If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Unilever is using artificial intelligence to influence more of its marketing, from processing insights to finding influencers. The advertiser has 26 data centers across the globe where scientists are using AI to synthesize insights from a range of sources including social listening, CRM and traditional marketing research. Like other advertisers, Unilever hopes the investments fuel a move away from mass reach channels toward more personalized communications that are also cheaper to produce and localize at scale. Unilever has been using AI and machine learning to sort through structured data within a database for years, but it hasn't been able to do the same for unstructured data until recently. Unstructured data is qualitative, which makes gleaning insights from content such as text, audio, social media and mobile activity harder.
Back in 2006, Phil Fernandez, Jon Miller, and David Morandi founded Marketo. At the time, they only had a PowerPoint. But then again, they also had a compelling vision to create a new category known as marketing automation. Within a few years, Marketo would become one of the fastest software companies in the world, as the market-product fit was near perfect. By 2013, the company went public and then a few years later, it would go private.
One of the terms that we seem to be hearing about a lot these days is AI (Artificial intelligence). The revenues gained from the use of AI in technology is massive, and this is evident from how little things like even the smartphone apps are changing. These advancements show us the type and scale of technology we can look forward to in the future. In regards to AI in marketing, it's evident that it's currently at an infant stage, and hence we're just beginning to see artificial intelligence being used in content marketing. Artificial intelligence is intelligence demonstrated by machines which in contrast is to mimic the natural intelligence displayed by humans.
Potential applications of machine learning are very broad indeed. But, although AI conjures up images of robot butlers and promises big changes to customer experience, marketing teams who are already making use of AI-powered tech are doing so to sell. Machine learning refers to statistical approaches to train models which incrementally improve the output of a system. This sort of predictive modelling is used to increase the likelihood that a customer will take a particular action – this could be opening an email, clicking an ad or viewing a recommended product. Marketers are therefore mostly using machine learning in their push for personalisation – fuelled by a desire to improve sales.
Implementation of artificial intelligence (AI) or machine learning is currently relatively low – but in the next three years, top marketers expect to integrate these technologies to a greater degree, per the latest report [pdf] from The CMO Survey. Among respondents who are currently using AI, some 56.5% said they were using it for content personalization. While personalization has proven to be effective for marketing efforts, it is also time-consuming and difficult to do at scale. AI may be able to alleviate these issues. Another 56.5% of companies employing AI employ the technology for predictive analytics for customer insights.
Keeping up with AI-driven developments in the search industry is the new normal for search marketers. Technological breakthroughs, such as advancements in voice recognition and the creation of powerful machine learning algorithms, greatly impact how people search – and consequently how we do search engine optimization. The idea of artificial intelligence taking over the digital landscape can be daunting to some marketers who view it as a risk to their professional careers. But while there is still a lot of guesswork involving the topic, there is likewise ample knowledge available for marketers who want to get up to speed on AI as it relates to search. On August 22, I moderated a Best of SEJ Summit webinar presented by Purna Virji, Senior Manager of Global Engagement at Bing Ads, Microsoft.
It's no secret to marketers that effective use of data is critical. It is the key to executing successful campaigns that engage consumers and drive towards long-term, profitable relationships, and artificial intelligence (AI) and machine learning are vital parts of analysing and optimizing data at scale. The amount of available data on consumers and their habits, preferences and behaviours continues to grow. It is therefore increasingly challenging to make sense of the data and make accurate predictions. Consumers sharing information about themselves via social media and e-commerce using mobile devices and personal computers are leaving behind data that can prove extremely valuable if marketers are able to look at all the data points to build holistic profiles of past, current and prospective customers.
Sometimes we over-complicate AI, thinking it's too high-tech and futuristic for us to use in our everyday work. But AI is not the future, it's the present. Let's not consider it an unattainable technology, because sometimes AI is so simple that we don't even realise we're using it. AI in marketing is here right now. Results from our latest State of Marketing research report show the highest-performing marketers are 9.7 times more likely than underperformers to be completely satisfied with their ability to personalise omni-channel experiences at scale.
Marketers are increasingly using AI to streamline workflows and automate monotonous tasks. According to an Adobe survey, about 15 percent of agencies are already using some form of machine learning, and 31 percent are planning to adopt it by the end of 2019. London-based Adthena is hoping to lure some of those soon-to-be customers with its AI-driven search marketing intelligence platform. Roughly seven years after its founding and a year after it established a presence in the U.S., the company is today announcing that it has raised $14 million in a series A funding round led by Updata Partners, bringing its total venture capital raised to $18.1 million. Founder and CEO Ian O'Rourke says the funds will be used to accelerate the company's stateside and global growth and to "strengthen" product development as it prepares to launch new channels.
Marketing automation has become the lynchpin of successful marketing campaign management, yet many brands struggle to fully maximize their marketing automation ROI. We settle for automating manual tasks -- like lead management, email campaign development and landing page creation –because we're too busy to learn what marketing automation can really do for campaign effectiveness. The time has come to move from simply running campaigns automatically to running them intelligently. For more about marketing stacks, watch the on-demand webinar MarTech Madness: How to evaluate your marketing stack. Thanks to artificial intelligence (AI), a new breed of marketing automation solutions can "mimic" human intelligence and recommend marketing actions.