The outgoing year 2025 has been a triumphant one for artificial intelligence. Its all-encompassing integration has shown up in every sphere, and in marketing it has been especially powerful.

We have already talked about how the rules of reputation management and SEO promotion for brands have changed: if earlier SEO was a routine discipline where we relied only on intuition and labor-intensive analysis, today neural networks have practically turned Search Engine Optimization into an exact science.

Implementing AI makes it possible not only to instantly obtain deep analysis of user behavior, but also to forecast trends and automatically adapt content to rapidly changing search engine algorithms.

At la-marketing.us, we have already explored AI’s capabilities for brand SEO in quite some depth, and in this article we will share what we’ve learned.

Why use AI in SEO and marketing?

In the new reality, effective digital marketing without full-scale AI integration is simply impossible. Life “in digital” is developing so fast that a human alone can no longer keep up. A neural network, however, can in the shortest possible time:

• analyze millions of search queries;
• build a detailed picture of behavioral factors and the competitive landscape;
• execute highly precise targeting;
• anticipate trends instead of merely chasing them.

For business, this translates into tangible benefits: advertising budgets shrink significantly, personalized content boosts conversion, and sales grow. Most importantly, a sustainable competitive advantage is formed, even in the most saturated markets.

A brief history of AI in SEO and marketing

The evolution of the relationship and gradual merging of artificial intelligence and SEO has unfolded right before our eyes:

• Initially, algorithms were used by search engines such as Google and Yandex to rank websites and fight low-quality content and spam.
• Marketers quickly found a response to this challenge in the form of automated tools for technical audits and keyword research.
• With the emergence of modern generative neural networks, a turning point came: straightforward analytics gave way to creative work and strategic thinking.
• Marketers obtained a powerful AI tool for comprehensive optimization and for producing highly relevant content, including advertising creatives.

Key areas of AI application in SEO

The areas and methods of using neural networks for search optimization and brand promotion are constantly expanding. For now, let’s focus on three core directions of marketing transformation.

Using AI to automate SEO tasks

Analytics and data interpretation

We’ve already mentioned that artificial intelligence can not only collect massive data sets, but also find hidden, non-obvious correlations.

AI tools are able to accurately detect and analyze:

• web analytics data;
• ranking dynamics;
• competitor traffic;
• market trends.

In doing so, they form for us a holistic picture that makes it easy to forecast, for example, how changes in Google’s or Yandex’s algorithms will affect brand visibility and reputation. At the same time, AI also proposes preventive measures, allowing you to quickly address emerging risks and take control of your digital reputation.

Automation of routine processes

Neural networks can now safely be entrusted with those monotonous tasks that are easily automated:

• collecting the semantic core;
• clustering queries;
• monitoring technical errors;
• preparing reports, etc.

This not only saves SEO specialists’ time and effort – it also minimizes the human factor where absolute accuracy is required.

Content and creative generation

High-quality content has always been and remains the key component of SEO success. But if in the past AI wrote texts at the level of an elementary school student, today generative neural networks have learned to create much more than just technically correct copy:

• informative articles;
• product descriptions;
• blog posts;
• video scripts and video content itself;
• instructions, guides, presentations, and so on.

This allows a brand not to depend on the workload or “creative slumps” of human authors and to scale content production as aggressively as the strategy requires. However, to achieve the ideal balance between volume, quality and relevance, human control is still necessary.

The best model is: AI generates the basis → a copywriter checks it, adds expertise → adapts it to the brand’s real voice.

Steps for successfully implementing AI in SEO

Step 1. Run an SEO audit of the website

Start with a comprehensive diagnostic. AI tools will help you quickly identify:

• obvious technical errors such as broken links, duplicate pages, etc.;
• more complex issues with indexing, loading speed, and poor data structure.

Step 2. Build the semantic core

Successful brand promotion is impossible without a solid semantic core. Neural networks can:

• analyze the full array of user queries;
• group them by user goals and intent;
• identify the most promising niches with low competition and high demand.

