Understanding Customer Experience Analysis and its Data Sources
Overview According to a recent report by Walker, customer experience is there to overtake price and product as the top brand differentiator. Moreover, 86% of customers say they're willing to pay more for a better customer experience. A positive customer experience adds to the success of your business because a happy customer becomes your loyal customer and helps you boost your revenue. First things first, let's understand what customer experience is. Customer experience is the first impression of your brand that your customers have throughout the entire buyer's journey. Therefore, it impacts factors related to your brand positioning, including revenue.
What is Customer Experience Analytics? Coming to customer experience analytics, it is the process of mapping the entire buyer's journey and the customer experience with the brand. The voice of the customer is derived from an AI-based machine learning platform to make data-backed decisions. Customer experience analysis evaluates both quantitative and qualitative data to monitor customer satisfaction.
Why Do Companies Need Customer Experience Analysis? Customer experience analysis is required for a variety of reasons, which include: ● ● ● ● ● ● ●
Boosting customer satisfaction Enhancing brand engagement and awareness Increasing sales conversions Better performance analytics Driving product improvements Improving public relations Augmented competitor awareness
What Are The Various Types Of Customer Experience Data Sources? There are three different data sources to acquire customer experience data and analytics: direct, indirect, and inferred. So, without further ado, let's understand these data sources. With customer experience data collection and analytics, you can use one of three data sources: direct, indirect, or inferred. Let's look at these data sources in more detail. ● ●
Director Sources Indirect Sources
How Is Customer Experience Analysis Done? First, to perform customer experience analysis, gather the relevant data, clean it up and process it through video content analysis, identify and extract entities, and remove critical aspects and features. Let's understand the customer experience analysis process in detail: ● ● ● ●
Gathering the data Processing the data Analyzing the data Visualizing the insights
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