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Date 24. January 2023
Author SavvyCompany
Categories Article

Data Science 2.0 – From Big Data to Smart Data with Customer Science

Not only since ChatGPT, AI was on everyone’s lips and dominated the discussions in the area of customer experience and in particular data analytics and data sciences. What kind of impact had these recent developments of AI-technology in these areas and how do they potentially enable us to design superior customer experiences?

At first glance, there are apparent fields of application like chatbots, image recognition and so forth but the vast majority of applications are naturally in data analytics and data sciences. AI enabled us to analyse the tremendous amounts of different forms of data, that have been collected during recent years. When in former times data analysts had to tediously analyse a certain data set. Now, different AI technologies can be used as a tool to put much bigger and much more diverse types of data in an often much more efficient and faster way to use.

However, this enabling factor meant also that these heaps of data had to be made accessible for exploration and analysis. Often this was the task of data scientists and data engineers and with many obstacles such as low data quality, tricky IT-infrastructure, limited timeframes and high expectations triggered by the buzzwords AI, ML or deep learning. Lead up times to actually start with the data analysis were often very long and much time is frequently lost in achieving the necessary data readiness. With these tasks data scientists are often caught up in very technical and engineering roles, which tend to be in itself relatively far away from the customers and/or business problems. This leads often to frustration within the whole organization and unsatisfying results with little to no impact.

So how can be AI technologies be used better and unlock the full potential of a more customer-centric future?

We at the savvy company believe that a domain or respective roles need to be added into the mix. AI-Technology combined with data engineering and sciences are still not enough to efficiently improve the customer experiences and thus grow business. Only with a profound knowledge of the customers and consumer behaviour in general as well as know-how of market dynamics can data sciences combined with AI be leveraged optimally. Data science needs more support to navigate the data jungle and this help must be equally scientific but in the realm of psychological behavioural science and market know-how. In essence, data science needs to be facilitated by customer science.

Profound knowledge about consumer behaviour combined with deep industry and market knowledge are essential for efficiently conducting AI-powered data analytics, which will have a lasting impact on the business – both of these traits classically educated data scientists often fundamentally lack. A ‘Customer Scientist’ trained in consumer behaviour science and in the best case with additional deep industry knowledge and domain experience could on the one hand steer and guide research processes to make them more efficient by avoiding irrelevant analyses and faulty hypotheses and thus streamline the process by enabling the usage of more efficient ‘shortcuts’. And on the other hand, fundamentally help to interpret and make sense of the results of the data analytics. A fundamental need for improved interpretation of data analytics also manifests in the current trend of ‘explainable AI’, which promotes analytical models in which humans can understand the decisions made by the AI in contrast to former ‘black box’ models in machine learning where even its designers could not explain why an AI arrived at a specific decision. Customer Scientists could be of great value in bridging this gap and facilitating the interpretation as well as an explanation of the outcomes and results.

In essence, the inclusion of customer science into AI-powered data science would allow for the development from big data to smart data. Smart data hereby represents the concept of high data quality, readily available and most importantly interpretable in a meaningful way trough deep behavioural science expertise.

the savvy company, not only has professionally trained consumer scientists with expert knowledge in Psychology and Behavioural Science, a deep understanding of different industries and markets but also has a profound knowledge of data analytics and AI at disposal. Thus, the savvy company is a perfect partner to design, accompany or review your AI or data sciences initiatives.

Contact us here for more information.

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