Big data: Data analysis is customer analysis

For the managers of European companies, big data and predictive analytics are key determinants of corporate success. They want to use the new instruments to improve customer experience and get to know their customers better, to increase market opportunities for their products.

The topic of big data has clearly arrived in companies. Almost three quarters of managers in mid-sized and large companies are convinced that big data can give them the edge on the competition. This proportion even rises to over 80% if the respondents have already dealt with the issue for some time.

Forecasting is still in its infancy

Companies have now also formed a pretty clear notion of which areas could benefit most from data analysis. In survey results presented by Forrester Research on behalf of Xerox, under the title “Big Data in Western Europe Today”, 39% of managers indicated that they believe that the companies that will prevail or even dominate the market over the next three years will be leveraging big data analyses to develop new services or even new business models.

And companies are starting to take action. For 21% of them – and thus the largest portion – big data is the top priority among their IT projects. Not too surprisingly, predictive analytics, i.e. data analysis for the purpose of predicting market trends and customer behaviour, comes in second place. It appears that managers hope to use big data analytics above all to avoid repeating the mistakes of the past.

Fewer flops and more loyal customers

In this context, two issues are repeatedly mentioned in both this survey and others:

  1. Companies want to leverage comprehensive analyses to avoid developing products that fall out of line with market trends. They want to rein in the number of expensive ventures that flop because customers do not want to buy what comes out at the end.
  2. In the last few years companies have come to realise that in a market of products that barely differ from each other, the image that customers have of the manufacturer is becoming increasingly important. One of the most important factors in this context is customer experience with the company.

These customer touch points are no longer limited to the odd sales pitch now and then. People today use a wide variety of communication channels: they telephone, send e-mails, letters or faxes, visit the website or Facebook page and follow individual company representatives on Twitter. Big data analyses can help get a broad view of these various forms of communication, allowing companies, following the analysis, to identify trends and to begin to convey a uniform outward image on all the channels. And above all, marketing and sales staff are then aware of where the customer already is when he or she keeps in contact via a new channel.

Privacy, data quality and expertise

There is nevertheless still a long way to go. As the biggest challenge cited in implementing a big data strategy, the managers surveyed mentioned data security and protection. That is all too understandable, considering that a complete customer profile often comes from pooling and analysing data from various sources in the company. Indeed, in accordance with German and European data protection laws and compliance regulations, such information must be strictly protected from unauthorised access.

After data privacy, the second item on the list is the issue of the quality of existing data. There are apparently still serious problems in this area: More than half of the respondents said their companies even lack processes with which high-data quality can be ensured.

The third and fourth most common concerns mentioned had to do with the lack of in-house specialists and expertise when it comes to data analysis. Most companies do not have any in-house expertise in big data analytics and the employment market seems rather depleted as well.

Customer satisfaction can be measured

No wonder, then, that most companies still tend to rely as much on their gut feeling and experience when making important decisions as they do on the analysis of big data tools. That, however, is likely to change in the next twelve months – in favour of corporate management that is based more on quantitative information and analysis. (rf)

Matomo