Customer intelligence involves gathering and analyzing in-depth data to obtain insight about customer behavior. Successful customer intelligence is based on customer feedback or interaction data from multiple channels. This data is easily harvested from thousands of daily customer interactions, including demographics, personal preferences, as well as needs and wants. The goal of customer intelligence gathering is to gain actionable insight that can be used to improve customer experience and increase customer engagement. The importance of customer intelligence, simply put, is that the more you know about your customers, the better your interactions with them will be.
On any given day, companies generally collect customer data across multiple channels that could impact any number of business decisions. The first critical aspect of customer intelligence is the ability to collect and store data at any time during the customer journey for further analysis. Equally critical is the technological infrastructure needed to analyze the aggregate data. Some companies use a combination of artificial intelligence (AI) and machine learning for gathering and analyzing data, giving them the ability to quickly deliver highly relevant content that can be used to improve customer experience.
There are several classifications of data collected by customer intelligence, including direct feedback provided to a business or review aggregators, indirect feedback, and inferred feedback. Business data is collected when a customer intentionally gives feedback regarding their journey with a business, versus data provided to review aggregators or third parties from customers. Customers also use indirect feedback to let others know how they feel about a company or brand, generally through social media, via text or other customer communication. This type of data is also collected indirectly from all customer-facing enterprise processes, such as purchase history and cookies.
Customer intelligence gathering helps organizations