Understand your ideal customer with artificial intelligence (AI)

Effective marketing starts with understanding your customers. Artificial intelligence (AI) tools can help you identify who your customers are, what matters most to them, and how they behave, allowing you to personalise your approach and improve performance.

AI platforms can build detailed customer profiles or personas by analysing:

• who they are – including demographics, location, and language preferences
• what they do – such as purchase history, engagement patterns, and risk of leaving (churn)
• what they think – using sentiment analysis to track their opinions, attitudes and interests

Segmenting your audience

Large Language Models (LLMs) are advanced AI tools trained on large amounts of text. They can understand and generate human language and help you group your customers into useful categories — for example, first-time buyers, inactive customers, or high-value clients. Creating these segments allows you to tailor your marketing messages and design campaigns that connect with each group.

Gathering insights

AI can help your business turn data into clear, actionable marketing plans. Different AI tools can identify engagement trends across regions, helping you target your audience more effectively. They can also draw insights from your own online content to support the development of interactive or data-driven plans.

In addition, AI can analyse online search behaviour to show what your audience is looking for, enabling you to tailor your messages and services around their interests and needs.

Artificial intelligence (AI) can help businesses quickly assess new markets and identify growth opportunities. By analysing customer sentiment, search trends, and competitor activity, AI can provide insights to support informed decision-making and maintain a competitive edge.

AI can support your market research efforts by helping you:

• identify emerging opportunities – by analysing search trends and social media conversations
• develop go-to-market strategies – including key messages, timelines, and channel selection
• use your own data more effectively – through custom AI models trained on your brand and business goals

AI tools can analyse online discussions and behavioural patterns to reveal what matters most to your audience. Custom AI models can also assess search engine optimisation (SEO) performance, highlight keyword gaps, and suggest areas for improvement - see search engine optimisation: adapting to AI search.

Use prompt engineering to improve outcomes

Prompt engineering involves writing clear and specific instructions to guide an AI tool in producing useful and relevant results. 

For example:

• Basic prompt: “Tell me about marketing.”
• Engineered prompt: “Summarise key digital marketing strategies for small businesses in the UK, including examples of successful campaigns in the hospitality sector.”

The second prompt example provides the tool with more context and direction, resulting in a more tailored and actionable response. 

AI tools can also apply strategic frameworks, such as Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis, to support business decision-making. 

For example, a well-structured prompt like: “Conduct a SWOT analysis for a local coffee shop planning to expand into online sales” might generate insights such as:

• Strengths: established local brand, loyal customer base, high-quality coffee.
• Weaknesses: limited online presence, lack of digital marketing experience.
• Opportunities: rising demand for speciality coffee subscriptions, potential for social media engagement.
• Threats: competition from large e-commerce platforms, delivery logistics challenges.

Artificial Intelligence (AI) helps businesses scale their marketing by automating content creation and campaign delivery. These tools streamline workflows, improve efficiency, and ensure consistent messaging across platforms.

AI can support the development of marketing content by helping to answer three key questions:

1. Who is the advertisement for?
2. What do your customers care about?
3. What is the main message you want to share?

Using these inputs, AI can generate detailed buyer personas, identify customer needs or challenges, and create engaging, tailored messages for each platform.

Repurposing existing content

AI technologies are increasingly used to transform existing content into new, engaging formats. For example, written materials such as blogs and PDFs can be automatically adapted into short videos, interactive carousels, or other visual content. This helps businesses reach audiences across different channels more effectively.

These tools also create high-quality visuals and simulate user-generated content, allowing businesses to maintain a consistent brand presence without relying on extensive design resources.

Advanced automated video creation

Modern AI platforms can now produce video content with realistic visuals and dynamic storytelling. These tools enable businesses to create engaging videos at scale without the need for a large production team. By automating key tasks such as scene generation, voiceover, and editing, AI helps teams produce professional-quality videos quickly and cost-effectively.

Ethical considerations

When using AI-generated content, it is important to be open about how AI has been used. If your content replicates or represents real people, make sure you have the right permissions in place. Using AI responsibly helps maintain your brand’s credibility and builds trust with your audience.

Artificial intelligence (AI) is changing how businesses measure and report on marketing performance. It can analyse large amounts of data — both structured and unstructured — to deliver real-time insights and useful recommendations.

Marketing data types usually falls into two categories:

• structured data – organised information such as spreadsheets, databases, and analytics dashboards
• unstructured data – less organised information such as emails, documents, customer reviews, and social media posts

AI is effective at interpreting unstructured data due to its training in natural language processing.

How to apply generative business intelligence to marketing analytics

Generative business intelligence (Gen BI) uses AI to automate and improve traditional data analysis. It turns raw data into clear, actionable insights through simple conversations.

Unlike static dashboards, Gen BI lets you ask questions in plain English. For example:

• "Which social posts performed best last month?"
• "Why did email open rates drop?"

The AI then creates reports, charts, and recommendations automatically. This makes data analysis easier for everyone, even those without technical skills.

Gen BI can also create new content — such as predictions about future trends or clear summaries — to explain what your data really means.

In marketing analytics, Gen BI can:

• Combine data from advertising and social platforms for a complete view of campaign performance.
• Use your company documents for more accurate, relevant answers.
• Identify which images, videos, or messages drive the most attention or sales.
• Get suggestions to improve your next campaigns.