Using Artificial Intelligence to Monetize Your Data

For a business like Squirro, whose success has been based on how we help organizations extract value from their unstructured data, we have always been very upfront about what we see as the value of data.

Yes, our Customer Insights product has on average seen organizations increase revenues by 3% and customer satisfaction by 15%, while our Service Insights product has delivered 30% reduction in mean time to resolution and up to 15% reduction in support costs.

But data on its own does not hold any value at all. Whether it’s big data, unstructured data, premium data, customer data or market data, the only way to find value in that data and to successfully monetize it, is to extract insight from it. 

Monetizing data has become a major priority for many organizations. They know there is incredible value in the data they hold, and they know that extracting insight is key to unlocking that value, but they aren’t always certain about the most effective ways in which to monetize that data. This article discusses some of the most effective ways of doing so.

The Hidden Value in Data

In June 2016, Microsoft surprised many in the international technology and business communities, when it announced plans to buy LinkedIn, the social network for professionals. LinkedIn had around 433 million users at the time, and Microsoft eventually closed the deal in December 2016 for $26.2 billion.

It’s a figure that felt high at the time, based on what LinkedIn was and what it could offer. Microsoft wanted to enter the business social networking space, so in that sense, the deal was a smart one. But $26.2 billion for what was essentially a lot of data was seen as expensive. Microsoft had seen the hidden value in LinkedIn data and had some ideas about how to monetize that.

Microsoft recently released its FY19 Q3 results, and reported that LinkedIn continues to see ‘record levels of engagement’, with on-platform sessions growing by 24%, while member numbers have reached 610 million. In terms of how Microsoft has monetized the LinkedIn data, revenue for the quarter has increased by an impressive 27%.

Using the Full Complement of Data for Monetization

Data can be monetized in many ways. This is as true for organizations that might not be as used to innovation and digital platforms as it is for large tech firms such as Microsoft. But to get the most value from data, it is important to utilize all the data you have at your disposal.

Yet most data is unstructured. A majority of CRM and other business systems are unable to manage it effectively. Salesforce has stated that on average, only 1% of a company’s data is used by its CRM system. When you consider that unstructured data – news alerts, customer call transcripts, earnings announcements, social media content – is where much of the real insight lies, it is easy to see why some organizations struggle to monetize their data.

This is why the right technology is essential, and Artificial Intelligence (AI) and Augmented Intelligence are two such technologies. Squirro’s solutions are based on these, adding structure to unstructured data and garnering all the insight contained within unstructured data. Monetization can be carried out more successfully. These are some of the more popular ways of approaching data monetization:

Creating new digital services – this is a high-profile way of monetizing data, with many benefits. Not only can it generate revenue, but it can also help an organization get more immersed in digital technology.

A good example of this is with the food processing equipment manufacturer, Bühler. The company’s customers were growing increasingly concerned about food and feed safety and the damage it could cause. But tracking and managing food safety risks and problems was a major challenge because the data came from so many different sources and was mostly unstructured.

Working with Squirro’s AI technology, Bühler developed Safefood.ai, an application that monitors hundreds of data sources – structured and unstructured – around the world to provide an accurate and real-time food safety monitoring and alert system. It already has more than 800 users, and Bühler has also used it to sell related services, solutions that can help address some of the safety concerns highlighted.

Addressing customer churn – few things in business are as frustrating as losing customers to your competitors, especially when you feel it is for a reason that can have been foreseen or addressed quicker. But how do organizations really address churn?

In essence, it boils down to delighting your customers, whether by providing them with a first-class customer experience or by addressing any issues that occur before they become a major problem. This can be achieved by the use of unstructured data, using its insight to know customers better and to gain a deeper understanding of the markets they operate in.

Unlocking the value and insight found in premium data – for Financial Services (FS) firms, premium data is seen as essential in learning more about markets. The data is used to improve trade and deal origination, to overcome regulatory challenges, and much more. But by itself, premium data is no different from any other type of data – it is just information that needs to be internalized. To really get benefit from it, and to monetize premium data, it needs the wider context that comes from seeing it alongside other relevant data.

Premium data is unstructured though, so most organizations are unable to integrate it within their CRM system. By deploying a solution such as Squirro though, organizations can monetize their premium data much more effectively, commingling it with other data in the CRM, to offer a much fuller picture and far greater insight.

The monetization of data is a key objective for most organizations in the modern data economy. By itself, data is almost worthless, and it has the insight that can be extracted from it that can be put to best use in data monetization.