AI search optimization: a step-by-step plan for a software company
By Outnamed · Updated
Key points
- Start from the questions your buyers ask, not from keywords.
- Measure before you change anything, and ask each question many times, because assistants rarely give the same list twice.
- Publish pages that answer one buying question each, using facts only you can state.
- Check the review and community sites buyers read, because assistants may draw on them too.
- Repeat the measurement every month, since assistants and their answers change over time.
Why does a software company need a plan for AI search?
Software buyers already use AI assistants to build shortlists. In the G2 Buyer Behavior Report from June 2026, covering 1,000+ software buyers, 8 in 10 software buyers used an AI chatbot to find recommendations in the last two years.
The same G2 report says 37% of buyers say chatbots shape their shortlist most, level with review sites at 38%. So a shortlist can be formed in a chat window before anyone visits your website.
That is the reason to work on this deliberately. The plan below has six steps. It does not depend on any one assistant, because how each assistant picks companies is not public, differs between them and changes over time.
Step 1: which buying questions should you list first?
A buying question is a question a buyer types when they want a recommendation, such as which tool fits their team or which option suits their situation. Write down 10 to 20 of them before you do anything else. Use the exact words buyers use, taken from sales calls, support tickets and review text.
- Category questions: the best type of software for a given team size or industry.
- Comparison questions: your product against an alternative, or two alternatives to each other.
- Problem questions: how to solve a specific task your product handles.
- Fit questions: whether a product works with a specific tool, rule or setup.
- Switching questions: how to move away from a product you replace.
See where you stand, free
Enter your website. You see what customers say about you, how you compare with the competitors people pick instead, and what to fix first.
Step 2: how do you measure where you stand today?
Ask each question in ChatGPT, Claude, Gemini and Perplexity, and record which companies are named. Do it many times. Assistants rarely give the same list twice, so one screenshot of one answer tells you very little. Around thirty runs per question gives you a share you can compare month to month.
Turn the results into one simple number per question: out of all runs, how often was your company named? Also note who is named instead of you, and whether the assistant cited a source. Use the same wording and the same settings each month, so changes mean something.
You can do this by hand in a spreadsheet. Outnamed does the same thing automatically, through the assistants' official programming interfaces with web search switched on, and counts who is named.
Step 3: what should your own website say?
For each buying question, publish one page that answers it directly in the first two or three sentences. Then back the answer with facts only you can state: what the product does, who it is for, what it does not do, which integrations exist, how setup works and what limits apply.
Be specific and keep each claim checkable. A page that says what you are not a fit for is more useful to a buyer, and easier for an assistant to quote accurately, than a page of general praise.
Make sure the pages can be read. Put the answer in plain text on the page, not only in images or scripts, and check that your site does not block the crawlers of the assistants you care about. Which crawlers each assistant uses, and how it uses a page, is not fully public and can change.
- Pick one buying question.
- Write the direct answer in two or three sentences.
- Add your own facts, figures and limits that support it.
- Add the follow-up questions a buyer would ask next.
- Have someone who knows the product check every claim before it goes live.
Step 4: which outside sources should you check?
Assistants with web search switched on may draw on more than your site. Buyers also read review and community sites, and the G2 figure above shows review sites matter nearly as much as chatbots for shortlists. Which sources a given assistant uses for a given question varies, so look at what the answers actually cite.
Check how your company appears on G2, Capterra, Trustpilot and Reddit. Look for wrong product descriptions, missing categories, old feature lists and repeated complaints. Fix what you control, and answer reviews honestly. Do not write fake reviews or post disguised promotion in community threads.
- Is your product description on each profile current and accurate?
- Is your product listed in the categories buyers search?
- What do reviews say most often, good and bad?
- Which competitors are named next to you, and for what reasons?
Step 5 and 6: how often should you update and measure?
Review your pages and your measurement every month. Product details change, assistants change, and the answers shift with them. Update the pages that went stale first, then add pages for questions where you are never named.
Compare each month with the one before, question by question. If a number rises, check what changed, but do not assume your page caused it, because the assistants change their behavior without notice. If it falls, check your facts and your sources before rewriting everything.
Outnamed runs this cycle for customers: it writes one answer page per buying question from the customer's own facts, the customer approves each page before it goes live, earlier pages are updated every month, and a monthly report shows the measurement.
What results can you expect from AI search optimization?
Nobody can say, and anyone who promises a mention, a position or a timeline is guessing. The assistants decide what to name, and they do not publish how.
There is one data point on the size of the channel. Ahrefs reported that, in its own traffic over 30 days, visitors from AI search were 0.5% of traffic and 12.1% of sign-ups. That is one company's traffic, not a benchmark for yours, but it shows why a small share of visits can still matter.
Treat the work as measurement plus useful pages. The pages help buyers who find them in any way, so the effort is not wasted if an assistant never names you.
| Where | What to do | How to check |
|---|---|---|
| Your website | One answer page per buying question, with your own facts | Does the page answer the question in its first two or three sentences? |
| Review sites | Correct profiles, categories and descriptions; answer reviews | Does each profile match your current product? |
| Community sites such as Reddit | Answer questions openly as the company, without disguise | Are threads about you accurate? |
| The assistants | Ask each buying question about thirty times and count names | Is your share higher or lower than last month? |
Questions people also ask
How long does AI search optimization take to work?
Nobody knows. The assistants do not publish how or when they pick up changes, and it differs between them. Measure monthly and judge the trend over several months, not one result.
How many buying questions should you start with?
Start with 10 to 20 real questions your buyers ask. That is enough to see patterns without turning the work into a project you never finish. Add more once the first pages are live and measured.
Can you do AI search optimization without a tool?
Yes. You can run each question by hand across the assistants and log the results in a spreadsheet. It takes time, because each question needs many runs to be reliable. A tool mainly saves that repeat work.
Should you block AI crawlers on your site?
That is your decision, but know the trade-off. If an assistant cannot read your pages, it cannot use them as a source. Which crawlers each assistant uses and how they behave is not fully public, so check the current documentation from OpenAI, Anthropic, Google and Microsoft.
What if a competitor is named instead of you?
Look at why a buyer would pick them: which facts, reviews or sources appear in the answers. Then make sure your own pages and profiles state your strengths and limits just as clearly. Do not copy their wording, and do not expect one change to flip the result.
Related guides
- AI brand monitoring: how to track what AI assistants say about you
- AI visibility tool: what it measures and what to check before paying
- What is answer engine optimization (AEO)? AEO vs GEO vs SEO
- What is generative engine optimization (GEO)?
Sources for the figures on this page: G2 Buyer Behavior Report, June 2026 (1,000+ software buyers); Ahrefs, own traffic over 30 days. These are their figures, not a forecast for your company. Outnamed does not promise a mention: the assistants decide. First published October 7, 2026.