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Common challenges in Gen AI marketing

Jan Dalsfort on January 1, 2025

Generative AI is transforming how marketers work, bringing personalization, scalability, and efficiency to the forefront. But, like any innovation, it comes with its challenges. From managing data quality to addressing ethical concerns, understanding these hurdles is key to getting the most out of AI-driven tools like Magnity.

Let’s explore the common challenges in generative AI marketing and how to tackle them effectively.

Maintaining brand consistency

Generative AI is incredibly versatile, but without proper guidance, it might create content that doesn’t align with your brand voice or values. This inconsistency can dilute your messaging and confuse your audience.

How to address it:

  • Use platforms like Magnity that allow you to define and train AI on your brand voice.
  • Set clear parameters for tone, style, and messaging
  • Regularly review and refine the outputs to ensure they stay true to your brand.

Balancing creativity and control

AI can generate ideas and content at lightning speed, but marketers often worry about losing creative control or ending up with content that feels too robotic or generic.

How to address it:

  • Treat AI as a collaborator, not a replacement. Use it to handle repetitive tasks while focusing your creativity on high-level strategy.
  • Leverage tools like Magnity to co-create—AI generates drafts, and you fine-tune them.
  • Regularly involve your team in reviewing AI outputs to add the human touch where it matters most.

Addressing ethical concerns

Generative AI raises valid ethical questions about transparency, bias, and responsible use. Customers expect brands to be clear about how AI-generated content is created and ensure it doesn’t reinforce stereotypes or misinformation.

How to Address It:

  • Regularly evaluate your AI systems for potential biases and train models with diverse datasets.
  • Use tools like Magnity that prioritize ethical AI practices, and compliance

Overcoming adoption resistance

Introducing generative AI into a marketing workflow can be met with resistance, especially from teams unfamiliar with the technology. Concerns about complexity or job displacement can slow adoption.

How to Address It:

  • Start small: Pilot AI on specific campaigns to show its value without overwhelming your team.
  • Offer training sessions to help team members understand and use AI tools confidently.
  • Frame AI as an enabler that frees up time for strategic, creative tasks rather than replacing jobs.

Scaling without losing quality

AI makes it easy to scale content production, but with that comes the risk of losing quality or personal relevance as output increases.

How to Address It:

  • Use AI to automate the repetitive parts of your workflow while keeping oversight on high-value content.
  • Opt for platforms like Magnity that specialize in scaling personalized content across languages and regions.

With Magnity, marketers can embrace AI with confidence, knowing they have the tools to overcome these challenges and unlock the full potential of generative AI.

Generative AI marketing isn’t without its hurdles, but each challenge presents an opportunity to refine your approach. By understanding and addressing these common pain points, marketers can harness AI to create meaningful, scalable, and impactful campaigns that resonate with audiences.

Why context is king in AI prompting

Jan Dalsfort on October 4, 2024

When it comes to getting great results from AI, it’s easy to think it all comes down to the words you use. But there’s more to it than just stringing the right phrases together. The secret sauce? Context. Without it, even the most sophisticated AI model will produce outputs that fall flat.

Context is what elevates a generic, one-size-fits-all response to something that feels on-point, relevant, and tailored for the task at hand. Think of it as the backbone of effective AI communication—without it, your prompts are aimless, your outputs lack direction, and your AI ends up missing the mark.

In this post, we’ll explore why context is crucial in AI prompting, how to build it into your prompts, and what happens when you get it right (or wrong).

What is context in AI prompts?

In the world of AI, context refers to all the background information that helps the model understand exactly what you’re asking for. It includes:

  1. Audience Details: Who is this content for? C-level executives? First-time buyers? A tech-savvy audience?
  2. Purpose and Objective: What’s the goal of the content? To inform, persuade, or entertain?
  3. Tone and Style: Should it be formal, casual, or somewhere in between?
  4. Domain-Specific Knowledge: Is the AI writing about finance, healthcare, or SaaS solutions? Each domain has its own terminology, best practices, and nuances.
  5. Language and Cultural Context: Are you targeting a global market, or focusing on a specific region with unique preferences and sensitivities?

