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How Unstructured Data is Revolutionizing Marketing

There’s no shortage of data but not all data is created equal. Structured data is easy to interpret. Unstructured data, on the other hand, isn’t. The thing is, unstructured data is where the real insights lie. With as much as 90% of data being unstructured, it can be overwhelming. 

Overwhelming for humans at least; AI, like BENlabs own deep learning AI tools, is already hard at work, helping marketers make sense of this rich source of insight. 

It’s no secret that marketers are always looking for new ways to draw actionable insights from data. Unstructured data is already revolutionizing marketing with the help of AI tools. And while deep learning AI can already draw incredible insights from unstructured data, we’re only really getting started.

What is Unstructured Data?

Unstructured data is data that has no predefined format or organization. Think of the glut of data present in various sources like social media comments, email, chat logs, customer feedback to start with. Unstructured data can be in the form of text, images, audio or video. It is unstructured in the sense that it doesn’t easily fall into simple categories. Unstructured data is complex and requires advanced data analysis techniques to make sense of it. Deep learning AI is required to draw insights from unstructured data at scale.

The Impact of Unstructured Data on Marketing

Unstructured data represents a largely untapped source that will change the way marketing, product, and customer success teams (to name but a few) analyze and understand customer behavior. 

By mining unstructured data and—importantly—making sense of that data, businesses can gain insight into how customers perceive their brand: what they like and dislike,what their needs and preferences are etc. With this information, businesses are equipped to create more targeted marketing campaigns, more personalized messaging, and better customer experiences overall.

One of the most significant impacts of unstructured data on marketing is in the field of sentiment analysis. Sentiment analysis is the process of using natural language processing (NLP) and machine learning techniques to analyze text data and determine the sentiment behind it. By analyzing unstructured data such as customer feedback, social media mentions, and reviews, businesses can understand the overall sentiment towards their brand and products. Understanding and taking action to maintain or improve sentiment is the next logical step.

Another impact of unstructured data on marketing is in predictive analytics. Deep learning and NLP AI can analyze unstructured data sources to identify patterns and predict customer behavior, preferences, and needs. Predictive analytics can help businesses create more targeted and effective marketing campaigns, as well as improve customer retention and loyalty.

BENlabs Predictive Analytics, for example, is a deep learning NLP AI tool that can predict the results of an influence campaign, in some cases before a single dollar is spent, with a predictive accuracy not available anywhere else. 

Challenges of Analyzing Unstructured Data

Unstructured data is perhaps the biggest opportunity for businesses today. The problem is that, by definition, this data lacks clear structure and as such, requires interpretation. Unstructured data is not organized. It’s “messy.” While human analysts can make sense of this data, AI and machine learning are the keys that unlock and the valuable insights unstructured hides at scale.

In short, unstructured data is a goldmine of business and marketing insight but most businesses are only beginning to look for the prospecting tools that will guide them toward the motherlode. That is an opportunity for forward-thinking marketers.

Make Sense of Unstructured Data
with BENlabs

BENlabs AI expertise powers Predictive Analytics, A/B Autopilot, Smart Targeting, ROI Intelligence and other proprietary tools that give marketers a clear lens on the insights unstructured data has to offer.

BENlabs AI is the key to surfacing insights early, and acting on those insights quickly to optimize campaign performance.

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