This allows you to focus correctly and work only with directions that are truly promising for the business.

Step 3. Optimize text content

Generative AI, based on a ready semantic core, can produce relevant, useful and accurate texts that meet both user expectations and search engine requirements. This type of optimization is often called AIO or GEO (Generative Engine Optimization).

(graphic — m.seonews.ru)

Step 4. Build brand reputation

AI systems help form a strong digital reputation, influence rankings, and provide effective tools for building trust in the brand.

You can delegate to them monitoring, detection of positive and negative mentions of the brand, and the search for opportunities to be referenced in authoritative sources and to place guest posts.

Step 5. Automate and delegate promotion

You can safely hand over routine monitoring and reporting to neural networks. Simply set up automated systems that will track your website’s rankings, traffic dynamics, and technical metrics.

Popular AI tools for SEO and marketing

Of course, not all neural networks are equally useful for marketing. Let’s look at the most popular AI tools used by our specialists.

ChatGPT and its analogues

Language models such as ChatGPT and Claude, as well as their local counterparts (for example, GigaChat), are very effective for idea generation, drafting texts, building content plans, writing emails and even basic programming. Their strength lies in their versatility and understanding of context.

Creative generation tools

For visual content generation, the current leaders are Midjourney, Stable Diffusion, DALL-E and Kandinsky. They allow you to independently create visually appealing and unique creatives without having to hire expensive designers each time.

Analytics tools

Specialized platforms such as MarketMuse, BrightEdge and others analyze the top of the search results, assess how relevant your content is, and immediately provide clear recommendations for improvement. Based on up-to-date data, they indicate which changes will give the maximum growth in rankings.

Principles for writing effective prompts for AI

Today, you cannot get high-quality output from AI by simply copying someone else’s overused prompt. You need to master at least the basics of prompt engineering.

Here are three tips that will help you communicate more effectively with AI without any special training:

• Be specific and always provide context: not just “write an article about SEO”, but “write an introduction for an article on technical website optimization for marketing beginners who run a small product business in Tashkent.”
• Always assign a role to the AI: ask it to “act as an experienced SEO copywriter with 10 years of experience and a track record of creating viral, helpful content for Moscow restaurants.”
• Always use an iterative approach: refine and improve your prompts based on previous responses.

The future of neural networks in SEO and marketing

When it comes to predicting the future of SEO promotion in collaboration with AI, there is always a risk of underestimating the scale. But already today it is clear that:

• Total personalization is coming — AI is ready to work with each individual user.
• Search engines will shift from analyzing keywords to evaluating the completeness and expertise of answers.
• As a result, the best rankings will go to those whose content AI considers the most comprehensive and authoritative.

Frequently Asked Questions

Can we already fully entrust SEO and SMM to a neural network?
Not yet. AI is a powerful tool that eliminates routine and enhances analytics, but strategic planning, creative decisions and final content approval must remain with humans.

Are neural networks ready to completely replace SEO specialists?
They have already replaced those who dealt only with routine tasks. However, strategists, analysts and SMM specialists will still be in demand, because someone has to set the right tasks for AI and interpret its results.

Conclusion and recommendations

The integration of artificial intelligence into SEO is not a temporary trend; it is here to stay. Companies that actively embed neural networks into their marketing gain a decisive advantage in the battle for visibility in search. The only important caveat is that you should not blindly follow whatever technology suggests. To get the results your brand needs, AI must be used thoughtfully and intelligently.

Constant change is built into digital marketing. With the rapid rise of GenAI, this natural volatility is only intensifying. New tools, platforms and communication formats are emerging all the time. Strategies that seemed effective just a year ago can now deliver zero impact or even turn into clear anti-trends. In this article, we will explore whether AI is truly the core trend in marketing and highlight other significant developments shaping 2026. AI versus traditional search: when should you prioritise GEO, and when is classic SEO still the better choice?

According to a survey by Onclusive, algorithm shifts are seen as the number one challenge for 2026. As AI is embedded deeper into search, these shifts become harder to predict and almost constant.

