Archiv für den Monat: November 2018

Big data gives the trade fair business a boost

The digital transformation doesn’t stop short of trade fairs and exhibitors. The trade fairs are reacting and are already using technologies such as blogs, social media, apps, and analog and digital screens in their communication. And they have digitalized visitor management and thus collect enormous amounts of data.
Evaluating and visually displaying data is the task of so-called business intelligence (BI) in order to gain insights that can be used to support the company when taking operative and strategic decisions. Using BI, trade fairs are able to answer economic and trade fair-specific questions by systematically linking, evaluating and displaying trade fair data. Key figures and evaluations at specific points of time, during and after the trade fair, in conjunction with target/actual comparisons provide better support for the management in order to improve the quality of operative or strategic decisions.

Trade fairs gather millions of items of data

Trade fairs possess an unbelievable amount of data, which can be considered a hardly exploited treasure. That is why trade fairs are predestined to use big-data analyses and can profit from these in order to better plan their business. The data comes from the registration of the visitors, from shop data, admissions and departures, no-show rates, sociodemographic structural questions (position, company size, business sector, interests), ticket sales, and support requests.
At the trade fair itself the visitors also generate data. Movement data is also available in anonymous form and in compliance with data privacy regulations, not only by accurately counting admissions and departures but also through heat maps of the premises. Furthermore, trade fairs also collect data from exhibitors and can thus provide matchmaking between exhibitors and visitors.
This data can be used more comprehensively. The trade fair company can, for example, search for correlations. Thus, using the anonymized data on visitor movements, it is possible to analyze the probability that a visitor will visit another exhibitor. Ticket and visitor data can be combined and used to produce forecasts. In future, it should be possible to anticipate potential industry-specific developments using predictive analytics.


Lunch & Learn bei dimedis – Als in Kalk noch die Traktoren rollten

Egal ob Wissensmanagement, neueste Trends im Bereich Social Media oder die richtige Bewegung am Arbeitsplatz: die regelmäßigen Lunch & Learn-Veranstaltungen bei dimedis werden immer gerne angenommen, um während der Mittagspause nebenher noch Nützliches und Interessantes zu lernen. Dieses Mal war Karl-Heinz Fuchs von der Geschichtswerkstatt Kalk e.V. zu Gast, um uns aus der Zeit zu erzählen, als in den heutigen Räumen von dimedis noch die Traktoren rollten. Für die Mitarbeiter gab es dann eine lebendige Geschichtsstunde, in der sie mehr über die Gebäude erfahren konnten, in denen sie nun Software entwickeln. Die Geschichtswerkstatt Kalk ist übrigens durch unseren vorherigen Blogbeitrag über genau dieses Thema auf uns aufmerksam geworden.

Karl-Heinz Fuchs von der Geschichtswerkstatt Kalk referierte beim Lunch & Learn über die Geschichte von Kalk und der Dillenburgerstraße. (Foto: dimedis)