What is AI marketing and why should we care?
BY JAMES WILLIAMSON
Today, artificial intelligence is an important driver of business growth, profitability and customer loyalty. The future of AI marketing is now - and we should care about it.
What is AI?
Artificial intelligence or AI is the general term for the algorithms (computer programs), technologies and techniques that make machines ‘smart’.
Algorithms make machines smart by setting the rules for the computer to follow and learn from. For example, learning to do long division by dividing the denominator into the first digits of the numerator, and so on, is a simple algorithm with a clear set of rules or instructions. Computers are ideal at running algorithms on an immense scale, at immense speed. The algorithm-driven calculation, learning and prediction is superhuman and super-scalable. This is the ‘killer app’ of AI.
“AI is the science of marketing machines smart.”
Machine learning and neural networks
At the heart of AI is machine learning or ML. The ML algorithm allows the machine to ‘learn’ with the goal of prediction or clustering. Prediction is where, from a set of input variables, the machine estimates the value of an output variable. Prediction is used for data with a precise mapping between input and output, called ‘labeled data.’ This from of ML is known as supervised learning.
A neural network is a form of AI that seeks to imitate the human brain’s interconnected neurons that exchange messages continuously. In AI, they’re called artificial neural networks, ‘neural nets’, or ANNs. Neural nets are taught to adopt cognitive skills rather than learning by supervision.
Deep learning, a subset of machine learning, is when layers of neural networks are put one after the other. The most famous example of deep learning (to date) is when Deep Mind’s neural net, Alpha Go, beat the world champion in the ancient Chinese game of Go in 2016. In January 2014, Google acquired DeepMind for US $500 million.
“Neural nets are taught to adopt cognitive skills rather than learning by supervision.”
Deep Mind’s Alpha Go defeats world champion Lee Sedol in 2016
Does AI make marketing smart?
AI’s machine smarts are designed to complement human intelligence, not supersede it. The machine, the algorithm, the AI technology, cannot think or feel or create like a human, or even make decisions like a human. But AI is very good at is calculating and predicting in ways a human cannot do. This makes it valuable as a tool in marketing and many other fields.
AI marketing effectively automates data collection and behavioural targeting to help businesses achieve their goals. In digital channels, AI marketing removes human bias. This is crucial because the data gathered is more objective and realistic in revealing actual consumer preferences and behaviour online. AI marketing is more scientific than traditional marketing, but it is no less creative.
Today, marketers have much deeper and more accurate information about how their customers consume products and services. This allows marketers to provide more personalised customer experiences, build brand, create more value, and drive sales and revenue for the seller (think Amazon’s sophisticated AI-driven product suggestions).
“AI marketing is more scientific than traditional marketing, but it is no less creative. ”
AI tools
Today’s marketers have a sharp (and growing) AI toolbox to implement their strategies.
Some tools can use data to curate messages at contact points without wasting time and the need for marketing personnel to trigger the response. Other tools include data analysis (like Polymer and Tableau), media buying, content generation (like Writesonic, Grammarly and Market Muse), natural language processing (like Alexa and Siri), SEO (like SEMrush), email (like Phrasee), automated decision-making, and real-time personalisation.
Feeding the machine
The digital world is awash with data which marketers have to make sense of to run effective campaigns. The challenge is to focus on the data that are most relevant to their business. AI-driven analytics and tools are ideal at processing the data to give marketers (and sales teams) better insight into their customers and prospects. Campaigns can be finely honed to provide higher engagement and conversion rates.
AI is predicted to take a huge chunk of marketing data analysis and data science tasks. Marketing teams will continue to leverage AI solutions to drive profitability targets. Data science has to be translated into more relevant action and more effective execution. What was a tedious, time-consuming task of collecting, processing, and analyzing data decades ago can now be accomplished by AI in minutes.
More relevant marketing metrics will help marketers assign value to their campaigns more accurately. These insights will continue to spur business growth owing to more responsive solutions and more strategic marketing initiatives.
Emerging trends in AI marketing
AI marketing trends1 set to emerge in 2022 include:1. Large Language Models to impact conversational AI
Over the next few years Large Language Models (LLM) will impact conversational AI (like chat bots). As LLMs are trained on massive datasets in the terabytes and multiple parameters in the billions, they’ll define the next-generation conversational AI. For marketers, this means more adaptive conversational tools that can enhance customer engagement.
2. AI solutions applied to boost cybersecurity
AI marketing accuracy relies on how well the models are trained. Again, this requires massive datasets which hackers can potentially access by reverse-engineering AI systems. To avert these attacks, AI solutions will also need to be implemented in cybersecurity.
3. The use of multimodal AI
Moving from single modal AI, multimodal AI will combine conversational AI models with visual modalities. Google’s Multitask Unified Model (MUM) is a familiar example of how this trend impacts AI marketing. Through Google MUM, the search experience is made better as search results are based on contextual information from multiple languages. Through Meta, augmented reality glasses and virtual reality headsets include optics and displays, computer vision, audio, graphics, haptic interaction, full body tracking, perception science, and true telepresence.
Virtual reality AI
4. New vertical AI solutions managed by platform providers
Platform and cloud providers have started to deliver tailored AI solutions for specific use cases. Amazon and Google offer vertical integration through Connect and Contact Center AI, respectively. Both enable bot-driven conversations, intelligent routing, and automated assistance. These are features marketing teams can leverage to improve customer experience during support.
5. Increased demand for responsible AI
As AI becomes more prevalent there will be greater demand for it to be more responsible. There’s still some mistrust in the use of AI due to data privacy issues and data control using facial recognition and access to confidential information. Marketers must balance the use of data to personalise services with ensuring it is used ethically. Responsible AI in marketing means businesses must commit to using sensitive data only when necessary and beneficial to their customers.
The future is now for AI marketing
Marketers need to quickly adapt to and adopt AI technology solutions to better understand their customers’ behaviour and preferences, improve customer experience, enhance operational efficiencies, drive conversions, and generate revenue.
This will be a challenge that both rewards and inspires. Not only does AI allow marketers to do things better and get better results, it frees them up to do what humans do best - create, harness opportunities, and provide enduring value.
References:
1 Influencer Marketing Hub
