There is no doubt that we are living yet another Artificial Intelligence Spring.
AI research has its own category in the USA President 2020 budget, with funds likely to hit a record 1 Billion Dollars (just for the non-military sector) and China’s budget is a close second.
This is hardly surprising if we think that AI is already used in many aspects of our daily life, from security to medical diagnoses and -of course- digital marketing.
The present wave of progress has led many marketeers and data analysts to proclaim that AI (at least in its “Machine Learning” form) is the future of digital marketing.
Machine Learning for digital marketing can indeed deliver amazing results, but the immense progress registered in the world of Machine Learning means we now need human intelligence to communicate with artificial intelligence. The “brute force” age when the only purpose of machines was to compute simple human skills at light speed is over for ever and with no regrets. Now we are living the stage of the “Digital Paradox”: using Big Data, we have trained machines to recognise patterns, solve problems and make accurate predictions, but the sheer sophistication of these operations now requires human intelligence to serve that data in a form that intelligent machines can understand and use.
How can marketeers make practical use of this cutting-edge technology today?
Much of digital marketing is about recognising patterns, finding meaningful paths among all the background noise of the web. But with vast amounts of data to process, it can be difficult for machines to pinpoint important information and this is where the human intelligence comes useful: you have to train machines to understand what is important to your business so they can turn data into insights.
Janusz Moneta, Senior Ads Marketing Director at Google, explains: “Marketers need to be able to see the whole picture, from the most obvious details down to the faintest patterns. Thanks to machine learning, this super-charged vision is now possible.”
In the Broadley Speaking marketing team, we apply cutting-edge ML technology to every step in our growth funnel to transform our marketing strategies. Adopting this technology has brought fantastic contributions to our clients’ campaigns – along with results.
Capturing the mood – ML and sentiment analysis
It can sound odd to talk about ‘sentiment’ in relation to machines. Indeed, B2B marketeers often favour rational messaging, ignoring the fact that business owners are human beings, with human drives.
Now we can analyse the engagement our messages receive, understand why particular messages resonate, and generate new messaging variations tailored to specific prospects.
This is the way social selling works – for example: identifying the best messages results in an increased level of performance (in some cases, with accurate targeting and messaging, we have seen CTR on our campaigns rise to more than twice the level of industry standards).
Predictive optimisation – the future is now.
B2B marketing often involves long purchase cycles, and its true value may not become clear for months. By analysing historical campaign data, ML systems can learn to predict the potential long-term value of an ad click and the interaction it will receive. This also has the potential to optimise future messages ensuring each prospect is only served messages appropriate to their needs.
ML technology is advancing so quickly that off-the-shelf solutions are starting to emerge, and we at Broadley Speaking are already using many of these tools with a clear benefit to our analysing, predicting and reporting capabilities. By implementing this technology, we’ve seen first-hand the key support role ML can play and now we have the power to identify and understand customer needs like never before.
For over 20 years, Broadley Speaking has helped its clients all over the world find business opportunities worth millions. If you would like to know how using Machine Learning for digital marketing can benefit your business, get in touch for a free initial consultation.