CRM initiatives are often driven with reporting in mind. As the saying goes, “If you can measure it, you can manage it.”
But just as the scope of CRM-managed data has evolved over the last several years, so has our ability to analyze that data in order to provide more actionable insights in a timely manner. Let’s walk through the iterations of CRM over time so we can get an accurate picture of where we’ve been.
First Generation CRM – circa 1980s and early ‘90s
In the first generation, CRM was predominantly Salesforce Automation, and the data being managed could be taken at face value, sort of a “what you see is what you get” scenario.
Reporting was predominantly focused on pipeline management: sales managers had some visibility into the overall health of the business and salesperson performance through a snapshot-in-time view of the current opportunity pipeline.
First Generation 360° View of CRM – 1990s and early 2000s
The next generation of CRM introduced the 360° view of the customer by combining Sales, Service, and Marketing applications in an integrated suite, essentially providing a complete view of customer-facing activity.
Reporting on this combined data made it possible to determine impact and inter-dependencies between Sales & Marketing and Sales & Service, and offered visibility into KPIs like MQLs and SQLs, along with volume and cost-of-service metrics related to sales pipeline and sales history.
Again, reporting against this data was primarily snapshot-in-time and was available as standard inside the CRM applications.
Integrated Internal Customer Insights
As ERP vendors such as SAP and Oracle joined the CRM game, integration tools enabled customers to combine their CRM applications in a meaningful way to their ERP systems, resulting in a new definition of the 360° customer view.
The new view combined customer-facing activity (sales, service, and marketing) with customer non-facing activity (sales order history, billing and payment history, profitability) to help companies understand how to leverage external analytics tools outside of CRM applications, like SAP’s Business Objects, Microsoft’s Power BI, Cognos Impromptu, and others.
Key considerations here included the ability to identify customers who are slowly or quickly attriting by evaluating sales history against current opportunities, and the main advantage was the ability to identify more valuable customer insights.
Unfortunately, these tools were generally found outside of the CRM applications, and therefore they were not easily actionable by the sales and service teams who could effectively act on the insights.
Internal and External Customer Insights
The pervasiveness of the internet, along with the advent of cloud-based CRM led by Salesforce, and the availability of useful data in the public domain has now enabled companies to extend the definition of the 360° view to include customer facing and customer non-facing activity.
That insight can be managed by the company itself in conjunction with public information that is known and available about their customers. This could include social media entries by or about their customers, quarterly financials, or data enrichment tools that provide additional insights.
By leveraging this external data, companies can compare their own sales trends per customer against the overall health of each customer. For example, a customer who has grown their own business while buying less from your company is now most likely buying from your competitors.
Today, we’re seeing a new macro dependency beyond the individual insights of each customer, whether managed internally or externally. The deadly COVID virus has had a significant impact on practically every business and sector. Some of that impact has been positive, but more often, the impact has been negative.
The ideal analytics and visualization platforms should allow companies to leverage all of the data listed and provide deep insights that can then be actioned in CRM systems. This should be done as quickly as possible since the dynamics are changing every day, especially in light of the unpredictable opening and closing of businesses and travel routes between states and countries.
Predictive Analytics and Visualizations – Perfect Timing for the Marriage of Salesforce and Tableau
Depending on the industry you compete in, your current goal could range from surviving, to thriving, to creating significant competitive advantage. The combination of Salesforce, Einstein, and Tableau now provide the ideal set of capabilities you need to:
Meet your business goals
Visualize insights and drill down against a multitude of filters in real time
Take the appropriate actions quickly in the Salesforce platform
Combining Tableau with Einstein helps you define actionable insights and allows Salesforce to take advantage of those insights.
The example provided in the attached graphic comes from our CT Mobile solution used by Life Science companies to call on physicians and detail their products using digital presentations. Those companies must remote detail (over the phone and screen share) in many states while social distance detail (in the office but from a safe distance) in others with the backdrop of the COVID map in context.
This one visualization allows for a multi-dimensional view and filtering of the data by rep, sales region, quarter, and customer, identifying trends and insights in real time.
These integrated tools are opening up new possibilities, which is critical in the current climate. If your organization isn’t taking advantage of these tools, you should at least hope your competitors aren’t either.
Dmitry Dmitriev is the Senior Business Intelligence Architect & Account Manager at Customertimes.
He has more than 10 years of experience in the Business Intelligence field, working with a broad range of technologies from companies such as SAP, Salesforce, Microsoft, Apache (open-source), and others. Dmitry has a unique blend of technical and managerial skills that allow him to build long-lasting relationships with clients, deliver high-quality solutions, and effectively manage project teams. He has helped clients in a wide range of industries, including retail, pharma, and life sciences, gain analytical solutions that drive business growth.