It’s the same for most marketers and I would say every LinkedIn user. For all the hype around AI technology, machine learning and AI-generated content, the LinkedIn posts that really connect are the ones showing a real person doing real people things: meeting, learning, talking.

Events aren’t separate from social media marketing anymore. They are social media marketing. Every talk, handshake, or quick selfie becomes social media content that can be shared across different platforms — a LinkedIn feed, an Instagram Reel, or a story on another social media channel. For small and medium businesses, events now act as ready-made content engines, producing brand content that supports brand awareness, feeds your social strategy, and helps maintain a consistent presence across social media platforms.

Events as a source of digital authenticity

There’s real power in showing up. Being physically present somewhere adds depth and credibility — something AI-generated images or automated posts can’t replicate. A photo of your team at a booth, or a short clip from a live demo, says more about your brand than the most polished ad campaign.

On social, authenticity wins. A behind-the-scenes photo or spontaneous video often outperforms a planned social media post or a templated content creation graphic. It’s real, unscripted and human, which is exactly what the algorithms reward. And for smaller brands, it’s a cost-effective way to show expertise, confidence and connection without a big production budget.

How events extend into digital life

The smartest marketing teams treat every event as part of their content strategy. What happens in a conference hall travels online within minutes and the best results come when it’s planned that way.

Before the event, your social media management tools (like Sprout Social) can help build anticipation: announcements, hashtags, speaker line-ups and invitations all signal activity and relevance.

During the event, content spreads fast. Attendees share photos, quotes, short videos and relevant posts that expand reach far beyond the room. Tagging other speakers or using event hashtags helps create a virtuous loop of engagement that builds visibility across social media channels.

After the event, the real opportunity begins. Every image, quote or demo becomes fuel for weeks of content generation. Recap blogs, video content, social posts and even snippets can deliver a solid content calendar for your Instagram account or YouTube channel. Events don’t have to end when the lights go out; they continue through your content creator’s workflow and across your platforms.

For tools to help you plan and deliver your event socials, contact us now.

Making events work for your online brand

Keeping up with social media content creation can be tiring. Planning shoots, writing captions and keeping your brand voice consistent all take time. Events solve part of that problem because they give you authentic material to use long after the day ends.

Capture content deliberately: team photos, audience reactions, short interviews and quick clips of demos. Afterwards, use AI models and generative AI tools to help sort, caption and schedule that generated content. With tools like Sprout Social, you can automate your posting calendar, analyse performance and extract actionable insights on what connects best with your target audience.

Those same clips and photos can become testimonials, influencer marketing collaborations, or mini case studies. They add proof, personality and consistency, which are all elements that make for strong social media marketing without the need for constant new shoots.

The new marketing loop: IRL, digital, repeat

Physical and digital marketing now reinforce each other. The event gives your brand something real to show. The social media posts keep the conversation going long after the event is over. That digital visibility leads to new invitations, partnerships and even influencer marketing opportunities.

It’s a virtuous loop. Each event gives your marketing strategy more to share, and each share strengthens your customer experience and credibility. One real-world action can deliver weeks of online visibility and measurable engagement across your chosen platforms.

Bottom line: The most human content wins over the algorithms

Yes, events have survived despite AI and algorithms. They came back in force after the pandemic. But more than that, they’ve become more valuable because of our digital life. As automated content creation grows, audiences value what feels authentic. A live clip from a talk or a team photo captures that human energy and keeps your brand grounded.

Algorithms reward authenticity, and nothing feels more genuine than real people, in real places, doing real work. As influencer marketing reports keep showing, the brands that perform best online are those that balance smart tools with human presence.

If your marketing strategy is built on data, give it something human to work with.

The post If the future of marketing is AI, why is your LinkedIn feed full of event selfies? appeared first on Albatrosa.

The reality of digital marketing in an AI-driven world

Artificial Intelligence (AI) agents have become key players in how content is curated and delivered. Search engines, social media platforms and e-commerce sites increasingly rely on AI systems to analyse user behaviour and make real-time decisions about what content to show. Marketers must consider how AI systems interpret, rank and recommend content. These AI agents act as intermediaries, deciding which brands gain visibility and which remain hidden. From search algorithms prioritising SEO-friendly content to recommendation engines suggesting products, AI has a hand in nearly every interaction consumers have with brands online.

This shift has created a hybrid audience consisting of both humans and AI systems. Brands need to engage human users while ensuring their content creation needs to take AI into account. Ignoring AI means missing out on opportunities for visibility while focusing only on AI can result in disengaged human audiences.

AI or algorithm, what’s the difference for a marketer?

For marketing professionals, the terms “Algorithm” and “AI” are often used interchangeably, but they refer to different concepts with unique impacts on marketing strategies.

Algorithms are rule-based systems designed to process data and make decisions based on predefined criteria. Search engines, for example, use algorithms to rank web pages based on relevance and quality. These systems follow fixed rules to filter and present content.

AI (Artificial Intelligence), on the other hand, refers to systems that learn and adapt over time. An AI model analyses large amounts of data to recognise patterns and improve decision-making without explicit programming. AI can personalise recommendations, predict customer behaviour and automate content delivery.

For marketers, this difference matters because AI systems can evolve and adjust how they interpret and prioritise content. This means strategies must be flexible and responsive to changes in how AI agents operate. While algorithms follow strict rules, AI can make more complex decisions, like predicting which content will engage specific audiences. Marketers need to understand both systems to create content that performs well across platforms. Optimising for traditional algorithms focuses on SEO and keyword use, while engaging AI requires adaptive content that reflects user preferences and behaviours.

How do the roles of AI and algorithms differ at each step of the marketing funnel?

AI and algorithms work together to influence every stage of the marketing funnel. Understanding how they operate allows marketers to tailor their strategies for maximum impact.

Awareness:

• Algorithms: Search engines and social media marketing platforms use algorithms to rank and display content based on relevance, quality and user engagement. This determines which brands new audiences discover.
• AI: AI analyses user behaviour to predict interests and personalise content delivery. AI-driven systems recommend trending topics and tailor search results, increasing the chances of content discovery.

Consideration:

• Algorithms: Algorithms filter and prioritise product listings, articles and service offerings based on user searches and engagement patterns.
• AI: AI recommendation engines suggest products or services aligned with user behaviour, improving relevance and guiding potential customers toward solutions.

