With over 20 years of experience, we transform your digital presence. We specialize in website and E-Shop development, SEO and Digital Marketing, ERP software and smart automation that take your business to the next level.
Address:
154 Egnatia Street, Thessaloniki 546 36
Phone:
+30 231 231 4095
E-mail:
hello@twodots.gr
Ready for the next step?;
AI writing tools have moved from experimental stage to operational use, offering e-commerce owners opportunities for more efficient content workflow, better SEO and email marketing support. Choosing the right tool depends on the needs of the store, not its popularity. Using them correctly can speed up production without sacrificing quality and brand voice, and AI should be strategically integrated into the content function.
Contents
AI writing tools have moved from the «experimentation» phase to the operational exploitation phase. For an e-commerce owner, this doesn't just mean being able to write product descriptions or social media posts faster. It means that he can organize a more efficient content workflow, reduce the time to produce first drafts, create variations of promotional messages and better support SEO, email marketing and customer support content. G2's article on the best AI writing generators showcases tools evaluated through real user reviews and highlights a basic truth: the right AI writing software is not necessarily the best known, but the one that best fits the use case, team, budget and level of control the business needs.
In e-commerce, content production has high operational pressure. A store with 500 or 5,000 products needs titles, meta descriptions, category descriptions, product descriptions AI workflows, FAQs, email flows, landing pages, video scripts, social media captions and possibly content for marketplaces. If every piece is written from scratch, the process becomes expensive, slow and often inconsistent in terms of brand voice. If, instead, the business relies uncritically on an AI content generator, it risks filling its site with generic text, duplicate wording, inaccuracies and content that offers no real value to the user. The right approach lies somewhere in between: AI writing tools act as accelerators, not as standalone replacements for strategy, expertise and editorial judgment.
The dynamics of AI in the business environment is clearly reflected in McKinsey's data. According to “The State of AI in early 2024”, 65% of organisations said they regularly use generative AI, almost double the 2023 figure. For e-commerce professionals, this increase isn't just a technology trend; it's an indication that their competitors are likely already experimenting with generative AI marketing, content marketing automation and prompt engineering to reduce timescales and increase productivity. As shown in the graph below, adoption has increased sharply in just one year.
Source: McKinsey, The State of AI in early 2024
| Year | Price |
|---|---|
| 2023 | 33 % |
| 2024 | 65 % |
A modern AI writing software can support many functions of an online store, as long as it is used with clear rules. In SEO, it can create drafts for category descriptions, meta titles, meta descriptions, FAQ sections and informative articles that target long-tail queries. In merchandising, it can help produce more convincing product descriptions, especially when there is structured data such as materials, dimensions, technical features, user instructions and benefits. In performance marketing, it can create multiple versions for headlines, primary texts and call-to-actions so the team can quickly test different communication angles. In email marketing, it can accelerate flows such as welcome series, abandoned cart, win-back campaigns and product recommendation emails.
The important thing is that AI writing tools don't perform equally well on all tasks. An AI writing generator can be great at quick brainstorming, but mediocre at content that requires specialized knowledge. Another tool may have strong brand voice controls, but lag in SEO content writing. Other platforms focus on AI copywriting for ads, others on rewriting, others on generating great articles, and others on integrating with team workflows. Therefore, the choice of tool should start from the actual needs of the shop and not from the list of the most popular software. The G2 article serves as a useful starting point because it compiles market tools and leverages user reviews, but the final selection should be based on your own testing with real products, real briefs and real business goals.
Using generative AI in content is no longer a marginal practice. According to the Content Marketing Institute and MarketingProfs' 2024 B2B Content Marketing Benchmarks, Budgets, and Trends survey, 72% of B2B marketers said they use generative AI tools. While B2B is not identical to e-commerce, the finding shows that marketing teams are already integrating AI content generation into their daily lives. The graph below shows the relationship between the use and non-use of generative AI by marketers in the survey.