Not long ago, a user entered a query into the search bar and simply received a list of links to various websites. By late 2025, even standard search began to include AI Overviews (Google AI Overviews) – a block with a generated answer at the top of the results page plus a list of sources on the right-hand side. Users can now also request a fully generated reply to their query in:

• Google AI Mode – generative answers displayed directly in search, with the option to continue the conversation and a list of supporting links.

• Generative AI models (ChatGPT, Gemini, Claude and others) – these tools produce their own response, often without a direct, visible link to a specific brand.

Against this backdrop, traditional SEO still plays a crucial role, but marketers are broadening their priorities and investing far more effort into GEO. In 2026, alongside rankings in classic search, brands also need to be recognised as trusted, expert sources that neural networks choose to quote.

At La-Marketing, we combine both approaches when promoting websites. We are confident that using SEO and GEO together is already a must if you want to build a long-term, stable and resilient traffic channel. 

Mass content generation by neural networks 

Throughout 2025, the line between human-written and AI-generated text has been fading. This trend now affects not only simple social media posts, but also specialised expert content that still carries an author’s voice and includes fact-checked information.

Mass generation has also moved into visuals and video. Just a few years ago, deepfake production required several different tools and a large library of original photos and footage. Today, neural networks are constantly refining their models, and new solutions appear almost every month. In the autumn of 2025 alone, the market saw the launch of:

• Imagine Art powered by Gemini

• Sora 2 from OpenAI

For marketers, these advanced technologies simultaneously open up opportunities and create serious challenges.

• On the plus side, they allow you to produce and adapt content quickly, cut production costs and scale creative ideas at high speed.

– On the downside, they put authenticity at risk, demand constant monitoring of what is appropriate, and can easily distract teams from truly strategic priorities.

At the beginning of November, Ukrainian social networks were flooded with fake videos and images of Angelina Jolie allegedly visiting cafés in different cities, shopping, working out and even receiving treatment. The situational campaign spiralled out of control: brands gained reach, but also faced a powerful wave of backlash. Users were angered not only by the unauthorised use of a celebrity’s image, but also by the absence of clear AI labelling.

Today, creators must carefully balance the efficiency of artificial intelligence with human input. Content strategy cannot be built on AI alone. It is important to remember that AI is prone to hallucinations, factual errors, lack of empathy and a poor understanding of your specific context at any given moment.

Real-time ad automation

Performance Max, introduced back in 2021, already offered end-to-end automation and personalisation for each potential customer. In 2025, Google rolled out an entire suite of additional features under the AI Max umbrella to push this adaptability even further. The system can now generate headlines automatically, pause underperforming ads and fine-tune strategies for different campaign goals.

For companies with modest budgets or highly specialised niches, adopting this approach is not always justified. The algorithms need substantial volumes of data and enough “space to test and fail” to perform well. Still, it is very likely that the capabilities and effectiveness of such automated advertising will continue to grow.

Important: even the most advanced AI tools still need human expertise:

• Initial configuration and strategy design

• Development of creatives (even if AI assists in production)

• Ongoing maintenance: updating and checking negative keyword lists, bid strategies and targeting settings

Meta is following a similar path. In October 2025, the company announced the Meta AI business assistant, designed to help optimise campaigns and drive higher sales results.

La-Marketing.us has extensive experience running advertising campaigns for businesses in a wide range of industries since 2010. This background enables us to manage different budget levels effectively, and our early access to Google’s innovations allows us to integrate new features quickly.

AI-based marketing agents – intelligent chatbots

Smart chatbots remain a powerful, ongoing trend and are steadily evolving. Large language models (such as ChatGPT) have significantly increased their capabilities and continue to improve in quality.

These bots rely on a company’s internal knowledge base enriched with neural network capabilities. As a result, they can provide personalised recommendations, handle both simple and complex queries, support customers in planning tasks and much more. 