Conversion:

• Algorithms: Algorithms manage programmatic advertising, deciding in real time which ads to display to users most likely to convert.
• AI: AI personalises ads and marketing messages based on detailed customer profiles, increasing the likelihood of conversions through targeted content.

Retention:

• Algorithms: Algorithms handle audience segmentation for email marketing, ensuring relevant content is sent to the right user groups.
• AI: AI continuously learns from user interactions to deliver personalised content and product recommendations, encouraging repeat engagement and loyalty.

Use Case: how to tailor your marketing for each of AI and algorithms in the consideration stage

Consider a small business selling fashion products online. In the consideration stage, potential customers are comparing brands and exploring products. Tailoring marketing strategies for both AI and algorithms during this stage is essential to stand out.

Optimising for Algorithms:

• SEO-friendly product descriptions: Use relevant keywords in product titles and descriptions to help search engine algorithms rank products higher. For example, instead of “Stylish Dress,” use “Summer Floral Midi Dress for Casual Outings.”
• Structured product data: Implement schema markup to provide search engines with detailed product information, such as size, colour and availability. This makes it easier for algorithms to index and display products accurately.
• High-quality visuals: Upload clear, optimised images with descriptive alt text. Search algorithms favour visually engaging and well-labelled content.

Appealing to AI Systems:

• Personalised product recommendations: Use AI tools to analyse customer browsing behaviour and suggest similar or complementary fashion items. If a customer views a summer dress, AI could recommend matching accessories or sandals.
• Dynamic pricing strategies: AI can adjust pricing based on demand, competition and customer behaviour, encouraging purchases during peak interest times.
• Chatbots for engagement: Implement AI-powered chatbots to provide instant responses to product queries, guiding customers towards making a purchase.

Balancing human connection with AI and algorithms

While optimising for AI and algorithms is vital, content marketers must ensure their marketing campaigns still feels human and relatable. For a small fashion business, blending technology with authenticity can create a more engaging experience.

Use authentic storytelling: Share the story behind products, including design inspiration or sustainable practices. This creates an emotional connection that resonates with human audiences while providing rich context for AI systems.

Showcase user-generated content: Feature customer reviews, photos and testimonials. Authentic feedback not only builds trust but also signals quality and engagement to algorithms.

Use real human faces and voices: Incorporate real people in product photos and videos, and use human narration in promotional videos. This builds authenticity and emotional connection while making content marketing more engaging for both audiences.

Maintain a conversational tone: Write product descriptions and marketing copy in a natural, relatable tone. Avoid overly technical language, ensuring content is accessible and engaging.

Include interactive elements: Use polls, quizzes or style guides to invite customer interaction. This boosts engagement, which algorithms recognise and reward.

Balance keywords with meaningful content: Incorporate relevant keywords naturally into content without compromising readability. Well-structured content appeals to algorithms while remaining enjoyable for readers.

Why ignoring AI or algorithms in marketing is a risk

Some companies still request “no AI” in their marketing, often due to concerns about losing authenticity or appearing too robotic. However, this reluctance overlooks how deeply embedded AI and algorithms already are in content production. 

Awareness:

• Without SEO optimisation and algorithm-friendly content, brands may fail to appear in search engine results or social media feeds. For example, for the small fashion retailer example above, not using relevant structured data or trending keywords could cause being overshadowed by competitors who do.

Consideration:

• Ignoring AI-powered recommendation systems means missing out on personalised product suggestions. A fashion brand not using AI to analyse browsing behaviour may lose potential customers to brands offering tailored product recommendations.

Conversion:

• Without programmatic advertising powered by AI, brands can’t efficiently target users ready to purchase. For instance, failing to use AI-driven ads could result in missed sales opportunities during peak shopping seasons.

Retention:

• Neglecting AI tools for personalised email campaigns can reduce customer retention. A fashion business that sends generic emails instead of targeted messages may struggle to keep customers engaged.

Understanding your new dual audience

AI agents and human consumers both influence content visibility and engagement, but they respond to different strategies.  

AI Agents:

AI scans, indexes and prioritises content using complex algorithms. They evaluate content based on relevance, structure and quality to decide what to show users. Understanding how these systems work is critical for achieving visibility.

• SEO optimisation: Incorporate relevant keywords naturally into content to help AI recognise context and relevance.
• Structured content: Use clear headings, bullet points and concise paragraphs to make content easier for AI to analyse.
• Metadata and schema markup: Provide detailed metadata and structured data to help search engines understand and categorise content effectively.
• Consistency and freshness: Regularly update content to stay relevant, as AI prioritises fresh, consistent material.

Humans:

While AI drives visibility, the human element drives engagement and conversions. Content must resonate with people emotionally and intellectually to build trust and encourage action.

• Engaging and relatable content: Share stories, real-life examples and relatable scenarios to make content meaningful and human.
• Authenticity: Use genuine language and avoid overly promotional tones. Customers value brands that communicate honestly.
• Visual appeal: High-quality images, videos and graphics make content more engaging and help convey messages effectively.
• Interactive elements: Polls, quizzes and interactive tools invite participation and build stronger connections.

Balancing authenticity with optimisation:

To succeed, marketers must balance AI optimisation with human engagement. This involves:

• Creating well-structured, SEO-optimised content that appeals to AI algorithms.
• Ensuring content is authentic, engaging and emotionally resonant for human audiences.
• Starting with human generated content and then optimising it for AI. For example, working with a human writer who is familiar with editing ai generated content or training AI tools
• Using real human voices, faces and stories to build trust while remaining technically optimised. For example working with a human content creator would be more effective than only using an AI content generator, no matter how good it is. You can often mix both.  

Defining genuine and authentic content

High quality content reflects a brand’s true identity, values and purpose. It avoids exaggeration and overly promotional messaging, instead focusing on transparency, honesty and relatability. This type of content generation is done with the audience’s needs in mind and builds trust by being sincere and consistent.

Key characteristics of authentic content include:

• Transparency: Sharing the brand’s values, sourcing, and decision-making processes openly.
• Consistency: Maintaining a uniform tone, voice and messaging across all channels.
• Relatability: Speaking in a natural tone that connects with the audience’s experiences.
• Storytelling: Highlighting real stories about products, customers or brand milestones.

