Gartner says that as much as 80% of business information is in an unstructured data form. This includes customer data that contact center agents write in their notes, surveys, emails, chats, and web forms.
Structured data is easier for models to understand and train within traditional customer retention strategies. This makes it easier for them to keep customers. You can’t keep track of everything that happens in your life. This is also the foundation of a “eyes only” retention plan.
Structured customer data can show you how many customers might cancel, but unstructured data can show you what your customers want, need, expect, and why they might cancel. Without these insights, your efforts to keep customers may have gaps in them, and with more competition and higher customer expectations, you may be a long way behind.
Here are six ways that unstructured data help customer retention strategies:
Because you can see why your customers might leave you, this is a good thing.
Survey-based customer feedback is still a good idea. If so, it’s not enough because it only has a few customers. This sample size isn’t representative of your whole customer base. Another thing that doesn’t work is that it doesn’t figure out what your customers want and why they’re ending their relationship with your brand.
Now, think about this: Your contact center agents write down all of their customer interactions in text format. It all depends on how big your customer base is. Each year, these notes can add up to millions of rows of data. Every customer interaction, pain point, and a sign of dissatisfaction can be found in these huge amounts of data. When you find out what these insights are, you will be able to understand every customer’s thoughts and intentions with unprecedented precision.
It allows you to find out about churn risk early and stop it in its tracks
There is a good chance that customer problems that go unanswered for any length of time could lead to churn. Unstructured text data helps you to lessen the chance of this happening. Applying text analytics to call center notes can show how customers feel, how much effort they put in, and how risky their interactions are. It can also read complicated behavior patterns that show that someone might leave. As AI and machine learning get better, they can help you get this powerful intelligence in real-time, so you can take preventative steps early in the customer lifecycle. In other words, don’t wait until a bad situation forces you to cancel your plans forever.
It lets you only deal with the risks that can be seen.
How many success stories have you heard that say 100% of the people who came to them stayed? In this case, there can never be any attrition because that is impossible. There will be some churn. For example, trying to keep a customer who moves to a place where you can’t serve them isn’t possible. You won’t be able to achieve a zero-churn rate if you push too hard. This will waste time, resources, and money. Instead, the goal should be to keep customers happy and keep churn at a minimum. You can find out why customers aren’t happy by looking at how agents and customers have interacted in the past.
It runs targeted marketing and customer retention campaigns
Recurring revenue businesses can have tens of thousands or even a million or more customers. This means that a one-size-fits-all way to keep people from leaving isn’t going to work. Having a customer-level understanding would be great. The good news is that you can. Take agent notes and add other customer data, like demographics, surveys, and transaction history, and you can think about how to build a powerful, unified intelligence about behavioral patterns, risk signals, and churn reasons for different customer groups. Plus, your marketing teams can now do more targeted marketing and come up with meaningful outreach programmed that keep people from leaving.
In this way, it can help you beat your competitors.
If you don’t do a good job for your customers, someone else will do it for you. Competition grows every day, and so does the number of options your customers have. However, if you pay attention to what your customers say, you can keep up with the rest of the business. Customers often talk about your competitors when they talk to service agents. When you apply name-entity recognition to text notes, you can quickly find these names and figure out what they’re offering that you aren’t so that you can improve your competitive strategy.
The more effort a customer puts in, the more likely they are to leave.
It’s always the case that a bad customer experience is the main reason for people to leave. When you’re a customer, you know how annoying it can be to keep following up on a service request over and over again. Every time you try to do more, the service provider’s service gets worse. By looking at your unstructured customer data, like call records, you can figure out what’s making customers call again and again. Based on this, you can then fix process gaps that make customers do things they don’t need to do.
When you think about that 80% figure, if you don’t use your unstructured contact center data, you’re leaving a lot of money on the table. This valuable but untapped source of information can help you find opportunities that you didn’t know about but that you’ve been desperately looking for.