Making a business case for documentation, post 4 - Learn how documentation drives revenue and traffic


This is the fourth post in a series about making a business case for documentation. In this post, we discuss how good documentation can drive revenue and traffic to your website.

In the previous post, we discussed how to assess the current state of documentation in your company and concluded with the "so what" question: so, what if documentation is not great? Now is the time to start connecting good documentation to specific business metrics. Let’s start with revenue and website traffic.
Appearing trustworthy and reliable to both customers and investors
Consistent, error-free documentation makes a product look more reliable for both customers and investors and can serve as a powerful competitive advantage.
According to Google Product Discovery statistics, about 50% of all product discoveries happen through Google. And when people look for a specific feature or functionality, software documentation has more chances to pop up in searches than official marketing landing pages.
Branded, readable, well-designed quality documentation can become your product’s best marketing asset.
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It reflects a commitment to process and quality, which likely permeates through the rest of your product. This reinforces brand recognition and trust among your audience.
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It demonstrates a product feature set with a clear Table of Contents.
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It gives both in-depth knowledge and a product overview.
An intuitive Table of Contents goes beyond just listing sections; it provides a structured and easy-to-navigate system that guides users to the right information quickly. This helps users explore the product’s capabilities effectively and make informed decisions based on what they find.
The list above refers to only three aspects of documentation, but there are many more. Good documentation makes your product more valuable because it makes it easier to approach and use. Your users or customers will recognize this and be attracted to products with quality docs.
Enhancing search engine optimization and accumulating organic traffic
Creating documentation that addresses common user queries and challenges can significantly contribute to organic search traffic.
By developing tutorials, guides, and how-to articles that align with users' search intent, companies can improve their search engine rankings and accumulate organic traffic. For instance, a tech company could provide detailed guides on various solutions and technologies, even those that are open-source and non-commercial, drawing in users searching for relevant information. This not only boosts visibility but also presents opportunities to promote additional features and services, ultimately converting organic traffic into valuable leads and sales.
Business value can be achieved by introducing search engine optimization (SEO). This drives organic traffic to your website, which potentially will convert into business contacts.
To make documentation search engine optimization (SEO) friendly, consider the following best practices:
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Incorporate commonly searched keywords into titles, headings, and content.
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Use concise titles and meta-descriptions for clarity and better search ranking.
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Add links to other relevant articles and authoritative external sources to provide additional value and improve content credibility.
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Provide descriptive alt text for images to improve accessibility and help search engines understand visual content.
While these tips offer a starting point, you can read a more detailed exploration of search engine optimization best practices in the article Search engine optimization (SEO) for documentation.
Preparing documentation for the age of generative AI
The increasing prevalence of generative AI models introduces a new dimension to how documentation can be discovered and used. While traditional SEO focuses on making content discoverable by human users through search engines, optimizing for AI consumption involves making your documentation understandable and usable by these intelligent systems.
Interestingly, many of the principles that make documentation effective for humans also contribute to its AI readability. AI models will likely process clear, well-structured content with logical hierarchies and precise language more effectively.
It’s worth noting the emergence of initiatives like llmstxt.org, which proposes a standard for websites to communicate their preferences regarding the crawling and use of their content by Large Language Models (LLMs). This signals a growing awareness of the need for explicit guidelines for AI interaction with web content.
In this evolving landscape, many product companies are proactively considering how to make their documentation accessible to LLMs. One approach is to make documentation available through a Model-Context Protocol (MCP). While specific widely adopted standards are still emerging, the underlying idea is to provide a structured way for AI models to access and process documentation programmatically.
Another increasingly common practice is providing users with the ability to download documentation in Markdown format. This allows users or even internal AI tools to easily ingest and process the content manually to ground the LLM with context.
The nuances of AI and content consumption could easily warrant a dedicated post in the future. For now, keeping these initial considerations in mind will help ensure your documentation remains a valuable asset in this evolving technological landscape.
Text of article ©2025 Ravi Murugesan, Lana Novikova
Released under Creative Commons Attribution 4.0 International (CC BY 4.0)