Key takeaways
- AI marketing uses tools such as machine learning, NLP and LLMs to optimise campaigns, personalise messages and analyse data for better marketing results.
- AI improves marketing through automation, personalisation, social listening and campaign optimisation, raising efficiency and customer engagement.
- AI supports content creation at scale, enables data-driven decisions, makes campaigns more efficient and keeps customers engaged 24/7 through chatbots.
- AI marketing has to deal with data privacy issues, limited emotional intelligence, possible bias or inaccuracy and less creativity than human marketers.
- Doing AI marketing well means setting goals, auditing your assets, choosing the right AI tools, building a strategy and continuously monitoring and adjusting campaigns.
AI is changing marketing in ways that are hard to ignore, from automating repetitive tasks and generating content to collecting and analysing data and insights about consumers. When it comes to editorial production, though, the measured results are a different story: we collected them in our analysis of AI content and SEO.
Combining AI and marketing also leads to more targeted and effective digital marketing campaigns that deliver the results companies want. AI is expected to contribute at least $16 trillion to the global economy by 2030.
Generative AI tools are widely used in this field and, according to the IBM Institute for Business Value's annual CEO study, more than 70% of top-performing executives attribute their competitive advantage to more advanced generative AI.
Want to bring AI marketing into your strategy to get better results? This guide covers how to do it:
- What is AI marketing?
- How is AI used in marketing?
- Pros and cons of AI marketing
- How to get started with AI marketing
What is AI marketing?
AI in digital marketing means using tools and technologies based on artificial intelligence to tackle the main marketing challenges and improve the odds of a campaign succeeding. AI in marketing relies on specific technologies to improve how brands reach their target audience, such as:
- Natural language processing (NLP): this subfield of AI teaches AI programmes to understand, interpret, generate and respond to human language. Examples of NLP in marketing include voice search optimisation, chatbots, social listening and content generation.
- Large language models (LLMs): LLMs are advanced AI models trained to generate human-sounding responses. Marketers can use LLMs for content creation at scale, hyper-personalised messaging and automated replies to customers.
- Machine learning (ML): ML algorithms analyse huge amounts of data to reveal trends, patterns and insights that are useful for your digital marketing. Marketers use ML for lead scoring, customer segmentation, churn prediction and campaign optimisation.
How is AI used in marketing?
AI can improve several parts of digital marketing, especially those that affect the customer experience and the bottom line. These are the main AI marketing use cases:
1. Automation
One of the main ways AI is used in marketing is to automate repetitive digital marketing tasks, such as A/B testing, content generation, data entry and customer engagement. AI-driven marketing automation aims to simplify workflows and improve operational efficiency.
Marketing automation saves companies time, so they can focus on strategy, creativity and customer engagement. Here are some ways to automate marketing tasks with AI:
- Scheduling: you can use AI tools such as Buffer and Hootsuite to schedule content for your social pages or website. These tools use AI to post at the best times, when your audience is most engaged, and help you stay organised when running several campaigns or platforms.
- Brand consistency: marketers can train generative AI tools such as ChatGPT on a company's tone of voice and guidelines, so they are reflected across all of the company's digital assets.
- Social media management: AI lets marketers automate social media tasks such as content creation, publishing and audience engagement.
- Lead scoring: AI helps to score and qualify leads automatically based on customer information and behaviour, to estimate how likely they are to convert.
2. Personalisation
Marketers use AI to personalise campaigns, which strengthens customer relationships, increases engagement and lifts conversions. Personalisation also helps you get the most out of your marketing spend and a good return on investment.
AI makes personalisation possible by analysing huge amounts of data to find trends, patterns and insights, so that content and campaigns match what the audience cares about. It also includes behavioural analysis and predictive models to recommend products and content to the target audience.
Generative AI tools such as Jasper and Gemini (formerly Bard) can help you generate content, recommendations and user experiences that are highly personalised, reflect your brand's voice and tone and address customers' pain points.
