The future of AI-enabled advertising: how marketers can win in a first-party data world

How Google and Facebook use AI

AI and machine learning rely on data to fuel everything they do. Today, Google and Facebook use machine learning and AI to run their platforms in two ways.

First, descriptive learning, which is totally ‘unsupervised.’ The AI teaches itself but in a very simple manner – it determines ‘what happened’ by capturing patterns and phenomena in data.

Second, predictive learning, which is ‘supervised’ learning. This relies on interaction from users and advertisers to assist in the teaching of the algorithms to better learn from past examples, allowing it to forecast the future more accurately – to determine ‘what will happen.’

AI in e-commerce

These processes aren’t the sole preserve of the world’s biggest tech businesses. Marketers (particularly those working in e-commerce businesses) use first-party data and AI to enhance and improve campaign performance in areas including product bundling; sales and demand forecasting; pricing optimization; and retargeting to predict past customers’ returning purchase behavior.

These techniques work amazingly well, but only through access to first-party data. The accuracy of the first-party data determines how effective the campaign will be.

Data is an area where e-commerce brands often shine because they can offer value exchange to garner first-party data through offers and rewards. A lot of the most established and accurate AI software applications are geared toward e-commerce retailers because of this access to up-to-date, reliable data.

AI outside of e-commerce

What of those businesses outside of the sunlit uplands of e-commerce? How can AI be used to support growth without readily-available access to first-party data? The answer lies in the clever integration of AI with lead generation. All too often, marketers focus on driving as many visitors as possible to a business (and optimizing ads). Little or no regard is given to where prospective customers or clients are being driven to. Yet, increasing the conversion rate at this point is often where the greatest benefits can be had and where AI can come into its own.

One of the best examples of this is AI-enabled landing pages. These work in two complimentary ways. First, the AI platform creates a landing page and section components based on industry, audience and campaign goals, using dynamic layouts to convert visitors and create new variants in a snap. The idea is to increase conversion rates by pulling data from conversions, then predicting which layouts and headlines work best for a target audience.

Second, by creating multiple variants of the same landing page, each with a slight difference in button color, headlines or similar. This uses AI-powered algorithms to match visitors to the variant they’re most likely to convert on.

This uses a process called ‘contextual multi-armed bandit theory’ to eliminate a one-page-fits-all approach to conversion optimization. The platform then serves relevant content to each visitor by learning from a visitor’s attributes (including their location and device, among others) to send them to the variant where they’re most likely to convert.

The future of AI marketing

What lies ahead? AI-driven conversational commerce, which will take the use of first-party data to the stratosphere and back. Conversational AI is gaining traction but is not quite up to the task yet – although at the enterprise level we are seeing massive advances.

The real revolution in conversational AI will be realized when it can be adopted en masse. This will see exponential advances and a fundamental change in marketing analysis, as we move from direct response to asynchronous conversations in the form of messaging. It will turn the world of lead generation upside down (in response times at least) and lead to a massive increase in engagement.

As for e-commerce, we will also have our purchasing decisions and behavior influenced through these asynchronous conversations. This will see us engaging with brands, large and small, in a far more personal way than we are used to. It will become imperative that brands of all shapes and sizes communicate with their customers and prospects via conversational AI.