“How is AI going to change marketing?”, “What is AI-powered marketing?”, “Should we use AI in marketing?”… All these are questions that I get asked a lot. By clients at the office, by strangers on forum boards, and even by my friends at restaurants and house parties.
The reason why this question is so frequent, is because there is still a lot of confusion around it. Academics have their own definition, which is somewhat restrictive; while vendors seem to be labelling anything they sell with “AI” to sell more of it.
The truth is, it doesn’t have to be complicated at all! Months of answering these questions allowed me to build a comprehensive approach to guiding people through what AI-powered marketing really means, how it is being used, and why it matters.
First, let’s start with the definition I typically give:
In other words, AI-powered marketing is the solution to the #1 problem that marketers have been facing ever since marketing emerged: how to get a precise understanding of customers.
This precise understanding is the most critical component of any successful marketing plan1 Marketers previously had essentially two ways of finding answers: market research, and gut instinct.
Both are very imperfect. Market research takes a lot of time and money, and can potentially be biased. Gut instinct is unreliable and virtually impossible to scale.
True, marketers also had massive amounts of data collected over the years (e.g. loyalty program history for each customer), but the data was too hard to be leveraged due to how large, dispersed and dirty the data sets were.
Artificial intelligence brought means of analyzing such data sets, thus giving marketing departments the opportunity to use this data to serve the purpose of understanding customers better.
AI-powered marketing was born.
The reason why it’s a game changer is because it dramatically changes how marketing approaches the matter of understanding with customers. AI-powered marketing allows to shift from an understanding based on identity (i.e. age, gender, zip code…), to a more precise understanding based on behavior (i.e. purchases, online activity, returns…).
To give you a more practical idea, here is non-exhaustive list of various AI-powered marketing techniques that are currently in use:
- Recommendation engines that can tailor product recommendation at the individual-level. Amazon and Netflix are the most famous examples, with an estimated 35% of Amazon’s sales coming solely from recommendations shown to shoppers2
- Dynamic pricing models that make prices fluctuate in real-time depending on the state of both demand and supply. Uber’s price surge is the most famous example. Yet, it could soon expand to other industries, like gas stations3
- Propensity models that can predict individual consumer’s behavior. MAIF (French insurance company) is using one to predict the likelihood of a customer leaving to the competition in order to take action before it happens4
- Sentiment analysis models that scan what people say about any given product to identify potential shortcomings and opportunities. Arby’s (US fast food chain) realized that its consumers were in love with their sauces thanks to it. Consequently, they launched the sauces as standalone products and leveraged the insight to fuel their marketing campaigns5
- Programmatic advertising models that automatically bids in real time for online ad spaces based on how likely it is that the viewer will end up buying whatever is being displayed.
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To illustrate how important it is, please refer to the following case studies I wrote: ↩, .
This project has been conducted by Artefact, a French startup agency that specializes in predictive marketing. Check them out here. Or Target (US retailer) that predicts the pregnancy of its consumers[footnote]This certainly is the most famous business case in predictive marketing. I wrote about it here.↩