Unstructured data is key to true customer insight

18th Oct 2017

Insight into customer habits, preferences, potential issues, likely intent and much more is high on the agenda of pretty much everyone in marketing, sales, CX and other business functions. We live in the era of the empowered consumer, with more choice than ever before and the means for a consumer or business to easily switch product or service providers.

So it stands to reason that organisations want to know more about their customers. They must learn what customers’ pain points are, identify when they might be unhappy and be able to take concrete and positive steps to address such concerns.

The ability to understand what a customer is interested in, is why so many organisations have made such a substantial investment in Customer Relationship Management (CRM) platforms, to manage customer data. But with most CRM systems unable to process unstructured data, how can firms unlock the insight held within the unstructured data they hold?

The limitations of structured data

Businesses in 2017 hold huge volumes of data on their customers. This big data means there is lots of information on a customer’s intent, preferences and any potential issues, and to extract this insight, companies have invested heavily in CRM systems.

But CRM owners are constantly looking for ways in which to get more from their CRM system. The growth in customer data has outstripped the rise of CRM systems and has led to a ‘data blackhole’ in many firms, whereby the most relevant and insightful data is not being picked up and analysed by the CRM system.

Most CRM systems work only with structured data, yet around 86% of enterprise data is unstructured. The issue is clear – enterprises are attempting to understand their customers based on a tiny fraction of the relevant information. Salesforce itself has estimated that only 1% of a company’s data is used by its CRM system, meaning that vast amounts of customer insight are left untapped.

Leveraging AI

Artificial Intelligence (AI) and Machine Learning are critical technologies when it comes to empowering CRM systems, accessing and unlocking the unstructured data that is so important to successful client relationships.

Much modern comes in files and formats that most CRM systems are unable to manage effectively. Unfortunately, this data is often the most valuable, containing rich insight into that particular customer and their specific needs and requirements. This unstructured data would include: any social content – Twitter, Facebook, LinkedIn, Instagram – by, and relating to that customer; email conversations between the customer and provider; service call scripts that detail any recent or historical issues.

This is the data that really enables an organisation to understand its customers. By deploying AI organisations can collect data from multiple sources and in multiple formats, extracting fresh and insightful meaning from it and helping to deliver a complete view of that customer.

Driving revenue with unstructured Data Insight

If a firm is able to enrich and unify any data type (structured or unstructured; internal or external) and index it for future CRM and client engagement use, so the value of that data grows. The insight derived from it can be used in a number of ways: growing new business opportunities, anticipating customer needs, adopting a client-centric view and even freeing up customer management time.

Not deploying unstructured data within a CRM is potentially a major problem. It means that huge swathes of potential customer insight are missing, which can have an impact on client service.

The implications of this are potentially dramatic. Given the increased choice and ease of switching, what is a customer’s motivation to stay with an organisation that does not understand their individual and specific needs?

Only through the availability of all relevant information does CRM become truly compelling and provide an organisation with the customer insight required to thrive in such a customer-centric environment.


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