Customer feedback plays a huge role in shaping the customer experience of any company. Unhappy customers are not afraid to let others know when they feel something has gone wrong or could have been done better. That goes for positive and negative feedback, so any company needs to align internal processes, strategy, and technology to facilitate customer feedback gathering as efficiently as possible. Customer feedback can often be challenging to collect because it requires someone at the customer’s side during several activities throughout their company journey. However, there are many ways that you can leverage the power of artificial intelligence and machine learning in conjunction with other customer-centric initiatives to make it easier — and even more effective — to gather customer feedback from your users via AI software solutions.
There are many ways to gather customer feedback via AI. Three of the most common approaches:
- Feedback Tools: One of the most popular and effective ways to gather customer feedback is through tools that enable companies to ask questions in a way that customers can answer. By creating a specific set of questions around key areas, like product features or quality, you can gather valuable insights from your users while interacting with your product or service. This data can then be used to shape future interactions or help prioritize improvements to a new design iteration or feature release.
- Automated Forms: Automated forms are another effective way for companies to provide customer feedback. These forms enable companies to quickly collect data from their users without interrupting the flow of their user journey. For example, imagine you want to find out how often people use different options in your app and how often they complete tasks on each option type. With an automatic form, you could create two simple questions about what happened up until the point where the user reached these options and then have them answer some basic demographics as well — this would give you a comprehensive view of how people use these different options in your app and help you make important decisions moving forward!
- Customer Surveys: Customer surveys are another effective way for companies to collect customer feedback and gauge satisfaction levels with particular features or services offered by their company.
Pick the right data to feed AI software
Before implementing AI software to gather customer feedback, it’s important to figure out what type of data best suits your specific needs. This might involve focusing on user behavior, internal communications, and employee feedback or even reviewing some of your product’s most recent customer interactions. Once you have a clear idea of what type of data will be used in the software, the next step is choosing a platform that will provide enough accuracy while being cost-effective. Many different solutions are available that use machine learning models trained on top company data and apply them at scale to automate tasks like gathering customer feedback.
Use webhooks to collect real-time feedback
One way to gather customer feedback is by implementing webhooks. These are simple HTTP requests that your software sends to an API of the company’s choice, which can then be processed and analyzed by the software. Webhooks allow you to receive messages in real-time, which lets you have a more fluid, customer-centric experience before your customers notice anything has changed. When you use webhooks, you don’t need someone to visit the website or app as often. This also means that you’ll be able to gather information about what customers are doing with your software — something that isn’t always possible when it’s just one person who’s tasked with collecting feedback from customers. That being said, a well-implemented webhook system can still capture valuable insights about customer behavior at any time. The key to making this happen is by ensuring that your AI solution is well-equipped for AI data collection in conjunction with webhooks and other forms of data gathering.
Integrate digital surveys into your product development workflow
Digital surveys are a great way to gather feedback from customers and prospects easily, quickly, and efficiently. Digital surveys allow users to provide product feedback more effectively and in less time than other methods. They also eliminate the need for human intervention, so they’re helpful when you have many different customer touchpoints. Additionally, AI software solutions can improve the flow of information to create valuable insights and patterns that would otherwise be difficult or impossible for a human being to accomplish alone. Using AI software solutions such as machine learning algorithms helps companies collect feedback faster and more accurately because it automates what might otherwise require human intervention. With digital surveys integrated into your product development workflow, it becomes easier for your company to gain valuable customer insights.
Develop the Right Technology for AI-Geared Feedback Collecting
Before implementing AI or machine learning, developing a technology stack will help you gather customer feedback is important. This includes developing an AI-powered feedback software solution that can function in all the different stages of a customer’s journey with your company. Machine learning and artificial intelligence technologies can be used to recognize patterns in customer activity, which are then used by algorithms to build customer profiles and provide insights into how individual customers interact with your products and services. One example is natural language processing (NLP) and machine learning, where users can answer questions about their use of products or services using voice recognition software. NLP and machine learning can also identify sentiment within user responses, which gives insight into what people think about different aspects of your business. This helps you design better products for your customers by more accurately understanding their needs, wants, and desires.
The best way to collect customer feedback is through an easily-accessible interface that enables them to provide input on what they want and doesn’t want. For instance, you could allow users harmed by a product or service to submit complaints anonymously through an online form. By leveraging AI software solutions like these, you can make it easier for customers with issues with a product or service to share their thoughts without fear of revealing their identity.
Use ML to prioritize user feedback questions
Machine learning can be leveraged to assess the different types of customer feedback, so it is easy to prioritize which questions you want to answer first. You can use AI software solutions to make it easier for companies to collect and prioritize customer feedback in a way that helps them better understand your users’ needs, create more engaging user experiences, and generate more revenue via effective customer engagement. You can also use machine learning for other purposes like predictive analytics or content personalization. Machine learning is a powerful tool with many applications in business intelligence.
Leverage sentiment analysis to understand user sentiment
Sentiment analysis software solutions can be leveraged with AI/machine learning to help you understand your customers’ thinking. Sentiment analysis is an analytics technique that measures a text’s emotions and opinions to determine if it is positive, negative, or neutral. It can also be used to determine whether a text relates positively or negatively to the brand, product, or service. When looking at sentiment, AI and machine learning are powerful because they provide a comprehensive view of the customer’s experience. This means that both positive and negative customer feedback can be gathered efficiently and thoroughly, which will allow you to better understand where your company is failing and how you can improve processes to appeal to more people and make them happier.
The Benefits of AI in Gathering Customer Feedback
Machine learning is a powerful tool that can help businesses collect customer feedback efficiently and quickly. AI software solutions can process large amounts of data, identify the important feedback from noise, and provide in-depth insights into customer behaviors throughout their journey with your company. While machine learning can be used for many different tasks, one way it can improve customer feedback collection is by using AI software solutions to automatically categorize various types of customer feedback into social media channels based on sentiment and language patterns to facilitate collecting valuable insights. This helps companies maintain a more accurate database of collected comments that they can use to shape their strategy moving forward. They can also use this information to better support customers who have already provided feedback via social media channels while they still exist or create new channels as necessary. Another way machine learning can help companies gather customer feedback is by automatically monitoring user behavior across different devices and websites. This will allow you to understand how users interact with your business across different platforms and devices and identify opportunities for revenue growth or other gains due to changes in user engagement patterns that were not previously detected by traditional methods. Lastly, machine learning is a powerful tool for companies who want to address their customers directly on social media. With this technology, companies will be able to automate responses based on the type of feedback received from customers, which means less time spent on manual responses from employees, ultimately leading to more time spent on addressing any challenges.