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Big Data and Artificial intelligence – Key Pillars of future Sales?

Big Data is not a “buzzword” anymore as more and more companies use is. This is driven by operationalizing of digital strategies – especially in Sales.

Based on a survey, 32 percent of around 1,750 managers see Big Data as very relevant in Sales. In 3 years, it is expected to increase to more than 48 percent. [i]

In particular, industries such as banking/ insurance, catering/ tourism, media and retail see Big Data as a value driver of their Sales activities. Taking advantage of Big Data efficiently can be a key to competitive advantages. If companies do not exploit the potential, they most likely hazard their (possibly) leading market position.

What is Big Data?

Focused analysis of big and unstructured data

Big Data can be referred to as big and unstructured data resulting from different areas and sources that is available to companies in general and to Sales specifically.

Big Data will be even more relevant in the future, which is shown by the following: in 2020, 40,000 Exabytes of yearly generated data is expected. This is around 40 billion gigabytes. In 2015, it amounted to only 8,500 Exabytes. This is a plus of 470 percent. [ii]

With the use of new technologies, companies can save and process the mass of data today. Therefore, many of our customers rely on CRM systems, which has several benefits, but solely by itself such a system is not a saviour.

Much more interesting is the process of evaluating data to generate value-added information for companies ­– also called Smart Data. With regard to this a lot of companies fail though.

How do I exploit the potential of Big Data?

Artificial and adaptive systems to analyse Big Data

Artificial intelligence is one of the key technologies in the digital change and has a significant impact on how companies are processing data in the future.

Today, artificial intelligence is used to execute predictive and cognitive analysis. Accordingly, it supports market research and provides Sales organisations with valuable customer insights. Areas of application include the forecast and diagnosis of critical indicators, including revenues, churn rate or price or and testing Sales Innovation.

It is also possible to cluster customers based on similar patterns. Furthermore, success causes or causal relationships can be derived to identify sales drivers or drivers for customer loyalty. Especially for Sales such information can be decisive in order to acquire new customers or to keep existing customers.

How is this done in practice?

Digital players and start-ups show how it is done

An example is the well-known super computer Watson of IBM. Watson has the ability to analyse, identify voices, aggregate, understand, and interpret data. Accordingly, it might replace the old-fashioned customer service and help customers with product-related problems. Watson does not only replace humans, but carries out the tasks better, faster and more efficient, which in turn leads to more satisfied customers.

Mercedes Benz also takes advantage of Big Data and artificial intelligence. The automotive manufacturer has developed an algorithm, which suggests potential car models to customers based on their preferences and hobbies. Therefore, Mercedes Benz individually meets the multifaceted needs of their customers. With increasing quantity of collected data, the algorithm learns and improves. It replaces the traditional car configurator and supports Sales regarding a need-oriented counselling.

The young grocery company Natsu also uses an algorithm. Based on a large number of data Natsu can determine when, where and how much of the inventories are sold. With the help of this the company can plan more precisely and minimize over stocks.

Summing up, all these examples show that there are plenty of opportunities to effectively use data, the so-called resource of the 21st century, with the use of artificial intelligence. According to a recent survey, only 28 percent of managers confirm that they have implemented Big Data processes or technologies. This needs to increase significantly to not miss the trend. [ii]

Contact us now in order to discover how you can generate competitive advantages with Big Data!

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of Daniel Meidl & Nikolaus Bremerich

 

Sources:

[i] Seidenglanz, R.; Nachtwei, J.; & Fischer, A. (2016). Profession Vertriebsmanagment 2016. Berlin. 2. Auflage.

[ii] Sopra Steria. (2016). Spezialisten für Data Science händeringend gesucht. Retrieved on April 28, from, von https://www.digitale-exzellenz.de/spezialisten-fur-data-science-handeringend-gesucht/

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