According to Gartner, as much as 80% of business information is in unstructured form. This information includes customer data captured from contact center agent notes, surveys, emails, chats, and web forms.
Traditional customer retention strategies only use structured data because it’s easier for their models to understand and be trained with. Not only is this a limitation, but the foundation of a myopic retention roadmap.
While structured customer data can tell you how many customers may cancel, unstructured data can reveal your customers’ wants, needs, concerns, expectations, and reasons for potentially canceling. Without these insights, retention efforts suffer gaps and with increasing competition and growing customer expectations, you may end up lagging significantly behind.
Here are six ways unstructured data strengthen customer retention strategies:
1. It lets you know why your customers may leave you.
Still, relying on survey-based customer feedback? If so, it’s insufficient as it only involves a handful of customers. This sample size isn’t an accurate representation of your entire customer base. In addition, it fails to identify your customers’ intent and why they’re ending their relationship with your brand.
Now consider this – your contact center agents document all their customer interactions in text format. Depending on the size of your customer base, these notes can grow to millions of rows of data annually. Such massive amounts of data contain every customer interaction, pain point, and signs of dissatisfaction. Unlocking these insights will enable you to understand the intent and sentiment of every customer with unprecedented accuracy.
2. It allows you to detect churn risk early and nip it in the bud.
Customer issues left unattended for any length of time are likely to become potential churn causes. Unstructured text data helps you minimize this possibility. Applying text analytics to call center notes can reveal sentiment, intent, effort, and risk signals from customer interactions. It can also decode complex behavioral patterns that hint at potential churn. AI and machine learning enable you to gather this powerful intelligence in real-time, allowing you to take preventive measures early in the customer lifecycle. In other words, act now before an uncomfortable situation leads to an irreversible cancellation decision.
3.It enables you to only tackle the identifiable risk.
How many success stories have you heard that boast 100% retention? The answer is none because zero attrition is impossible. Some churn is inevitable. For example, trying to retain a customer who’s relocating to a non-serviceable location isn’t feasible. Pushing too hard will only result in an unnecessary expenditure of time, resources, and money because again – You’ll never be able to attain a zero-churn rate. Instead, the goal should be to minimize churn risk and address the reasons for customer dissatisfaction, which you can identify using agent-customer interaction history
4. It orchestrates targeted marketing and retention campaigns.
Recurring revenue businesses can have thousands or hundreds of thousands of customers. This means a one-size-fits-all retention approach is likely to fail. It would be great if you had a customer-level understanding and the good news is – you can. Take agent notes and add additional customer data like demographics, surveys, and transactional history and you can explore possibilities to create a powerful, unified intelligence about behavioral patterns, risk signals, and churn causes for different customer segments. Plus, your marketing teams are now better equipped to perform targeted marketing and create meaningful outreach programs that reduce churn.
5. It decodes customer voices to help you beat the competition.
If you don’t serve your customers well, somebody else will. Competition increases every day and so does the availability of options for your customers. However, if you listen to your customers carefully, you can stay ahead of the competition. While interacting with service agents, customers often mention your competitors. When you apply name-entity recognition to text notes, you can easily extract these names and identify what they’re offering that you aren’t to upgrade your competitive strategy.
6. Customer effort is directly proportional to churn likelihood.
A poor customer experience is always a top reason for churn. As a customer, you know how frustrating it can be to follow up on a service request repeatedly. Each time you put in extra effort, your experience with the service provider gets worse. By analyzing your unstructured customer data, like call records, you can identify what’s causing customers to call repeatedly. Based on this insight, you can then address process gaps that force customers into making unnecessary efforts.
Reflecting on that 80% statistic, if you aren’t using your unstructured contact center data, you’re leaving a lot on the table. This invaluable but untapped source of insight can unlock opportunities you never knew existed but that you have desperately been missing.
So, delay no more!
This blog Originally published at VOZIQ AI Blog
Image credits: Adobe