How AI can be used to make content more discoverable

Q: How?

A: The landscape has changed dramatically over the last year for digital publishers: the introduction of AI Overviews and AI Mode by Google, changes in which rich snippets are supported in Google’s search, growing reliance on Google Discover traffic as search traffic trends downwards, industry discussions on how to monetise AI crawlers, and the mainstream rise in the use of AI chatbots including OpenAI’s ChatGPT and Google’s Gemini.

Despite all these changes, the core principles remain constant. High-quality content, robust SEO strategies and a focus on content discoverability are key. There is additionally the challenge of more competition as new digital-only publishers emerge and also the different surfaces that content now appears on; eg. summarised in AI responses. This makes it more important than ever to ensure content is relevant, well-optimised, and regularly updated.

Search traffic is still the dominant source of traffic for most publishers and is likely to be so for the short and medium term. This makes it a good area to start with when exploring and testing how AI can help improve discoverability of content to gain advantage over competitors and also enhance internal understanding of the data a publisher has at a scale that can’t be achieved manually.

AI can help perform content audits using the data from Google Analytics, Google Search Console and other analytics software you may use to capture user behaviour. In the past, it would require manually carrying out keyword analysis and gap analysis, checking links between pages, monitoring evergreen content and updating when it’s outdated or needs refreshing, and flagging where there are content and topic gaps compared to competitors to discover new areas to focus on. Now, you can set up specific tools, or even work with general LLMs to get the basics in place to perform this analysis and go through entire archives of content to uncover topic authority, including by theme and synonyms, that would have taken multiple times the effort to do manually. On top of this, if the AI has access to traffic data, it can help predict likely traffic or, at least, audience demand and interest likelihood.

Next, after analysing the source audience and search data, the area of focus is on the content itself as it’s being created. For example, AI can help optimise headlines based on previous headlines that have done well from engagement metrics and ensure they match the editorial style guide. Also, AI can be applied to metadata, alt text on images, and reviewing content to ensure it meets the editorial style and is aligned with the brand’s topical authority.

Further optimisations can be offered after the article has been published. AI can generate smarter keyword and entity optimisation by using enhanced entity recognition to really understand what the article is about: both by overall sentiment and entity-level sentiment. By understanding the connection between the entities, including people, places and companies for example, AI tools can align the recommendations with the knowledge graphs used by search engines more effectively. This is key to ensuring the content can rank highly and therefore be discoverable not just in search but on other platforms including Google Discover.

Another recent hot topic is whether content should be tailored to the question-and-answer formats that have been reported as performing well in LLMs. Not every article can or should be written in this format, but it does highlight the importance of well-structured articles and the use of headings and subheadings where appropriate to present the content to the user in a clear format. Ultimately, the best way to ensure discoverability in any environment is to produce content worth discovering by human audiences. As soon as content becomes totally focused on keywords, gaming search engines and other platforms, it may have initial success but over time, the platforms will catch up and penalise sites that prioritise gaming algorithms over serving their readers.

It has recently started to become possible to monitor the impressions and clicks from AI platforms where content can be cited or referenced. This monitoring can enable insight into how and when the brand is being used. While still at an early stage, this is an area that will grow over the coming year and reporting tools will be adding capabilities to cover this.

A lot has changed recently, but the core principles of digital publishing have not. Producing high-quality content for your audience is key and can lead to greater engagement, subscriptions and return visits. AI’s real value is in supporting rather than replacing journalists, editors and SEO experts. Publishers who approach AI as an experiment, and iterate on those learnings are the ones already seeing measurable benefits.

Q: What are your three top tips?

1. Don’t let the technology take over the focus on high-quality journalism and content creation but use it to support the process
2. Traditional search is still an important source of traffic. Don’t completely turn off your focus on search and shift only to AI chatbots.
3. Don’t reinvent the wheel. There are a number of newsroom-friendly AI tools on the market to help with discovering opportunities to make your content discoverable in the constantly changing digital publishing world.

Bright Sites is a leading tech company producing innovative content creation systems and newsroom tools for publishers, including our flagship product, Flow, an AI-enabled publishing platform. Also, we make Storycue, which is a news gathering tool monitoring social and search and which presents unique opportunities for your publications based on your data and style guide.

Email: brian.alford@brightsites.co.uk

Tel: 07719 019091

Website: www.brightsites.co.uk

Website: www.storycue.com