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    li: "li"
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    children: [_jsxs(_components.h2, {
      id: "use-cases-rule-them-all",
      children: [_jsx(_components.a, {
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        href: "#use-cases-rule-them-all",
        children: _jsx(_components.span, {
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      }), "Use cases rule them all"]
    }), "\n", _jsx(_components.p, {
      children: "The current AI wave is in many ways similar to the coming of marketing automation 1.0 more than a decade ago. The pace is just faster, and the buzz is bigger as we are not talking about some processes that affect under the hood."
    }), "\n", _jsxs(_components.p, {
      children: ["The biggest similarity relates to the early days of marketing automation when the hunt for concrete use cases was still on. The question for getting bang for the buck for an individual company was, did the company just end up doing the same email campaigns with a heavier tech stack and cost base? Today, while examples like ", _jsx(_components.a, {
        href: "https://forbes.com/sites/jackkelly/2024/03/04/klarnas-ai-assistant-is-doing-the-job-of-700-workers-company-says/",
        children: "Klarna"
      }), " are concrete examples of change, it's clear that chat-based solutions are just the starting point of AI's potential."]
    }), "\n", _jsx(_components.p, {
      children: "In marketing automation, it could take months or years before organizations found the way and managed to complete the setups in a way that began to make an impact. Many are continuing on this journey."
    }), "\n", _jsx(_components.p, {
      children: "What sets the GenAI era apart is the immediacy we can now get on board and start making things happen. GenAI's trial and testing are no longer slowed by extensive deployment and technical setup, providing a quick way to get started."
    }), "\n", _jsxs(_components.h3, {
      id: "the-right-attitude-and-investments-in-time-and-money-will-help-some-companies-achieve-an-unfair-competitive-advantage",
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      children: "However, distinguish this from a mere plug-and-play scenario. AI is a transformational project requiring clear objectives and ambition from the management. The technology is here, but integrating it into our workflows requires time and proper experimentation. It also involves ambition from companies developing AI-based services to create intuitive solutions that remove the need for clumsy prompting and that go beyond content creation or chatbots."
    }), "\n", _jsx(_components.p, {
      children: "As we've worked with all kinds of organizations from US to Finland, we have learned the GenAI transformation journey proceeds in four stages in a simplified way:"
    }), "\n", _jsxs(_components.ol, {
      children: ["\n", _jsxs(_components.li, {
        children: ["\n", _jsx(_components.p, {
          children: "Learning and mapping: learn to work with GenAI and identify use cases and bottlenecks without heavy IT projects or data integration. Sounds easy, but the winners will be the companies that invest enough time in this and don't leave it up to the employees. Test different services and think outside of narrow content generation use cases."
        }), "\n"]
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        children: ["\n", _jsx(_components.p, {
          children: "Leveraging data: Start by using non-sensitive data stored in your CMS and marketing platforms. Incorporating it into your GenAI processes can significantly improve analytics and content production results."
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        children: ["\n", _jsx(_components.p, {
          children: "Fine-tuning for business impact: with a solid understanding and proven initial use cases, the focus shifts to fine-tuning LLMs. This phase is intensive and requires investment, time and a willingness to experiment."
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      children: "The guiding principle should be clear: Use cases rule them all. The true measure of AI's value is not only in its technological power but also in its ability to solve real-world problems."
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return {
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};


Transformation


## Generative AI and SEO

The introduction of generative AI disrupted the SEO market, leading many tool providers to allow their users to create large amounts of content with little cost and effort. Instead of being a highway to the stars, this was just another spam stunt similar to keyword stuffing. Rather than offering value to end users, attempts at SEO were primarily focused on getting attention from algorithms.

Luckily, the recent update to [Google's spam policies](https://developers.google.com/search/blog/2024/03/core-update-spam-policies#scaled-content) severely penalizes sites that apply this tactic and forgot that whatever happens in the technology front, you should always keep your site reputation healthy and content authentic.

### Quality over quantity

AI should serve a much greater purpose in marketing than simply providing narrow, one-off solutions. It should be used to help organizations craft quality content. This can become a reality only if AI is used to conduct smart analyses and strategies, which in turn help create accurate, relevant communication that resonates with end-user preferences.

Large language models' powers go beyond content creation - they are super well equipped to help you in data crunching, combining data from multiple sources and highlighting the right insights from this raw data. 

SEO is not just a numbers game. Your brand's SEO performance is shaped by your ability to create valuable, informative content that speaks to your target audience. It's a game between adopting efficient SEO techniques and prioritizing meaningful content that aligns with user intent.

