Sales Intelligence impact on bottom-line…

In my earlier blog, Salesforce and Predictive Analytics, I was making a point why Salesforce has taken a keen interest in predictive analytics software.  Salesforce has turned the market inside out by taking the complexities of IT and infrastructure delays, and not to mention out-of-the-box implementation features, easy enough for small companies to implement with minimal budget and external help. Getting the CRM up and running is only the first step. Managing the data and integrating it with the enterprise, as well as enriching it with external data is where the true value lies.

Having the right Sales Intelligence strategy provides right information and helps reduce the time for gathering and analyzing the information to improve the sales hit ratio. Key ingredients for sales intelligence are data quality and enriched data. Salesforce is a key enrichment option to the Salesforce platform. pikto

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Master Data Management will provide the key foundation for successful Sales Intelligence by combining combines enterprise data with Salesforce data through integration to ensure data quality. Predictive analytics and other advanced analytics needs data to predict meaningful recommendations. Combining third-party data and social media with the ability to segment the customers yields winning targeted recommendations.

Data science and Big Data provide the context, touch points, behaviors and customer experience opportunities. This can be leveraged if and only if the underlying customer data has the most current customer information. Companies have deployed multiple instances of Salesforce for convenience or deliberately for divesting. But having the right Data Strategy to leverage the most current information is the bare minimum for the enterprise to succeed.  Predictive analytics depend on all the data one can get in real-time or near real-time.

See also:  Salesforce and Customer Master

About the Author

Shankar RamaNathan is a Senior Enterprise Architect with 25+ years of experience in successfully developing and implementing IT strategy and Information Governance ( Master Data Management, Metadata Management, Data Quality and Data Governance) programs.

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