Real-time analytics and the threat to privacy

For several consecutive years, personalisation has been one of the dominant trends in marketing, gradually transforming into full-scale hyper-personalisation. AI now enhances not only user interactions with brands, but also the depth and detail of behaviour analytics across multiple channels.

Looking ahead, the emphasis will shift from “more personalisation” to safeguarding user privacy. The following aspects are worth incorporating into your processes now, as they are likely to become baseline expectations:

• Rely only on data that the brand has collected directly from the user with explicit consent.

• Store this data securely and avoid sharing it with third parties (including other brands).

• Choose communication channels and contact frequency with care.

• Follow not only regulatory requirements, but also clear ethical standards.

• Design communication strategies thoughtfully and limit the number of touchpoints per individual user.

To move from basic traffic tracking to meaningful, data-driven decisions, you need a professional, end-to-end analytics setup. This is an area where cooperation with specialists can significantly speed up progress.

The growing influence of Gen Alpha

It feels like only recently the industry was focused on Gen Z and the need to adapt strategies to younger audiences – and yet it is already time to prepare for the next generation. Generation Alpha, born between 2010 and 2025, is becoming a paying audience (with parents’ support, but often using their own bank cards).

For children’s banking products (ages 6 to 14), special rewards and mechanics have been introduced. Kids can win sweets, branded gifts or even trips to destinations such as Disneyland.

Some key figures: 68% of children have their own devices with internet access. 63% play video games every day, and 48% of them watch gaming streams. 36% of Ukrainian children already actively use AI for entertainment and study.

Generation Alpha discovers brands mainly through mobile apps and social media platforms, including:

• Minecraft

• Roblox

• TikTok

• Instagram

• YouTube

The main tools for attracting this new youth audience include:

• In-app advertising

• Collaborations and integrations with influencers

• Special social media projects (contests, quizzes, promotional campaigns)

• User-generated content (UGC)

Old content still matters in 2026

For many years, content has been the backbone of website promotion. Even now, older articles on your blog can remain valuable. CRO expert Neil Patel regularly highlights how important it is to revisit and refresh legacy content.

To bring old content back to life, you should:

• Update information on a regular basis – not just change the date, but add fresh industry insights, expert commentary, news and case studies.

• Rework your CTAs – your products, positioning and priorities may have shifted, and your calls to action should reflect those changes.

• Refocus from pure traffic to conversions – add subscription forms, lead magnets and direct links to mentioned products or services.

• Expand beyond your home market – use AI translation as a starting point, but always rely on human specialists for proper localisation.

• Update the publication date to match the latest revision.

You do not have to launch new pieces constantly. If your blog is already extensive, you almost certainly have articles that are still relevant but would benefit from a thorough review and refresh.

A new level of UGC – collaboration with customers

In recent years, encouraging customers to create content for brands has evolved from a minor tactic into a powerful, long-term trend. This model is especially visible in the beauty sector. The movement has gone far beyond social feeds, forming tightly knit, loyal communities around brands.

For example, British cosmetics brand REFY organised a community trip to Mallorca, turning loyal customers into true brand advocates.

In Ukraine, the retailer Lullaby allows clients to redeem loyalty points not only for discounts, but also for membership in a closed community with different access tiers, bonus gifts and invitations to exclusive events.

This type of engagement not only drives sales and loyalty, but also encourages satisfied customers to generate content on their own and spread it organically. Brands can then reuse this UGC in social feeds, ad creatives, product pages and other marketing assets.

AI challenges for 2026

As AI technologies continue to automate, generate and optimise more and more tasks, they simultaneously create new types of pressure for marketers. The most notable challenges include:

• AI fatigue among professionals, caused by the explosive pace of technological growth. Every year, tens of thousands of new startups enter the market, while tech giants constantly update and expand their product lines. Many of these tools look extremely promising and highly relevant. In practice, however, it is impossible to test everything at once.  

• The need for continuous learning. AI platforms give digital specialists end-to-end control over planning, tracking, content creation, personalisation and advertising. But this requires more than just access to tools: you need hands-on skills, a solid understanding of prompting, and in some cases basic coding knowledge.  

