Marketing with Machine Learning

Anecdotally, we know that most local business owners and managers who control marketing budgets, only have a limited understanding of how 'machine learning,' (aka artificial intelligence, or AI), can improve their online marketing performance.

This is usually because they are flat out making all of the day-to-day hands-on decisions required to keep their enterprise moving forward, so they don’t have time to drill down into the nitty-gritty of algorithms and how they can be used to keep refining the returns they are getting from their advertising investment.

If this situation feels familiar, click on the link below and spend a couple of minutes engaging with this little mind-tool from Google, you may find it will get you heading down the same track in the new year. If you want to pursue it further, give us a call.

In our case, Flametree improved the quality and quantity of our sales enquiries by 15% in 2021, and we did this simply by fine-tuning our understanding of the way Google employs machine learning and applying this to our own website.

To grasp the basics of what big data involves it is important to understand that every online decision you make and many offline actions result in data being created and stored in some shape or form. In 2020 every human generated an average of  of 1.7 megabytes of data every second and this is growing by20% per annum. Perhaps the term “big data” is an understatement. All this data is stored in millions of databases around the world and used for many purposes from planning cities to tracking the spread of a viruses. 

The use that you are probably most aware of though is marketing. Personally, I know that I often feel I'm being milked of personal data whenever I visit a new website. I try to only offer my details when absolutely necessary (which is increasingly more often) in fear that I will be unnecessarily targeted with unwanted and irrelevant ads at a future time. However, if this data is used effectively it can help marketers target and personalise their offerings to customers resulting in ads that respond to specific demands. Research showing that 91% of smartphone owners bought or planned to buy something after seeing an ad they described as relevant (Google research 2017). This targeted delivery of a marketer’s message not only sees their costs fall but may also mean less unwanted marketing material being directed to you as was the case in the days of the mass market saturation strategy.

The difference here is between smart use of data and dumb use of data. As data collections become larger and larger the challenge lies in how to use this resource intelligently. This is where data analytics is becoming increasingly more sophisticated and there are many smart businesses that are developing systems to make better use of existing data sources and planning for future scenarios.

A couple of local companies in this space are IXUP who have developed systems that enable data owners to share data in a secure encrypted state that still allows analysis of specific parts of the data to occur. Sharing data can results in powerful new insights. Another is Dug Technology –a local company who offer big data services. They have built four super computers around the world that can offer customers 35 petabytes of storage and 29 petabytes of computing power for analytics. Offering a hardware solution and software analytics expertise they have over 200 customers from 48 countries including the CSIRO and the The Square Kilometre Array project.

As the race to gain insights into our behaviour becomes more and more competitive the realm of Machine Learning also gains importance. MachineLearning, sometimes known as Artificial Intelligence allows data scientists to program computers to analyse massive amounts of data points and extract insights as it measures, compares, evaluates and tests. The following link provides a powerful explanation on how Google applies Machine learning to help its customers gain marketing insights.

Peter Sondergaard from Gartner research noted: “Information is the oil of the 21st century and analytics is the combustion engine.”

‍CLICK HERE