You may know who your local competitors are, but how well do you understand how you stack up in the eyes of prospective customers?
As competition in the self-storage industry intensifies, it becomes more important to understand how nearby facilities are pricing, positioning, and presenting themselves. A competitive analysis can help you spot weak points in your own business, identify missed opportunities, and prioritize where to focus next.
In the past, building that kind of report could take days of manual research or require outside help. Today, AI can help operators do much of that work in a fraction of the time.
This guide walks through how to use a large language model, or LLM, such as ChatGPT or Claude, to organize public information, summarize patterns, and surface useful insights about competitors in your market.
Understanding the Limits of an LLM Competitive Analysis
Before you begin, it helps to understand what an LLM is and where its limits are.
An LLM is a type of AI trained on large amounts of text. That training allows it to recognize patterns in language and generate natural-sounding responses.
For competitive analysis, an LLM can act like a fast research and writing assistant. It can help organize information, summarize what it finds, compare themes across competitors, and turn messy notes into a more structured first draft.
That said, it still has limits. It can make mistakes, miss context, or present weak information too confidently. It also cannot visit competitor facilities, verify facts on its own, or replace the judgment of an operator who understands the local market. That is why it is important to review the output carefully and check the sources behind any meaningful conclusions.
Preparing Your Sources
Your competitive analysis will only be as good as the information you provide. Before you begin, identify the self-storage facilities within your trade area, typically within a 1-, 3-, or 5-mile radius of your location.
Next, create a simple source list for each competitor you want to analyze. In most cases, this should include links to:
- the facility’s main website
- its Google Business Profile
- customer reviews
- pricing or rental pages
- current promotions
- basic location details, such as hours, policies, and amenities
Be sure to include the same source list for your own facility for a thorough comparison.
As you review each source, pull the same types of information for every facility so your comparison stays consistent. The goal is not to collect every possible detail. It is to give the LLM a clean, structured snapshot of how each competitor presents itself and what customers seem to think.
Creating Your Competitive Analysis
Once your research is organized, you are ready to start prompting the LLM.
Step 1: Define the Competitive Question
Start with a clear, focused question such as: “How does my facility compare with the top five competitors listed below?”
If you want a narrower analysis, you can ask more specific questions, such as:
- How does my pricing compare with my top five competitors?
- How does my brand positioning compare with my top competitors?
- How does my customer experience compare with my top competitors?
Whatever you ask, make sure you give the model the information it needs to answer well.
Step 2: Paste in Structured Source Material
Below your question, paste in the source material you prepared earlier. Label each section with the facility name, and make it clear which one is yours. A simple tag like [my facility] works well.
The more structured and consistent your notes are, the better the output will be and the less likely the model is to drift into guesswork.
Step 3: Generate a First-Pass Summary
Before you submit your prompt, add a few instructions that tell the model how to handle the material.
Additional instructions:
- Summarize each competitor
- Identify strengths and weaknesses
- Highlight differences in pricing, messaging, and convenience
- Flag anything unclear or missing
Your complete prompt should include your opening question, your source material, and your additional instructions. Once those are in place, send the prompt and generate an initial draft of the analysis.
Step 4: Ask for a Comparison Table
Your first result may be thorough, but it can also be longer than you need. If so, ask the model to tighten it up or highlight only the most important findings.
Better yet, ask it to organize the findings into a table with columns such as:
- Facility name
- Price positioning
- Website quality
- Promotions
- Reputation
- Standout features
- Risks to your facility
This gives you a quick, high-level view of the competitive landscape and makes the analysis easier to use.
Step 5: Ask for Strategic Takeaways
One of the biggest advantages of using an LLM is that the analysis does not have to stay static. You can keep asking follow-up questions to dig deeper.
Prompt the model to answer questions such as:
- Where are competitors stronger?
- What customer needs are not being addressed well?
- What should my facility emphasize more in its marketing?
- What should be reviewed manually before making decisions?
