AI for Marketing: The Rise of AI Search Engines in Self-Storage
AI Search Engines, such as ChatGPT, Gemini, Claude, and Perplexity, are gradually replacing traditional search engines. As a result, the rules for SEO in the self-storage industry are evolving. Optimizing for traditional search engines will not guarantee you high visibility anymore.
We have put together a little overview to help you make sure that your business continues to be visible and thrive in the ever-changing competitive marketplace:
Why AI Search Engines Matter
Searching for information in an AI Search Engine is fundamentally different from a traditional search engine. The average search query in Google is 4 words long. On ChatGPT, it is 23 words. The former is a question; the latter is a small chat. 70% of these queries have a unique intent. What we mean by that is: Customers ask AI Search engines to perform tasks that they would never or seldom ask of a traditional search engine. They can ask the AI to conduct research, provide recommendations, or even perform a complex analysis. Self-storage customers are likely to ask AI Search Engines for more complex tasks, such as:
Finding the best storage options near them.
Comparing features and prices of different operators in the area.
Requesting recommendations based on their specific storage needs.
If your business, like most in the self-storage industry, relies heavily on traditional search traffic, you will need to learn and play a brand-new game to ensure that you stay relevant. Remember, most customers go with the first self-storage operator they discover. To stay ahead of your competition, you need to consistently rank high in AI search results.
Optimizing For AI Search Engines for Self-Storage
In summary, to rank high in an AI Search Engine result, a business must:
Make sure their pages and brand enter the AI index – aka are crawlable by the AI bot.
Persuade the engine to retrieve those for relevant queries – aka signal trustworthiness and authority to the bot.
Pass the ranking/filtering stage – aka format content in a way that matches the longer-form queries in AI Search Engines.
We collected practical advice on how exactly you can achieve these three goals in the following section. :
Location-based Considerations
Self-storage is a location-specific business, so it is important to optimize for search queries with geographic relevance. For our industry, Google My Business and reviews in Google Maps will be one of the most important sources of information for the AI Search Engine. Therefore, it is crucial to maintain a strong presence, ensure detailed and up-to-date information about your storage site, and as many 5-star reviews as possible.
List Mentions
List mentions are one of the primary considerations in a ranking. Ensure that your brand frequently appears in different high authority "Best Storage for XYZ" or “Cheapest Storage in [City]” listicles and comparison posts about self-storage. It might even be worth it to pay to be featured in those, especially ones that compare storage businesses in your surrounding area. Make sure your business is regularly featured in publications or the website of your regional Self-Storage Association.
Website & Topical Authority
Domain authority is another measure. Ensure the overall site credibility of your page and maintain strong backlinks. Build measurable brand search volume by establishing your expertise. Even though AI Search Engines work differently from traditional Search Engines, ranking well on them will help your AI Search Engine Performance. Microsoft's 49% ownership of OpenAI means ChatGPT pulls from Bing results, and Gemini from Google. Only Gemini and the Apple Bot can deal with JavaScript. Websites with clean HTML markup will perform better. Your site should also be optimized for faster loading times. In other words, do not neglect existing SEO best practices. Optimizing for LLMs should happen on top of your current activities.
Trusted Affiliations
As mentioned above, you need to clearly establish and show subject matter authority on your website. Getting referenced on high authority sites, like reputable news sources, Self-Storage Association website, or user-generated content, will associate your brand with other credible brands and organizations.
This will help demonstrate E-E-A-T – Experience, Expertise, Authority, and Trust.
Online Reviews
When it comes to online reviews of your storage business, quality across multiple diverse sources beats quantity. Authentic and detailed reviews is what we want for a good ranking. Make sure that your business is also present on niche, industry-specific rating sites, and encourage your customers to leave their feedback there. Ideally, encourage them to write feature-focused reviews that an AI crawler can read and index.
We cannot predict how exactly AI Search Engines will develop and how much of the market share of traditional Search Engines they will take over. But they are here to stay, and the search volume going through them is increasing daily. Investing in an "LLM-friendly" online presence will most certainly generate leads for your business. In the very least, it will improve your current SEO.
How AI Search Engines Work (R-A-G)
Let's start with a little deep dive into how AI Search Engines actually work and deliver information.
Large Language Model (LLM)- creating content that is conversational, contextually rich, and structued to meet both humans and AI.
Retrieval-Augmented Generation (R-A-G) This process lets an LLM, look up information in real time, rather than relying only on the data it had access to during training. It can access new and verified content and generate an answer from that. The advantages are fewer hallucinations, better citations, and overall, more recent, relevant information for the user.
Let’s use the query “Give me the best climate controlled self-storage options in my city” as an example. In the retrieval stage, the system breaks down the user's query into several smaller questions. It then searches a database of self-storage listings. The system compares reviews, prices, and available unit options. Finally, it ranks the results by relevance and selects the top options.
Even the best LLMs have a so-called "knowledge cutoff" (that's when they stopped training it on new data). This is where the A for Augmenting comes in. The AI Search Engine can use the retrieved snippets to avoid this limitation and give the user more concrete and citable responses. In our example the system would look up updated rates, available unit types and sizes and the newest ratings.
In the final step, the model uses all of this to write an answer and present it to the user. Different from traditional search engines, which just output a list of websites, a response generated by an AI Search Engine can be a summary of information from multiple sources, formatted in a specific way, and even include citations if needed. To answer the user query, the AI Search Engine could provide the following response:
A list of facilities that offer climate-controlled units in the city
Current prices for various unit sizes, either as an average or a range
Notable features, like 24/7 access, security, etc.
Snippets from recent customer reviews
Currently, there are no ads in AI Search Engines yet, but we firmly believe that they will be coming soon and most likely play a role in the third step. Due to the personal nature of interaction between users and chatbots, these ads can be hyper-personalised, based on the information the model possesses about the user.