Key strategies for winning in AI marketing

To stay ahead in an AI-driven marketing landscape, businesses must adopt strategies that balance technology with human connection. Here are key approaches to succeed:

Understand the AI agents shaping your industry:

• Identify which AI systems and algorithms impact your industry—search engines, social media algorithms or recommendation engines.
• Research how these systems rank and prioritise content so you can align your marketing efforts with their criteria.

Design content that AI can easily interpret, and humans find engaging:

• Use structured content formats, clear headings and concise language to help AI systems process your content.
• Use generative AI as your first step in content production, this will help create SEO optimised content that is ready to be improved through human written content (see next bullet point). 
• Pair this with human input, authentic storytelling, visuals and relatable messaging that connect with audiences.

For more on how to leverage AI content writing tools while retaining oversight as a human marketer, see our blog here. 

Invest in AI-driven analytics to refine your strategy:

• Leverage AI content marketing tools to analyse customer data, track engagement and identify trends.
• Use these insights to adjust content strategies, apply human creativity, optimise campaigns and improve targeting for better results.

Stay updated on developments in AI and adapt quickly

• Follow industry news, attend webinars and engage with thought leaders to stay informed about AI advancements.
• Be flexible and adapt marketing strategies as AI technologies evolve, ensuring your content remains relevant and competitive.
• Trial new tools and assess how well they work for you. There’s a constant stream of new marketing platforms being released on the market and finding the right one will set you up for both the short and long terms. 

If you’d like to know more about how AI is impacting search marketing, here’s a good read by the Content Marketing Institute.

The post Should you create marketing content for AI or for humans? appeared first on Albatrosa.

This article explores how integrating the latest AI marketing tools can help small businesses work smarter. We’ll introduce a mix of tried-and-tested platforms like HubSpot and emerging players like Jasper, each designed to streamline specific areas of marketing. The right AI tool can help you maximise your budget, create impactful content, and reach the people who matter most to your business.

How can AI save time for small business marketing?

AI automation can handle repetitive tasks, letting you focus on more impactful areas of your business. From social media scheduling to customer service chatbots, AI helps streamline workflows. For example, tools like Jasper and ChatGPT assist with content creation, allowing small teams to produce quality marketing materials quickly and consistently deliver a better customer experience. 

Can AI help me spend my budget wisely?

With AI-powered analytics, small businesses can get smarter about where they invest their marketing dollars. Tools like Google Analytics and Funnelytics provide insights into which campaigns bring the best results or drive the highest customer satisfaction, helping you direct resources to the channels that perform. By understanding what’s working and what isn’t, you can make informed decisions that maximise your budget.

How can I reach the right audience?

AI makes it easier to target specific audiences with personalised content. Tools like HubSpot and Acquisio analyse customer data to segment your audience based on behaviours, preferences, and buying patterns. This data-driven approach allows you to create tailored advertising programmes or email marketing campaigns that speak directly to the people most likely to engage with your brand, increasing your chances of conversion. By using the right AI solution, you can also increase customer interaction, making it easier to connect with your audience.  

Will AI help with planning content?

A successful marketing strategy begins with a well-researched content plan, and AI tools can make this process much simpler. By using data-driven insights, these tools help you identify trends, understand audience interests, and choose topics that will engage readers.

• AnswerThePublic: This tool uses search data to reveal common questions and topics within your industry. the AI algorithms help you generate content ideas that directly address what your audience wants to know. It’s a great place to start when planning a new marketing campaign. 
• BuzzSumo: BuzzSumo uses AI to analyse trending content across the web, showing you which topics are currently resonating in your field. With this insight, you can create a content plan that taps into popular trends.
• Google Trends: Although not exclusively an AI tool, Google Trends provides a clear view of what people are searching for over time. It helps ensure your content covers timely topics that are actively being discussed.
• Moz: Moz offers keyword research and SEO analysis to identify high-impact content opportunities. With its Keyword Explorer and other features, Moz provides insights into keyword difficulty and search volume, helping you plan content marketing that aligns with search demand.
• Ahrefs: This AI powered marketing tool helps businesses create targeted content strategies by analysing market trends and audience behaviour. It’s especially useful for understanding the larger content landscape and finding gaps where your content can stand out.

How can AI support content creation?

Creating high-quality content on a consistent basis can be challenging, but AI tools simplify this task by generating ideas, drafting text, and even creating visuals.

• ChatGPT: Often regarded as the ‘Big Daddy’ of generative AI, ChatGPT is a versatile tool for creating various types of written content. Whether it’s social media posts, blog outlines, or email drafts, ChatGPT helps small businesses produce content quickly and with ease. Read our guide about how to use ChatGPT in marketing.
• Jasper: Jasper is ideal for marketers looking to produce marketing copy such as articles, product descriptions, and social media posts without sacrificing quality. Its AI capabilities assist in maintaining a consistent tone and style, helping you keep your brand voice on point.
• Canva’s Magic Write: Canva’s Magic Write tool generates AI-powered text to accompany visuals, making it perfect for creating social media posts or promotional graphics. Combined with Canva’s design templates, it enables businesses to produce visually appealing content without design expertise.

How can AI help optimise content?

Once you’ve created your content, optimisation tools help improve it for readability, search engine performance, and audience engagement.

• Grammarly: Grammarly uses AI to check for grammar, tone, and readability, ensuring your content appears professional and polished. It also provides SEO-friendly suggestions that can help improve your content’s search ranking.
• MarketMuse: MarketMuse analyses content to identify keyword gaps and content weaknesses. It suggests ways to improve your articles’ SEO, making them more comprehensive and relevant for search engines.
• Frase: Frase is designed to help you optimise content for SEO by analysing competitor pages and highlighting areas to improve. With keyword suggestions and topic recommendations, Frase ensures your content aligns with what people are searching for.
• Yoast SEO: Perfect for WordPress users, Yoast SEO offers real-time optimisation tips that improve readability, keyword usage, and other SEO factors. It’s an essential tool for making your content search friendly.

Can AI help in measuring results?

Understanding how your content is performing is key to improving your marketing efforts. AI tools can track important metrics, giving you a clear picture of what’s working and where you might need to adjust.

