The Internet of Things (IoT) will be common in 2020 and will change the interactivity with the customer in the web. The number of connected devices will increase from approximately 5 billion in 2015 to 25 billion in 2020. All areas of daily life will be affected. [1]

With the IoT more data can be collected to obtain a more obvious picture of the customer and get a detailed customer profile. Of course user data will be collected, but also data about the surrounding, such as location data, interactions with other users, or items which are equipped with sensors have to be included in the profile. [2]

Data Mining Tools within IoT

To collect all these data, different tools are required. A huge number of free data mining tools are available. They can be used for different use cases:

• Statistical analysis can be done with R.
• Weka is a tool which can be used for several data mining tasks, it is a java-based application.
• Another data and text mining software is RapidMiner, it is easy to use by drag and drop.
• Knime is a well-known data mining software which supports all major file formats and databases.
• Gephi is the right tool for visualization of networks and complex systems.

Cloud solutions which automatically support multi-channel marketing, with integrated tools for content management across different channels, with social media tools for customer engagement and analytical tools for creating customer profiles are all-in-one solutions for marketers to create customer profiles in the IoT. [3]

Marketers believe that the development in IoT technologies will have a huge impact on their business. New ways of user communication are possible, because many of the objects which are connected to the internet do not have a screen anymore. Nevertheless, they interact with the user and with other objects. Data management will be a big challenge, because users will not have 5-10 devices, but a non-countable number of devices. Not only smartphones, tablets and other mobile devices, but all connected objects they use. A possible solution could be to create a customer profile by the usage of a combination of different data from normal mobile devices and IoT devices. [4]

IoT will have a positive influence on customer profiling, but only if the data is collected among all used touchpoints and from all used connected devices.

The legal perspective on profiling, data privacy and security are relevant topics in this research area. These topics are important for the future development of customer profiling in the IoT and their development should be part of the enhancements in customer profiling.

Sources:

[1]        Brandt M (2014) Infografik: Internet of Things wird bis 2020 alltäglich | Statista. In: online. http://de.statista.com/infografik/2937/mit-dem-internet-of-things-verbundenen-geraete/. Accessed 27 Dec 2015
[2]        Portugal N (2013) How the Internet of Things Will Change the User Experience Status Quo. In: Matera M, Rossi G (eds) Trends Mob. Web Inf. Syst. MobiWIS 2013 Int. Work. Paphos, Cyprus, August 26-28, 2013, Revis. Sel. Pap. Springer International Publishing, pp 1–5
[3]        Compton J (2015) The Marketing Cloud wars—revisited. In: thehubcomms.com. http://www.thehubcomms.com/marketing-cloud/the-marketing-cloud-warsrevisited/article/457789/. Accessed 27 Dec 2015
[4]        Emarketer.com (2015) The Internet of Things: Tracking the “Cross-Everywhere” Consumer – eMarketer. In: Online. http://www.emarketer.com/Article/Internet-of-Things-Tracking-Cross-Everywhere-Consumer/1012644. Accessed 27 Dec 2015