The Role of AI in Ad-analytics

A Lexus advertisement has become a part of folklore in advertisement circles. Why? Well, it is the world’s first ad to be scripted by AI. The system fed on data from many past advertisements of many other luxury products and came up with a script. The ad showed an engineer marveling at his creation who then turns sad as his creation, the automobile is taken away from him to be subjected to a grueling test. In the end, the power brakes that he has built into the car saves the day. The advertisement was directed by Oscar-winner Kevin Macdonald of “The Last King of Scotland” fame. This does bring us to the question that can Artificial Intelligence do the work which used to be reserved for human expertise?Is the world of advertising ripe for an AI takeover?

Ad-analytics has primarily been used to better infer the efficacy of an advertisement. In some ways, this is the holy grail of marketing.Ad-analytics helps us understand how the various moving parts of campaign work, with what effectiveness. With the growing dominance of digital and social media, marketers have been able to increase the number of touchpoints with their consumers and they have been able to do that economically. But companies are also faced with what can be only be termed a data deluge.

In such a scenario it was only a matter of time AI became an integral part of this industry.Sure enough,we have started seeing newer use cases revolving around AI in Marketing analytics.

The “now” playground of advertisement is digital media. From this channel, it is extremely easy to collect, store, and process data. This is a world of oxymorons, and all the major campaigns are going through mass-customization. Customized-targeted campaigns are the norm of the day.

Currently, two-thirds of all digital spend is being reserved for digital platforms. The AI spend in this segment is slated to grow at an exponential rate of 29.79% between 2018 and 2025. Which translates to approximately $ 6 billion in 2018 to $ 40 Billion in 2025. APAC is likely tobe the highest growth region and search advertising could take the biggest share of the pie.

Research reports like Salesforce’s Digital Advertising 2020 Report show that advertisers are seeking data from newer sources.  Half of all North American advertisers want to increase the use of third-party data. Of course, all this data will have to be crunched through a robust AI system to contextualize the traditional segmentation, targeting, and positioning.

Let us look at a few use cases propelling this phenomenon.

Recommendation engine.

Think Netflix or Amazon. Don’t we love the recommendations about which show to watch next? Don’t we get an advertisement about which product to buy next? This is driven by massive data-crunching happening behind the scenes.

Search engine.

Google embodies the whole concept of AI algorithm-based search engine and optimization. Doesn’t it come across as unreal how the Google Ads thrown our wayare so similar to our search history?  With NLP and semantic search features many FMCG companies are trying to use search engines to make their Ads reach out to a wider audience while targeting better.

Visual Social-listening.

Target allows its customer to click pictures and then scan for similar products available on their website. Similarly, customerscould get ads about similar products or products which could be bought together. This visual social listening is allowing brands to know how a potential customer interacts with their brand and allows them to contextualize their campaigns.

Sentiment marketing analysis.

Companies like Samsung are trying to find out what customers are saying about their products? Is there any negative feelingabout their product? Is there any valid feedback out there?They also promote the fact that they are listening to the customers and trying to fix issues.  

Product pricing.

You must have noticed how the price of a room changes once we have searched for that on the Airbnb site, and also when you see ads about similarly priced rooms. That’s AI in action again.

Predictive marketing analysis.

Predictive analysis will let brands know what a particular customer may do soon. That actioncould range from jumping ship, to which productsshe might require next? Loyalty programs, as well as customized bundled offers, are created on the fly and targeted for that customer. All by AI, of course.

Most organizations are gravitating towards a culture where decisions are automated and data-driven. AI-based advertisements or campaigns will become more important in those scenarios. The quintessentialsegmentation, targeting, and positioning of the product can be customized with a 360-degree view of the customer. With a better understanding of the customer, the strategy can be personalized. The future is exciting and innovations beckon. The next stage of AI-based advertisement could well be to make the ads more interactive, in line with what Lego came up with by partnering with IBM. AI is set to make its presence felt in the ad world. And marketers couldn’t be happier.