Will machine learning be the death of content A/B testing?

Machine learning is changing the content marketing game. With the democratization of artificial intelligence tools — meaning you don’t need a data science degree to implement machine learning technology — you have at your fingertips a whole new world of content optimization, customization, personalization and relevance, at scale, whatever industry you’re in.

That means you’re able to deliver more engaging and meaningful content for your customers, with carefully crafted content style and beguiling calls to action at the right time and with the right cadence.

You’ve already got a vast volume of data about your customers and your market at hand; even more data is being produced and for sale every day. Machine learning is the tool that unlocks the underlying insights that data leads to, allowing you to map data and content to the right audiences.

And once people engage with your content, machine learning can help you make sense of the data you gather, revealing what’s working, what’s not — and how to turn that into insight that optimizes your campaign and turn setbacks into leaps forward for not just your current campaigns, but future ones, allowing you to deliver truly personalized experiences at scale.

Machine learning offers a huge leap forward in content marketing, which in most organizations tends to be strictly siloed — social marketers might be coordinating with the research team and the content marketing team, but marketers running each channel have a different — sometimes significantly different — view of who their customer is and what they want, across each of their individual campaigns. And that can lead to dissonance for your customers.

And then there’s machine learning, which gathers together all the data your marketing campaigns and research uncovers, in every channel, from email to social, search, discovery, promotion, and more. Better yet, it breaks down the silos between all these channels, giving you a unified view of your entire customer base. Machine learning can link the propensity and behaviors of your customers at all points of contact, allowing you to develop a truly comprehensive view of what your marketing target audience is.

Getting ready to launch a new campaign? Machine learning offers you a perspective on and insight into customer engagement: a factual, data-driven view, in one place, of what worked in each and every one of these channels. From there, you’re not only able to tailor your campaigns based on your gut instincts, but work with the insights and feedback that your machine learning solution offers, from statistical significance to actual feedback and suggestions for future campaigns.

Companies like Marketo are now deeply invested in machine learning in the marketing space, working with customers to uncover everything that a machine learned algorithm can offer a marketer, says Arun Anantharaman, chief product officer at the company. Marketers are particularly eager to replace hunches with data. As Anantharaman explains, “One of our corporate marketing customers said AI is taking the guesswork out of determining what content will resonate for each person that interacts with their brand.”

Companies are now moving beyond A/B testing — up till now the primary way to understand the impact of content — to a place where data-fed algorithms are achieving significant results for something called Content AI.