Digital Transformation fueled by data monetization: Internal and External
I got a call from an events marketing company yesterday and we spoke about data monetization and how more and more CEOs expect their CIOs and LOBs to launch data powered products. Not surprising! I have been hearing from our CEO that “It’s all about data” ever since I joined Persistent. That has now been extended to “It’s all about data monetization”. I am a firm believer that digital transformation is all about new ways of doing business – disrupting your business models, launching new products and transforming customer experience. And leveraging your data is key to all that.
Recently we hosted a customer from the real estate industry and the first thing we heard from the CTO was that they were a “data” company and they needed to build products powered by that very data. Talk about software eating the world!
A few months back we recommended that a customer of ours (a cable television provider) monetize the viewership data that they had collected over the years, since its value lay untapped. The products crafted using this data can be invaluable to both broadcasters and advertisers. Deeper insights into viewer behavior help broadcasters better plan their programming and promotions, while analysis into ad views helps advertisers better reach their target audiences and better plan their ad spend. The net new product line launched by our customer has opened a new revenue stream, with hard dollars being charged to advertisers and broadcasters for these insights.
Another customer with multi-billion dollars in revenue is using machine learning to understand how customers can be segmented based on their past behavior and transaction history and then launch targeted marketing campaigns for upsell and cross sell. While segment marketing has been around for some time, its effectiveness is only recently being unlocked by tapping into the vast sources of yet unexplored social and enterprise data.
A few days back we embarked on a journey with a leading global manufacturer and supplier of consumer beverages and food service packaging products. There is strong evidence that when chemical characteristics of the product in consideration are on the boundaries of acceptable ranges, it takes longer to manufacture the packaging product. Constant changes of mill parameters results in lower throughput and also in wastage. How do we avoid this? We are building a self-service predictive analytics solution to answer business queries that were not possible earlier, be it to better margins or better customer (retailer) experience.
I can keep going on, but I think you get the point. So let me switch gears and talk about what I call internal data monetization.
Salesforce recently came up with their AI and machine learning platform ‘Einstein’, using which they have been able to surface insights into their products such as Sales Cloud and Marketing Cloud. An example is the ability to provide lead scores in a predictable manner thus helping the sales team chase the right leads at the right time with the right next action. While one can argue that it is only increasing the operational efficiency of sales people, it is also going to positively impact Salesforce’s customer’s top line by focusing on the right leads and opportunities that are going to close.
Let me ask all those CFOs, sales operations and sales management executives who are in forecast calls, daily or weekly. Do you like those calls? There are a bunch of companies which focus on predictive forecasting using sales data. This is driving predictability in forecasting in a scientific way (yes, sales art is always involved) and is providing insights to gain a better hold on sales processes, sales cycle and closure rates and the most important – predictable forecasts.
Persistent Systems too recently launched a product called ‘Engage 360’ that helps transform customer service for enterprises. It empowers their service agents with unified, intuitive and proactive access to information beyond Service Cloud thereby positively impacting CSAT. The data stored in Service Cloud, communities such as Jive, Community Cloud and documents in Sharepoint is mined to be able to provide such functionality to service agents.
So let’s take a pause – spend a few days trying to understand what monetization use cases you can focus on (internal or external) and go make it happen. I can assure you, the DATA is there!!