• Google Analytics: Google Analytics tracks website traffic, engagement, and conversions, offering a detailed view of your digital presence. Its AI-powered insights can even predict trends, helping you make informed marketing decisions.
• HubSpot: For businesses that use multiple channels, HubSpot offers an integrated view of customer interactions across email, social media, and website visits. It provides insights into customer behaviour, showing which campaigns are most effective.
• Funnelytics: Funnelytics maps out customer journeys, showing you where users drop off or convert. It provides a visual representation of your funnel, making it easy to identify successful touchpoints and areas that might need improvement.
• SEMRush: SEMRush is an all-in-one tool for tracking SEO performance, competitor analysis, and advertising data. With insights into keywords, backlinks, and more, it helps you refine your strategy to drive results.

How can AI make reporting easier?

Creating clear, insightful reports is essential for reviewing performance and guiding future campaigns. AI-driven reporting tools make it easy to compile data into visual formats, highlight key metrics, and even offer predictions based on trends.

• Google Data Studio: Google Data Studio pulls data from multiple sources, including Google Analytics, to create custom reports that are easy to read and share. It’s a great tool for tailoring data presentations to different stakeholders.
• DashThis: DashThis consolidates data from various platforms, creating unified reports with interactive visuals. It’s ideal for marketers who need to present data from multiple sources in a single report, simplifying analysis and sharing.
• Power BI: Power BI offers advanced data visualisation and reporting features, transforming raw data into actionable insights. Its AI capabilities help identify trends and predict outcomes, making it a valuable tool for data-driven decision-making.

What budget should I allocate for AI tools?

Budgeting for AI marketing tools doesn’t have to be intimidating, and many tools offer flexible pricing models to suit different business sizes and needs. From free trials to scalable subscriptions, there are options to help you find a balance between cost and value.

• Free and freemium options: Many AI tools, such as Google Analytics, offer free versions that provide essential features without the need to invest immediately. Tools like Canva and AnswerThePublic also have free plans that allow you to explore basic functionality before upgrading to a paid plan. These can be a good starting point for small businesses looking to experiment with AI without committing funds or overspending on digital marketing.
• Subscription-based tools: For tools that add more robust AI-driven capabilities, expect to budget between £10-£100 per month. Tools like Grammarly and Frase offer plans in this range, providing advanced features like SEO optimisation and detailed content suggestions. Many of these tools also offer monthly and annual pricing, allowing you to evaluate the impact before making a commitment.
• Enterprise-level AI solutions: If you’re looking to integrate more comprehensive AI functionality, such as predictive analytics or full-service customer relationship management (CRM) platforms, the costs may be higher, often starting at £100+ per month. Tools like HubSpot and SEMRush fall into this category and are ideal for small businesses with growing marketing needs. They often include a range of features from automated reporting to personalised campaign recommendations.

To find the right fit, start by identifying the areas where AI can add the most value to your business. Taking advantage of free trials will help you see real results without stretching your budget.

Is implementing AI the missing piece in your marketing strategy?

Embracing AI doesn’t mean overhauling your entire marketing strategy. The key is in how you use AI. We suggest adding tools that enhance what you’re already doing, helping you work efficiently and connect better with your audience. From planning content to measuring results, AI offers small business owners a way to stay competitive without requiring vast resources. They can also help you improve and automate customer support, enabling you to retain more clients. 

Starting small, testing tools, and focusing on the areas where AI can make the biggest impact will help you see real benefits. With so many affordable and accessible options, AI is no longer just for large corporations. It’s an opportunity for every business, regardless of size, to make data-driven decisions, save time, and reach customers more effectively.

Now’s the time to find the best AI tool or suite of tools that can support your goals, get more results from your marketing effort, and give your small business the edge it needs in a crowded market.

The post AI Marketing for Small Businesses appeared first on Albatrosa.

At Albatrosa, we follow the school of thought that says that AI will not replace marketers, but rather act as a tool to make them work faster and smarter. In this blog, we’ll explore how ChatGPT can help you develop write or create engaging content as well as develop a targeted and realistic marketing strategy. 

Table of Contents

Before we start, let’s understand what versions of ChatGPT are available, particularly if you are strapped for budget, and what are the essentials you need to know about ChatGPT:

What is the difference between the free and the paid versions of ChatGPT  for marketing success?

You can use ChatGPT for free, or pay $20 monthly for additional features, here’s a comparison between the two:

Free version of ChatGPT

• Model Access: The free version grants access to GPT-3.5, which can handle basic marketing tasks like content creation, brainstorming, and drafting simple marketing ad copy. While effective, it has limitations in terms of creativity and complexity.
• Performance: Users of the free version might experience slower response times during peak hours, making it less ideal for teams needing to generate large amounts of content quickly.
• Usage Limits: There are daily or hourly limits on usage, which could slow down progress on larger marketing campaigns.
• Explore GPTs: The free version provides limited access to the “Explore GPTs” feature, where users can browse and interact with specialised GPT models. However, these models tend to be based on GPT-3.5, limiting their capabilities for advanced or niche marketing tasks.

Paid version (ChatGPT Plus)

• Model Access: The paid version, available for $20 per month, provides access to GPT-4, which is more powerful and nuanced. This results in better performance for complex marketing tasks, such as personalised email campaigns or SEO optimisation.
• Performance: Faster response times and higher reliability during peak hours make this version more suitable for businesses working with strict deadlines.
• Explore GPTs: In the paid version, users can explore GPT models built on GPT-4, which offer more advanced and fine-tuned capabilities for specialised marketing tasks. This version allows users to access more sophisticated GPTs, including custom-built models for specific industries and functions, making it highly useful for a strategic marketing campaign or if you’re looking to implement marketing automation to improve customer service.

What are GPT effective prompts and how important are they for marketers?

A GPT prompt is the text or query you input into an AI model like ChatGPT to generate a desired response. GPT prompts are inputs that help the AI understand what you’re trying to achieve and guide it to provide more specific, relevant responses. The output will vary greatly depending on how detailed and clear your prompt is. It can be as simple as asking a question or as complex as outlining specific instructions. 

How to structure your AI prompt

The quality and specificity of the prompt directly affect the output. A well-structured prompt provides clearer, more relevant responses, which saves time and ensures the content aligns with the marketer’s goals. Poorly worded or vague prompts, on the other hand, can result in less useful outputs, requiring further refinement or manual editing.

For example, a prompt like “Write a blog about email marketing” will generate a broad response, while “Write a 300-word blog post on how to use email segmentation to increase open rates for small businesses” will yield a more targeted, useful result for marketers.

