Have you ever wondered how much your customers care about the experience they’re getting from you? Or, most importantly, have you ever tried to measure their satisfaction to get transparent data on their engagement level?
Without proper systems that give you real-time insights into what your customers think, it’s easy to lose control of their experience, which can lead to fewer opportunities, negative word of mouth, and more, harming your business in the long term.
How Can Customer Experience Get Out of Control?
There are many reasons a customer experience can get out of control, but ironically, many are indeed within your control.
Factors such as lack of employee training, accountability to ensure the products or services you provide are always of the highest quality, and the right technology to enhance customer experience are among the reasons why many businesses find themselves wondering why their customers repeatedly keep choosing the competition while the answers are right in front of them – they just need the right tools to measure them.
How Data Analytics and AI Helps Uncover Blind Spots in Customer Experience
Just a couple of decades ago, knowing exactly which marketing campaign or any change you make to your business works and which doesn’t was every marketer’s wildest dream. Today, thanks to data analytics and AI technology, this dream has become a reality. However, many managers still seem oblivious to the fact that the answer to increasing their market share is so close.
By collecting real-time data on customer behavior, businesses can get an inside look into their customers’ needs and preferences, both those addressed and unaddressed, to double down on the areas that bring results and close the gaps where they might be lacking.
Using Customer Experience Data to Retain Customers
Attracting new customers is expensive, especially in a tight economy. It’s much easier to retain existing ones, and one of the best ways to do that is to consistently overdeliver on their needs and keep bringing value into their experience. But in order to do that, businesses need to know what their customers want in the first place. And this is where data analytics comes into the picture.
Knowing how the business operates today, including factors related to the staff, offer, and customer service, allows companies to better understand what makes their customers happy. With this knowledge in mind, they can make well-informed business decisions that drive growth and increase customer loyalty.
“Data has become an indispensable element of any business’s operations. Those who leverage it to the fullest have a one-of-a-kind opportunity to increase customer loyalty to a level that was unheard of just a couple of years ago, while those who fail to leverage the latest data technologies will soon find themselves struggling to stay afloat.”
HappyOrNot is an innovative customer experience and data company offering a wide range of feedback terminals that allow businesses representing all industries and sizes to collect customer data in real time and access it through an intuitive dashboard. Their solution has now been trusted by over 4000 companies across the world, and this figure keeps rising as the economy forces businesses to take new measures to stay competitive.
3 Benefits of Data Analytics
While there are many benefits to using data analytics in customer experience, there are 3 main reasons why businesses decide to implement a feedback solution.
First, having access to vast amounts of data creates new opportunities for growth that often go unnoticed when businesses lack the resources to closely monitor every part of their business. Data analytics makes this process simpler, allowing for a more cost-efficient process.
Second, data analytics gives every team member an opportunity to take an active part in growing the business. This includes those who might lack the necessary customer experience knowledge, yet their insights are just as valuable.
Lastly, when customers know their opinion matters, they’re much more likely to do business with a company again and see how their feedback contributed to the growth the brand has displayed.
The Challenges of Having No Data Access
Managers who don’t have the time to manage their data analytics solutions face multiple challenges, including risking not fully understanding the ins and outs of their business, which can lead to not being able to properly communicate the business’s situation to other stakeholders, particularly the higher-ups.
How Managed Services Work in Customer Experience
Managed services allow companies to get a better understanding of their data without having to build in-house data analytics teams, saving resources that can then be allocated to improve the areas in which the business might lack based on the data findings.
5 Benefits of Merging Data Analytics with Managed Services
- Informed decision-making: With a clear idea of what makes customers happy or not, businesses can shift their operations in a way that best addresses customer needs.
- Predictive analysis: Knowing how customers behave today makes it possible to predict how they might act in the future. This allows businesses to address the needs customers might not even know they have yet.
- Efficiency: As a cost- and time-efficient solution, managed services offer savings of resources compared to running an in-house data department.
- Personalized Experiences: Using data analytics to enhance customer experience allows them to make their journey feel more personalized, further increasing their loyalty.
- Continuous improvement: Collecting data is a constant process, meaning companies can continue to leverage their power as long as they work with their managed services provider.
Managed services allow businesses of all sizes to analyze customer data in a professional manner and drive actionable insights from the feedback they’ve collected from their customers.
As the technology develops, we can expect more businesses to take advantage of this solution, further deepening the gap between themselves and the competitors who fail to acknowledge the importance of data collection and analysis.