Through these platforms, marketers can gain a more nuanced and comprehensive understanding of their target audiences.

The insights generated by AI drive conversions and simultaneously alleviate the workload for marketing teams.

What is AI marketing?

AI revolves around programming computers to execute tasks that traditionally demand human involvement — such as speech recognition, decision-making and even learning from experiences. Instead of being disconcerted by this concept, envision having an adorable robot ally within your computer, always ready to assist with any task at hand.

AI-powered marketing tools leverage data and customer profiles to discern optimal methods of communication, subsequently delivering tailored messages at precisely the right moment — all without the need for manual intervention. This synergy ensures maximum efficiency.

Popular types of AI marketing

Many industries have adopted AI or are in the process, and it's no different for marketing. So, what types of AI are available for marketers and how are they used?

Data analysis
This refers to collecting and sifting through large amounts of marketing data from various campaigns and programmes that would otherwise have to be sorted manually.

Natural language processing (NLP)
NLP refers to creating a human-like language for content creation, customer service bots and experience personalisation.

Media buying
This approach to AI marketing predicts the most effective ad and media placements for a business to reach its target audience and maximise marketing strategy ROI.

Automated decision-making
Here, AI marketing tools help a business decide what marketing or business growth strategy they should use based on past data or outside data inputs.

Content generation
The approach refers to writing both short and long pieces of content for a marketing strategy, such as:
  • video captions
  • email subject lines
  • web copy, and
  • blogs.

Real-time personalisation
Change a customer's experience with a marketing asset, such as a web page, social post or email to fit the customer's past preferences and encourage a specific action.

Types of AI marketing solutions

Machine learning
Machine learning, driven by artificial intelligence, involves computer algorithms capable of autonomously improving digital marketing campaigns through experience-based analysis.

Devices harnessing machine learning assess new data within the context of historical data, allowing them to inform digital marketing campaigns based on past successes and failures.

Big data and analytics
The advent of digital media ushered in an influx of "big data", presenting digital marketers with opportunities to comprehend their efforts and accurately attribute value across channels.

However, this abundance of data has led to data saturation, with marketers grappling to identify worthy datasets. AI marketing emerges as a solution, swiftly filtering and analysing data to unveil essential insights — thus guiding future digital marketing campaigns.

AI marketing platforms and tools
Efficient AI-powered marketing solutions furnish digital marketers with centralised platforms for managing the mammoth data influx.

These platforms glean valuable marketing intelligence from your target audience, empowering data-driven decisions regarding optimal engagement strategies. Frameworks like Bayesian Learning and Forgetting aid marketers in grasping a customer's responsiveness to specific digital marketing efforts.

The benefits of AI in marketing

It's important to begin with a thorough plan when leveraging AI in marketing campaigns and operations. This will ensure marketing teams minimise costly challenges and achieve the most value from their AI investment in the least amount of time. 

Before implementing any AI marketing tools, there are a few key factors for digital marketers to consider: 

Established goals
As with any marketing programme, it is important that clear goals and marketing analytics are established for your AI marketing programme from the outset.

Start by identifying areas within campaigns or operations that could stand to be improved, such as segmentation. Then, establish clear KPIs that will help illuminate how successful the AI-augmented marketing campaign has been — this is especially important for qualitative goals such as "improve customer experience".

Data privacy standards
At the outset of your new marketing programme, be sure that your AI marketing platform will not cross the line of acceptable data use in the name of data personalisation. Be sure privacy standards are established and programmed into your AI marketing platforms as needed to maintain compliance and consumer trust.

Data quantity and sources
In order to get started with AI marketing, digital marketers typically need to have a vast amount of data at their disposal.

This data will train the AI marketing tool in customer preferences, external trends and other factors that will impact the success of AI-enabled marketing campaigns. This data can be taken from the organisation's own CRM and previous marketing.

Data science talent
Many marketing teams lack employees with the necessary data science and AI expertise, making it difficult to work with vast amounts of data and deliver insights.

For more information, visit www.11thhouse.co.za. You can also follow 11th House Digital Marketing on Instagram.