Performance and Score Based Models Both sound aligned and both create problems. Payment tied to mentions creates pressure to shape the prompt set toward questions you already win, which is measurable improvement that means nothing.
Ask who specifically will do the work, and ask to meet them. Capability in this field is thinly distributed and frequently sits with one or two people inside an agency of any size. A pitch delivered by a strategist who then hands the account to a junior is common enough to be worth checking for directly, and the question is easy to ask without giving offence.
A retainer describing ongoing optimisation and strategic guidance with no countable deliverable is a subscription to a relationship. It may still be worth having, and you should know that is what you bought.
If your category still gets meaningful traffic from those, a proposal scoped only to assistants will leave that work undone. Conversely, if somebody proposes an answer engine optimization programme and delivers only snippet optimisation, they are working on the older half of the definition.
A reasonable rule for planning a content programme is to publish fewer pages and maintain them properly. Twenty pages carrying current figures will out-earn a hundred that were correct on the day they shipped, because freshness is weighted and stale specifics actively cost you. Most teams discover this by building the hundred first, then finding they cannot review them and quietly letting the whole set go out of date.
Finally, pay attention to how they talk about their existing clients. Somebody who describes a client's category accurately, names the specific constraint that made the work difficult, and mentions something that did not work has actually done the job. Somebody who describes every engagement as a success in identical language has either been unusually lucky or is describing a template.
The risk is scope drift into activity that is easy to report and hard to value. The protection is to have the retainer specify countable units: prompt set runs per month, listings audited, corrections submitted, pages published or rewritten, outreach attempts made.
The version that fails is the vendor comparison where every row favours the publisher. It is transparent to readers and useless as an impartial source, which is why it appears in citation lists far less often than its authors expect.
This is where the two disciplines meet. Work done to make pages quotable for assistants tends to help here as well, because the underlying problem is the same. A model is looking for a passage it can lift and attribute.
The caveat is that most published question sections are marketing in disguise, containing questions no customer has ever asked, phrased to permit a favourable answer. Those get ignored, and they are easy to spot.
Where the Distinction Does Matter One place, and it is worth being alert to. Read broadly, answer engine optimization includes surfaces that are not generative at all, such as featured snippets and structured result features.
Expect the vocabulary to keep shifting, and expect new terms to arrive with each wave of positioning. The underlying work has been stable since these systems started retrieving live sources, and it is the work rather than the name that you are buying. get recommended by ai
Be wary of proposals where the largest line is content production. It is the easiest work to scale, the easiest to bill and the least likely to be the constraint, particularly before a baseline exists. A proposal weighted toward diagnosis, technical fixes and third party corrections is usually cheaper and almost always sequenced better.
The truthful answer is that different parts of the work move at very different speeds, and knowing which is which lets you judge an engagement at the right moment instead of the convenient one. get recommended by ai
If the budget is substantial, add the earned coverage work, which is the slowest and most expensive component and the one you genuinely cannot do quickly on your own. Buying that first, before the cheap fixes are done, is the most common way money gets wasted in this field. get recommended by ai
Generative Engine Optimization The broadest of the three in common use. It refers to being visible in systems that generate an answer rather than returning a list, which covers assistants, AI summaries on results pages and any interface that synthesises rather than links.
Existing reputation helps disproportionately. A brand with review volume, press history and consistent details is starting from a partly assembled record. A brand with none of that is building identity from scratch, and identity work is slow because it depends on re-crawling sources you do not control.
One overlooked cost is your own time. Every engagement in this field needs somebody inside the business to confirm figures, approve crawler changes and answer factual questions, and a plan that assumes this is free will stall. Budget a few hours a month explicitly and name the person, because the alternative is an agency waiting on answers and billing for a month in which little shipped.