Conversational Search and the role of video and structured data
Conversational search moves beyond keyword searches to natural language search including voice activated queries and interactions with chatbots.
The way users search for information is changing rapidly. Gone are the days of typing short, fragmented keywords into a search bar. Today, users are engaging in conversational search, asking questions, using natural language, and expecting precise, contextually relevant answers.
This is the beginning of human like interactions with search engines and devices, and follows on from the growing acceptance and use of voice assistants such as Siri, Alexa and Google Assistant, as well as through advancements in AI and natural language processing (NLP).
This presents both a challenge and an opportunity. How can you ensure your content including videos are discovered in this new era of search? The answer lies in a combination of good research to understand user intent, and in the use of structured data and schema markup to ensure the search engines understand your content.
Not surprisingly this development requires a fundamental change in SEO strategy and this post looks to explain some of the changes and how to adapt your strategy to succeed. We’ll explore conversational search, its impact on video discovery, and how schema can help your content stand out.
Key Characteristics
Conversational search refers to the way users interact with search engines using natural language, often in the form of questions or full sentences. For example, instead of typing “best pizza Manchester,” a user might ask, “Where can I find the best pizza in Manchester?” This shift mirrors how people communicate in real life, making search engines more intuitive and user-friendly.
Search engines have adapted to this trend by leveraging AI and NLP to understand the intent behind queries. They aim to provide direct, actionable answers, often pulling information from featured snippets, knowledge graphs, and video content.
Conversational Search as the name implies uses natural language, users speak or type as they would in a conversation. Search has contextual awareness, search engines consider user history, location, and intent.
Search can give direct answers and users often seek concise answers rather than just links to the point where many, many searches are now fully answered in an AI overview such as Google’s and drawn from one or more key authoritative pieces.
Long-tail keywords, such as “Where can I find the best pizza in Manchester?” are increasingly important as search is focussed on specific, detailed phrases rather than just broad terms. This may seem much more complicated than just identifying single key words but actually finding powerful phrases that answer queries will be much more fruitful and give far more opportunities to be found as you are no longer competing for a single word, the intent is now much more important too.
Conversational Search also offers multi-modal input, basically multiple modes of interacting with a system, incorporating voice, text, and images, again bringing more opportunities to get your content found.
Key Challenges
Optimising content for natural language queries is essential as is adapting to voice search and different devices.
Understanding user intent accurately is becoming increasingly important as users are learning to expect more accurate and better informed searches, and content needs to be targeted accurately.
Users are looking for concise information and relevant answers and the search engines can deliver that. Content that is seen as authoritative will be favoured, it is becoming increasingly important to concentrate on the quality of the content and how it is delivered.
Some search will of course still be transactional, whether the user is looking to make a purchase or complete a task, and local where they are searching for businesses or services in a specific area but this information needs to be clearly identifiable by search and the role of structured data in search is also increasingly important.
Embracing the Future of Search
Conversational search is reshaping the way users find and consume content online. For businesses, this means adapting to a more natural, question-based search environment. By leveraging schema markup, you can make your content and videos more discoverable, improve their visibility in search results, and align with the intent behind conversational queries.
Combine content and video and for conversational search, use the best practices for optimisation and focus on user intent and provide valuable content. Use natural language and long-tail keywords and optimise for voice search by using conversational language. AI can be used very effectively as a research tool to make understanding your customer intent cost effective and accurate. Monitor performance and adapt your strategy accordingly and success will follow.
