Customer intelligence (CI) is the process of collecting and analyzing detailed customer data from internal and external sources to gain insights about customer needs, motivations and behaviors.
CI helps organizations understand customers better so they can improve interactions and deliver more personalized customer experiences. It also provides the crucial information organizations need to improve customer communications with segmentation strategies and optimal campaign planning. All of this then helps improve customer journeys and drives the organization's future growth.
Improving the customer experience (CX) is becoming imperative for businesses to stay ahead of competitors. To deliver elevated CX, businesses need to gain critical insights into customer behaviors, including what they need and where they are in the buying journey. When available in real time, these insights provide a comprehensive view of customers that goes beyond their name, age, gender or other simple "signals" of purchasing intent or other targeted behavior. Here's where CI comes in.
CI helps create a powerful, comprehensive, sophisticated customer analytics ecosystem that enables businesses to create dynamic customer profiles and deliver superior CX to each customer. When these capabilities lead to actionable recommendations, businesses can understand customers better and design tailor-made cross-channel communications and marketing strategies at every stage of the customer journey. These strategies, when properly implemented, can increase conversion rates and customer retention.
Besides boosting marketing effectiveness, CI is a linchpin in customer relationship management (CRM). Together, CI and CRM enable companies to more effectively manage their interactions with current and prospective customers. Further, they can deliver more relevant, timely and personalized campaigns that delight customers and deliver great results for the company. Some other benefits of CI include the following:
CI is most effective when gathered from both internal and external sources. Combining these sources helps create a more complete picture of customer motivations and behaviors, which then enables organizations to take the right action to enhance CX.
Internal CI can be generated by any customer interaction. Usually, it's stored in the following locations:
External CI can also emerge from many different sources. It typically falls into one of the following three categories:
Personal demographics. This includes data such as the following:
Such data might be analyzed to explore buying patterns of people in specific income brackets, changes in sales as people age or sales comparisons of homeowners and renters.
Geographic demographics. This includes data aggregated from specific locations that could be analyzed to explore regional buying patterns. What works best in rural areas, for example, may not perform as well in urban centers where most residents are young professionals.
Attitudinal data. This includes information about how an existing or potential customer perceives the company. It may be gathered from the following:
Some companies also use speech analytics to collect and examine voice recordings to understand customer sentiment and behaviors. Others use website metrics such as the following:
External CI is particularly useful for sales and marketing teams in many different industries such as banking, retail, telecommunications and consumer goods.
Modern organizations use numerous technologies to gather and process both internally and externally collected CI. Examples include the following:
The application of business analytics to customer data is called customer data mining.
The CI process usually involves the following steps:
The CI process starts with the collection of customer information from multiple channels, including but not limited to emails, websites, phone calls, mobile apps, text messages, physical forms and contact center recordings. This data may be demographic (personal or geographic) or attitudinal; it may also be one of the following types:
While demographic data is a key aspect of CI, organizations increasingly look to transactional and behavioral data to better understand user preferences and guide their marketing and branding decisions.
Once the organization collects customer data, the next step is to categorize it for better analytics and insights. Typically, collected data falls into one of the following three classes:
A wide range of analytics tools and algorithms are available to analyze customer data collected from various channels. These tools facilitate audience grouping or segmentation based on similar patterns in the collected data. Some of these technologies include the following:
Once the analysis is complete, actionable insights are presented to relevant stakeholders in a comprehensible form like dashboards, alerts or customer journey maps. These insights help improve customer service workflows and guide future marketing campaigns to improve customer journeys, customer satisfaction and customer experiences.
See also: Tips for effective customer data mining, social listening, customer success manager, chief experience officer, customer-centric
25 May 2022