In these days of heightened customer expectations, having customer data scattered throughout different systems makes it nearly impossible to provide the personalized attention people expect—whether that’s a consistent buying experience across channels, a well-informed service rep when they make a call, or proactive suggestions for what to buy next.
Demographic and transactional customer data often resides separately in multiple systems, such as ERP, CRM, POS or eCommerce. But if it can be brought together as unified data and used for predictive analytics, then functions such as marketing, sales and service can extract more value from the data to strengthen customer loyalty and grow sales.
The solution for doing this is a customer data platform (CDP) such as Microsoft Dynamics 365 Customer Insights, which enables business users who aren’t developers to tap artificial intelligence (AI) to find new insights about customer behavior, predict customer outcomes and then optimize response.
These capabilities are not “nice to have” options for consumer brands. The real-time responsiveness of social media channels and dominant eCommerce platforms have trained consumers of all types to expect always-on personal attention across all brands they interact with.
This is especially true in brands that have an omni-channel sales and marketing strategy, such as retail. In fact the retail industry is a leader in growing customer relationships at scale using ERP and a CDP. The outcome is revenue growth. McKinsey reports that companies that are able to personalize customer experience across digital and physical channels can expect 5% to 15% revenue growth.
How Dynamics 365 Customer Insights works
The solution’s menu provides an easy-to-understand interface to identify sources, such as data from a website and sales transactions. Then, the “Unify” function enables users to:
- Map fields from the existing databases into a new customer database
- Match customers from the different databases using rules based on specific or fuzzy logic
- Merge the data to find out which customers should be carried forward into a new database
Once the unified database is created, users can create rules to isolate different customer segments, which then becomes a source for identifying specific past behaviors. Users can also derive data-driven predictions using AI for attributes such as lifetime value, churn or next-best action.
This data-driven knowledge is the key to more fruitful and cost-effective decisions within marketing, sales, service and even product/service development. It can also accelerate the sales cycle because customers are more informed and can make faster decisions.
From fragmentation to a 360-degree view
Of course, new technology alone won’t get you there. Moving an organization from a fragmented view of customers to a complete view also involves managing change, working with existing systems and understanding the unique constraints of the overall business model and industry. In short, it takes a comprehensive plan that will work today and tomorrow.
Do you have the right infrastructure and IT skills? How long will it take to see results? Are there additional opportunities for process automation? Do you have realistic goals and the right KPIs? How is business continuity going to be affected?
Addressing these and other questions early on can make the difference between simply adding new technology and achieving meaningful change in business performance.
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