Examples of marketing-specific prompts

• “Generate 5 social media post ideas for a product launch targeting Gen Z. The product does XYZ and removes the pain of having to XYZ”
• Create 5 different pieces of advertising marketing copy for a product launch targeting Gen Z. The product is the first of its kind in the market and helps them to do XYZ”
• “Create an email template for a customer retention campaign offering 10% off for returning customers.”
• “Summarise the top three SEO trends in 2024 that small businesses should focus on.”

How to easily train ChatGPT to help your content marketers

Although “training the AI” might sound intimidating to marketers, it’s much simpler than it sounds. Essentially, it just means entering specific prompts that guide ChatGPT to understand and remember everything you want it to know about your company and optimise your marketing activities. This includes details like your business goals, brand guidelines, tone of voice, product description, and target audience. The great news is that you only must do this once per account. ChatGPT is rolling out a “memory” feature that allows it to remember instructions and follow them for all future work. 

Here’s how to structure prompts to train ChatGPT effectively

Define your brand voice: 

When starting a conversation, give ChatGPT context about your company’s tone. For example, “We are a luxury brand, so our tone should be professional, refined, and premium.”

Be clear about your audience:   

Specify who the content is aimed at. For example, “Our target audience is environmentally conscious millennials interested in sustainable products.”

Mention your industry and products: 

Provide details of your industry or product line to ensure ChatGPT generates relevant outputs. Example: “We are in the tech industry, specialising in wearable fitness devices.”

Provide examples: 

Use past examples of marketing materials, social media marketing posts, or a good email campaign to guide ChatGPT. Example: “Here’s an email template we use for product launches. Can you create something similar but for a seasonal sale?”

How to get ChatGPT to avoid using specific words, expressions, or styles in your content.

We’ve all spotted some content that was clearly AI-created with little to no human oversight. From token turns of phrase to an overload of emojis in social media content, these particular pieces of content are easy to spot and discount as bot-created jargon. We do therefore recommend that, in your instructions to ChatGPT, you include information about what you would like it not to do. For example, you can start by explicitly listing the words or phrases you don’t want included, such as: “When writing this content, please avoid using words like ‘cutting-edge,’ ‘innovative,’ or ‘leading’”.  You can also define the tone or style you’d like ChatGPT to steer clear of by specifying: “Please maintain a professional tone and avoid casual expressions like ‘awesome’ or ‘cool.'”

How to use ChatGPT’s memory feature

ChatGPT’s new memory feature takes this process one step further by allowing the AI to remember key details about your company between sessions. This feature is currently being rolled out, and when activated, it can remember specific information, such as your brand guidelines, target audience, and tone of voice. The memory feature ensures that your ongoing interactions with ChatGPT become more consistent and personalised to your company’s specific needs, saving time and improving the quality of generated content.

Here’s how to use the memory feature in ChatGPT

• Activate Memory: In your ChatGPT settings, enable the memory feature. This allows ChatGPT to retain information between interactions, which means you don’t have to repeat details about your brand in every session.
• Feed It Information: When you give ChatGPT instructions, make sure to say something like, “Remember that our brand is a playful, family-friendly retail company,” or, “Our target audience is tech-savvy entrepreneurs.” Once it’s remembered, ChatGPT will tailor future responses accordingly.
• Update and Refine: If your tone or guidelines change, simply tell ChatGPT to update its memory: “Our tone is now more formal and professional,” or “We’re targeting a new audience—young professionals interested in personal finance.”
• This feature can be particulary effective when you want to leverage ChatGPT to take customer feedback into account. For example, you can use search history to keep improving your AI chatbot, ensuring it has answers to the most common enquiries or questions that people ask in your customer support centre. 

How to best use ChatGPT to write your content- blog example

While you can certainly generate an entire piece of content with a single prompt, it’s often more effective to write it one section at a time. This allows you to carefully review and refine each part, ensuring that your content flows well and covers your key points thoroughly. It can also help you to ensure any keyword research, or industry slang that you want to use are properly integrated. By taking it step by step, you’ll also have the opportunity to think more deeply about each segment and address any questions or additional angles that come to mind during the process.

When you create content one section at a time, ChatGPT often provides a brief recap at the end of each section. We recommend simply deleting these recaps, as they can disrupt the flow of your final piece.

How to prompt ChatGPT to write the introduction of your blog

Example ChatGPT prompt to write an introduction

If you want to write a blog about using AI in Marketing, here’s a good prompt to give the AI: “Write a compelling introduction for a blog post on how AI is transforming marketing. The introduction should explain how AI tools are becoming more common in marketing, mention the benefits such as automation, data analysis, and personalisation, and briefly hint at the use of tools like ChatGPT. The tone should be informative and engaging, aimed at marketing professionals who are new to using AI in their strategies.”

This prompt ensures that ChatGPT knows to cover the right key points (AI’s rise, benefits, and the introduction of tools like ChatGPT) and guides the tone and audience focus. You can then use this intro as the foundation for the rest of your blog. In this prompt you can also 

Steps to get ChatGPT to write the next sections of your blog

To write the next section of the blog, follow a structured approach that builds on the introduction. Here’s what you can do:

• Identify the Next Section: Think about the logical flow of your blog. After introducing AI in marketing, a good next section might be “The Key Benefits of AI in Marketing”, or “How AI is Changing Marketing Today.” This helps break down the topic into digestible segments for the reader.
• Craft a Clear Prompt: Give ChatGPT a specific prompt to guide its writing. For example, if you want to focus on the benefits of AI in marketing, you could use:

Example to write the next sections of your blog

“Write the next section of a blog post titled ‘The Key Benefits of AI in Marketing.’ This section should discuss the benefits of AI in marketing, such as automation, improved data analysis, personalisation, and how AI helps marketers make better decisions. Include real-world examples of AI tools like chatbots and analytics software that companies are using today.”

What to do once ChatGPT has written those sections

• Review and refine: Once you get the output, review it for accuracy, flow, and tone. If any section needs further detail or clarification, you can create more specific prompts, such as: “Can you expand on how AI helps with personalisation in marketing, including examples of how AI tailors content to different audience segments?”
• Proceed section by section: Use this process to write each subsequent section. By giving clear, step-by-step prompts, you’ll ensure each part of your blog is well-structured and thoroughly covers the topic.

How to get ChatGPT to write the conclusion of your blog

Many people do not include a conclusion in their blogs. But if you would like to leave your readers with a summary of key points while reinforcing the main message of the blog or delivering a call to action, you can ask ChatGPT to create it. You can then review and refine it to align it perfectly with the rest of your blog.