• The risk of low-quality and homogeneous outputs as a side effect of widely available AI. Recognising the limits of GenAI for automated copywriting may itself become a defining trend in 2026. To avoid content that looks identical to hundreds of other AI-generated texts, brands must adapt models to their own voice: training on in-house materials, building custom prompts and thoroughly editing AI drafts.

Summing up: what should marketers expect from 2026?

Every year, AI systems grow more powerful and capable of handling increasingly complex tasks. As a result, the balance between human creativity and machine efficiency will continue to shift. Marketers will likely need to double down on uniquely human strengths – understanding cultural and ethical nuance, emotional intelligence, the ability to learn quickly and retrain. Consequently, soft skills will play an even more central role.

Brands should already be thinking about building relationships with the youngest audience – Gen Alpha – and planning advertising formats and integrations inside ecosystems such as the Roblox metaverse. Expert content will remain valuable (even if created years ago, as long as it is regularly updated), as will community development and working with micro-influencers.

If you are uncertain about your next steps in 2026 or, conversely, already convinced that you need GEO and advanced ad automation, the team at La-Marketing.us can run an initial audit and help you define, prioritise and execute your digital goals for the coming year.

The rapid development of generative language models such as GPT-5 and Gemini has fundamentally changed how people search for information on the internet. Users no longer want to scroll through long lists of results with thousands of links – they expect instant, direct and meaningful answers.

Traditional SEO approaches no longer guarantee that it will be your content that appears in front of the user. This is why AI search optimization – often called GEO (Generative Engine Optimization) – is becoming critical: it focuses on optimizing content for generative AI models.

What Are Generative Language Models and How Do They Work?

Generative language models (LLMs) are AI systems that use machine learning algorithms to create answers. They synthesize and process data from a huge number of sources and can generate short, accurate responses to user queries – which is very different from classic search engines that simply return a list of links.

How it works:

1. The user enters a query. It can be simple (“weather in Kyiv”) or complex (“compare the advantages of a vacation in Turkey and Greece”).
2. The model analyses user intent. It determines what exactly the person wants to get: an instruction, a list of links, tips, images and so on.
3. AI looks for relevant information and scans thousands of sources: websites, forums, social networks, knowledge bases, documents. Algorithms evaluate the quality, freshness and authority of the content.
4. AI combines fragments from different sources into a logical, concise and synthesized answer.
5. In a dialog format AI can ask clarifying questions and provide a list of sources (usually links to the pages used are hidden at the bottom of the block).

What Is GEO (AI Search Optimization) and How Is It Different from SEO?

Generative Engine Optimization (GEO) is a new approach to content optimization focused on getting into the answer blocks generated by large language models.

Content optimized for AI search can appear in:

• AI Overview (AIO) – Google’s generative result block with AI-based snippets.
• Answers of voice assistants such as Siri and Google Assistant.
• Responses of AI chatbots: ChatGPT, Gemini, Bing Chat and others.

By the way: the Webpromo editorial team has explored how ChatGPT algorithms work and collected practical tips that help your content appear in chatbot answers. You can read about effective ways to “become friends” with AI assistants in their article.

Key differences between SEO and AI search optimization (GEO)

AI search optimization is becoming necessary for modern businesses because people increasingly get information not through classic search, but via AI models. This leads to more “zero-click” situations: users receive a complete answer immediately and do not need to visit a website.

If your content does not appear in AI answers, your business becomes less visible to potential customers. AI-oriented optimization allows you to become the source from which AI pulls information – and even without clicks this affects awareness, authority and trust in your brand.

Optimizing Content for AI: What Kind of Content Do LLMs “Like”?

According to a 2024 Gartner study, only 23% of companies have a defined AI search (GEO) strategy. On one hand, this is a challenge for marketers and content creators, because there is still no fixed set of best practices that guarantees a place in AI answers.

