Six Stages to Develop a Customer Intelligence (CI) Strategy


    Customer intelligence (CI) is the most effective strategy for gathering information from both internal and external sources.

    For businesses to stay ahead of the competition, providing an improved customer experience (CX) is essential. Customer intelligence (CI) assists businesses by providing superior customer experiences to each customer while producing robust, thorough, and sophisticated customer analytics that allow them to analyze dynamic customer profiles. A good customer intelligence strategy requires teams to use centralized technologies, as real-time data comes from multiple sources. Marketers need to know what they can use for collection, storage, analysis, and action.

    Data transformation into intelligence

    It makes no difference if marketers have access to an abundance of data if that data is not utilized wisely to draw insights and improve the business strategy. There are countless methods for gathering client data as the first step in the customer intelligence (CI) strategy.

    While transactional and behavioral data are being used by businesses to understand user preferences better and inform their marketing and branding decisions, demographic data remains a crucial component of customer intelligence.

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    Data Categorization & customer satisfaction

    As a brand, being loyal to the customers is more critical than customers being faithful to the brand. This customer loyalty can be created by engaging and interacting with the customers on their desirable platforms, building a strong customer relationship once brands get access to the customer intelligence.

    The brand must ensure that customers are being served with better services so that they do not switch services because customers like to put effort, money, and time only where they get better and more satisfying services.

    The data science team plays a crucial role in satisfying the customer by giving useful, valuable data insights.  Closing the loop on unsatisfied customer feedback by taking favorable steps to control customer issues, builds credibility for the brand.

    Data-driven decision-making

    The data analytics reports are reliable in developing effective solutions and generating better results. Many business executives enhance their skills to help businesses integrate analytic tools into their decision-making process.  Data-driven decisions help businesses to optimize their customer intelligence to the best of their ability. Prioritizing business actions as per business goals, companies could focus on quick wins or invest in more significant opportunities and carry out activities with greater levels of success.

    Vet, cleanse and format business data

    Since businesses aim to derive well connected customers’ views, establishing the data that is correct, clean, and formatted, and can be matched with other attributes and signals, becomes the need of the hour. Recognizing the inaccuracy of data sources is required and the team needs to work with a partner to identify and resolve these issues.

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    Resolve to a single identity

    In order to resolve multiple fractional profiles to a single identity, enterprises require to partner with a full identity graph that offers a single unified view online and offline, across channels and devices with accuracy and persistence over time. This upstream identity customer intelligence and segmentation via onboarding and activation through all the measurement efforts. An end-to-end system of identity is the key to successful data enablement.

    Optimize and repeat

    To develop a better customer intelligence strategy, brands must constantly strive to offer a better customer experience. This involves regularizing the customer information from time to time and updating the customer database. Creating customer groups personas that comprise customer intangible information such as values, beliefs, attitudes, and preferences makes customer communication smarter.

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