When you include this context in your prompts, you give the AI a roadmap. Without it, it’s like sending the AI off into the wilderness with nothing but a vague idea of where it’s supposed to go.

Why context matters: From good to great outputs

Let’s get practical. Imagine you need to generate a product description for a new B2B software tool. Here’s what happens when context is absent:

Prompt without context:
“Write a product description for our new software tool.”

Output:
“Our software tool helps businesses increase productivity and efficiency.”

Sure, it’s technically correct. But is it compelling? Is it relevant to your target audience? Not even close.

Now, let’s add context:

Prompt with context:
“Write a product description for a new project management tool targeting mid-sized SaaS companies. Highlight its ability to streamline team collaboration, automate repetitive tasks, and integrate seamlessly with popular tools like Slack and Trello. Keep the tone professional but approachable.”

Output:
“Our project management tool is designed for fast-paced SaaS teams looking to simplify collaboration and boost productivity. Automate repetitive tasks, manage projects effortlessly, and integrate seamlessly with tools your team already loves, like Slack and Trello. Get more done with less hassle.”

See the difference? By adding details like target audience, key features, and tone, the output becomes infinitely more useful.

Types of context you should include in your prompts

Building context into your prompts isn’t just about making them longer. It’s about adding the right type of information. Here are the core types of context you should consider:

  1. Target Audience
    • Specify who the content is for, their role, and their industry.
    • Example: “Create a blog post targeting IT managers in the healthcare industry who are concerned about data security.”
  2. Intended Outcome
    • What do you want the reader to do after engaging with the content? Sign up for a demo? Share the post? Buy a product?
    • Example: “Draft an email campaign to promote our new software. The goal is to encourage recipients to sign up for a free trial.”
  3. Tone and Style Guidelines
    • Define the voice of the content. Should it be persuasive, informative, humorous, or professional?
    • Example: “Generate social media copy for a new SaaS product. Use a playful, engaging tone to appeal to startup founders.”
  4. Specific Content Elements
    • Include requirements like word count, formatting, and key points to include.
    • Example: “Create a 300-word product description highlighting features X, Y, and Z. Use bullet points to emphasize each benefit.”
  5. Regional or Cultural Nuances
    • If you’re creating multilingual content, be clear about cultural preferences, idioms, and sensitivities.
    • Example: “Translate this blog post into French for an audience in Canada. Maintain a professional tone and replace American cultural references with Canadian ones.”

When context goes wrong: The risks of under-explaining

Leaving out context in your prompts can lead to a range of issues:

  • Generic Outputs: Without audience details, the AI’s response is often broad and bland, failing to resonate with anyone.
  • Misaligned Tone: If you don’t specify tone, you risk ending up with a piece that feels off-brand—either too formal or too casual.
  • Cultural Missteps: A lack of regional context can lead to outputs that feel inappropriate or out of touch, especially when translating content.

In a business context, these missteps are more than just minor annoyances—they can hurt your brand’s credibility and lead to missed opportunities.

How to build context-rich prompts in Magnity

At Magnity, we take context seriously. By incorporating local writing rules and robust contextual prompts, our platform is designed to produce outputs that feel authentic and on-point in every language and market. Here’s how you can apply it in Magnity:

  1. Leverage Local Writing Rules: When creating multilingual content, add rules that specify tone, preferred terminology, and even sentence structure variations for each language.
  2. Use Structured Prompts: Instead of a single-sentence prompt, build a structured prompt that includes target audience, objective, and any key phrases you want the AI to incorporate.
  3. Include Contextual Metadata: Magnity allows you to attach metadata to your prompts, making it easy to maintain consistency across outputs. Use this feature to keep track of brand voice, compliance requirements, and regional preferences.

Crafting context-rich prompts might take a little extra time upfront, but the results are worth it. By giving your AI a clear sense of direction, you’re setting it up to produce content that doesn’t just tick the boxes—it hits the mark.

So, next time you sit down to craft a prompt, remember: every detail counts. Define your audience, clarify your objective, and set the tone. Because in the world of AI, context isn’t just important—it’s everything.

