How AI Unlocks Brand Value in Unstructured Data

Ido Ramati Ido Ramati
March 26, 2020 Big Data, Cloud & DevOps
Unstructured data is being wasted by companies the world over. It is estimated 90 percent of an enterprise’s data is unstructured, living in emails, online reviews, or other untouched and ultimately useless formats. This data – defined as “unstructured” and growing at 55 to 65 percent each year – offers valuable customer insight if properly understood.
The good news is that technology exists for brands to leverage it and plan for the long term – all they need to do is pick up the data and analyze it.
Artificial Intelligence allows brands to receive and respond to customer feedback in real-time, both through influencer analysis of social media platforms and the in-depth capturing of customer expectations, preferences and aversions.

From unstructured data to quantifiable insights

Just because data is tough to read does not mean it is useless. Service center calls, online reviews, social media mentions and open-ended survey questions can reveal important customer sentiment about any given brand or subject.
Understanding this information previously warranted manual and lengthy searches – until now. AI is being used in a number of ways to quickly reveal customer insights from this unstructured data. For example, natural language processing can be used to extract the meaning of business documents, emails, journal articles, and social media posts. Pattern recognition algorithms can be used to identify people, animals, or other objects in catalogs of digital images. Meanwhile, speech-to-text conversion can be used to turn audio speech into searchable text.
Translating unstructured data into structured data makes information much easier for Big Data machines to process, bringing exciting customer service prospects into the fray.

The promise of today

The explosion of customer feedback channels only continues to grow the size of unstructured data. This is daunting as there is no shortage of data, but it is more complex. However, today is an opportune moment for market researchers and product innovators looking to understand their customers at scale. 
This is a far cry from previous manual research. This process could take brands months if not years to actually comprehend customer sentiment and recover from mistakes. A failed product launch could literally continue to fail for six months until the given brand realized and corrected course.
Previously, companies would receive generic insights quarterly or monthly, disabling decision makers to dig deeper. This is simply not good enough in today’s digital, diverse world. Giving structure to today’s customer feedback makes customer sentiment much easier for brands to collect and consider.

The potential going forward 

It is hard to understate the promise of unlocking unstructured data. Collection and collation of this information offers brands of all shapes and sizes a complete market analysis, including deep brand portfolio insights and competitor portfolio understanding. Further, product marketers are finding it useful for a multi-dimensional analysis of customer service, product innovation, and brand.
Mining this data properly also works to alert companies to failures or errors much earlier than before. Drawing from unstructured data pays dividends in the long-run as it cuts the feedback loop short by a magnitude of months to days. The previously unharnessed insights assist teams to provide better product, service, sales, marketing and purchase experiences. Better customer experience means better customer service, and understanding the views of the customer is vital to this process. Unstructured data matters because it reflects the overlooked yet integral inputs of the market.
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