0:00
/ 0:00
Das KI-Spielbuch: Ein praktischer Leitfaden zu KI für Marketingfachleute
Werden Sie mit Ihrem KI-Wissen vom Generalisten zum Guru und heben Sie Ihre Marketingbemühungen auf die nächste (übermenschliche) Stufe - Ihr Team wird es Ihnen danken, Ihre Kunden werden Sie lieben und Ihre Konkurrenten werden nicht wissen, wie ihnen geschieht.
Introduction
AI and machine learning has sparked a revolution in marketing, reshaping how we connect with our audiences, save a bunch of time, and drive real results. In fact, it lowkey changed everything about it.
And here's a secret: Only the best marketing organizations, digital teams, and business leaders will tap into its full potential.
From content creation to customer insights for the ultimate personalized experiences, AI empowers us to do more with less. It acts as a tireless (literally, can we get some of that energy?) team member that eliminates repetitive tasks and frees us to focus on creative, high-value work that makes the difference to your customer journey.
Buckle up. Our AI playbook 2.0 is about to teach you everything you need to know in our about introducing AI into your day-to-day as an infinite workforce... rather than just another chatbot on the side.
What you'll learn:
- The real-world impact of AI on both your team's and customers' experience
- What it takes to be an AI agent boss (and beat your competitors to it)
- How we're helping marketing and digital teams use AI to double their productivity
- Questions to ask to measure your organization's AI maturity
- How to efficiently implement agentic AI with a 30-60-90 day action plan
- Which brands are already leading the way with Optimizely Opal (and how)
Understanding AI in marketing
While many of us initially feared that AI was about to steal our jobs, the reality is way more exciting.
AI isn't replacing marketers, it's amplifying our capabilities. By integrating AI into our workflows, experimentation programs, and general tech stacks, we're unlocking unprecedented efficiency and effectiveness.
But to create something truly magical in the fields of marketing and digital, you've got to consider two sides to the equation:
- Your team: How we can work more efficiently and optimize engagement
- Your customers: How they interact with digital experiences and content
Sure, AI can make our lives a helluva lot easier, allowing us to spend more time on the fun, creative, and more strategic stuff — but it can really benefit your customers too.
With AI totally changing the search game (it's impossible not to mention GEO or AIO at this point), it's important for you to be meeting customers where they are. That means being aware of what good content looks like, and ultimately being the brand that people and AI algorithms actually want to talk about.
On top of that, the more customer research and data you have to feed your AI tool, the more you can feed your AI tool, and ultimately, the more practical and productive you AI usage will be.
The better the input = the better the output
And don't you forget it
Practical applications of AI in marketing
AI can — and we in our minds, absolutely should — be seen as members of your team. In fact, team members with a difference. These ones don't care about doing the mindless, repetitive, boring, hit-your-head-against-the-desk kind of tasks; AI is actually a master at that type of thing.
But there's more to this robotic teammate, and it all rides on your organization's AI maturity.
A few small steps to apply AI in a meaningful way = one giant leap for your MX and CX.
3 simple ways AI helps the marketer experience
-
Use generative AI
Create basic content (eg. text, images, music) using standard AI prompts and open source LLM (large language model).
-
Automate tasks with AI agents
Expand the functions of AI beyond just "create" and into other actions such as recommendations (eg. actions to take) and analysis (eg. insights).
-
Create brand-specific content at scale
Increase the quality of output by giving AI more specific content (eg. your brand data, industry benchmarking, etc.)
3 simple ways AI helps the digital team experience
-
Test variations
Generate additional headlines for every experiment to improve outcomes and deliver more personalized experiences for your customers—without slowing down your team.
-
Strengthen SEO foundations
Use AI to scale keyword research, optimize metadata, and surface content opportunities. Fun fact: You can *actually* save 10+ hours a week with AI here.
-
Performance tracking
Quickly analyze tests, content, and campaign performance—filterable by region, stakeholder, or goal—so you can focus on what's working and iterate (way) faster.
3 simple ways AI helps the customer experience
-
Optimize for AI-powered search
Ensure your content is structured, relevant, and optimized for AI-generated search results, so customers find you fast (and in the way they interact in this AI era).
-
Adapt websites to real behavior
Use AI to help define audiences with existing data, tailoring your content and site layout based on how customers engage today—by device, location, search behavior (eg. "Here is an audience of high-spending customers with low engagement").
-
Personalized content at scale
Allow AI to take user-level attributes into account (in real-time) and make decisions to personalize individual experiences, increasing engagement and UX without the manual lift.
