Microsoft Dynamics 365 Customer Insights ("Customer Insights" or "CI") is an intuitive and flexible customer data platform that can unlock insights and power personalized customer experiences. It is intended to make it easy to connect to customer-related data from multiple sources and consolidate it into rich, comprehensive customer profiles. Those profiles can then be exposed to your users in a variety of ways, including directly as 'Customer Cards' within D365 CRM, as the basis for Power BI reports and dashboards, as input into Power Automate workflow processes, and more. It includes the ability to predict missing data values, customer churn, and more based on other similar profiles, and you can even extend the AI capabilities by creating custom machine learning models using Azure Machine Learning. 

That's a lot of promising possibilities for many types of businesses, whether small/large, B2C/B2B, or products/services. Nearly all organizations have large and rapidly growing islands of customer data, and it is nearly always spread across multiple systems and repositories. Customer Insights provides the possibility of easily bringing your disparate data sources together, and without making enterprise-level investments or waiting weeks, months, or years for other types of solutions. Even though Customer Insights is a fairly new SKU, it's based on a lot of Microsoft's existing technologies, including Power Platform Connectors and the Power Query engine, with Azure services providing additional storage and functionality, if needed. It's also worth noting that Microsoft is going all-in in terms of investment on this product, and it continues to mature quickly, with new capabilities being added at a rapid pace. 

 As with all things that seem too good to be true, there is a small disclaimer along with all these hopes and dreams. The main factor, which is likely to limit the potential realization of the CI vision, has nothing to do with any shortcomings in the product itself. Rather, it is the age-old law of data processing known as 'garbage in, garbage out.’ That is, if your source data is sparse, incomplete, inaccurate, outdated, inconsistent, or duplicative, the resulting reports and analytics will be more of a source of confusion rather than trustworthy insights. It is important to ensure you are capturing all the relevant data you need and investing in ongoing efforts to achieve and maintain high data quality, to leverage the potential benefits of analytics and AI solutions. 

Here are some of the things that can be done to clean-up your CRM data and ensure it remains clean: 

• Analyze Existing Data - Identify quality problems and gaps in your existing data. 
• Create a Data Quality Plan - Prioritize issues, identify remediations and solutions, and define cadence for both initial and ongoing efforts. 
• Implement Account and Contact Deduplication - Multiple techniques exist for identifying and merging duplicate records. 
• Reparent Orphan Records - Determine which account a contact belongs to via smart field matching. 
• Leverage Data Validation Services - Utilize vendor services for validating names, addresses, emails, websites, and more. 
• Enrich Your Core Data - Identify data vendors for supplemental information about companies (firmographics) and people (demographics). 

Customer Insights offers some very compelling capabilities, and when you combine it with the power of Microsoft's Dynamics 365 CRM, Power Platform and Azure Machine Learning, the possibilities grow exponentially. Just remember that it all depends upon having a solid foundation of high-quality data in place!