurked blanks, i.e. the Zonk or, in the USA with presenter Monty Hall, goats. At the start, the candidate always chooses a gate behind which he believes the prize to be hidden. Then, the presenter can try to change the candidate´s mind to other gates by offering cash. He can also open gates in order to increase the excitement.

Starting Point

In order to be able to use an effective customer relationship management, it is of great importance to have robust knowledge about one's own customers and customer structures - especially in the area  of campaign management. Personal information about customers, events and changes in the customer situation and behaviour in a CRM system can be used as opportunity for communication. By means of this existing data, a personalized interaction with the customer, such as offers and services, becomes possible.

Many businesses are currently starting to make initial experiences with the use of big data methods. By means of statistical methods, these methods promise to generate additional knowledge about the customers from huge amounts of mostly unstructured data in very short time. Frequently, automatically generated data such as log files or clickstreams collected from the use of the website, a web shop or data from social networks, is used for this purpose. This knowledge can be of good use for CRM activities. In this context, the question of the significance of data quality in the use of big data methods arises. Because: The analysis and thus the generated knowledge can only be as good as the quality of the data used.  

I have been an intensive SPSS user since my time as psychology student. Accompanying me across all versions during this time were the simple brief commands in order to show me descriptive statistics. These short commands quickly become second nature and thus enable a fast data viewing.

Currently, my tool focus is on R. It is an excellent alternative but despite extensive experience with this open source tool, I still feel a lack of the usability of SPSS. I simply miss my short commands. However, it is relatively easy to add simple commands similar to SPSS as functions in R yourself.

Time after time, one comes across types or variants of graphics which at first glance apparently cannot be implemented with arcplan. With simple tricks, however, almost all graphics can ultimately be realized with little effort. Anyone who is currently looking into SUCCESS by Hichert and Partners will encounter e.g. clear notations for value types in bar charts.

Starting Situation

Isolated applications which make a standardization of processes impossible can be found in tool landscapes of media forecasting with regional focus. The media types often require specific budget allocation tools, availability checks and booking of placements for their forecasting. The forecasting results are manually transferred and checked for target group acceptance and visually prepared via a geo-information system (GIS). All outputs are subsequently exported separately in Excel format, manually compiled and formatted to the customer's CI - on request, this is also implemented in PowerPoint. If a customer feedback results in an adjustment, the process is repeated.

These factors cause both manual processes and a high coordination and communication effort in the interaction of customer consultant, media planner, creative agencies and the advertising customer - this results in inefficiencies and high processing costs for all involved parties.

This situation is the starting point of an optimization project regarding the implementation of a marketing resource management system (MRM) at a leading German media agency. Together with its sister companies, it is the fundamental element within one of the largest forecasting and purchasing agency networks worldwide.

With the new version, significant innovations have been implemented in arcplan 8 which have a very positive influence on future projects involving the arcplan product suite.

The new HTML5 client and the responsive design must be mentioned here. They make developments of BI applications for mobile terminals significantly more efficient; this also applies to desktop applications.

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Starting Situation

The modern market is overcrowded by a variety of providers of goods and services. Many of them try to reach the customer not only via traditional ways, such as e.g. billboards in the streets or shop windows, but also online. One type of online marketing is location based advertising (LBA) which is sent to the customers' mobile terminals. In this context, it is decisive that the dispatch is aligned with the customers' location. Thus, the customer receives an offer at the time he/she is in the vicinity of a promotion location. The rule for location based advertising is: "Right offer, right location, right time".

The Technical University Munich (TU Munich), ETH Zurich and b.telligent haven been working on the PROSET research project for three years from February 2011 to February 2014. The project centered on questions which cannot usually be pursued in everyday working life due to lack of time. In this context, questions which are not only relevant for practice, but also bring to light new findings for research are raised. In the PROSET project, we have concentrated on the question of increasing productivity by means of service experience management.

In presentations and in reporting, the primary purpose of graphics is to convey information quickly and efficiently. That means that graphics are supposed to illustrate important messages, such as e.g. trends, deviations, patterns and conspicuous behavior such as peaks, outliers etc. at a glance. This applies in particular if the objective is to use the Hichert©SUCCESS Rules in presentations and in reporting.

Starting Situation

A customer operating in the financial sector has been using a proprietary CI tool for conducting direct marketing campaigns for some time. This has been tailored to the individual needs of the client over the years and constantly updated. However, as the requirements posed on the solution by the department have grown disproportionately over time, the proprietary development did not meet the latest requirement analysis of the department.

In an internal project, it was e.g. determined that the user interfaces can no longer be expanded with reasonable effort. Thus, as a result of the requirement analysis, it was resolved to replace the proprietary development with a new, external and sustainable campaign management solution. Accordingly, b.telligent was retained in order to conduct an evaluation of external campaign management solutions within a fixed time period.

Starting Situation

Despite the functioning implementation of CRM tools, an efficient success reporting is essential for the evaluation and future strategic alignment of marketing measures. A well-known leading provider in the VoD (video on demand) field has already been using CRM measures for some time now, but due to a lack of monetary success measurement, there is no information about the performance of the campaigns rolled out so far. This lack of economically relevant data is thus similar to a flight without route and radar.

The CRM reporting in place at the outset of the project only insists of information provided by the email marketing provider, such as dispatch quantity, opens, clicks etc. and does not provide any information e.g. about a financial or qualitative success of a campaign.

In arcplan, the individual selection constitutes a fixed list of elements which were selected by the developer. Up to arcplan Enterprise 6, a database query for an individual selection did not take place. Thus, this could be used for performance optimizations or for a pre-selection. However, customers frequently requested an add-on for updating the displayed texts.  As a database query did not take place, there was no update here, either. For example, a typo corrected in the database was not updated in a performance indicator as it was not screened against the database. From a performance perspective, this was optimal, as well.