On the other hand, investing in AI search optimization today gives you a competitive advantage and a chance to win user attention. Content becomes the main tool in this race.

LLM models tend to favour content that:

1. Is clearly structured: clean heading hierarchy (H1, H2, H3), short sections, lists and tables. One question – one clear answer.
2. Is written in simple language, without overloading with jargon or keyword stuffing. LLMs can pull snippets from any part of the page, so the quality of the entire article matters, not just the first paragraphs.
3. Matches user intent: gives clear answers to “what”, “how”, “when”, “why”. For example, if a user asks how SEO works, the answer should contain a definition, a simple analogy and a short description of the mechanism.
4. Includes verified facts, statistics, case studies and quotes. Not just rewrite, but unique analytical content with a focus on E-E-A-T.
5. Has optimized microdata: Schema.org (FAQ, Article, HowTo), Open Graph, canonical tags – all this helps AI “understand” the page.
6. Is up to date and regularly updated.

Images, infographics and videos also help AI better understand and interpret the page content.

How to Combine SEO and AI Search Optimization

You don’t need to choose between SEO and AI optimization. The best results come from using both at the same time — so your content stays visible in Google and also appears in AI-generated answers.

• Focus not only on keywords, but on real user intent.
• Optimize pages that already trigger AI Overviews.
• Create expert, high-quality content with visuals and clear structure.
• Group your content into related topic clusters.
• Make sure your site is fast and mobile-friendly.
• Add FAQ blocks for better AI visibility.

How to Measure AI Optimization Results

• Does your content appear in AI answers?
• Is branded and direct traffic growing?
• Are users spending more time on your site?
• Are there more brand mentions online?

Should You Replace SEO with AI Optimization?

No. SEO is still the foundation. AI optimization strengthens it. Without strong SEO, it’s almost impossible to appear in AI answers. Together, they give you visibility, authority and long-term growth in 2026.

FAQ

What is AI Search Optimization (GEO)?

It is a strategy that helps your content appear in AI answers on platforms like ChatGPT, Google AI Overviews and Gemini. In simple words — it’s SEO for AI-powered search.

Can AI optimization replace SEO?

No, it doesn’t replace SEO — it supports and enhances it.

What content works best for AI?

Clear, expert and easy-to-read content with real value for the user.

CMS is the foundation that determines how effective your organic search promotion will be, how fast you can implement strategies, and how scalable your content will become.

In this article, we focus on choosing a CMS for SEO, because among all marketing channels, Search Engine Optimization (SEO) is the most demanding when it comes to the technical basis of a website. The effectiveness of attracting organic traffic, loading speed and flexibility of the internal structure directly depend on the capabilities of the CMS you choose.

Criteria for choosing a CMS for SEO: what to pay attention to?

CMS (Content Management System) is software that lets you manage a website without having to write code manually. With a CMS you can:

• Add and edit pages, articles, images and video.
• Manage menus, categories and tags.
• Configure design templates and plugins to add extra functionality.
• Optimize the site to meet search engine requirements.
• Manage user access and roles on the website, etc.

The modern market offers many CMS platforms, but not all of them are “SEO friendly”. If a system does not support SEO features, then even high-quality content and a consistent promotion strategy will not bring traffic, and the site will lag behind competitors.

Let’s look at the key features a CMS must support for effective SEO.

SEO components a CMS should support

Comparison table of CMSs for SEO

Read also: “Is SEO dead?” Why search engine optimization remains essential in the age of AI

The best CMSs for SEO

WordPress

WordPress is one of the most popular open-source CMS platforms. Interestingly, it was originally created as a blogging tool but has evolved into a universal platform for websites of any complexity.

Advantages:

• Simple content management thanks to an intuitive interface.
• Ability to create SEO-friendly URLs with keywords.
• Huge number of plugins to create and edit meta tags, manage XML sitemaps, analyze content for keyword usage and readability, etc.
• Most modern WordPress themes are responsive and display correctly on mobile devices.
• WordPress has clean code that search engines can crawl easily. With the right plugins, you can achieve high page speed.

