Benchmarking Competitors in AI Answers: A Practical Scorecard

Pick the field

Choose three to five competitors. Include the one you lose deals to most often, the one with the biggest marketing budget, and at least one smaller company that seems to punch above its weight in AI answers. The last one is often the most instructive, because it is usually winning on page quality rather than brand size.

Do not include twenty. The scorecard gets unreadable and the weekly run gets expensive. If the category is crowded, benchmark a core group and track "any other company" as a single bucket.

Run the same prompts

Use your existing prompt set, the one built from real buyer questions, and score every company on every prompt. Do not build a separate set per competitor. The point is to see who the engines pick for the questions that matter to you, under identical conditions.

For each prompt, each engine, each run, record which companies were mentioned, in what order, which pages were cited, and what sentence was attached to each name. The sentence is the part people skip and it is the most useful thing in the dataset.

The scorecard

Five columns, one row per company, computed per engine and in total.

Mention rate: share of answers that name the company.

Citation rate: share of answers that link to a page on the company's domain.

Position: average place in the list when mentioned. Being named first in a list of five is different from being named fifth.

Source presence: share of cited third-party sources, the review sites and lists and threads, that include the company. This is the column that explains the others.

Description: the most common phrase the engines attach to the company. "Enterprise-grade, expensive" and "cheap and simple" are both positions. You want to know which one you have and which one you want.

Share of answer, as AEO GEO Labs reports it, is a weighted combination of the first four, but the raw columns are more useful for deciding what to do.

Reading the gaps

A competitor with a high mention rate and low citation rate is coasting on brand. The engines know them but are not reading their pages. You can beat them on citations fast with pages written to be quoted, and over time the mentions tend to follow.

A competitor with high citation rate and low mention rate has good pages and a weak entity. They will probably fix that eventually. Until then, their pages are a useful model for what the engines in your category like to cite.

A competitor who dominates source presence is in all the lists and threads. That is the hardest gap to close and the most durable advantage. The work is being in those sources yourself: real reviews on the sites that get cited, honest participation in the community threads, inclusion in the roundups. No shortcuts here. Paid placements and planted reviews tend to get recognized and tend to hurt.

A competitor with a better description than yours has a positioning edge. Compare the phrase the engines use for them with the phrase on their homepage. It usually matches. Then compare yours. If the engines describe you with words you would never choose, your own pages are not supplying a better sentence.

Keep it moving

Run the scorecard weekly alongside your own tracking. Most columns move slowly. Position and description are the ones to watch, because they tend to shift before mention rate does. When a competitor's description changes, go find the new page that caused it. It is usually a recent rewrite of their comparison or pricing page, and it is a direct lesson in what the engines picked up.

Build the first one this week

Three competitors, your existing prompt set, one run per engine, five columns. It will take an afternoon and it will reframe the whole program from "are we visible" to "where exactly are we losing and to whom." If you want it built and maintained with a weekly read, AEO GEO Labs includes competitor benchmarking in every audit.