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Gain Customer Data Maturity, with Effective Data Onboarding

Achieve Buyer Knowledge Adulthood, with Efficient Knowledge Onboarding

Companies are striving to deliver data-driven brand experiences at all stages of customer lifecycle. For proving their value, businesses are spending a significant amount of time, effort, and resources to extract insights from customer data to make informed business decisions.

However, to elevate customer data maturity, enterprises must plot a careful, strategic course that employs data and analytic tools to drive accuracy, velocity, and efficiency. Since variety, volume, and velocity of data keeps on increasing, organizations require solutions with the flexibility to handle both legacy and emerging data.

Let us delve into intricacies of customer data maturity model for better understanding.

Customer Data Maturity Model

Customer data maturity model represents a measure of companies’ ability to understand the sophistication of their user analytics and identify where your business is in this progression. It serves a primary role in helping organizations define and prioritize their customer experience requirements and then translating them into customer data requirements. This maturity model allows organizations define a future roadmap to leverage, and ultimately monetize customer data by identifying and unlocking synergies.

However, to realize these benefits, organizations must collaborate to master 6 elementary dimensions:

  1. Strategy: First step is to define a strategy with the help of a unified customer profile while keeping their demands and experiences in mind. Strategies help to tie customer data to insights and actions, which should ultimately drive better business outcomes.
  2. Structure: Next is the organizational structure. Companies need to have skilled customer data management staff in place that is well-versed with market trends and changing customer behavior.
  3. Data: This step is all about how data is collected, managed, integrated, and prepared by data experts and programmers for usage.
  4. Process: In this phase, valuable customer insights are generated with the help of workflows, data and analytics projects are listed and prioritized, rules are set out to execute these projects, and results are shared with the organization.
  5. Analytics and measurement: In this phase methods are defined by which enterprises can apply diverse statistical methodologies to customer data.
  6. Technology: In this final and most important phase, users leverage integration tools to help integrate and activate diverse customer data and insights. They use integration platforms to create a smooth onboarding journey for customers that allow enterprises to improve customer experiences, thereby building a steady growth curve.

Companies that aim to set a good customer maturity score need to take all these 6 dimensions into account. However, there are still many who are unable to move up the maturity curve because their data onboarding patterns fail to provide adequate support for their key objectives. Worse, they feel working on employing new or improved customer data onboarding practices is of no significance, and they ultimately miss the boat.

Role of Customer Data Onboarding in Building Customer Data Maturity

Customer data onboarding is a well-known practice as it establishes a seamless connection between offline data (such as retailer’s purchase records) and online attributes (such as online purchasing, social posts or site visits) to create a cohesive and comprehensive identity for more actionable marketing.

Customer data onboarding, by bringing offline data sets online in a privacy-conscious manner, helps companies create a complete audience view and identify customer behaviors and trends with ease and precision. Once the unified data is available and customer personas are understood, companies can sharpen their customer engagement and management capabilities. This builds maturity. Companies can, therefore, use data to detect, interpret, and engage with customers to make better decisions easily.

Put differently, without effective customer data onboarding model in place, companies are unable to avail and channelize immensely useful offline and online data and harness it properly. Not to mention, their ability to understand their customers greatly diminishes. As a result, they end up making major broad business decisions based on a myopic view, which can be detrimental to the health of the organization.

In short, companies are half-blind without data onboarding. The trouble lies in considering data onboarding tactics to be a footnote and that hurts companies’ aim to understand their customers and deliver accordingly.

To stay relevant and maximize outcomes, enterprises need to use robust customer data onboarding software. It helps companies reap many benefits, from achieving a better understanding of their customers by moving up the maturity curve to better use of marketing budgets, leading to improved results.

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