Here’s a step-by-step approach:

1. Recap the blog’s main points: The conclusion should briefly recap the benefits and impact of AI in marketing that were covered in the body of the blog. This ensures the reader walks away with a clear understanding of the key takeaways.
2. Provide a Call to Action or forward-looking statement: Encourage readers to think about how they can incorporate AI into their own marketing strategies or point them toward additional resources to continue learning about the topic.
3. Craft a clear prompt: Give ChatGPT a prompt that reflects these goals. Here’s an example:

Example Prompt for ChatGPt to write your conclusion:

“Write the conclusion for a blog post about using AI in marketing. Summarise the main benefits discussed, such as automation, data analysis, and personalisation. End with a forward-looking statement about the future of AI in marketing and encourage readers to explore how AI tools like ChatGPT can enhance their own marketing strategies.”

How to check your content for an AI overload and paraphrasing.

As you may have guessed, we are not against using AI, we see it as a great tool for productivity, but not one to replace humans. As mentioned above, it’s important not to get too complacent with it and fall into the trap of disingenuity. For all content, we recommend the following tools to check for AI and paraphrasing online:

Word 

• AI Detection Plugin: Microsoft Word offers an AI detection plugin called GPTZero, which can identify AI-generated content directly within the document.
• Integrated Thesaurus: The Lookup feature helps users find synonyms and definitions, which can assist in avoiding inadvertent paraphrasing by providing alternative word choices.
• Contextual Suggestions: It provides contextually relevant suggestions, ensuring that the synonyms fit well within the sentence structure and meaning.

ZeroGPT

• AI Content Detection: ZeroGPT specialises in detecting AI-generated content, highlighting sentences written by AI and providing a gauge showing the percentage of AI content.
• Batch File Uploads: Users can upload multiple files at once for batch processing, making it efficient for checking large volumes of content.

Quillbot

• AI Content Detector: Quillbot’s AI Detector can identify AI-generated text and distinguish between AI-generated and AI-refined content.
• Paraphrasing Tool: It offers a powerful paraphrasing tool that helps rewrite, edit, and reformulate text while preserving the original meaning.
• Detailed Analysis: The tool provides a detailed report, highlighting the likelihood of AI-generated content and offering insights into the text’s originality.

How to build a marketing strategy with ChatGPT

ChatGPT will not replace you as a marketer, but it will help you create your plan much faster and overcome those brain fog or writer’s block moments. As we said above, the better your ChatGPT prompts, the more specific and useful the output will be. Just remember to check everything and edit where needed or ask ChatGPT to redo the work whether you feel the whole plan needs re-writing or certain parts should be fine-tuned. Here’s how we recommend doing it: 

1. Define the type of output you want

First, specify the format you want for your final strategy document:

• Example: “This will be packaged as a PowerPoint presentation with 10 slides, including visuals.”
• Example: “I need a detailed report with sections on audience segmentation, channels, and messaging.”

2. Provide business information

ChatGPT needs to understand your business to craft a strategy that fits:

• Company Overview: Provide details about your business, its mission, values, and long-term goals.

• Example: “We are a sustainable clothing brand focused on eco-conscious consumers.”
• Products or Services: Clearly outline the products or services you offer.
• Example: “We sell eco-friendly sportswear, with products including sustainable running shoes and recycled-material yoga mats.”

3. Define your target audience

To help ChatGPT create tailored messaging and channels:

• Demographics: Age, gender, income level, location, and other key factors.

• Example: “Our audience is primarily women aged 25-40, interested in fitness and sustainability.”
• Psychographics: Interests, values, and lifestyle of your target audience.
• Example: “They are eco-conscious, value high-quality materials, and lead an active lifestyle.”

4. Give the tool your market and competitor analysis

Understanding the market landscape and competition is crucial for strategic planning:

• Industry: Describe the industry and any trends affecting it, using any market research that you have. 
• Example: “The sustainable fashion market is growing as consumers become more environmentally conscious.”
• Competitors: Identify key competitors and their strengths or weaknesses.
• Example: “Our main competitors are Patagonia and Allbirds, both known for sustainable products.”

5. Let ChatGPT know what your marketing objectives are:

Specify your main marketing goals to ensure ChatGPT focuses on the right outcomes:

• Key Objectives: Whether it’s increasing brand awareness, boosting sales, or improving customer retention.
• Example: “Our primary goal is to increase brand awareness in the US market and grow our social media following and achieve digital marketing excellence.”
• KPIs: Define the metrics you’ll use to measure success.
• Example: “Our KPIs include website traffic, conversion rate, and social media engagement.”

6. Feed-in your preferred marketing channels

Let ChatGPT know which platforms or channels you plan to use, as different platforms require different approaches:

• Digital Marketing Channels: Preferred social media platform, email marketing, Search Engine Optimization (SEO) tactics, content marketing, paid advertising.
• Example: “We focus on Instagram, Facebook ads, and email marketing for customer engagement.”
• Offline Channels: If relevant, include traditional media such as print, TV, or in-person events.
• Example: “We participate in eco-friendly fashion events and pop-up stores.”

7. Input your brand tone of voice and messaging

• Provide guidance on how ChatGPT should align the strategy with your brand’s tone of voice:
• Tone: Whether it’s casual, professional, playful, or authoritative.
• Example: “Our tone is approachable, friendly, and informative.”
• Key Messaging: Highlight any core brand messages or unique selling points (USPs) to focus on.
• Example: “We want to emphasise our commitment to sustainability and the use of recycled materials.”

8. Enter your budget

Specify your budget to ensure that the strategy is realistic:

• Marketing Budget: Give a clear idea of your budget to help guide recommendations on paid channels or marketing efforts.
• Example: “We have a $50,000 budget for the next quarter, with $20,000 allocated to social media advertising.”

9. Give ChatGPT a timeline

Outline any deadlines or campaign timeframes:

• Example: “We need the strategy to cover the next six months, focusing on a product launch in December.”

Example prompt:

“Please create a marketing strategy for a sustainable fashion brand that targets eco-conscious consumers aged 25-40. Focus on Instagram, email marketing, and Facebook ads, with a friendly and approachable tone. The strategy should include a competitor analysis of Patagonia and Allbirds, and focus on increasing brand awareness and social media engagement. We have a budget of $50,000 for the next quarter and plan to launch a new product line in December.”

