Trends in big data search and analytics: Business Intelligence in the age of digital transformation

This is a guest blogpost by Daniel Fallmann, CEO, Mindbreeze

In light of the current vogue for digital transformation, it’s more critical than ever before to have a comprehensive view of the customer. The modern consumer has unlimited access to digital information right at his or her fingertips and makes purchase decisions more confidently and from a more mature and informed place than their parents and grandparents, who viewed lifelong customer loyalty as a central pillar. Add to that the breathtaking speed at which trends and preferences – and thus markets – are changing, and it’s clear that keeping a finger on the consumer pulse is imperative.

According to a recent global KPMG survey, despite being positive, CEOs recognize competitive challenges are growing exponentially. Among the issues keeping them up at night, according to that survey were: customer loyalty (86%); new entrants disrupting their business models (74%); and keeping current with new technologies (72%).

The good news: there’s more information available than ever before to gain insight into the minds of customers and thus to help companies understand what drives purchase options and to react quickly to changes or new trends. Alongside classic systems like CRM, marketers have access to innumerable consumer touch points such as e-mail, social media or call centre notes. The downside: with traditional tools such as Business Intelligence (BI), it is very difficult to garner and process the information – which consists increasingly of unstructured data – in a way that facilitates rapid and informed decisions.

What’s to be done?

Admittedly, the concept of BI arose at a time in which the amount of data was manageable and conveniently located in databases over which – much to the chagrin of business users – the IT department had exclusive control when it came to how applications were used; and only power-users could actually understand how to wield the mighty tools.  However, the current demand for BI is on the rise and Gartner forecasts a worldwide sales increase of 5.2% to $16.9 billion US dollars in 2016.

What is needed today are systems that can be handled by the relevant business departments and which also have the ability to integrate a variety of data sources, both structured or unstructured, in their analysis. While modern self-service business intelligence (SSBI) solutions have made significant headway in enabling business users to access and work with corporate data without needing a techy or statistical analysis background, they quickly hit a wall when it comes to their ability to process unstructured data.

The solution to this dilemma could be Search-driven Business Intelligence, combining the best of the BI world with the benefits of big data environments. Big data analytics not only has the wherewithal to handle the rapidly growing data conglomeration, but, with intelligent functions like semantic analysis of text documents or even videos, it can also gracefully manage to transform unstructured data into structured information and integrate it into BI system analysis.

What does that mean in practice?

Suppose an insurance company wants to get to know its customers better in order customise its marketing campaign. The challenge is to have access in the analysis and planning to all available information about a particular group of customers – that also includes damage reports, contract changes or customer requests, all of which is often unstructured in the form e-mails or letters. Manually entering and incorporating the relevant data into the database is both time consuming and error prone.

With a big data solution that happens automatically.  The system analyses an email or the PDF of a scanned letter, extracts relevant information like date of birth or policy and address information, uses keywords such as “home” and “burglary”, which are placed in a semantic context, to recognize and classify the data and its source. With the appliance’s machine-learning capabilities, this continuous process becomes even more accurate the longer the system is in use.

The Chief Marketing Officer, armed with accessible and applicable information which has been classified, intelligently processed and linked to other sources such as CRM, now possesses a comprehensive picture of the individual customer and customer groups. Inspire’s web portal, which is as easy to use as an online search engine, can be used to refine the search and combine and query the data in whatever way necessary to get personalised, customized results and analyses. Using dashboard-typical visualization elements such as pie charts and timelines, the CMO can quickly recognize the patterns and trends that will help her to design the marketing campaign.

This level of sophistication and technology transforms scattered and unstructured customer information into data-driven and data-informed insights that will ultimately help businesses tune into the complexities of customer behavior and loyalty and ensure that a company‘s marketing messages are timely, customized and relevant. InSpire has no less than 450 connectors at its disposal, so that the final search result can be exported with a single click into any known business intelligence application for further processing.

This functionality can be practically and effectively applied not only in the insurance sector but also in countless other lines of business as well as in the public sector. In the latter case, particularly the health care sector can reap huge benefits from search-driven business intelligence – for example, in diagnosis and treatment. Thus, customers and patients alike can profit from the digital transformation. And companies taking the best of breed approach are poised to look to the future of the digital era with unbridled optimism.