Source: Content Marketing Institute and MarketingProfs, B2B Content Marketing Benchmarks 2024
| Category | Quota |
|---|---|
| They use generative AI | 72% |
| Do not use / did not declare use | 28% |
The first selection criterion is the quality of the produced text in relation to your brand. A good tool should not just write «correct» Greek or English, but should be able to follow tone, style, level of detail, commercial logic and constraints. For example, a premium fashion brand needs a more aesthetic and editorial style, while an electrical equipment store needs precision, technical clarity and less hyperbole. This is where the concept of brand voice is critical. Look for tools that allow for brand guidelines, saved prompts, knowledge bases, style rules or example texts so that the result doesn't look like it was written by a different copywriter every time.
The second criterion is reliability. AI tools can create inaccuracies, especially when asked to describe technical products, materials, certifications, compatibilities or legally sensitive information. For e-commerce businesses, an error in a product description can lead to returns, negative reviews or compliance issues. Therefore, AI copywriting should always go through human review, especially in categories such as dietary supplements, cosmetics, children's products, electronic devices and health products. The AI can suggest wording, but the business remains responsible for accuracy.
The third criterion is integration into the existing workflow. If your team works in Google Docs, Shopify, WooCommerce, Magento, Notion, Slack or project management tools, consider whether the AI writing software offers integrations, export formats, team collaboration, approval flows and multi-user management. The real time savings come not only from fast drafting, but from reducing movement between tools, standardizing briefs and the ability to pass content through review without chaos.
The fourth criterion is SEO. A tool that promises SEO content writing must help with intent, structure, headings, headings, user questions, semantic coverage and not just repeat keywords. The focus keyword must come in naturally, LSI keywords must support the topic and the final text must answer real search needs. For example, in the topic of AI writing tools, a good article is not enough to mention the phrase multiple times. It needs to explain how they are chosen, how they are evaluated, what the risks are, how they relate to e-commerce KPIs and when human intervention is needed.
The fifth criterion is cost versus performance. Don't just compare the monthly subscription. Calculate the time saved, the number of texts produced, editing time, training needs, quality of the final assets and the impact on conversion rate, organic traffic or email revenue. A cheap tool that produces mediocre drafts may cost more in editing, while a more expensive tool with better governance can reduce errors and support a larger team.
Step 2: Define use cases before you see tools. Don't start by asking «what is the best AI writing generator?». Start by asking «what exactly do I want to produce better or faster?» If the core need is product descriptions, you need mass production capability with a fixed structure. If the need is blog, you need support for research, outline and semantic SEO. If the need is ads, you need multiple variations and fast testing.
Step 3: Create a small test set. Choose 10 products, 3 categories, 2 email campaigns and 1 article. Give the same briefs to 2 or 3 AI writing tools and compare results. Don't just evaluate the first draft. Measure how much editing was needed, how close it was to the brand voice, how many factual errors there were, whether the content was commercially useful and whether it could be published with reasonable interference.
Step 4: Create prompt templates. Prompt engineering is not a theoretical skill; it's a practical productivity tool. Create templates for product descriptions, category pages, meta descriptions, ads, email marketing copy and FAQs. Each template should include target, audience, tone, prohibited wording, desired structure, mandatory attributes and call-to-action. The clearer the inputs, the better the outputs.
Step 5: Apply editorial workflow. No AI content generator should publish directly without verification. Define roles: who writes the brief, who checks accuracy, who edits style, who approves SEO, and who publishes. For small teams, roles can be owned by the same person, but the process should be clear. This reduces errors and maintains consistency.
Step 6: Measure results for 60 to 90 days. Compare productivity, organic impressions, clicks, conversion rate, assisted revenue from emails, ad engagement and production time. Tool selection shouldn't be based on the feeling that it «writes well,» but on business results. If a tool reduces 40% of production time but increases 60% of editing time, it's probably not the best choice.
