By Alex Aparecido

Companies all over the world are facing a common challenge: data analysis. With a huge range of information generated by various sources, in the midst of an increasingly competitive and constantly changing market scenario, unifying and harmonizing it has never been more important for business success and the adoption of Artificial Intelligence (AI).

In this sense, Data Analytics plays a fundamental role in transforming raw information into actionable insights, enabling companies in all sectors to develop robust and effective solutions. However, it is essential to keep an eye on trends in order to optimize profits with assertive data analysis.

To give you an idea, according to Gartner, 61% of companies are being forced to evolve or rethink their Data & Analytics (D&A) operating model due to the impact of disruptive AI technologies. Given this scenario, one alternative is to strategically exploit data from CRM (Customer Relationship Management) systems and other legacy systems, as well as those external to CRM, to boost organizational performance.

The journey to effective management

Before we delve into the technologies for analysis inside and outside CRM, it’s important to point out that it all starts with developing a data strategy. Its aim is to understand what information is relevant in supporting the organization’s decision-making, as well as how this data can be transformed into knowledge to direct assertive strategies to different areas of the business.

For less mature companies, the journey begins with structuring the data to ensure that everything relevant is captured consistently and stored in an organized manner. Other companies, more technologically advanced, already have a structured base, but often face the challenge of how to deal with such a large amount of information in order to extract the best insights.

In this case, it is first necessary to look at the cleanliness and quality of the data, which, if inaccurate or duplicated, can lead to erroneous analyses. Advanced tools can automate much of this process. Architectural concepts such as Data Lakehouse or Datamesh, for example, guarantee a managed environment, leaving the only source of truth at the base, with complete and certified data. This reduces the time it takes to process information, allowing employees to reduce their operational efforts and focus on more strategic activities.

The final part of this journey is analysis through detailed reports, the process of which has gained even more value with the development of Artificial Intelligence, capable of analyzing and correlating data in order to generate important insights for decision-making and predicting what might happen. Whether adjusting marketing campaigns, improving customer service or optimizing internal operations, decisions based on data tend to be more effective and aligned with business objectives, bringing a personalized experience to the customer.

Where to collect the information from?

As mentioned earlier, combining internal CRM data with external sources can be very strategic, as you can get a holistic view of customer behavior and needs.

The market has analytical solutions integrated with CRM that are optimized to work with the data directly generated by customer interactions. They deliver a detailed and specific perspective on consumer behavior, allowing for an in-depth understanding of their individual preferences and needs. This results in more targeted and personalized actions, increasing satisfaction and loyalty rates.

On the other hand, analysis tools that operate outside the CRM provide a macro view, integrating multiple data sources – such as social networks, market research, Internet browsing behavior, among others – to offer a broader perspective. They are ideal for identifying market trends, analyzing general consumer behavior and assessing the impact of external factors on the business. The flexibility of these tools, in turn, allows for the creation of complete dashboards capable of understanding, in a 360º view, different scenarios of interest to the business.

The importance of specialized support

Navigating the complex universe of Data Analytics requires expertise. With technology, companies are evolving more and more quickly and the process of adapting to the organization and cross-referencing of data is a constant challenge.

Relying on a consultancy can be the difference between a successful strategy and a wasted effort. This is because specialized companies offer not only the right solutions, but also the experience needed to implement the best collection, integration and analysis practices, which can reduce costs and project deadlines by up to 60%.

In an increasingly data-driven world, the ability to manage and analyze data effectively is essential for business success and competitive differentiation. From now on, managers must be increasingly attentive to internal governance, while at the same time seeking to improve the quality of external data. This ensures that the organization extracts maximum value from the information available, turning it into strategic insights that drive growth and feed AI.

Alex Aparecido is Head of Delivery and Operations at Everymind, a leader and reference in Salesforce implementations, with over 20 years’ experience in data.