### AI integration in SEO 

With AI technology becoming more sophisticated, search engines like Google are refining how they deliver search results. AI-driven tools, such as [Google's Search Generative Experience (SGE)](https://blog.google/products/search/generative-ai-search/), are reshaping the search landscape by offering highly curated AI-generated snapshots at the top of the search results page. To stay visible in such an AI-centric search environment, marketers need to learn how to optimize content so that it appeals to both traditional SEO metrics and the AI-specific ranking factors employed by SGE.

### The balancing act of content length

Long-form content has historically been the cornerstone of effective SEO. However, recent trends indicate that shorter content is favored in certain contexts. This doesn’t mean the 'ultimate guide' approach is obsolete, but rather that there's a growing appreciation for brevity and direct answers to user queries. It's about assessing the intent behind searches and providing just the right content to satisfy that intent. Marketers should monitor industry trends to understand whether shorter or longer content is preferred and adapt accordingly.

### Leveraging the potential of Google Perspectives 

A relatively unexplored SEO frontier is '[Google Perspectives](https://blog.google/products/search/google-search-perspectives/)'. This feature emphasizes user-generated content such as reviews, forum discussions, and social media interactions. Brands may need to pay more attention to the conversations surrounding their products and prompt more user-generated content that Google's algorithms could favor. This calls for a clear strategy to encourage customers to generate content that can improve visibility and credibility in searches.

### AI is your new strategic partner in SEO

In 2024, the landscape of SEO strategy will become faster and more efficient. Companies that learn how to use AI services such as [Superlines](https://www.superlines.io/use-cases/seo) in their process to gather relevant information faster can iterate their marketing and outpace competitors with greater speed. Companies can focus more in understanding how to produce content that truly delivers value to your audience and experiment with different approaches.

It's important to understand the AI's possibilities beyond the basic use of SEO tools or conducting keyword research. Effective SEO strategy in 2024 requires a deeper comprehension of content creation and its impact on search engine rankings.

Generative AI and SEO in 2024


## Use cases rule them all

The current AI wave is in many ways similar to the coming of marketing automation 1.0 more than a decade ago. The pace is just faster, and the buzz is bigger as we are not talking about some processes that affect under the hood.

The biggest similarity relates to the early days of marketing automation when the hunt for concrete use cases was still on. The question for getting bang for the buck for an individual company was, did the company just end up doing the same email campaigns with a heavier tech stack and cost base? Today, while examples like [Klarna](https://forbes.com/sites/jackkelly/2024/03/04/klarnas-ai-assistant-is-doing-the-job-of-700-workers-company-says/) are concrete examples of change, it's clear that chat-based solutions are just the starting point of AI's potential.

In marketing automation, it could take months or years before organizations found the way and managed to complete the setups in a way that began to make an impact. Many are continuing on this journey.

What sets the GenAI era apart is the immediacy we can now get on board and start making things happen. GenAI's trial and testing are no longer slowed by extensive deployment and technical setup, providing a quick way to get started.

### The right attitude and investments in time and money will help some companies achieve an unfair competitive advantage

However, distinguish this from a mere plug-and-play scenario. AI is a transformational project requiring clear objectives and ambition from the management. The technology is here, but integrating it into our workflows requires time and proper experimentation. It also involves ambition from companies developing AI-based services to create intuitive solutions that remove the need for clumsy prompting and that go beyond content creation or chatbots.

As we've worked with all kinds of organizations from US to Finland, we have learned the GenAI transformation journey proceeds in four stages in a simplified way:

1. Learning and mapping: learn to work with GenAI and identify use cases and bottlenecks without heavy IT projects or data integration. Sounds easy, but the winners will be the companies that invest enough time in this and don't leave it up to the employees. Test different services and think outside of narrow content generation use cases.

2. Leveraging data: Start by using non-sensitive data stored in your CMS and marketing platforms. Incorporating it into your GenAI processes can significantly improve analytics and content production results.

3. Fine-tuning for business impact: with a solid understanding and proven initial use cases, the focus shifts to fine-tuning LLMs. This phase is intensive and requires investment, time and a willingness to experiment.

 The guiding principle should be clear: Use cases rule them all. The true measure of AI's value is not only in its technological power but also in its ability to solve real-world problems.

TransformationThe different stages of AI transformation

Focusing on use cases with a business focus and investing enough time and resources in AI transformation will make successful companies stand out from the rest

Use cases rule them all

The right attitude and investments in time and money will help some companies achieve an unfair competitive advantage

Read more about
Transformation

Generative AI and SEO in 2024

TransformationThe different stages of AI transformation

Focusing on use cases with a business focus and investing enough time and resources in AI transformation will make successful companies stand out from the rest

Use cases rule them all

The right attitude and investments in time and money will help some companies achieve an unfair competitive advantage

Read more about Transformation

Generative AI and SEO in 2024

Read more about
Transformation