How Machine Learning and Artificial Intelligence Are Spearheading A New Generation of Data Driven Advertising.


The alert for Google Adwords had gone off, letting me know that my client had been outbid for another keyword.



All day, my client a small family owned hygiene company was pushed off of keywords related to facial wipes by a giant corporation.

I tried turning to long tail keywords or more obscure low competition search phrases.

It didn’t matter.

In a matter of minutes, we were outbid on every search term.

Confused and frustrated, I called a friend of mine who used to work at Google to ask him about what was going on.

“Oh.” he replied, “That big company is probably using programmatic advertising. It’s basically an algorithm which learns what the competitors are doing and then adjusts the bids using machine learning to always end up in the top spot. You can’t beat it.”

That was my introduction to artificial intelligence (AI) and machine learning (ML) in advertising.

That happened in 2016 and since then I have become fascinated by the effects that AI and ML are already having on advertising and what they are going to do in the future.

5 Ways That Advertisers are already using ML and AI:

  1. Search. The most obvious way that AI and ML are already influencing advertising is the way web users search. Using AI and ML to analyze the way customers think, search and buy to figure out more effective and cost efficient ways to get marketing messages in front of them. Google already assists Adwords buyers with things like optimization of their campaigns and keyword suggestions.
  2. Recommendation. If you’ve ever shopped on a site like Amazon or Asos or used Netflix or Hulu you are already familiar with recommendation engines the stealth salesman of the web. Recommendation engines use AI and ML to suggest the perfect complimentary product or next tv show or movie to binge on. It’s not just for B2C either as some larger companies like IBM and Waze are using recommendation engines for everything from navigation to traffic control systems.
  3. Voice/speech Recognition. Voice recognition is on everyone’s mind lately given the popularity of Amazon’s Alexa and Google Home. Voice and speech recognition are used to navigate, buy, and browse.There is even a trend towards integrating voice recognition with chatbots to create a bot that responds to vocal cues like a real human.
  4. Social Listening. Social listening refers to the idea of monitoring what is said around the web about your products and services. Before companies had to employ humans to comb through a million different social media platforms by hand. AI has eliminated the need for humans by allowing intelligent bots to comb social media and find all the posts, questions and comments you are looking for.
  5. Content Creation. Last but certainly not least, content is now being created by AI. Several sports sites use AI to create recaps of games and summary articles often by aggregating social media. Now bots are even able to turn existing articles into videos. While the quality is still lower than a professional human writer, there exists a possibility for AI to take over jobs that were once thought to be the domain of humans exclusively.

Let’s put a pause on the present for a few moments, and look into the future

5 AI and ML Trends that might be next

  1. Image Recognition. One of the big achilles heels currently in AI is image recognition. A quick google search will find stories like this one in Wired where scientists fooled an image recognition system into believing a rifle was a helicopter. But that all might be changing soon based on the idea of capsule networks. Old AI uses a convolutional neural network which can have problems differentiating between items and space. But capsule networks works much more similarly to human eyesight and is able to recognize images and items with 50% greater accuracy than old networks.
  2. Data Driven Storytelling. Research suggests humans are hardwired for stories. Now data scientists and entrepreneurs are racing to figure out how to turn all this data from the big data revolution into stories that will sell. That’s where data driven storytelling will come in as it uses ML to transform data points into a story about products or services. Data driven storytelling will be the next step up in user experience as you tap into the consumers deep neural pathways in order to create a story based on what you want to hear about the product or service.
  3. Even more granular targeting. We already have granular targeting where you can make sure that your ads end up in front of the right people based on demographics like age, income and buying behaviors. As more and more data sets get crunched every day targeting will get even more granular until you will be able to target your ads to 56 year old men named Sandy who ate a plain bagel for breakfast and use twitter as their main social network.
  4. Dynamic Pricing. If you’ve ever gotten stuck somewhere and had to take an Uber during surge hours you’re already familiar with how dynamic pricing works. As demand rises AI raises the prices. As companies integrate machine learning look for prices to become more and more dynamic. This could even lead to a world where the more affluent pay higher prices based on their data trail.
  5. Cognitive Marketing. Do you know what cognitive marketing is? It’s a sanitized term for messing with people’s heads using advanced marketing tools and strategy created by you guessed it Artificial intelligence and machine learning. It has been predicted that 50% of companies will be using cognitive marketing by 2020. Cognitive marketing takes advantage of human emotions and behaviors to create that has been designed to get a certain response or emotion from the prospect as companies segment their audience into smaller and more tightly defined groups then personalize their content to their emotions and behaviors.

Pretty mind blowing stuff right?

AI and ML are already affecting how ads are created, the type of content they are displayed on and who they are displayed to.

Currently there are dozens of ways that ML and AI are spearheading a new era of data driven data in areas like:

  • Search
  • Recommendation
  • Speech
  • Social Listening
  • Content Creation

In the future this will continue with the further refinement and greater deployment of techniques such as

  • Image Recognition
  • Data Driven Storytelling
  • Even more granular targeting
  • Dynamic Pricing
  • Cognitive Marketing

Now is the time to take action.

If you are already using data and even employing a little bit of AI or ML then the time is now to up your game and start incorporating services companies such as WorkFusion are providing.

A new generation of data scientists and marketers are coming ready to use AI and ML to take business to a place it’s never been before, don’t miss out on the next big thing.