Disadvantages:

• Too many plugins or “heavy” themes can significantly slow down the site.
• Because of its popularity, WordPress is a frequent target for DDoS attacks, which can lead to hacks and data leaks.
• If indexing is misconfigured via SEO plugins or robots.txt, WordPress can generate duplicate pages.
• Full optimization (e.g. performance tuning, caching configuration) may require technical skills or help from a specialist.

Joomla!

Unlike WordPress, Joomla! was initially designed for more complex, structured corporate sites, portals and communities.

Advantages:

• Built-in SEO tools that don’t require additional plugins (metadata, robots.txt and .htaccess management, URL settings, etc.).
• The menu and category system makes it easier to build website architecture.
• Supports multilingual sites, which simplifies optimization for international audiences.
• Offers a high level of control over source code and server settings for experienced developers.

Disadvantages:

• To use some SEO features correctly, you often need to edit the .htaccess file manually, which requires technical knowledge and can be difficult for beginners.
• When complex technical issues arise, it can be harder and more expensive to find a qualified Joomla developer than a WordPress specialist.
• If the site is not configured properly (caching, database optimization), it can be slow.

Drupal

Drupal is suitable for large and complex projects that require unique architecture, scalability and strict security. Think government and educational institutions, large media portals.

Advantages:

• Thanks to “Content Types” and “Fields”, you can build logical and well-structured data models.
• There are many SEO modules: automatic creation of clean URLs, meta tag management, sitemap generation.
• With proper configuration, Drupal sites demonstrate high loading speed and low server load.
• Drupal is considered one of the most secure CMS platforms.

Disadvantages:

• High entry threshold: even basic configuration requires technical skills.
• Fewer ready-made solutions: although the platform has modules, they still need manual setup. This takes more time than installing an out-of-the-box SEO plugin in WordPress.
• Not suitable for beginners or very tight-budget projects, as it requires constant involvement of a qualified developer.

Photo: Drupal

Shopify

Shopify is a leading international SaaS commerce platform designed for creating and managing online stores. It is ideal for small and medium businesses as well as large companies that want to quickly launch and scale sales.

Advantages:

• Easy to use with an intuitive interface.
• A store can be launched in a matter of days: you pay for a subscription, and Shopify provides hosting, maintenance, security and updates.
• All-in-one e-commerce solution: tools for inventory management, payments, logistics and even marketing.
• Handles heavy traffic during peak periods (e.g. seasonal sales).
• Clean code, built-in CDN and automatic image optimization ensure high page speed.

Disadvantages:

• No access to server files: you cannot edit .htaccess or fully manage robots.txt, which limits deep technical optimization.
• For advanced design customization, you need knowledge of Shopify’s Liquid templating language, not just HTML/CSS.
• Shopify forces prefixes in URLs such as /products/, /collections/, /pages/. You can only edit the “tail” of the URL, which complicates structure creation.
• Requires a monthly subscription and charges an additional transaction fee (usually 0.5%–2% depending on the plan) if you don’t use Shopify Payments.
• Basic blogging functionality, which is a drawback for content-driven businesses.

Photo: CMS Critic

OpenCart

OpenCart is one of the most widely used solutions for small and medium e-commerce businesses. The platform is known for its relative simplicity and modest hosting requirements.

Advantages:

• Designed with online stores in mind, making it easy to manage a large number of product pages, categories and brands.
• Built-in basic SEO tools: clean, readable URLs for products and categories, meta tag and heading management.
• Supports multilingual sites and lets you manage multiple stores from a single admin panel.
• With proper configuration (minimal unnecessary modules and quality hosting), the site can be very fast.

Disadvantages:

• Without additional modules, OpenCart can generate duplicate pages (for example, the same product accessible via multiple URLs), which pollutes the search index and hurts rankings.
• Built-in SEO tools are basic. Full-fledged work (e.g. XML sitemap generation, canonical URLs, automated meta tags) requires paid or free modules.
• Creating and managing content pages (long-form blog articles, for example) is less convenient than in other CMSs.