AI prompting for multi-lingual content creation

Jan Dalsfort on October 4, 2024

Creating content in multiple languages sounds like a straightforward task—until you actually try it. You quickly realize that there’s more to it than just translating text from one language to another. Local idioms, cultural context, tone, and even sentence structure can vary significantly across regions. For global brands, nailing this multilingual complexity is non-negotiable. One misstep, and your content can come off as awkward, irrelevant, or even offensive.

That’s where AI prompting for multilingual content comes in. With the right approach, you can create content that speaks directly to your audience, no matter what language they speak. But here’s the catch: your prompts need to go beyond basic language translation. They need to incorporate local writing rules—the subtle yet critical details that can make or break your message.

Let’s dig into how to leverage AI and effective prompts to produce multilingual content that’s not only accurate but also feels authentically local.

The challenge of multi-lingual content creation

Creating multi-lingual content isn’t just about swapping words; it’s about crafting messages that resonate in different languages, markets, and cultural contexts. A direct translation can completely miss the mark, and traditional content management workflows are often clunky and time-consuming.

For B2B enterprises targeting diverse markets, this complexity is amplified. You’re not just dealing with consumer audiences; you have to consider the nuanced communication needs of C-level executives, department heads, and technical buyers—all with their own jargon and expectations.

The solution? AI models paired with localized prompt engineering. By embedding local writing rules and contextual instructions into your prompts, you can tailor content outputs to fit each specific region, tone, and audience type.

Why local writing rules matter

Local writing rules go beyond grammar and syntax—they encompass tone, formality, and even the preferred sentence structure for each language. For instance, the directness appreciated in English might come off as too harsh in Japanese or French, where a more nuanced, softer approach is preferred.

Consider these examples:

  • English: “Boost your ROI with AI-driven solutions.”
  • Spanish: “Mejore su rentabilidad con soluciones impulsadas por IA.”
    (The structure is similar, but word choice and formality are adapted.)
  • German: “Steigern Sie Ihren ROI mit KI-gestützten Lösungen.”
    (The formal “Sie” is used, reflecting a professional tone, and “KI” is used instead of “AI.”)

The same applies to punctuation, idioms, and even how you format numbers and dates. By incorporating these nuances directly into your prompts, you’re telling the AI: “Don’t just translate—localize.”

Effective AI prompts for multi-lingual content

The secret to getting multilingual content right lies in precision prompting. Let’s look at some strategies you can use to ensure your prompts yield high-quality, locally relevant content in every language.

1. Start with a strong base prompt

Your base prompt should include clear instructions on tone, audience, and format. Don’t just say, “Translate this content into French.” Instead, be specific:

2. Incorporate local writing rules

Local writing rules dictate how the AI should modify the content to fit the linguistic and cultural norms of each region. In Magnity, we integrate these rules directly into our prompts to ensure accuracy and relevance.

3. Leverage contextual cues for clarity

Always include contextual details to help the AI maintain the integrity of your message. For example, if you’re translating a campaign for a specific industry or use case, include that in your prompt:

4. Test and refine Across multiple variants

Even with well-crafted prompts, it’s essential to test variations. Use different prompts to see how changes in phrasing impact the output. Here’s an example of two similar prompts and how the results can vary:

  • Prompt 1: “Translate this press release into German. Keep it formal and factual.”
  • Prompt 2: “Translate this press release into German, ensuring a formal tone but allowing for slight adjustments in phrasing to maintain fluidity.”

The second prompt is more flexible, giving the AI room to optimize the language for readability, which is crucial for German’s complex sentence structures.

How Magnity enhances multi-lingual prompting

At Magnity, we’ve integrated local writing rules directly into our platform to streamline multi-lingual content creation. Here’s how it works:

  1. Automated localization framework: Magnity’s AI doesn’t just translate; it applies localized rules based on the target language. This means your content isn’t just accurate—it feels like it was crafted by a local expert.
  2. Customizable tone and style guides: Tailor prompts to adhere to your brand’s voice in every language. Whether you need a formal tone for German executives or a conversational style for Brazilian SMBs, Magnity makes it easy to set these parameters in your prompts.
  3. Multilingual content testing: With Magnity, you can generate multiple versions of a single prompt in different languages and regions, making it easy to spot inconsistencies and adjust on the fly.
  4. Built-in compliance and sensitivity filters: Our platform includes sensitivity filters to catch and flag culturally sensitive content, helping you avoid unintended missteps.

