Capturing data from unstructured sources such as open-ended surveys, phone and email support, and social media networks like Twitter and Facebook provides valuable opportunities for financial services organizations. This “voice” data offers direct, candid feedback from customers and prospects.
But how can you combine this unstructured data with traditional structured data to gain a more complete picture of the customer experience?
Leveraging all your customer data for a complete picture
Companies have access to a wealth of structured data such as customer profiles, transaction histories, and surveys. Data mining and modeling of this data can yield actionable insights for issues such as attrition, customer service, and risk management. Adding unstructured text data, you can incorporate text mining into the analysis, enabling you to extract complex concepts and analyze sentiment to identify service and operational issues, as well as emerging trends of concern, cross-sell opportunities, and more.
Structured and unstructured data can each be used to enhance analysis of the other, or be combined into a common model:
- Flags representing complex concepts and sentiments found in unstructured text can be added into a model with structured data to create a combined analysis.
- Conversely, modeling of structured data can suggest a data subset that would benefit from text mining.
As an example, modeling of structured data could identify that attrition of checking account customers is most significant for single males ages 18-25 who have less than 3 accounts. You could then use text mining on unstructured comment sources to uncover checking issues for that subset of customers, and gain better insight into their pain points. For instance, including in your analysis customer comments such as “dissatisfaction with new multiple ID requirements” and “difficulties balancing accounts using online banking” could provide valuable missing pieces to the attrition problem you’re trying to solve.
Combining sources to maximize insights from social media
While social media feedback such as tweets and Facebook posts are a key source for customer experience insights, monitoring all of it can be overwhelming. Combined modeling of this unstructured data with social media metadata –such as user profiles, location data, followers, demographic details, and cookies– can help you target the most important comments. This strategy gives you a clearer picture of who’s saying what, and what it means, so you can respond more effectively.
Mining and analyzing structured and unstructured data together can create a powerful lens into the customer experience, enabling you to make truly informed decisions that will lead to better business outcomes.