By Moustafa Mahmoud, Founder and CEO, Cognitev
Advertising is the engine that fuels the growth of any business, whether it be offline or online. As brands start to shift their advertising dollars from offline mediums to online channels, there is a larger need for speed, data-driven decision making, and continuous testing.
It sounds very altruistic, right? Not so. Over many years of online ad practice, advertisers used to rely on clicks as a broad measurement of campaign performance. With time, clicks have dwindled due to a variety of reasons, leading to a drop in measurable interaction between web users and online advertisements.
All of these were not possible in the offline world, but to do them well online requires significant data-crunching capabilities and resources to act on that data.
The biggest bottleneck to truly unleash the true power of the online advertising medium is the number of people you have working on your online advertising, whether it’s in-house or outsourced, the number of people (and their skills) is directly related to how efficient you can be.
Artificial Intelligence (AI) is revolutionising industries across the board, bringing automation and machine intelligence to remove such bottlenecks. It is paving a new wave of future innovation in every sphere, and it is changing the face of online advertising forever.
So, why do digital marketers need AI? The short answer: To make their lives easier. Marketers have depended on tools and technology to automate their work and reduce manual effort for a while. Yet, there has always been a gap in terms of effort and quantifiable results. Intuition about the right audience and time to send messages isn’t enough to answer a digital marketer’s basic questions: Who should I reach out to? What should I send? When should I send the message? Over what channel?
The answer to these questions is the key to creating engagement and growth, fostering sales and building a brand. As these questions remain unanswered for marketers across the spectrum, they must harness the power of data.
Data is everywhere. Every customer in the digital space brings with them an amalgamation of data and is constantly creating new data for marketers to understand, process and act on.
The problem is this: big chunks of data don’t necessarily make things any easier. In fact, they can make things so complicated that the first instinct is to abandon the data and go by intuition alone – but this won’t give you the right results.
AI and machine learning can understand human behaviour to the extent where big data sets are not only analysed, segmented and filtered, but meaning is also derived from them.
Which customers hate receiving your emails and delete them as they hit your inbox?
How can I make sense of all of this data I have from our campaigns?
Which customer would like a particular product?
How can I personalise the user experience and make it “sticky”?
Using AI in online advertising can not only help answer marketers these questions – in some cases, it already is. This gives back marketers time to innovate and grow their brand, rather than worry about how to automate emails to millions of customers at a time.
Here’s how AI is leading the evolution of online advertising:
AI provides efficiency
AI is being adopted by many technology companies to improve the efficiency and relevancy of online advertising campaigns, resulting in better performance, which is the ultimate goal of every marketer.
Machine-learning algorithms used to drive efficiency across real-time bidding networks will generate $42 billion in annual ad spend by 2021, up from $3.5 billion in 2016.
Machine-learning algorithms do the heavy lifting, intelligently identifying consumers and serving relevant ads, but there are still pieces that can only be recognised and managed by a human, of course.
These include accounting for sales and promotions, the integrity of brand assets and other issues that arise and can be accounted for only by humans.
AI provides personalization
Personalisation has been a buzzword and a big focus in online advertising for some time, yet consumers are worried of their information being used for advertising purposes and the resulting influence it may have on their purchase decisions.
More than 78 per cent of US Internet users said personally relevant content from brands increases their purchase intent.
Ultimately, it comes down to the quality and relevancy of the personalised message, whether consumers realise it or not.
Personalisation technology has evolved to become a standard in advertising for many brands, but the technology must continue to evolve for brands to deliver powerful experiences amidst changing consumer behaviours, platforms and media.
Going beyond products, this personalisation includes the messaging or offer within the ad and even the placements and timing of the ads.
For new customer acquisition, algorithms can take top-performing products from retargeting campaigns and find similar products in a feed to serve to high-value lookalike audiences. Even consumers who have never been to your site can have a relevant ad experience.
AI provides performance
Retargeting campaign performance used to just be a matter of having the right creative. If a campaign wasn’t performing well, it was probably because the creative needed to be refreshed.
Humans are inefficient in this, since this kind of testing process makes it nearly impossible to test or analyse the performance of multiple factors at once. Sad, but true – we simply aren’t intelligent enough to understand or predict human behaviour across multivariate ad testing.
Dynamic creative optimisation, also known as DCO, is an important application of AI in online advertising. Using behavior and purchase data, machine-learning algorithms create a wide variety of ads using simple templates and test them among consumers to find the most effective ads that lead to conversion, and DCO can do it all without any human bias mixed in.
AI predicts the future
When AI is applied to any commercial product or service distribution, it becomes a unique extension of who we are. It works phenomenally in e-commerce recommendation systems. Amazon, as an example, trusts its self-learning algorithms.
The company’s patented algorithm-based “anticipatory shipping” system can ultra-precisely define customer purchase patterns and predicts brands, price ranges and products that will be bought. Based on that, Amazon ships products to distribution centers before an order is even placed – revolutionising the e-commerce industry.
AI, especially deep learning, is the perfect tool to predict a user’s desires in the advertising industry.
The technology is simplifying our everyday user experience by bringing deeply targeted ads that contain not only products we are more likely to buy, but also those we haven’t seen or haven’t even thought about.
Advertiser deep-learning tools will lead to changes in the way we recommend products, carefully weighing the value of a potential buyer, predicting conversion probability and, most importantly – learning about their desires.
Self-learning algorithms help to achieve super-accurate user analysis and as a result make advertising approximately 40 per cent more efficient.
In the near future, advertisers and users will experience the evolution of advertising. While it may seem a little bit sci-fi, it’s more likely a natural progression to make online activities more efficient than ever before.
The article appeared in the October 2017 issue of Gulf Marketing Review.