AI-powered content creation is powerful, but it’s not foolproof. Without thoughtful prompts that incorporate local writing rules, even the most advanced models can produce outputs that miss the mark. By taking the time to craft precise, context-rich prompts, you can unlock the true potential of multilingual content creation.

The B2B marketers guide to prompt engineering

Jan Dalsfort on October 4, 2024

Since you’re here, chances are you’ve heard about how AI is transforming marketing. But let’s cut through the noise. AI is only as good as the instructions you feed it. If you want your AI to spit out something useful—whether that’s a killer blog post, an engaging email campaign, or a strategic recommendation—it all starts with mastering the art of prompting.

We’re talking about prompt engineering. For marketers, understanding how to craft effective prompts is what separates the AI amateurs from the pros. It’s like giving your AI a map versus saying, “Good luck, find your way!” So, let’s dive in and see what it takes to make your AI work for you.

Why you should care about prompt engineering

Think of a prompt as the command that sets your AI in motion. It’s like setting the GPS for a road trip. A vague prompt like “Create a marketing plan” is the equivalent of saying “Drive somewhere fun.” Sure, you might end up at a decent destination, but it’s probably not going to be exactly what you envisioned.

For enterprises juggling multiple markets, regions, and languages, this precision is even more critical. You’re not just looking for good content – you need the right content, tailored for every stakeholder, every time. Without clear prompts, you risk getting outputs that are off-brand, misaligned, or just plain irrelevant.

Types of AI prompts you need to know

Not all prompts are created equal. Depending on your goal, you might need a simple directive or a highly detailed instruction. Let’s break down the main types of prompts and where they shine:

  1. Basic Prompts: These are straightforward commands like, “Generate a 100-word email introduction for our new product launch.” It’s fine for quick content, but it won’t win you any awards.
  2. Contextual Prompts: Here’s where you add some meat to the bones. A contextual prompt might sound like, “Write a LinkedIn post targeting procurement managers in manufacturing, focusing on cost efficiency and compliance.” The context helps your AI narrow its focus and align with specific personas.
  3. Complex Prompts: This is where things get fun. A complex prompt could be: “Create a 3-part email series for mid-level managers in the healthcare industry. Each email should highlight a different benefit of our product, focusing first on compliance, then ease of use, and finally, ROI.” With this, you’re guiding the AI through a whole journey.
  4. Conversational Prompts: Perfect for chatbots and interactive content. It’s about framing the conversation flow. For example: “If the user asks about pricing, respond with a general price range and offer a meeting for a detailed quote.”

When used correctly, these prompts aren’t just instructions—they’re the key to turning AI from a passive tool into an active collaborator.

The biggest mistakes marketers make with prompts

Look, we’ve all been there. You throw a half-baked command into your AI, and then spend the next hour wondering why the output is all over the place. Here are the top three prompting mistakes marketers make (and how to avoid them):

Being too vague: If your prompt is generic, your output will be, too. “Write a blog about AI” isn’t going to cut it. Instead, try: “Write a blog post for B2B tech companies exploring how AI can optimize supply chain management.”

Trying to do too much: Don’t overload your AI with endless instructions. “Generate a content plan, social posts, emails, and ad copy for our new product” is a recipe for disaster. Split these into separate, focused prompts for better results.

Ignoring tone and style: AI will take the path of least resistance. If you don’t specify tone, style, or audience, don’t be surprised when the output feels flat. Always include these elements to keep your content consistent.

Crafting prompts for real-world marketing challenges

Okay, so how do you actually build effective prompts for your needs? Let’s talk strategy. For enterprise marketing, the stakes are high. Your prompts need to be tailored to handle complex messaging, diverse audiences, and multi-channel outputs.