Photo: OpenCartBot

MODx

MODx is a framework for building websites focused on flexibility and customization. It appeared in 2004 as an alternative to more rigid, template-based systems like Joomla or WordPress.

Advantages:

• Absolutely clean code: MODx does not add extra HTML or CSS elements because the developer builds the structure from scratch.
• The system enables creation of highly readable URLs without extra prefixes or restrictions.
• Thanks to clean code and the absence of unnecessary plugins, MODx sites usually show excellent Core Web Vitals metrics.
• Security is a strong focus, which is why MODx is often used for large corporate sites.

Disadvantages:

• SEO quality largely depends on the developer’s skills and experience.
• Unlike other CMSs, the MODx interface is not intuitive. Content updates, adding new blocks or managing pages often require technical skills from the content manager.
• The user and developer community is relatively small, which makes it harder to find plugins or qualified support.
• No universal SEO plugin: all elements have to be configured manually or via separate, less powerful modules.

Photo: MODx

Recommendations: which CMS to choose for your niche?

The choice of CMS should be based on project type, scale, budget and your team’s technical skills:

• For blogs, media and content sites, the priority is easy publishing and SEO flexibility. In this case, consider WordPress or Joomla!.
• Corporate sites must be reliable, integrate easily with internal CRM systems and scale smoothly. Good options include Drupal or MODx.
• E-commerce projects require a special approach, because SEO success depends on correct catalog structure, product page optimization, site speed, filter configuration, etc. Ukrainian online stores can look at Horoshop, as well as Shopify and OpenCart.

Choose a platform that removes most of the technical burden so you can focus on what matters most: content and sales growth.

Proper SEO is not just about a site’s technical parameters. It is a comprehensive approach: from catalog structure and product page optimization to user behavior and analytics. These are the aspects that determine whether your business will reach the top of search results.

If you want a stable stream of targeted traffic and higher sales, entrust your SEO to the Webpromo team. Contact us today to get an individualized growth strategy and achieve maximum results in search.

FAQ

What is a CMS and why do you need one?

A CMS (Content Management System) is software that lets you create, edit and publish content on a website without writing code from scratch. This way, marketers and content managers can run the site through an intuitive admin panel, while built-in tools and plugins simplify SEO optimization.

Does the CMS affect SEO in 2026?

Yes. Even the most interesting, high-quality content will not rank if the site loads slowly, has duplicate pages, poor filters and tags, or messy code. The CMS is the technical foundation for successful SEO.

What should you pay attention to when choosing a CMS for an online store?

For e-commerce, the key priority is easy scaling. The CMS should support automatic Canonical tags for filter pages, bulk meta tag generation for products and categories, structured data markup and more.

What are the most popular CMS platforms?

The market is dominated by two main groups: universal CMSs and commercial SaaS platforms. The most popular include:

• WordPress: flexible, with a strong user and developer community and suitable for any type of project, from a blog to an online store.
• Shopify: a leader among SaaS platforms for e-commerce, popular thanks to its simplicity and technical reliability.
• Joomla! and Drupal: common in the segment of complex, corporate and government portals where data structure and security are crucial.

Which essential SEO features and tools should a good CMS include?

A CMS that is good for SEO should allow you to edit meta tags (Title and Description) for every page, create clean URLs, automatically generate and edit sitemap.xml, and manage robots.txt for indexing control. These features are the baseline for modern CMS platforms.

However, some older or less supported systems may require complex manual coding. Some commercial SaaS site builders (like Tilda, Wix on basic plans) can limit access to technical SEO features. For example, they might auto-generate sitemap.xml but not allow full manual control, or limit 301 redirects to paid plans only.

What should you do if your CMS has limited SEO functionality?

In that case, you can either bring in a developer or migrate your site to a modern, SEO-friendly platform, paying special attention to 301 redirects so you don’t lose existing traffic.