Yeah, that's right — we are going *way* beyond "write a blog". Use AI (including specialized agents) to analyze data, complete tasks while you're sleeping, and create hyper-personalized output.
AI agents: Everything you need to know
AI agents and specialized AI tools use context and instructions provided by you, the user, to perform a whole range of tasks — no humans necessary. The whole concept of agentic AI is changing the way we use AI and the way we work... for the better.
By incorporating AI agents into your marketing and digital strategies, you'll see:
- Increased efficiency
- More productivity
- Enhanced creativity
- Data-driven insights
How? Because AI agents take on the (painfully) mundane tasks that you don't want to, offer new ideas and insights that align with your brand guidelines, and deliver quick data analysis whether it's campaign results or other performance metrics you want to dive into. Meanwhile, you won't break a sweat.
Now, we know what you're asking: how do you get your hands on them? Well, for one, AI agents are manifested via Optimizely Opal, your AI workforce working alongside our entire product suite.
Optimizely Opal: Meet your agentic workforce
Given that generative and agentic AI have totally revolutionized the marketing and digital realm, and that realm is kinda our thing, it felt natural — no, essential — that we not only talked the talk, but walked the walk.
We use it
We test it
We build it
That's right, we are constantly building highly-specialized agents so our customers can benefit. So, on that note: say hello to Optimizely Opal — here to improve the marketing and digital team experience, and ultimately your customers'.
Embedded across our entire suite of products (also known as Optimizely One), Opal is there at your service. Far more than just an AI assistant or chatbot, it's an AI-powered workforce that acts as an extension of your marketing team, automating tasks, and providing proactive insights.
Here are some of Opal's key use cases:
- Speed up content creation and ideation: Spark new ideas and craft compelling content faster than ever. Opal helps you create complete campaigns: including ideating, crafting comprehensive briefs, generating text, and even creating images in various formats and sizes with smart cropping. Plus, AI tagging keeps your assets super organized.
- Deliver personalized experiences: Make the most of Opal to give you ideas for personalizing live webpages so you can easily maximize impact. Put its recommendations to the test, with on-brand, generated content in seconds.
- Boost experimentation velocity: Receive smart, data-backed recommendations to ideate on your next experiment, ensure your test plan is in tip top shape, develop variations (without a developer!), and summarize your results to apply learnings.
- Uncover data insights and trends: Dive deeper (and quicker) into your performance data by getting Opal to analyze complex information, spot emerging trends, and make smarter, data-driven decisions that propel your marketing forward.
... and the results speak for themselves
In our recent report, How Optimizely Opal saves time + drives results for teams like yours, we found a bunch of stats that you might be interested in.
Highlights for marketing teams
- +75% reduction in time to complete tasks
- +56% additional campaigns delivered
- +77% assets created
Highlights for experimentation teams
- +50% increase in experiment velocity
- +150% variations created per test
- +126% winning experiments
"We're incredibly excited about Optimizely's vision for Opal and the future of AI in content marketing and campaign automation. The potential to streamline everything from brief creation to content production, optimization and repurposing and even translation is game-changing.” John Habib, Director, Content Strategy @ Diligent
What makes Optimizely Opal truly unique?
- Context and brand aware: Access to all customer data such as guidelines, assets, and tests
- Connected across the workflow: Fully-unified AI platform across Optimizely One
- Fully agentic: Autonomous agents that use logic and reasoning to take action
- Intelligent tools: Hundreds of pre-built, highly-sophisticated tools
- Domain expertise: Built on decades of leadership in content and experimentation
Benchmark your organization's AI maturity
But how ready are YOU to leverage AI capabilities in your marketing? This is where we’d like to introduce the concept of AI maturity.
Recognizing the importance of understanding where a brand is at (and where it can be improved) is exactly why Optimizely has been busy developing an AI maturity model, to help brands assess and enhance their marketing capabilities in the age of AI. This allows them to see what can be improved, and spot the gaps in their existing processes and tech stacks.
Measuring your AI maturity: Questions to ask
-
How does your marketing organization currently use AI?
Think about how marketers – in each area, like content marketing, event marketing, campaigns, etc – leverage AI right now... if at all. Is there a process in place or, at least, a recommended process on how to use it? Is it followed or do people do their own thing?
-
What’s your data infrastructure looking like?
For quality output with AI, you need quality input. If you want things personalized and unique to your brand, data is the answer. So, what’s the level of quality and accessibility of data? Are there robust data management and governance practices in place? And are you taking advantage of that? You know, data analysis, segmentation, and insights – all that good stuff.
-
Just how advanced are your team’s AI skills and knowledge?
