How to Use Big Data More Effectively?

In our last couple of articles we got you closer to the top marketing and advertising trends discussed at Web Summit this year. (you can also read: “3 Big Marketing Trends from Web Summit”)

Yesterday we focused on emails and the new wave of technologies allowing marketers to connect their email and advertising campaigns (to learn the full article “Email is Not Dead” follow the link here). Now it's turn to Big Data and what is the key towards unlocking its potential.

To speak about Big Data being a popular subject in the advertising (and not only) industry is an understatement. The opportunities and strategic implications of Big Data are being passionately discussed on a daily basis and it was one of the most often mentioned topics at the Web Summit.

According to most of the speakers however we are still at the early stages of using effectively Big Data. Although we have grown accustomed to the term “Big Data”, and we’ve started to become aware of the value it brings to advertising efforts, we are not yet near taking the full advantage of its many opportunities.

“Marketers and advertisers collect data but they don't know how to make good use of it.” was an often heard statement at Web Summit, which shouldn’t surprise anyone. Big Data is… well.. big. We are talking about a massive amount of information produced in the digital space every second which needs to be collected, examined, and analyzed carefully so it can be put into effective actions. The workload itself is beyond the basic human capabilities, not to mention the speed with which these tasks need to be done.

For this reason Artificial Intelligence is the key. Artificial Intelligence advertising technologies can help marketers and advertisers overcome the challenges and use Big Data more effectively in their strategies. The algorithms of these technologies are able to process billions of data points simultaneously. They explore the vast realm of data and analyze in manner of milliseconds the information load to extract the most relevant and useful information for the advertiser’s needs. These could include: building new richer audience segments, getting more understanding of user’s behaviour and preferences, market patterns (when is the best time to buy ads and at what channel), feedback on advertising campaign performances, etc.

The value added here is to be able to gain these insights in real time and act upon them. Machine Learning algorithms, like the ones included in Campaign Optimization Engines, learn from all your existing data and explore the digital space in real time, collecting all the information produced and predicting the market’s direction. This is how the engine optimizes your campaign directly on the spot.

For example, if you have a running campaign now about your Cyber Monday offer, our campaign optimziation engine R.Skott.io can decide in the milisecond a webpage loads if it’s a good opportunity for you to post your ad there, is it going to be relevant to the person who will see it and at what price would be best to bid for the ad space.

So let’s say you’ve got an online hi-tech marketplace and you’re currently promoting special offer on tablets. You want to show your offer to those users that are most likely to respond to your advertising. A user opens an online magazine page and in the time it is loading, the Campaign Optimization Engine can determine if that person has been on your website before, how frequently, has he shown interest to a specific offer, has he searched recently for tables and is he likely to purchase soon.

All that thanks to the Big Data that Machine Learning algorithms analyze in real time and compute to make the best decision.

Big Data is already a popular notion in the minds of marketers and advertisers, the next step is to accept the key to using it effectively, i.e. Artificial Intelligence advertising technologies, as integral part of the decision-making process.

If you’d like to learn more about Artificial Intelligence and Machine Learning, you can also read: