Machine Learning and Advertising

Machine Learning and Advertising

Why Machine Learning Might
Be The Saviour of Advertising

Daryn Mason, Senior Director, Solution Consulting @CxDaryn


Why AI will give rise to better ad blockers consumers and brands alike

Advertisers have come up against a wall. The use of ad blockers is on the rise as consumers look to control how much interruptive advertising they receive online and over social media. eMarketer predicted that more than one quarter of US internet users will be using an ad blocker by the end of 2016.

People may not welcome what they see as an endless barrage of messaging, but that doesn’t mean they want to block everything. They just want communications that are relevant. In the UK, for instance, the Internet Advertising Bureau (IAB) found that more than half of consumers would turn ad blocking off to receive the content they want.

 A wave of “intelligent” software will allow advertisers to probe deeper into each shopper’s digital interactions to learn which brands, products and services most appeal to them.  

Machine learning may be the technology that takes advertising to this next level. A wave of “intelligent” software will allow advertisers to probe deeper into each shopper’s digital interactions to learn which brands, products and services most appeal to them and target them with genuinely impactful content.  

On the right track

Today’s online marketing is definitely more personalised than it used to be. The use of programmatic advertising has been a major leap forward in terms of communicating with customers based on their online activity and purchasing habits, but customers still find themselves overwhelmed by the volume of messaging they are sent. Hence their growing preference for ad blockers.

The problem is that ad blockers are generally inflexible. As Aiden Joyce, Chief Executive of anti-ad-blocking start-up Oriel, has said: “Ad blocking technology is a blunt instrument which, by default, makes no differentiation between poor and quality advertising.”

Some do offer a limited degree of control. AdBlock Plus allows users to whitelist advertisers and publishers who have agreed to abide by user-generated criteria.

A battle of the digital wits

Many companies’ response to ad blockers has been to implement software that circumvents them.

Facebook launched a workaround to AdBlock Plus and other similar services this year, and as a result saw its desktop advertising revenue jump 18%. The practice has also gained traction in the publishing space, with major media outlets like The New York Times and The Guardian rolling out ad-blocking workarounds to secure their advertising revenue.

What we’re seeing is essentially a battle of the wits where ad-blockers and merchant workarounds are trying to outsmart each other in increasingly sophisticated ways. This dynamic doesn’t breed better content and is not a sustainable way forward.

Welcome to the machine

Machine learning brings greater nuance to the way consumers manage content and to how brands distribute it. The technology is turning ad blockers from all-or-nothing sorting programs into sophisticated ‘content brokers’ that scrutinise adverts for relevance based on each customer’s needs. 

 Machine learning brings greater nuance to the way consumers manage content and to how brands distribute it.  

Just like Google anticipates search terms based on our browsing history, ad blockers will increasingly rely on artificial intelligence (AI) to curate brand messages on a customer’s behalf. And, much like Google, these programs will develop a deeper understanding of each user over time, which means they’ll only become more accurate.

The use of AI will continue to evolve for both merchants and customers, and by 2020 we will see volume-based marketing dialled back as more targeted, productive communications take its place.

Syncing up marketing and sales

It’s worth highlighting the importance of timing in determining the impact of marketing. Overexposing a prospect to messaging when they aren’t primed to buy or if they are already in talks with your brand’s sales team runs the risk of turning them off.

 Marketing and sales departments need to align more closely when dealing with customers.  

That’s why marketing and sales departments need to align more closely when dealing with customers.

Consider the case of a mobile software start-up that needs to buy additional bandwidth from a telecoms provider to reach more customers. Chances are the company has already researched a number of vendors online, and a programmatic approach to advertising would see them targeted with adverts to capitalise on their interest. However, if the start-up is already speaking with sales then the continuous wave of marketing might just come off as aggressive and unhelpful. 

The keys to effective advertising are relevance and timing, and as people continue to adopt sophisticated ad ’brokers’, brands will need to work harder to deliver content that is both opportune and valuable. Those companies that put in the effort will find themselves getting closer to their customers and prospects, rather than continuing to drive them back behind a wall.  


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