Are you already using artificial intelligence in your daily work? Writing texts, code…
ChatGPT, Perplexity, Gemini - all these tools have long become familiar assistants at work. And many have already integrated them into their workflows. I did the same and want to share how I use various AI services in marketing, where speed and accuracy come to the forefront.
Table of contents
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The Marketing Data Chaos
Marketing teams face data chaos daily. Website audits, content analysis, search position tracking, competitor comparisons - all this requires many hours, sometimes entire days. As a result, we as specialists spend energy not on strategy, but on manual routine.
Tables and graphs provide numbers, but don’t always show direction. You can spend weeks gathering analytics but still not understand where exactly conversion is being lost. And there’s also the human factor: fatigue, errors, missed details.
Now I try to use AI so that it helps see not just numbers, but meaning.
How I Work with AI Tools in Marketing
When I started my marketing career in 2010, we thought in terms of: keywords, text length on the site, and number of links. There were essentially two marketing channels: Google advertising and organic search. Cool, right? :)
Then Google started saying: think more about the user, create content not for machines, but for people. And we did: part of the text for people, and part just for ranking.
Then new social networks appeared, targeting, chatbots and many other interesting things. Accordingly, time spent working with different channels became more and more. And so the question of marketing automation arose.
For marketing and SEO, tools like Similarweb and Ahrefs already existed back then, which collected statistics on marketing channels, keywords and competitor links. Visual AI practically didn’t exist yet, except for experiments with generating simple banners.
Over time, services for visual content appeared, such as Canva and other similar platforms, which allowed creating images, banners and logos in just minutes.
Probably the turning point was the appearance of GPT-3 from OpenAI in 2020, when everyone started using ChatGPT to create texts and generate answers to any questions.
SEO and analytics also reached a new level. Tools like Surfer SEO, GrowthBar and Wrytix appeared, which allow analyzing positions, identifying weak pages, finding growth opportunities and building strategies based on facts, not guesses.
Marketing Research
Previously, marketing research took me almost a whole week. I had to collect data about competitors, monitor positions, analyze keywords, study reports and open databases. Sometimes it seemed I spent more time with spreadsheets than with strategy.
Now I use AI to speed up this process. Services analyze open sources, social networks, statistics, user comments and build the overall picture in just minutes. I see not just numbers, but trends, audience behavior and competitor weaknesses.
I always verify data, check sources and assess how much the conclusions correspond to reality. This allows me to make decisions faster and focus on what truly affects strategy.
For me, the main plus: I can test hypotheses and adapt strategy in real time. AI helps see what a person easily misses: unexpected demand changes, new niches, growth points. I spend less time on data collection and more on its analysis and application.
Popular AI Tools
Over the years of working with marketing, I’ve tried countless AI tools. The value of any service manifests only with proper integration into the process, not in the beauty of the interface or loud name.
For working with texts and content, I’ve tried almost all tools like Jasper, Rytr, Wrytix, Copy.ai. I use them to generate ideas for posts, blogs, emails and landing pages. In practice, I create several text variants and then adapt them to the audience and brand style.
Also useful at the start is Marketing Personas Generator from Wrytix, and for customer support automation: Chatbase, BrightBot and EmailTree.
Adcreative.ai and Anyword are especially useful if you need to optimize ad texts or newsletters for specific campaigns - they speed up the process, but still require control.
For visual content, I’ve tried many services and still settled on Canva and Looka. With their help, you can quickly create banners, logos and posts for social networks. I use AI as a starting point, and then correct and combine variants to preserve visual uniqueness and corporate style.
For video and multimedia, I use HeyGen or Rephrase (Synthesia didn’t work out for me somehow). They help quickly get video basics - short clips for social networks or personalized materials for email. I set the script, adjust the pace and intonation so the result fully corresponds to the communication strategy.
For social media management, Hootsuite, Ocoya, Metricool and Postwise will be useful. In practice, I don’t use them. Played around a couple times and that’s it.
For SEO and analytics, proven tools are Surfer SEO, GrowthBar and Wrytix. They give a clear picture of weak pages, keywords and competitor actions.
Let me tell you more about each marketing channel.
Social Networks
Previously, I spent hours on texts and visuals, trying to predict what would hook the audience. Now I give AI a general theme or idea, and it suggests text variants that sound natural. Jasper and Copy.ai don’t replace my voice, but give a starting point from which I can work further.
What’s important: AI immediately analyzes subscriber reactions. I see which wording hooks and which doesn’t. Sometimes these are unexpected results. For example, a post I thought was boring turns out to be the most engaging. This way I learn to see the audience differently and adjust content faster.
Content Marketing
Texts for the website, blogs, landing pages - I used to write them myself or delegate. Now AI helps structure material, suggests headlines, article ideas and video scenarios. But the key point: I always edit and check so the text doesn’t lose liveliness and expertise.
Wrytix, Jasper, Copy.ai - these tools allow me to make the process faster, but don’t replace my understanding of how the audience reads and perceives content. Without this, AI turns into a word generator, not an assistant.
SEO and Analytics
Collecting keyword data, site audits, competitor comparisons used to take almost a week. Now SurferSEO and NeuronWriter do most of the work: analyze pages, select keywords, show where there are gaps.
I get a map I can rely on: which pages to improve, what content to strengthen. But decisions about priorities remain mine. AI gives facts, but not strategy. It’s important for me to understand how this data affects business goals, not just fix errors.
Visual Content
With Midjourney or Canva AI, I can see banner or image variants in a few minutes. This doesn’t mean I take the first result. I compare, choose and adjust. For me, the main thing is to speed up the process, but not lose control over aesthetics and visual meaning.
How I Implement AI
I start with specific tasks: where I can reduce routine and speed up processes while maintaining expertise. This can be content, analytics or advertising. Then I choose tools, integrate them with CRM and other systems, verify data and adjust.
Very important: I don’t delegate everything to AI. Control and understanding remain mine. AI works for me, not the other way around.
How to Implement AI in Marketing Strategy
When I decided where to use AI, I started with a simple question: what do I do manually and how much time does it take? Content, advertising, analytics, customer support: all this turned out to be potential automation points.
The first step for me is always this: define the task and understand what can really be trusted to the algorithm, and what requires my participation. For example, AI can suggest post variants or collect website analytics, but decisions about strategy and priorities remain mine.
Next, I choose tools that fit the specific task and connect them to existing systems: CRM, email services, analytics. It’s important that data flows into one system, and I see the full picture.
What’s next..
The next stage is team training. I can’t just turn on AI and wait for results. I need to explain to colleagues how algorithms work, where their limitations are and what to pay attention to. Sometimes it seems AI does everything itself, but without understanding the process you risk losing control.
The last, but key point is optimization. I check results, adjust settings and gradually expand automation. This is not a one-time process, but constant work, where AI becomes my assistant, not a magic button.
Mistakes I Avoid
Relying completely on AI without verification would be a big mistake. I always check text, analyze data and control that recommendations correspond to the real situation. Often algorithms can give unexpected conclusions that at first glance seem correct, but in the business context - no.
What I See in the Future
AI is gradually transforming from a tool into a partner that helps quickly navigate the data flow and see new opportunities. But the human factor still remains key. Algorithms speed up work, show patterns, but I make decisions about strategy and actions.
Conclusion
For me, AI tools mean freeing up my time: getting the opportunity to focus on what’s important! Finding statistics faster, testing hypotheses faster, understanding what works for my audience, changing and finding new hypotheses. And so each time to get results.