  1. Start with the goal: Every prompt should begin with what you want to achieve. Is it an email that drives clicks? A social post that boosts engagement? A whitepaper that educates? Be clear about the endgame.Example: “Create a 5-page whitepaper for mid-sized tech companies on the benefits of using AI in marketing. Use a professional tone and include at least 3 case studies.”
  2. Layer in context: Add background information to help the AI understand what it’s working with. Include target audience, tone, and any specific messaging angles.Example: “Draft a landing page targeting CFOs in the finance industry. Highlight cost savings, risk reduction, and ease of implementation.”
  3. Specify constraints: Set limits like word count, structure, or required keywords. These constraints act as guardrails to keep your AI on track.Example: “Create a 200-word email introducing our new service. Use the keywords: AI-driven, compliance, and scalable.”
  4. Iterate and fine-tune: Don’t expect a perfect result on the first try. Test different variations of your prompt, and refine based on what works best.Example: If the initial email comes off as too formal, adjust your prompt to specify, “Use a conversational tone.”

Unlocking Magnity’s full potential with AI prompting

Magnity isn’t your average AI platform. It’s built to handle the complexity of enterprise marketing, supporting content generation across any market or language. With Magnity’s capabilities, you can transform prompt engineering into a scalable process that saves time and resources. Did you know we have more that 100 prebuild prompts each with a specific purpose. This should make it alot easier to create quality content.

  • Personalization at Scale: With Magnity, you can create personalized content for multiple personas, geographies, and industries—all from a single prompt. Imagine setting up a prompt for a product launch that generates different emails for C-level execs, middle management, and front-line employees, each tailored to their unique concerns.
  • Localization Made Easy: AI prompting isn’t just about language translation. It’s about capturing the nuances of different markets. Use prompts that specify local preferences and regional pain points to produce content that resonates globally.
  • Content Optimization in Real-Time: Want to test different messaging angles? Use Magnity’s built-in testing features to refine your prompts and see what works best, without having to start from scratch each time.

Prompt engineering is more than just typing a few words into a text box. It’s a skill that, when mastered, can transform your AI from a content generator into a strategic partner. For enterprise marketers, mastering prompt engineering isn’t optional—it’s essential. So, next time you sit down to craft that perfect prompt, remember: the clearer the map, the better the journey.

The challenge of personalization at scale

Jan Dalsfort on August 4, 2024

Personalization at scale is a significant challenge for many businesses. Crafting personalized marketing messages traditionally takes a significant amount of time and resources, which many companies find difficult to manage. The complexity of tailoring content to meet the unique needs of every customer often results in generic campaigns that fail to engage.

According to research by Forrester Consulting, commissioned by Adobe, 98% of digital marketers agree that overcoming personalization challenges is crucial. However, the process is often hindered by the time and effort required to collect data, create content, and deploy personalized campaigns efficiently​ (Adobe)​​.

While B2C companies can leverage more straightforward personalization techniques (like personalized recommendations or emails), B2B brands need to cater to highly specific needs and preferences of each business client. This requires a more nuanced and scalable approach to personalization, which can be difficult to implement effectively​.

The Cost of ineffective personalization

The impact of ineffective personalization is profound. When businesses fail to deliver relevant and timely content, they miss out on potential engagement and revenue opportunities. Customers today expect personalized experiences, and when these expectations are not met, they are more likely to disengage.

Failing to personalize marketing efforts can lead to several issues:
  • Decreased Customer Engagement: Generic messages do not resonate with customers, leading to lower engagement rates. Personalized content significantly boosts customer interaction and satisfaction.
  • Lost Revenue Opportunities: Without personalization, businesses miss chances to convert leads into customers. Personalized marketing strategies are proven to drive higher conversion rates.
  • Weakened Customer Loyalty: Customers who do not feel valued and understood by a brand are less likely to remain loyal. Personalization helps build stronger relationships and fosters customer loyalty.

The same study found that 80% of surveyed organizations rate personalization as critical to business growth. Moreover, 75% of experience leaders are expanding their personalization efforts, recognizing that relevant content increases customer engagement and loyalty​.