You can use these tools to tailor messages and offers to the needs and preferences of individual customers.
3. Social listening
You probably want to know what people say about your brand. Besides asking people individually for their opinion, the internet now lets you find out what is said online about your brand, your industry and your competitors.
AI speeds up social listening because it can analyse huge amounts of data in real time, in seconds. That means nothing slips through and you have everything that could help you improve your processes and strengthen your reputation online and offline.
Through natural language processing (NLP), AI analyses what is said in posts, comments, reviews, online forums and testimonials. It can also help marketers flag PR risks early, spot trends that matter in the industry and identify problems or opportunities based on competitors' messaging.
4. Campaign optimisation
Campaign optimisation is the process of adjusting marketing strategies in real time to make them more efficient and effective. It involves refining specific digital marketing strategies or campaigns to get the results and performance a company wants.
AI takes the guesswork out of marketing optimisation by analysing customer behaviour, interests, preferences, demographics and purchase history. Marketers can also use AI keyword generators and other AI marketing tools to A/B test different campaign elements, such as copy, headlines, images, formats and CTAs, so they run the best-performing combinations.
With tools such as Meta Advantage+, you can adjust ad campaigns in real time and even reallocate ad spend to the best-performing campaigns, platforms, audiences and creatives. That way you can stretch your budget further and get more value from it.
Pros and cons of AI marketing
As AI becomes a core part of marketing strategies, you need to understand both its benefits and the problems it brings. Below we go through the pros and cons to help marketers make better-informed decisions.
Benefits of AI marketing
By bringing AI into your marketing strategy, you can get the following benefits:
- Content generation at scale: AI tools can produce tailored content and graphics for companies quickly and effectively, with minimal human effort.
- Data-driven decisions: AI tools analyse big data to uncover the trends, patterns and insights that inform marketing strategies.
- More efficient campaigns: marketers use AI to automate repetitive tasks and increase the efficiency and productivity of a team.
- Round-the-clock customer engagement: AI chatbots let companies offer customers support on better terms: 24 hours a day, 7 days a week.
Drawbacks of AI marketing
Although around 50% of companies already use AI in their marketing, 11.5% have not yet adopted it and a further 9.5% do not plan to. These are some of the drawbacks of AI in marketing that are holding some marketers back:
- Data privacy and security issues, because AI handles large amounts of customer and lead data
- A lack of human intuition and emotional intelligence, which leads to replies without empathy or cultural nuance
- Inaccurate or biased information sources, which lead to misleading targeting and messaging
- Limited creativity and intuition, because AI tools work from patterns and trends and lack originality.
How to get started with AI marketing
Bringing AI into your marketing takes several steps if you want it to work properly and deliver results. These are the steps to follow:
- Define your marketing goals: knowing your marketing goals helps you pick the AI tools best suited to reaching them.
- Audit your online assets: check your website and social media accounts to make sure you give your audience accurate and complete information. Feeding AI tools accurate information helps keep bias and hallucinations to a minimum.
- Choose the right AI tools: select AI tools that fit your marketing goals, your company size, your budget and your technical skills.
- Build a plan: draw up a detailed AI marketing strategy, including how you will improve the return on investment (ROI) of your marketing with AI.
- Adjust: AI in marketing is not a set-and-forget project. It needs constant monitoring of performance and results, and changes to the marketing strategy as new AI tools and techniques become available.
You can learn how to apply AI in marketing from companies such as Netflix, Starbucks and Nike, which have already done it successfully. We cover these AI marketing examples in more detail in a separate article.
Change your marketing strategy with AI services
Want to change how you do marketing and gain a competitive advantage? Then it is time to bring AI into your digital marketing strategy. You can do it yourself, but an AI marketing agency can help you move faster and keep your AI marketing strategy up to date.
At Visilay we offer AI-driven SEO services to help you maximise your organic visibility across every search engine and platform. Contact us now to start building a solid marketing strategy with the help of AI.