The ROI of AI writing tools should be measured on three levels: productivity, quality and business impact. In productivity, measure how many assets are produced per week and how long it takes from brief to publication. In quality, measure percentage of content that needs significant rewriting, number of revisions per draft, compliance with brand voice and accuracy of information. In business impact, measure organic traffic, keyword ranking, CTR from search results, conversion rate to product pages, revenue from email flows and engagement in paid campaigns.
A practical measurement model is to establish baselines before adoption. For example, if the team currently needs 45 minutes for a quality product description, record the time. Then implement AI-assisted workflow and measure again, including time for prompt, review and editing. If the time drops to 20 minutes without a drop in quality, there is a clear productivity gain. If CTR in organic results improves at the same time or returns decrease due to cleaner descriptions, then the benefit becomes more substantial.
Pay particular attention to SEO. Mass production of content with AI does not guarantee an increase in organic traffic. Search engines reward content that actually helps the user, meets search intent and provides primary value. For e-commerce, this means that descriptions and articles must incorporate real product knowledge, comparisons, helpful selection guidelines, answers to objections and data that is not available as such on every competing site. Producing content with AI is cost-effective when fed with your own data: customer reviews, support questions, product features, shipping policies, after-sales experience and commercial knowledge.
The quality of brand voice also needs a system. Create a short brand voice document with examples of desirable and undesirable phrases. Define whether you speak in the singular or plural, how technical the style is, how aggressive the sales copy can be and which words you avoid. Then pass these elements into the prompts or tool settings. AI text generators work best when they aren't asked to guess your style.
Finally, create a usage policy. What data is allowed to be entered into the tool? Is customer data allowed? Who approves content for legally sensitive categories? How are claims such as «best», «certified», «clinically proven» or «eco-friendly» checked? Governance is not bureaucracy. It's the way to use AI writing tools safely, consistently and professionally.
AI writing tools can fundamentally change the way an online store produces, optimizes and distributes content. But they are not a magic solution. Their value depends on the brief, the data you give them, the clarity of the brand voice, the quality of human editing and the link to real KPIs. G2 offers a useful starting point to look at available solutions and user reviews, but the best choice for your business will only emerge through structured testing.
For e-commerce owners, the smartest approach is to start small and measurable. Choose a use case, such as product descriptions AI or email marketing copy, create templates, measure time and quality, and then expand to SEO content writing, ads and social media captions. This way, AI becomes part of a mature content operation, not just another tool bought because it's in the news. The difference won't be judged by whether you use AI, but by how well you integrate it into your strategy, data and team experience.
Step 1: Map the content needs. List how many product descriptions you need per month, how many SEO articles, how many emails, how many ads and how many social media captions. Divide them into recurring, strategic and sensitive content. Recurring is ideal for automation, strategic needs close human guidance, while sensitive requires tight control.
AI writing tools speed up content creation, improving efficiency in SEO, email marketing and customer support. They can quickly create ad drafts and variations, reducing production time and enhancing brand voice.
Key benefits include faster creation of product descriptions, SEO optimization, and production of quality content with consistent brand voice. They also facilitate performance marketing with multiple versions of promotional messages.
You need to consider text quality, reliability, integration into existing workflow, SEO and cost versus performance. The choice should be based on the specific needs and goals of your store.
Create a brand voice document with desired phrases and adjust the tool settings to reflect your style. Use clear prompts and templates to guide the AI in creating content that fits your brand.
Measure productivity, quality and business impact. Record time saved, quality of copy and impact on organic traffic, conversion rate and revenue from email campaigns.
AI writing tools can boost SEO by creating content that targets long-tail queries and meets search intent. Incorporate real product knowledge and useful data to achieve better organic rankings.
Consider whether the tool offers integrations with your platforms and create a structured editorial workflow. Define clear roles for brief, review and content editing to maintain consistency and efficiency.
G2: Best AI Writing Generators
McKinsey: The State of AI in early 2024
Content Marketing Institute: B2B Content Marketing Benchmarks, Budgets, and Trends
Google Search Central: Creating helpful, reliable, people-first content
