The Direct Link between Business Intelligence (BI) and Business Revenue

Customer relationships have greatly evolved in light of social, economic and technological changes. We have noticed that “advancements” in the domain of information access increase customers’ influence over companies. In addition, with the explosion of social media and the web, clients become active participants in their relationships with brands and let their voice be heard across these channels. As such, customer relationship management has become a primordial concern for businesses.

Clients now require a unique, personalized offering tailored to their needs. Thus, companies must meet these requirements. Today, businesses need to have a 360 degree view of their activities: from marketing to inventory management and client-generated revenue. CRM and ERP software vendors have properly identified these needs by offering solutions that meet this demand.

In this blog post, we will understand the importance of collecting customer data for businesses and of the use of tools to deploy efficient strategies to increase revenue. Nowadays, it is necessary for businesses to be aware of, understand and anticipate customer purchasing behaviour. Companies collect, generate and manipulate this data. Furthermore, businesses spend more time collecting information than actually using it. Historically, businesses have always hired armies of analysts that spend 80% of the time collecting information and 20% analyzing it.

CRM solution to increase sales productivity for manufacturing companies

In these context, we can ask ourselves some questions to see which element is missing with regards to the use of this information, and what that magic key to transform data into decisions is. This is where we can see the concept of business intelligence (BI) appear. According to an article by an SMB Portal (portailpme.com), “Business Intelligence refers to the transformation of raw data into information useful for sound decision making. The output of a BI system is information ready for action. With this knowledge in hand, managers can make better decisions with increased confidence, resulting in higher profits”.

If we understand it correctly, business intelligence allows us to make better decisions based on the collected data. Doesn’t this seem simple? Yet a study on Les affaires’ website reminds us that business intelligence is a way to obtain information in order to reach a business goal, but it must be followed by actions.

Thus, in short, business intelligence allows for the analysis of data to make better decisions and consequently acts to increase revenue. But we must ask ourselves, in which direction should we orient these decisions? In other words, what solutions are appropriate in a specific situation: a strategic, tactical or operational decision? For example, when analysts perform conversions to demonstrate that Store A generates more sales revenue than Stores B and C, due to its promotion strategy, an operational decision imposes the implementation of the same operational method for Stores B and C. These analyses are the result of using a tool.

The BI, at its foundation, relies highly on tools. These tools allow for efficiency. Let’s look at this as a timeline. Reports collect data illustrating a business’s state at a specific moment. They provide a detailed look at a precise instant, T. This is an image frozen in the past. Now, let’s look at the present. The dashboards show data in real time. These are performance indicators that allow you to rapidly react when faced with a particular situation, demonstrating the capacity to adapt and the flexibility of a business. For example, in the case of digital marketing, if a business notices that the number of visitors declines week after week, a corrective marketing action is necessary.

Finally, there are also all of the analytics, which allow to anticipate things. We look into the future and at projections. Predictive analysis proposes to adapt future actions based on a past situation. Here is a non-comprehensive list of common predictive analysis methods: linear/logistic regression, survival analysis, cluster analysis. Similarly, software such as QlickView, Power BI or SQL Server will guide you to work with your data.

In conclusion, this post sheds light on the fact that business intelligence goes far beyond simply collecting information. It is truly about “making data speak”, as this data contributes to the success of the business. Data evolves continuously and it constantly allows for refined targeting. For example, certain online advertising campaigns can be better targeted and personalized to website visitors’ behaviour.

Business intelligence is a powerful method to guide decision making through proper tools, allowing you to orient your operational, tactical and strategic choices in order to increase your company’s sales revenue.

Leave a Reply