We hope you found this blog helpful. If you’d like to know more about how to use ChatGPT in marketing, contact us now.

The post How to use ChatGPT in marketing appeared first on Albatrosa.

Marketers increasingly rely on Artificial Intelligence (AI) as a reliable tool for generating factual information and crafting data-driven strategies. It is particularly useful in digital marketing, creating content, generating calls to action and recommending keywords and hashtags. However, even AI can become delirious , which seems like something from science fiction. One such flaw is AI hallucination—a phenomenon where AI systems produce information that appears convincing but is, in fact, incorrect or entirely fabricated. 

AI hallucination can occur when AI models, particularly those used in language processing, generate outputs that are not grounded in reality. This may happen due to biased training data, the model’s limitations, or errors in the algorithm’s interpretation of data.

For marketers, the implications of AI hallucination can be significant:

• Misleading content: AI-generated text may contain errors that misinform audiences.
• Brand reputation: Inaccurate information produced by AI can harm a brand’s credibility.
• Customer trust: Reliance on AI-generated content that turns out to be false can lead to a loss of trust among consumers.

While AI offers powerful tools for marketing, understanding and mitigating the risks of AI hallucination is crucial to maintaining accuracy and trust in brand communications.

Understanding AI hallucinations

The term “AI hallucination” refers to a phenomenon where Artificial Intelligence systems, particularly those using advanced language models, generate information that seems plausible but is actually incorrect, misleading, or entirely fabricated. Unlike human errors, where misinformation might result from misunderstanding or lack of knowledge, AI hallucinations occur despite the system’s seemingly vast and accurate database. 

AI models are trained on extensive datasets, absorbing patterns and information to generate responses, recommendations, or content. However, these models don’t truly understand the content they produce; they simply predict what comes next based on the data they’ve processed. When the data is incomplete, biased, or taken out of context, the AI may generate outputs that aren’t grounded in reality. This is what we refer to as hallucination. 

For instance, an AI might produce a confidently written marketing message that cites statistics or facts that don’t exist. While the output might look and sound professional, the information could be entirely fabricated, leading to significant risks if used without proper verification.

Understanding AI hallucination is crucial because it highlights the limitations of AI, reminding marketers that while AI can be a powerful tool, it requires careful oversight and validation to ensure the accuracy and integrity of the information it generates.

How does AI hallucination occur?

AI hallucination occurs when an Artificial Intelligence system generates outputs that are factually incorrect, misleading, or entirely fabricated. This phenomenon stems from a few key factors in how an AI driven large language model is developed and functions. You might also come across something called “Lllm hallucination” which happens when a large language model (LLM) produces a response that is factually inaccurate, illogical, or unrelated to the input prompt.

• Training data limitations: AI models are trained on vast datasets, absorbing patterns and associations from the information they process. However, if the training data is biased, incomplete, or contains errors, the AI can produce outputs that reflect these flaws. When an AI model encounters a situation where it lacks adequate data or context, it may “hallucinate” by generating a response that fills in the gaps, often with fabricated or misleading information.
• Overfitting and generalisation errors: Overfitting occurs when an AI model becomes too closely aligned with its training data, learning to replicate specific patterns rather than understanding broader concepts. This can lead to generalisation errors, where the AI applies incorrect patterns to new, unseen data. In such cases, the AI might produce outputs that are inaccurate or nonsensical, appearing to “hallucinate” as it attempts to apply its over-learned patterns inappropriately.
• Lack of true understanding: Despite their sophistication, AI models don’t understand the content they generate. They function by predicting the next word or phrase based on probabilities derived from their training data. This lack of genuine comprehension can result in outputs that sound plausible but are incorrect. The AI is not discerning truth from falsehood; it’s simply following learned patterns, which can sometimes lead to hallucinations.
• Contextual misinterpretation: AI models may struggle to interpret context accurately, especially in complex or nuanced situations. Without a clear understanding of the surrounding context, the AI might generate responses that are out of sync with reality, further contributing to the phenomenon of hallucination.

How to spot generative AI hallucination

Detecting AI hallucination can be challenging, especially when the outputs seem polished and credible. However, with the right approach and tools, marketers can identify and address these inaccuracies before they cause any harm. Here are some strategies to help spot AI hallucination:

• Cross-check information: One of the simplest ways to detect AI hallucination is to cross-check the AI-generated content against reliable sources. If the AI produces a statistic, fact, or claim, verify it by consulting trusted references. This step is crucial for ensuring that the information is accurate and not a result of hallucination.
• Look for unusual patterns or inconsistencies: AI hallucination often manifests as inconsistencies or patterns that don’t align with the context. For example, if the AI output includes unexpected information or shifts in tone that seem out of place, it may be a sign of hallucination. Pay close attention to any parts of the content that feel off or don’t quite fit with the rest of the message.
• Test the AI on known information: Before relying on AI for critical tasks, test it on subjects where you already know the correct answers. This can help you gauge the AI’s reliability and spot any tendencies towards hallucination. If the AI produces incorrect or misleading content in these tests, it’s a clear indicator that you need to apply more scrutiny to its outputs.
• Use AI tools designed to detect hallucination: Some advanced AI platforms include features that help identify potential hallucinations. These tools can flag content that may be questionable, allowing marketers to review and correct any inaccuracies before publication. Integrating these tools into your workflow can add an extra layer of protection against the risks of AI hallucination.
• Seek human oversight: AI should be seen as an assistant rather than a replacement for human judgement. Having a human review AI-generated content is a key step in spotting incorrect information and hallucinations. A human reviewer can apply context, experience, and critical thinking to identify and correct errors that the AI might miss.

How to prevent AI hallucination

It is essential to maintain the integrity of your marketing efforts to prevent AI hallucinations. While AI can be a powerful tool, it’s important to recognise its limitations and take proactive steps to minimise the potential for inaccuracies. Here are some strategies to help manage the risk of AI hallucination:

• Implement robust verification processes: Before deploying any AI-generated content, establish a rigorous fact-checking routine. This involves cross-referencing AI outputs with reliable sources and ensuring that any data, statistics, or claims are accurate. This step is critical to prevent the spread of misinformation and to maintain the credibility of your marketing materials.

