AI: From Buzzword to Bottom Line
In recent years, we have been overflooded with artificial intelligence, and quite regularly we are using the concept as a synonym for machine learning. Even though Al is hot, there is a long way to fall in love with the concept to be able to implement it in the business and measure it on the bottom line. But this is about to change within the Business AIShare article:
When talking about advanced algorithms that can automate our business processes, machine learning is often the most correct term to use, but in the realisation that the concept of artificial intelligence has become so widespread in everyday speech, we here in Geomatic tend to use the term of business AI.
Big data and business AI
A couple of years ago big data was the great buzz term and the excitement around it came partly over the pace that data now is created with and the technological progress that gave us software to handle big data volumes. After the first hype, the challenge of getting the benefit of big data appeared, and this is a challenge many companies still batte with today. This is because the “data ocean” is enormous, and the process from big data over relevant data to smart data requires strategy, resources and overview.
AI is a hungry animal
This is where the business AI term come in to play, because using machine learning can crunch massive amounts of data - and large amounts of data are needed to get smarter about your business; you already know your turnover and margin per customer, so the value-added customer knowledge that can help you reduce churn, improve your segmentation, execute more effective campaigns, and lay the foundation for optimised customer experiences requires more and other things than transaction data. But what data? And how should you and your organisation handle all this data?
Since our founding 17 years ago we have been analysing our clients' customers as well as their markets, and during the years numerous new data and methods have been added. We have always provided comprehensive analyses to our customers based on quality-assured data. Over the years the combination between our customers' data, and the data we distribute, has become a cornerstone of the analysis work. Because it is exactly with the use of many variables and data sources, we can create the most efficient analyses and action codes.
Business AI platform is fast-tracking your AI journey
We are now taking things a step further; with our new Data Analytics Platform, we have built a platform that can facilitate your company's AI journey from big data over data blending to predictive modelling. We use machine learning to fast-track the boring part of the process, which is concentrated about structuring data, blending it, and identifying the significant variables (both among your data and the external 3rd party variables).
Not only is it smart, it's also effective: Geomatic’s data blending engine can be accessed as a self-service solution on the platform. What could take up to a year when testing hundreds of variables can now be done in a few minutes. This will allow you to quickly move on to the more fun part of your AI journey; the
creation of predictive models and the implementation of the modelling's output and scores in your processes with pricing, marketing automation, product mix, etc. (however, a good data- and analytics strategy is still a necessity for success).
Your customers win
The implementation of business AI in your business will be a benefit for your customer; with a comprehensive awareness of them, their needs and preferences, and the ability to estimate when you are most relevant to them. The reality today is that we are too often sending something out because we as a dispatcher want to communicate this or that, but we all become happier consumers ourselves when a company hits us with the right offer in the right time and in the right channel. And with happy customers comes, as you know, turnover. Our many use cases are also confirming this; with business AI we improve the bottom line.