Becoming AI Native Marketer

AI Native Marketer

It’s time for marketers to become AI native by incorporating Artificial Intelligence (AI)*, Machine Learning (ML)* and Deep Learning (DL)* into their role. Let’s examine how marketers can use AI tech and become AI native marketers.

By 2023 businesses are expected to be spending over £87 billion on AI-based technology*. This will lead to organisation-wide shift towards being familiar with AI  and require marketers to start using AI tech in their marketing activities.

Put aside your seniority or specialism within marketing – now is the time to develop new skills around AI. Here are some examples of how marketers can use AI and work towards becoming AI native marketers.

Build marketing strategy

Marketers are analysing various internal and external data sources to create effective marketing strategy. AI in combination with ML can be used to find patterns and understand trends in large volume of data to gain meaningful insights to build marketing strategy. 

Create intelligent content

AI tools are currently being used to display similar content based on recent activity and recently read articles.

AI can also curate content  for social media or create emails, ad copy or personalised messages. They key tools for content automation are Word.ai, Articoolo, Persado and Scoop.it

Humans are much slower in spotting recurring problems while AI-powered chatbots can do this fast. In addition they can predict what’s causing issues for a user and come up with suggestions on product/service customer needs to solve their problem.

Achieve personalisation and optimal customer experiences

You can use AI to automate personalisation. For example, as a website owner you can display most relevant offers to each visitor based on their location, demographics and browsing history.

This is how brands can increase visitor engagement and make it more rewarding for both parties. 

Manage cross-device and cross-channel promotions

Thanks to AI tech companies are able to identify and target customer on different devices. This speeds up sign up process and enables customer to complete actions  at the right time and the right place for them.
Brands are using augmented reality to show their products  in 3D and bridge the gap between offline and online experience.

AI-enabled Real time forecasting 

To create optimal  forecasting data is being used from various sources from internal CRM, ERP, IoT and other systems, as well as external information such as partners, market intelligence, social media to name a few. AI relies on algorithms and adapts in real time and takes into account daily, weekly, yearly or seasonal variances and learns to minimise risks and capitalise on opportunities.

Upskill to enhance your career and work towards being AI native marketer

Marketers need to leverage AI in their everyday marketing activities. It doesn’t mean that you need to become data expert. Instead be sure to speak the language of DL, ML, and AI to collaborate with data scientists.  Data science is largely centered around coding, so you might give it a go or get your junior team members or even your kids inspired. Please read the article: 8 Reasons Coding for Kids is Not Just Another Fad here
Alternatively, consider upskilling and learn to do advanced data analysis, and some visual machine learning to become marketing analyst. The opportunities are out there, so make the most of them. 

Do you have examples of using and implementing AI in your marketing activities? Let’s talk on LinkedIn or Twitter

*According to the recently updated International Data Corporation (IDC) Worldwide Artificial Intelligence Systems Spending Guide, spending on AI systems will reach $97.9 billion in 2023.

*DL is subset of ML where systems can learn hidden patterns from data by themselves, combine them together, and build much more efficient decision rules. 
*ML is subset of AI that involves programming systems to perform specific task without having to code rule -based instructions.
*AI – Any system that leverages human capacities for learning perception and interaction at a level of complexity that ultimately supersedes our own abilities.