Want a Successful Conversational AI? Incorporate SEO from the Start🤓

Table of contents:

1. The future of Search
2. Conversational AI and SEO: concrete steps
3. A real use case: From Google search to WordLift’s AI powered chatbot
4. Takeaways

Conversational AI has been part of the enterprise landscape since 2016, but it has entered the scene in pandemic times. It has supported customer service and provided content suggestions to help businesses and people through difficult times.

In this scenario, it has become increasingly necessary for enterprises to invest in developing conversational AI to cope with changing user behavior. Conversational AI is therefore among the top 5 categories in AI software spending and its evolution from simple rule-based bots to intuitive chatbots that can accurately mimic human responses by providing assistance to customers and company employees. 

So the evolution of user behavior has also led to a change in how search engines work. Google search is increasingly becoming a dialog. The advancement of conversational search inevitably affects SEO. In this article, I’ll show you how you can build a Conversational AI by using SEO to provide users with an optimal experience that increases the number of visits and the time users spend on your site.

The Future Of Search

Search could be reimagined as a two-way conversation with question answering systems synthesizing and answering users’ questions much as a human expert.

Metzler, Donald, et al. “Rethinking search: making domain experts out of dilettantes.” ACM SIGIR Forum. Vol. 55. No. 1. New York, NY, USA: ACM, 2021.

Today, when you do a Google search, you get results appearing in different Google rankings and features: SERP, top stories, People Also Ask, Google Knowledge Panel, etc.

Thanks to conversational AI, search will take the form of a dialog between the user and the search engine, which is not only able to answer a query, but also to anticipate the user’s wishes. 

If you own a website or are an SEO, then you need to be able to fit into this workflow.
In “traditional” search, SEO was required to:

• Rank at the top of Google’s search results for target queries, e.g., “GPT-3”.
• Earn a knowledge panel in Google’s Knowledge Graph for your business, people, products, etc.
• Rank relevant video content on the first page for target queries.
• Answer specific questions to be featured in the People also ask (PAA) section.

With conversational AI, the plan of action changes, and to make this happen, it is necessary:

• Win the SERP competition for target keywords.
• Provide a great user experience on your website.
• Make it easy for users to find the right content (UI, navigation, search functionality, chatbot, ..).
• Optimize for user retention whenever the information is available on your website.

For this to be possible and for you to get into conversational search, you can use your content. By storing your data in the Knowledge Graph, you can make your content accessible and reusable for developing a conversational channel such as a chatbot.

Building a conversational AI channel on your website is crucial in taking advantage of the opportunities and benefits of interacting with your customers. This will allow you to leap ahead and gain a significant competitive advantage over your competitors.

But let’s go through the concrete steps that will help you build a successful conversational AI starting from SEO.

Conversational AI and SEO: Concrete Steps

In this scenario, SEO plays a crucial role. How can you build a successful conversational AI ? To do so, you need to follow the steps below.

1. Build your Knowledge Graph. In this way, you can leverage the power of entities and the relationships between them to provide Google with all the information it needs to understand your site content and to provide users with results relevant to their search queries.
2. Earn a Knowledge Panel. Through it, Google provides quick and reliable information about people and brands. Getting a Knowledge Panel on Google depends on the data. The more accurate and consistent they are, the more accessible Google will put the information together and return a perfect Knowledge Panel.
3. Use the VideoObject. Adding Schema Markup’s VideoObject feature, you can use video as a magnet to attract traffic to your content by building irresistible, clickable snippets.
4. Use FAQ Schema Markup. FAQPage structured data format can help you increase the footprint of your results on the SERP.

Having a bot and having the KG + FAQ you can deliver a better user experience to the users on the website itself (and eliminate the requirement to go back to Google to search for another info).

A Real Use Case: From Google Search To WordLift’s AI-Powered Chatbot

WordLift is replicating what Google is doing (at the scale of a single website).

• Leverages the same data published on the website
• Creates a chatbot on top of transformer-based models

In terms of information retrieval, a chatbot works like a search engine. So what I do for Google will improve my chatbot (and my internal search). The same content we prepare for Google can also be used to train an artificial intelligence for conversations like a chatbot. And that’s exactly what we did to develop the chatbot for our documentation.

We trained our chatbot using Jina AI DocsQA’s q-a service and we extended its knowledge by adding to the indexing flow also FAQs (question and answer pairs) from our knowledge graph. Structured data content (such as FAQPage markup) is available using WordLift GraphQL end-point.

In this example, you can see how to take ownership of the user journey with WordLift.

Case 1: Google directly provides the answer to the question/search query. It’s the
top page result.

Case 2: Google returns the passage that talks about GPT-3 in the article about generation product descriptions.

Case 3: Google displays the questions/answers that are added as FAQ schema markups to the article.

Developing a chatbot like WordLift’s that can replicate Google’s responses has many benefits:

• Improve the user experience by providing answers to their questions
• Avoid losing a user we worked hard for by keeping them on the site once we have an answer.
• From an analytical point of view, increase the number of users visiting the website and increase the time spent on the website (if this happens, it means that we serve users better).

Takeaways

• Rethinking Search. Search can be reimagined as a conversation.
• Two visions. Know-it-all AI vs. relevant and accurate information.
• No additional effort. Same content that is created to support Google ranking and visibility can be used to train an AI to converse like a chatbot.
• Multibot orchestration. Stack of bots, master bot and bot grouping.
• Personalization. Era of hyper personalization for users and for businesses.
• Multimodality. Enable text, image, videos, etc. in a single query.

To know more about how Conversational AI meets SEO, watch the video👇