Examples of this data include raw text, social media comments, log files and call transcripts. Structured data is housed in a traditional database and as a result, is highly schema-dependent.
For example, customer information forms are a source of structured data since they have predefined fields that customers enter information into. This data can be customer or user-generated and is present in predefined templates. One of the main challenges of generating actionable insights is the need to deal with both structured and unstructured data.Īnalyzing structured data is straightforward. "Analytics must cope with both structured and unstructured data to achieve optimal results," Sofer said. While ML algorithms offer great insights, they're fully dependent on the data they're fed during their learning and maturity stages. Preparing data for analysis: Structured and unstructured data While the human agent still has discretion over the process, the algorithm makes their job easier and more efficient. For example, a financial company can use an ML algorithm to quickly assess a loan applicant's credit-worthiness and provide a human agent with a recommendation to approve or disapprove the loan. These days, analytics platforms rely on AI and machine learning (ML) algorithms to drive actionable insights. If the information a company receives enables stakeholders to make decisions, modify current processes or overhaul them, then that's an actionable insight. Information by itself isn't an actionable insight. "Actionable insights arising from analytics and AI are no longer a luxury, but a necessity for achieving competitiveness," said Eitan Sofer, head of developer platform at Sisense, an analytics provider. Social media listening strategies also help to gather raw data and turn them into actionable insights.Įvery industry could use actionable insights. These data points are fed into an analytics platform, from which users can derive conclusions.īusiness leaders might notice that customers aren't as keen on a product feature that was popular in the past and that they're asking for a new feature or enhancement. For example, business leaders could track a customer's behavior on a platform that can indicate their sentiment regarding a product. Businesses need to use actionable insights to drive decisions, but what is an actionable insight, and how exactly is data used to create one? What are actionable insights?Īn actionable insight is a process that is derived from raw data analysis. While companies are collecting more data than ever before, many struggle to figure out what to do with it.
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