NORA search results? How Google is thinking about AI-powered search

Following on the heels of their first Bard announcement, Google held another one on Wednesday where they gave some insight into the kinds of search results that AI will be best-suited to provide.

Fitting with Google’s long-standing affinity for acronyms, they’ve called this concept NORA.

NORA stands for “No One Right Answer” and refers to the kind of response best suited to a question that has - you guessed it - no one right answer.

So, an example would be a search query like “what are some great places to get coffee within 5 minutes of here?” … anything where the answer is contextual, contested, subjective, or dependent on a range of factors.

Google has been using AI and machine learning to understand these sorts of queries for some time (at least since BERT), especially with voice search making them more common, but now AI is going to be used to formulate the answers.

So what do you think…is there going to be a way to optimize for NORA results? What kinds of NORA-questions are most common in real estate?

I think optimizing for NORA results means further targeting for your audience, rather than general traffic. If Google keeps pushing the concept of not creating content specifically targeting search engines, then all SEO specialists and content creators alike can continue to do is create content as dedicated to their user base as possible.

This, mixed with quality content that’s also relevant and unique, and falls within the many factors Google may be ranking it based off of, is the only way forward.

With the many updates that Google has put out, intent seems to be at the core of much of the ranking processes that Google continues to uphold. If there is “No One Right Answer”, we still want to be achieving one of the best right answers there could be.

The concept of NORA - “No One Right Answer” - is an interesting development in the field of AI-powered search. It acknowledges that some search queries cannot be answered definitively with a single correct response and require a more contextual, nuanced approach to provide a satisfactory answer. This is particularly relevant for real estate search queries, where factors like location, price range, and personal preferences can greatly influence the outcome of a search.

While it may be challenging to optimize for NORA results, there are certain steps that businesses in the real estate industry can take to increase their chances of being featured in these types of search results. For example, providing detailed and comprehensive information about a property, including its location, amenities, and unique features, can help to contextualize a search query and provide a more personalized and relevant response.

In terms of the most common NORA-questions in real estate, these are likely to be queries that are subjective or contextual in nature, such as “what are the best neighborhoods for families?” or “what are some affordable yet stylish apartments in the city center?”. By using AI and machine learning to understand these types of queries and formulate appropriate responses, search engines like Google can provide more accurate and useful search results for users.

Overall, the development of NORA in AI-powered search is a positive step towards providing more personalized and contextual search results. While it may require some adjustments to current search optimization strategies, businesses in the real estate industry can benefit from the increased focus on personalized and nuanced search results.

I wonder if there will even be something like “optimizing for NORA results”. If anything, it’s unlikely to be “provide a comprehensive answer to the question”, since what the AI is trying to do is draw in a bunch of different sources, so it’s unlikely that it’ll lean on a single source, no matter how nuanced and open-ended.

For example, if someone asks “What is the best music for parties?”, the AI will probably try to draw together a bunch of different answers, emphasizing the importance of individual taste, guests, nature of the party etc. It probably won’t report verbatim an answer like that if it appears in one source. Rather, I think if you give a clear answer + context, that will be more likely to appear with - hopefully - a reference note. So your answer should be something like “Classical music is a great choice for a formal party where guests are expected to mingle and make conversation”.

Summary: I think appearing in NORA results won’t be about providing comprehensive nuanced answers, but rather 1 clear answer + context.

Optimizing content for NORA might involve:

  1. Providing a clear and concise answer: Giving a straightforward answer that is easy to understand can increase the likelihood of your content being considered by AI systems like NORA.
  2. Adding context: Explaining the rationale behind your answer, offering examples, or elaborating on the factors that influence the answer can help make your content more valuable to AI systems.
  3. Acknowledging different perspectives: Recognizing that there may be other opinions or viewpoints on a topic can show that your content is well-rounded and open-minded, which may make it more attractive to AI systems that prioritize diverse perspectives.

Ultimately, it is essential to remember that AI systems are continually evolving and improving, and the strategies for optimizing content to be more visible in their results may also change over time. As these systems advance, content creators will need to adapt to new techniques and best practices to maximize their visibility and relevance.