Integrating CRM with BI-Analytics - Creating a powerful closed-loop of feedback and reporting, serving all levels of the organization and empowering right-time synergic management.
In order to achieve a closed-loop of feedback and reporting, serving all levels of the organization, we must integrate the CRM with an adequate "Business Intelligence (BI) System. We stress the word adequate because Business Intelligence (BI) is a broad umbrella term. Cloud CRM Systems has taken this crucial step forward by integrating CRM with adequate Business Intelligence (BI).
In the 70's the acronym CRM, standing for Customer Relationship Management, began appearing on the business scene. It represented the philosophy of putting the customer at the center of your business strategy by establishing a strong symbiotic relationship with the customer. Today, CRM is no longer thought of as an acronym but as an umbrella term for a broad approach to business strategy.
Initially CRM systems were rigidly structured, located on the premises, costly, administration oriented and appealed primarily to large enterprises. Today, most CRM systems are cloud-based, flexible, easily customized and compatible with installation of Add-Ons. CRM has become the de facto core of the overall Business Operation system (unified platform), integrated with a variety of apps and verticals.
The "heart" of the Business Operation platform is the classical Marketing and Sales CRM. Each CRM task is assigned to a "module" which is integrated with and "speaks'' to other modules and the system functions.
The classical CRM usages such as marketing and sales automation have flourished, becoming more user-friendly, sophisticated and affordable.
Despite the aforementioned progress, the feedback and reporting capabilities of the CRM systems remain relatively limited and haven't kept up with the needs of modern Marketing and Sales management strategies.
The following definition from Wikipedia demonstrates how broadly Business Intelligence (BI) is used as an umbrella term.
"Business Intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis of business information. BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies include reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. BI technologies can handle large amounts of structured and sometimes unstructured data to help identify, develop and otherwise create new strategic business opportunities. They aim to allow for the easy interpretation of these big data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability.
Business intelligence can be used by enterprises to support a wide range of business decisions - ranging from operational to strategic. Basic operating decisions include product positioning or pricing. Strategic business decisions involve priorities, goals and directions at the broadest level. In all cases, BI is most effective when it combines data derived from the market in which a company operates (external data) with data from company sources internal to the business such as financial and operations data (internal data). When combined, external and internal data can provide a complete picture which, in effect, creates an "intelligence" that cannot be derived from any singular set of data. Amongst myriad uses, business intelligence tools empower organizations to gain insight into new markets, to assess demand and suitability of products and services for different market segments and to gauge the impact of marketing efforts."