• Select an AI system with built-in safeguards: Not all AI tools are created equal. Some platforms offer features designed to minimise the risk of hallucination, such as content validation tools that flag potentially fabricated information. When choosing an AI tool, consider those that prioritise accuracy and provide mechanisms for detecting and correcting hallucinations.
• Do your research before generating AI content: Before you prompt an AI to generate content, provide it with accurate, well-researched information. Include links or basic facts that the AI can use as a foundation. Make sure that these sources have been checked by humans for accuracy to reduce the chances of the AI producing hallucinations based on faulty data.
• Balance AI use with human oversight: While an AI algorithm can generate content quickly and efficiently, human judgment is still invaluable. Ensure that all AI-generated outputs are reviewed by a human before publication. This oversight allows for the application of context, critical thinking, and domain-specific knowledge, which can help identify and correct any hallucinations that the AI may have produced.
• Educate your team about AI limitations: Your marketing team must understand both the capabilities and the limitations of AI. Provide training on the risks associated with AI hallucination and equip your team with the skills to spot and address these issues. Awareness and education are key to preventing the unintended consequences of relying too heavily on AI.

• Develop clear guidelines for AI use: Establish internal policies that outline how AI should be used in your marketing efforts. These guidelines should specify when human intervention is required, how AI outputs should be verified, and the steps to take if hallucination is detected. Clear guidelines help ensure that AI is used responsibly and that its outputs are always subject to appropriate scrutiny.
• Train your AI: Whereas AI development might be beyond the reach of most marketers, whenever you have a chance, do train your AI to be accurate, focused on your target audience and to get its information from reliable sources. 

Need support to build your AI governance?

Real-world scenarios of AI hallucination in marketing

AI hallucination is not just a theoretical concern; it could manifest in real-world marketing scenarios with significant consequences. These hypothetical scenarios highlight the importance of vigilance and careful management when using AI in marketing.

• The case of the fabricated product description: Imagine a major online retailer using AI to generate product descriptions for its vast catalogue. While the AI efficiently produces thousands of descriptions, it might start fabricating details about certain products. In one scenario, the AI could describe a simple office chair as having “massage functionality” and “ergonomic support,” neither of which are true. This could lead to customer complaints, product returns, and a dip in trust as consumers realise the descriptions are not reliable. The retailer would then need to quickly revise its content generation process to include human oversight and validation.
• False claims in AI-generated advertising: Consider an AI-driven advertising campaign for a new health supplement that goes viral for all the wrong reasons when it is discovered that the AI has generated baseless health claims. The AI, tasked with creating catchy taglines, might invent benefits like “proven to cure chronic fatigue” and “guaranteed to boost your immune system by 200%.” These claims would be entirely unfounded, leading to regulatory scrutiny and potential legal issues for the brand. This scenario would highlight the risks of relying on AI to generate content in highly regulated industries like healthcare.
• Misleading customer service: Picture a global telecom company implementing an AI chatbot to handle customer inquiries. While the bot could be effective in managing routine questions, it might hallucinate when faced with more complex issues, providing customers with incorrect billing information or even making up non-existent service plans. This could lead to customer frustration and a spike in complaints. The company might then have to intervene by retraining the AI model and increasing human oversight in customer support interactions.
• The misinterpreted data analysis: Imagine a large financial services firm using AI to generate insights for its marketing campaigns. The AI, analysing customer data, might incorrectly identify a trend suggesting that younger customers prefer premium, high-cost financial products. Based on this faulty analysis, the firm could launch a targeted campaign that completely misses the mark, resulting in poor engagement and wasted marketing spend. It might later be discovered that the AI overgeneralised a small subset of data, leading to a hallucinated conclusion that doesn’t reflect the broader customer base.

What AI tools are safer to use to avoid AI hallucination? 

When considering the safety of generative AI tools, it’s important to look for platforms that prioritize transparency, accuracy, and ethical use. Here’s a list of generative AI tools that are generally regarded as safer to use, but never forget to put safety practices in place, such as the ones we listed above, to protect your content from errors.  

• OpenAI’s GPT-4
  • Why it’s safe: OpenAI offers is probably the world’s most used and well known generative AI model. While a level of ChatGPT hallucination could be expected, the tool offers extensive safety protocols, including content moderation tools and guidelines to prevent misuse. Users can fine-tune the model for specific applications, which increases the chance of generating accurate information and appropriate content.
• Google Cloud AI Platform
  • Why it’s safe: Google’s AI tools are backed by strong safety measures, including data verification, bias detection, and explainability features. These tools help ensure that generated content is both accurate and aligned with ethical standards, and is very helpful to small businesses and startups.
• Microsoft Co-pilot
  • Why it’s safe: Integrated into Microsoft 365 and enhanced by real-time search capabilities when used via Microsoft’s Edge browser or Bing Chat, Co-pilot generates content with cited sources and direct links, ensuring that information is accurate and verifiable. Microsoft also includes safeguards to prevent the generation of misleading information.
• IBM Watson
  • Why it’s safe: IBM Watson emphasizes transparency and explainability, allowing users to understand how AI models reach their conclusions. Watson also includes tools for monitoring and improving model accuracy, making it a reliable option for generating content with reduced risk of hallucinations.
• Adobe Sensei
  • Why it’s safe: Adobe Sensei is integrated into Adobe’s suite of creative tools and is designed with accuracy and consistency in mind. Adobe’s focus on quality control helps ensure that AI-generated content aligns with user expectations and industry standards.
• Grammarly Business
  • Why it’s safe: Grammarly’s AI-powered tools are designed to assist with grammar, tone, and clarity, with a strong emphasis on correctness and reliability. Grammarly’s focus on linguistic accuracy makes it a safer choice for generating written content.
• Salesforce Einstein
  • Why it’s safe: Salesforce Einstein is tailored for CRM and marketing applications, ensuring that AI-generated insights and content are based on accurate, context-specific data. Salesforce also prioritizes data privacy and provides robust tools for verifying AI outputs.

Conclusion

When used properly, generative AI models can be fantastic tools for marketers, offering unparalleled efficiency, personalisation, and data-driven insights. However, like any tool, the key to success lies in how it’s used. To mitigate AI hallucinations, make sure you implement quality control measures and retain human input to ensure that AI-generated content and strategies are not only compelling but also accurate and trustworthy. 

Want to learn more about AI generated hallucinations: we recommend reading this article: How Can We Counteract Generative AI’s Hallucinations? | Digital Data Design Institute at Harvard

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