Advanced Analytics

Society has always been fascinated by imagining and predicting the future, but we know that we will never find the answers in crystal balls. This mystical object is now relegated to movie sets or theatre stages. In the real world, it takes the form of sophisticated tools capable of predicting trends.

So is it possible to predict the future? Yes! At least in the business world. This can be done with advanced analytics. A significant amount of data is analysed – often using artificial intelligence – to find patterns or trends that generate insights and establish predictions.

According to Gartner, graphical, semantic and sentiment analysis, network and grouping analysis, multivariate statistics, data or text mining, machine learning, complex event processing and neural networks are some of the most common techniques found in advanced analytics. 

Each one of these techniques examines different data types and formats that will support predictive analyses and that are explored by the most diverse market segments, such as insurance and other financial services, medical and pharmaceutical products, telecom, supply industries, retail and consumer goods, etc. The list is endless but the common denominator among these sectors is the abundant amount of data available and a data-driven mindset.

Challenges to implement advanced analytics

Executives interested in using advanced analytics are faced with two major challenges: shortage of qualified labour and a poorly disseminated data-driven culture.

There is a number of tools in the market focused on Big Data. However, it is not as easy to find people with advanced knowledge or command of the required platforms and techniques. 

Additionally, these professionals need to know which data will be relevant for the required analyses. In other words, it goes beyond having IT training; they must have an integrated view of the business and be results-orientated.

Another important aspect is to have a data-driven mindset throughout the organisation. Marketing and technology or business intelligence can develop the most sophisticated dashboards but they will be useless if the rest of the company does not leverage their efforts or initiatives based on these insights.

Predictions will not always provide input to every department. However, the achievements and results from the advanced analytics should be shared with the entire company to encourage buy-in from its human capital in their quest for data-based performance.

Advanced analytics focused on sales results

A recent study by Bain & Company shows examples of companies that have implemented advanced analytics applied to sales and marketing through prescriptive analyses.

Using a lead attraction strategy and collecting data that showed purchase intention, advanced analytics was applied to find potential decision makers in the database. These users were then targeted with personalised content to arouse their interest faster. They were managed based on their behaviour throughout the sales funnel through marketing activations that would direct them to conversion.

In sales, advanced analytics was initially used to analyse wins and the sales pipeline. The potential revenue of the main offers at the customer level was also analysed. This data generated insights for the development of the best sales opportunities, which were also focused on personalised offers and carefully built through sales activities and pitch. The result was a 15% increase in sales and 95% accuracy in predicting new business.

These and other studies and cases available show how the evolution of digital analytics and business intelligence is already a reality in many companies today. Combining technology innovation and machine learning with the expertise of highly trained professionals, advanced analytics is the most modern solution to predict trends and anticipate strategies to achieve even more exceptional results.