Enter Magnity.ai, your solution to the personalization at scale dilemma. Magnity.ai leverages the power of AI to transform how you create and deliver personalized marketing campaigns. Here’s how we make personalization effortless:

Speed and efficiency
Magnity drastically reduces the time required to craft personalized marketing messages. With our platform, what once took days can now be achieved in mere seconds, allowing you to stay ahead in the fast-paced business landscape.

Comprehensive email personalization
Magnity.ai excels in building highly personalized emails. From subject lines to call-to-actions, every element is tailored to engage your audience effectively.

Multi-language translation
Expand your reach with our built-in translation capabilities. Magnity.ai personalizes content in any language, ensuring your message resonates with global audiences.

Integrated with major platforms
Seamlessly integrate with major platforms, including Salesforce, Marketo, and HubSpot. Leverage existing tools and data for a streamlined workflow.

Discover how Magnity.ai can help you create personalized marketing experiences that resonate deeply with your audience and propel your business forward.

Gen AI is perfectly imperfect and hugely Impactful

Jan Dalsfort on July 26, 2024

Generative AI has made significant strides, but it’s important to remember that we’re still in the early days of its development. A notable milestone was the launch of Chat GPT-3 on November 30, 2022. This event marked a significant step forward in AI capabilities, yet it also highlighted the challenges and limitations that remain.

Why AIs and LLMs struggle with counting ‘R’s in strawberry

One intriguing limitation of large language models (LLMs) and AI is their inability to count specific letters in words accurately, such as counting the ‘R’s in “strawberry.” This difficulty arises because LLMs don’t read words as individual letters but rather as tokens. Tokens are chunks of text that can be whole words or parts of words that the model processes. This token-based approach enables the AI to understand and generate text in a human-like manner, but it also leads to challenges in tasks that require precise letter-by-letter analysis.

On social media, it has been pointed out several times, that LLMs like Chat GPT cannot even count the number of the letter R in Strawberry. If you ask Chat GPT something like “how many Rs are there in strawberry?”, it simply replies 2, instead of the correct answer 3. This is because LLMs breaks languages down into tokens rather than letters. And from there, it can predict the next tokens. You can of course get the correct answer by giving some context to the task and guardrails.

95% quality in 1% of the time

One of the most compelling advantages of using AI in content creation is the incredible efficiency it offers. Achieving 95% quality in just 1% of the time traditionally required is a game-changer for businesses. This efficiency means teams can produce high-quality content rapidly, freeing up valuable time for strategic planning and creative endeavors.

The rapid pace at which AI can generate content translates to substantial time savings, allowing businesses to meet tight deadlines without compromising on quality. For instance, marketing campaigns that once took weeks to plan, draft, and revise can now be executed in a matter of days. This speed not only enhances productivity but also provides a competitive edge in fast-paced markets where timely communication is crucial.

Understanding AI hallucinations

Despite its many strengths, AI has a critical flaw: it can generate incorrect information with remarkable confidence. This phenomenon is known as a hallucination. AI can sometimes fabricate facts or present false information convincingly. This isn’t due to any malice or intent to deceive but rather a byproduct of how AI models learn and generate text. They predict and generate text based on patterns in the data they were trained on, which can sometimes lead to confidently presented inaccuracies.

To mitigate the risk of AI hallucinations, it’s essential to provide the AI with clear context, well-defined goals, and strict guardrails. Context helps the AI understand the topic and the nuances of the content it needs to generate. Clear goals ensure that the AI’s output aligns with the intended purpose, while guardrails act as constraints that limit the AI’s ability to deviate from accurate and relevant information. These measures help ensure that the AI produces reliable and factual content.

Magnity’s approach: Ensuring consistent and high-quality Content

At Magnity, we prioritize the quality and consistency of our AI-generated content. By using your own content on your own website, we ensure a consistent tone of voice in all our email communications. Additionally, we have an extensive set of writing rules, compliance guidelines, and detailed persona descriptions. These elements work together to significantly improve the quality of the output, ensuring that the content not only meets but exceeds your expectations.

By leveraging these advanced AI techniques and maintaining stringent quality controls, Magnity helps you harness the power of AI while minimizing its pitfalls, ensuring your email campaigns are both efficient and effective.

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