If you’ve found people on your team are already using AI, how are they finding it? Look into the prompts they’re using, for example – are they pretty simple or more advanced?
By surveying your team, you’ll discover if they’re excited about AI and wanting to learn more. This should also influence your own research into the opportunity for further education – whether done by the ‘local’ AI expert on your team, or an external option.
-
What level of confidence do you have in writing your own AI instructions?
The quality of what you get out of AI depends heavily on what you put in. So, how confident are you – or your team – in writing clear, effective prompts or instructions that actually drive useful, on-brand output?
Are people just experimenting with one-liners and hoping for the best, or are they deliberately structuring their inputs with tone, brand voice, and context in mind? Are they tailoring prompts for specific tools or use cases (eg. blog drafting vs. subject line optimization)? Do they know how to refine outputs, give feedback to the AI, or create repeatable templates?
-
What tools are people using?
What tools are people using? Are people signing up to the free version with their own email addresses, or is there a paid-for company account people can really make the most of? This doesn’t just include separate chatbots or image generators – they're may be AI capabilities within tools that are already in your martech stack.
Assess what tools people are using, what they’re using them for, how they integrate with existing tools, and where the gaps are.
Your 30-60-90 day action plan for AI implementation
Here’s the thing: AI implementation that actually moves the needles won't happen overnight. Integrating it into your marketing and digital strategy is a process that requires thoughtful planning and execution... not to mention enablement.
It’s a journey of continuous learning and adaption, and you’ll undoubtedly find new ways to leverage AI to drive efficiency and effectiveness along the way.
That’s why we’ve developed a 30-60-90 day action plan to help your integrate AI into your marketing operations in the most effective way. Let’s break it down.
30-60 days
Getting started
In the first 30-60 days, it’s all about assessment and planning to get ready for the more advanced stuff. This can look something like:
-
Understand your current state of AI usage
Understand your current state by conducting a thorough audit of your existing marketing tools and processes. Identify areas where AI could add the most value. Is your content creation process bottlenecked? Are you struggling to clearly define your target ICP and segment your audiences? Also, assess your data readiness to ensure you have the quantity and quality of data needed to fuel AI algorithms effectively.
-
Define clear goals for your AI implementation
Whether you're looking to increase content production, improve personalization, or enhance customer insights, set specific, measurable KPIs. For example, aim to increase content production by 50% or improve email open rates by 25% through AI-driven personalization.
-
Build a strong team
AI implementation isn't just a marketing initiative - it requires collaboration across departments. Assemble a cross-functional team including finance, IT, marketing, and data science, with clearly defined roles and a common framework for collaboration.
-
Research and choose your tools (wisely)
With your team in place, start exploring AI solutions that align with your needs. Consider factors such as integration capabilities with your existing martech stack, ease of use, and scalability.
90 days and beyond
Advanced implementation
You’ve set the foundations for efficient AI usage, building out an achievable roadmap and making sure your team is aligned. Now it’s time to get into the nitty gritty, and level up:
-
Develop data-readiness strategies
As you move into more advanced implementation, data becomes crucial. Implement robust data governance policies to ensure data quality and accessibility.
Develop a data pipeline that can feed your AI models with fresh, relevant data. This might include setting up data lakes, implementing data cleansing initiatives, and integrating disparate data sources.
-
Start with pilot projects in high impact areas
There's nothing like running a test program to gather real-time learnings to inform future projects. Launch pilot projects in areas where AI can make a significant impact. Continuously monitor these pilots against your KPIs and regularly share learnings across the business.
For example, try out various agents in your workflows and see where they can make the biggest impact. -
Implement AI and agents for more complex use cases
Going beyond simple content creation, you can consider more complex, more niche use cases for AI agents that lighten the load for your team. This might look like advanced experimentation agents that can generate code to create and edit variations, reducing bottlenecks that come with technical dependencies.
By following this structured approach, you'll be well on your way to successfully integrating AI into your marketing strategy, setting the stage for innovation and improved performance.
0:00
/ 0:00
The power (ahem... *necessity*) of human context
No matter how impressive the next new AI technology may seem, the human touch remains crucial. The key is striking the right balance between AI efficiency and our human creativity and strategic thinking.
We need to make the most of AI having zero emotions and endless energy by letting it handle the boring, repetitive or data-processing tasks, but also tee it up with some extra juicy AI prompts and AI instructions.
After all, human input is essential to the quality of the AI output, helping you create effective content, campaigns, and digital experiences a whole lot faster.
Check out our Hype to Hero video series for simple (and quick) tips on using AI.