Are Customer Experiences Helping Businesses Redesign their Data Strategy?

By Amit Luthra, Director & GM – Data Centre Solutions, Dell Technologies, India

Amit Luthra, Director & GM – Data Centre Solutions, Dell Technologies, India

Over the last decade, consumers began seizing control of their decision journey by changing the way they research and buy products. They actively pull information that they find helpful vis-à-vis passively responding to a marketing push, leading organisations to reinvent the steps involved in a customer’s journey. Through the enormous amount of data that retailers are privy to about customers, they offer targeted, personalised offerings to influence customer buying decisions. Data is collected to understand customers behavior to drive an intuitive and predictive customer experience strategy.

As per a report by Forrester, companies that prioritisd customer experience have 1.7 times higher customer retention, 1.9 times return on ad spend, and 1.6 times higher customer satisfaction rates. Holistic customer journey experiences that include discovery, research, purchasing as well as customer support have become a key driver for both, customer loyalty and retention. Despite the growing thrust on customer experience, organisational leaders still grapple with fundamental challenges that interfere with extracting value from customer data to deliver an effective customer experience:

  • Information overload: With businesses going omnichannel, the number of customer touchpoints have increased considerably. The emergence of new hardware and software development coupled with evolving media channels as well as devices makes the data management process even more complex.
  • Identifying well-defined data sets: Most organisations deal with primarily two types of data: transactional data, the volume for which may fluctuate during various time periods (eg. The retail industry may experience increased sales during festivals)  and unstructured data which is usually generated based on a customers’ experience and response to how they interact with a brand or product. Hence, data types can lead to data loopholes and hamper scalability needs in the future.
  • Fragmented technology infrastructure: To manage the increasing flow of information and data, organisations engage with quick fixes through patching or adding new computing options to their legacy systems. This ad-hoc approach creates data silos with data stored not in complete sync with the new environment which may hamper data visibility for accurate decision making.
  • Accessibility of information: A consolidated view of the customer is the key element that helps in standardising services to customers and ensuring a more positive customer experience. A 360-degree dashboard reflecting the customer engagement across touchpoints is a necessity for all the teams to work cohesively which can be achieved by dissolution of data silos and operational coordination aloing with adoption of cloud.

A well-planned customer experience strategy thrives on personalization, which requires a significant amount of data. It is extremely important for organizations to identify the potential of this data, take measures to protect and store this data before deciding to adopt a hybrid cloud strategy or move compeletely to the cloud. The ability to retrieve and update customer information across touchpoints in real-time fuels the customer strategy. Moreover, this flexibility and scalability along with overcoming location-based restrictions of a cloud strategy can help limit application outages and latency issues during high traffic season. In the years to come, organisations will increasingly take cognisance of the nature of the data they collect and establish strong data governance policies to comply with regulatory requirements. A safe, accessible harbour for data has the potential to unlock immense potential for businesses with machine learning and artificial intelligence to build predictive models that can take customer experience to the next phase.

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