You can also rerun the same analysis on a monthly or quarterly basis and ask the model to highlight any changes or emerging trends.
Example Prompts
Another advantage of using an LLM for competitive analysis is that you can keep refining the output with follow-up prompts. If the first response is too broad, too long, or not focused on the issue you care about most, ask the model to rework it. The key is to be specific.
Below are a few simple prompts operators can copy, paste, and adapt.
Prompt for Competitor Summaries
Use this when you want a straightforward overview of each facility in your comparison set:
“Using the source material below, summarize each competitor facility in 3 to 5 bullet points. For each one, highlight its apparent strengths, weaknesses, target customer appeal, and any notable differentiators. If anything is unclear or missing, flag it.”
Prompt for Pricing and Promotion Comparison
Use this when you want to understand how your pricing strategy compares with what nearby competitors are advertising:
“Compare the pricing and promotions of the facilities listed below. Identify which competitors appear to be competing on price, which are using aggressive move-in offers, and where my facility appears more or less competitive. Present the findings in a concise table.”
Prompt for Review Sentiment Analysis
Use this when you want to understand how customers talk about each facility and what patterns appear across reviews:
“Review the customer feedback provided for each facility and identify the most common positive and negative themes. Pay close attention to comments about customer service, cleanliness, security, ease of rental, billing issues, and overall satisfaction. Then explain how my facility compares.”
Prompt for Positioning and Messaging Gaps
Use this when you want to see how competitors are presenting themselves and whether there are any missed opportunities in the market:
“Analyze the messaging used by each facility on its website and promotional materials. What themes or value propositions come up repeatedly? What customer needs are being emphasized most? Are there any important needs, concerns, or differentiators that competitors are not addressing clearly?”
Prompt for Recommended Next Actions
Use this when you want the LLM to move beyond description and suggest practical takeaways.
“Based on the competitive analysis above, identify the three to five most important actions my facility should consider next. Focus on areas such as pricing strategy, website messaging, promotional offers, customer experience, reputation management, and local positioning. Separate high-confidence observations from anything that should be reviewed manually.”
The best prompts are specific, constrained, and tied to a clear business objective. Instead of asking the AI to “analyze my competitors,” tell it exactly what kind of analysis you want and how you want the answer delivered.
Turning Insights Into Action
Once the LLM generates your analysis, look for the patterns that matter most. Pay attention to how competitors are pricing their units, how often they rely on generic marketing language, where they are building trust well, and where they are not. Also look for missed local SEO opportunities, such as weak location-specific messaging, thin Google Business Profiles, or poor visibility for relevant local search terms. Reviews are especially useful here because they can reveal the gap between what a facility claims and what customers actually experience.
From there, turn those observations into action. Use the findings to refine your website messaging, promotional strategy, paid search copy, review response approach, follow-up communication, and even sales scripts. A simple framework is to fix what is weak, match what has become table stakes, and differentiate where competitors are sounding the same.
Ask the model you have created for 5-10 actionable steps to take moving forward. Review the results, apply your best judgement as an operator, and move forward with those that resonate the most.
Common Mistakes to Avoid
Before you start overhauling operations or changing your marketing strategy, make sure you avoid a few common pitfalls:
- trusting the AI without checking source material
- feeding it incomplete or inconsistent inputs
- asking for conclusions without defining the business question
- treating a one-time scan as a full market strategy
- copying competitor claims instead of differentiating clearly
It can also be useful to run the same prompt through more than one LLM and compare the results. If you see major contradictions, that is usually a sign that you need to review the underlying material more closely. Some tools are also better than others at staying objective, so treat the output as a starting point, not a final answer.
Start Small and Stay Practical
You do not need a data science team or a complicated tech stack to get real value from AI. Used well, an LLM can make competitive research faster, more organized, and easier to act on.
The key is to stay practical. Start with one facility, one market, and one narrow question. From there, you can refine your process, improve your prompts, and build a clearer view of where your business stands.
To explore more practical AI use cases for self-storage operators, visit Storable’s AI hub.
