Predicting the Future With Analytics

Predictive analytics puts information gained from data in correlation in order to forecast events which are likely to take place. In economy, especially in marketing, there are many possibilities. More and more companies are recognising this as a competitive advantage. According to Forbes, 89% of marketers have predictive analytics on their roadmap for 2016. (http://www.forbes.com/sites/louiscolumbus/2016/01/24/89-of-b2b-marketers-have-predictive-analytics-on-their-roadmaps-for-2016/#132cfc4ed291).

In predictive analytics, forecasts on future developments are made based on the analysis of data, e.g. on the purchase behaviour of customers. This helps companies to adapt their actions to these forecast models, as well as identify risks and possibilities. The procedure basically detects reoccuring patterns and therefore, the forecasts should only be considered as probabilities and not as facts. There are many different deployment scenarios for predictive analytics, in marketing, for example, for the assessment of customer behaviour and automated response with suitable communication. 49% of marketers already use predictive analytics, another 40% are planning to implement it within the next 12 months (Forbes).

With Predictive Analytics to Customer-centred Communication

Requirements of customers on marketing and service communication of companies are increasing. Customer-centricity is a vital success factor. If you can predict your customer's future interests, actions or purchases, you can adapt your communication accordingly and automatically output the right measure at the right time. For companies based on subscriber business models, predictive analytics may be useful, e.g. to forecast cancellations and thus initiate automated counteractions.

The system registers responses and purchases of the customer, analyses them, tries to find communalities with the data of other customers and thus derive generally valid patterns (customer who buys product A and shows these properties, later buys product B with x% probability). Over time, the system independently learns (machine learning) and develops increasingly more precise prognostics.

You can find more information on the topic of machine learning and artificial intelligence in our trend post on The Next Web Europe 2016: https://www.artegic.com/blog/next-web-europe-2016-trends-business-models-artificial-intelligence/

artegic AG supports companies in the construction of customer-centred, digital, best-in-class direct marketing. With 10 years of experience in marketing engineering, our service portfolio includes consulting, IT-integration and technology for realtime marketing automation and online CRM. artegic is the leading German specialist supplier of standard software for marketing automation via email and mobile. artegic is also operator of one of the largest software-as-service platforms for digital marketing in Europe.

With 65 employees at its German sites in Bonn and Munich, as well as international branches, artegic stands for sustainable and successful dialogue marketing with significantly better results and less operative expenses.

82% of German internet users are in contact with companies via artegic's multi-award winning ELAINE technology. Our customers include RTL, PAYBACK, BMW, BURDA, Web.de, REWE, maxdome, as well as one in three DAX companies.

Every month, approximately 2.7 billion emails, SMS and social media messages are sent in 141 countries.

artegic is certified company-wide by TÜV Rheinland according to the international standard for IT and data security ISO/IEC 27001 and has received several awards for its innovative and trend-setting implementation of data protection requirements, including the eco Internet Award, the Cased Security Award and the International Business award (Stevie).

artegic AG
Zanderstraße 7
53177 Bonn

Mr. Sebastian Pieper

Tel: +49(0)228 22 77 97-0
Fax: +49(0)228 22 77 97-900
pr@artegic.de
http://www.artegic.com
Twitter: http://twitter.com/artegic_uk
GooglePlus: https://plus.google.com/111057448053888319461/posts

This release was published on openPR.