How AI is changing the Digital Marketing Landscape

The machines are taking over and we couldn’t be happier. It’s “Name your PC” Day, Nov 20th (seriously, it’s a thing), and Artificial Intelligence is no longer a distant concept, most people view AI as an idea straight out of Science Fiction, however most of us have unknowingly had AI already integrated into our everyday lives. The technology is leaving its footprint in almost every sphere of life and marketing is no exception. Almost all marketing experts are busy speculating how AI will influence marketing, consumer intent, business futures, consumers’ buying habits, advertising, and so on. The wildest part is that AI is only just warming up.

Both our personal and professional lives have started experiencing the potential of artificial intelligence, thanks to home and personal device technology such as Alexa and Siri, Not to mention the Machine Learning analytical software that is being integrated into different developmental fields. With these areas being just the tip of the iceberg for what is to come in the advancement of AI technology, you can see why marketers are less fearful of a HAL 9000 situation and more excited about what AI can do to enhance their marketing efforts.

Here are some categories of AI that will help usher in these changes in the field of marketing;

Machine Learning

This technology does exactly what the name implies. Software that can comprehend data and problem-solve independently of human input, thereby “learning” on their own. In a marketing context, it can be applied to a number of applications - ad targeting, lead generation and search optimisation, just to name a few.

To some extent, this part of AI will be the basis on which machines will start making more business decisions, thus, at least theoretically, freeing up time and space for business owners and workers to focus more on the human components of business and marketing activities. One example of decision-making in this scope is the use of digital personal assistants, such as the Google Assistant.

Consumer Behaviour & Intent Focused Marketing

AI is all about data-driven approaches to marketing and decision making. Different platforms collect and store all kinds of analytics these days as a part of analysing customer patterns in order to develop more intuitive automated systems and customer profiles. This helps marketing target specific people along a sales funnel that may not even fit the traditional mould of a target market.

Software that can both view and understand where a consumer’s interests are, can then in turn further cater to the consumers needs, leading them down the sales funnel in a faster, almost instantaneous fashion. This method helps secure more spontaneous sales within those moments of spontaneous desire.

Semantic Searching

This is simply an expanded look at the ideas of machine learning and meta-analysis. Semantic searching refers to the capacity for machines to essentially understand user searches contextually, in order to offer a set of results that are customised. This is achieved through the AI’s ability to understand more about the contextual meaning of certain search phrases and patterns, along with considering things like the user’s search history, all feeding into the results page.

A mishmash of these elements within an AI assisted search, results in Search Engine Optimisation (SEO) becoming more nuanced. In short, Semantic searching is all about the AI systems digging deeper and getting to the bottom of why a person is searching for something, rather than just showing the users results from the standard word search they have entered.

Content Creation and Curation

Do you have that friend that you hang out with so much that they begin to know what your thinking before you even say anything? That friend that knows your preferences on different subject matter? Kinda annoying, kinda great right?

AI used for content creation and curation, is much like that friend of yours. A software that observes your preferences and overtime manages to gain a roundabout understanding of what types of content you wish to see more or less of.

We see examples of this all the time, through subscription services such as Spotify. The music streaming service gathers data with every song you listen to. It then manages to market to you more content that it believes you will be inclined to enjoy.

Voice Search and Speech Recognition

One of the most prevalent forms of AI in more recent years has been the use of both Voice search and speech recognition, thanks to Home and Personal Devices that offer services such as Siri and Alexa.

What was once deemed as a gimmick has been improved upon and widely adopted by the market as a credible search type. These days, conducting a search through a quick chat with an AI system is much more efficient than having to handle a device, exit programs and manually look into the matter yourself.

As the error rate within the speech recognition software improves with each passing day, so will the ability for these devices to promote particular products and services relevant to what a user is enquiring about.

Lead Generation

One of the biggest challenges every marketer faces is within the context of lead generation. Now imagine a software that not only can sift through piles of data to find the ideal customers and clients for you, but also let you know where each lead is on their customer journey.

This removes the daunting task of discovering new leads so that you can spend more time formulating your specific pitches and sales calls.

Chatbots

Up until now, chatbots have been rather underwhelming. A lot of customers that jump on a website have been met with an answering machine of automated answers to specific question paths. The whole experience can be rather jarring and frustrating. A lot of customers have shared that they do not feel respected when they’re left to talk to a robot with few ways to converse.

However the advancement of Chatbots has them on a trajectory towards passing the Turing test. Some Chatbots have gone as far as to have spelling errors and linguistic fillers, such as “Ums” and “Ahhs”, in order to disarm online viewers and simulate online chat between two people.

Automation and Personalisation

The current marketing landscape has been built upon a whole lot of trial and error, just a bunch of people attempting guesswork on the current market, with different forms of “A/B Testing” in order to understand buyer behaviour. While our analytical tools have come a long way, we’ve always been limited by the human/data analysis factor.

Machine learning and AI is being used as a means of cutting through the noise and comprehending data in a way that only a computer can, in order to have an advanced understanding of the market.

Automation is one of the most interesting and useful AI applications in digital marketing, based on the fact that it can use large amounts of data to essentially choose a way that it will direct certain information. With this in mind, we can expect advances in automation to help with optimisation in both B2B and B2C. 

Conclusion

A lot is happening in the world of marketing with respect to technologies like AI and machine learning. Marketers need to see this technology beyond its data analytics capabilities. It is time to think of this technology in terms of consumer needs and not just submit to the inflow of technological innovation. 

We may think of AI as some sort of invasion of privacy, but part of your job as a digital marketing professional is to understand how to use it ethically. AI-directed tools will continue to become more commonplace and are abundantly useful when it comes to analysing and predicting the buyer’s journey.

The future looks bright.