M
Market
The number of relevant buyer decisions made in your category each year.
THE MAXIFI MODEL · REVENUE AT RISK
How much revenue is at risk when AI engines don't cite your brand?
Buyers now ask AI before they shortlist. When those answers name your competitors and not you, the cost is real — and it can be calculated, not guessed.
THE DEFINITION
What "revenue at risk" means
Revenue at risk is the annual value of buyer decisions influenced by AI answers that cite your competitors instead of you — calculable, per the MAXIFI model, from six numbers a business already has.
The behaviour behind the number is documented. Forrester's January 2026 buyer research found that 94% of B2B buyers now use generative AI during the purchase process, and 54% call AI chatbots the single biggest influence on their shortlist (Forrester · Jan 2026). If AI answers shape the shortlist and those answers don't cite you, part of your pipeline is being decided before you know the conversation happened.
THE MODEL
What is the MAXIFI model?
The MAXIFI model values AI visibility by multiplying six factors — each one a number your business already has, or can agree in one conversation.
A
Ask-AI
The share of those buyers who consult AI engines while researching. Forrester (Jan 2026) found 94% of B2B buyers now use generative AI in the purchase process.
X
eXposure
Your citation share — the proportion of relevant AI answers that name your brand.
I
Influence
The agreed rate at which an AI answer influences the shortlist or decision. Forrester (Jan 2026) reports 54% of B2B buyers call AI chatbots the single biggest influence on their shortlist.
F
Finish
Your close rate — the share of influenced decisions your business actually wins.
I
Income
The average value of one won decision, from your own records.
AI-influenced revenue per year
M × A × X × I × F × Income
Revenue at risk — the citation gap variant
M × A × (Xcomp − Xyou) × I × F × Income
Replace your exposure with the gap between competitors' citation share and yours: the value flowing through answers you are absent from.
Break-even on an engagement
fee ÷ (F × Income)
The number of AI-influenced decisions needed to pay back the fee.
DEFENSIBILITY
Where do the numbers come from?
Your figures come from your records; the influence rate is agreed, never asserted.
Every output of the model is labelled by how defensible it is. There are three tiers:
01
Measured
Every input comes from your records or a live citation audit. Nothing is estimated. This is the strongest tier and the standard we work towards in every engagement.
02
Modelled
Some inputs are agreed assumptions where records do not yet exist — always stated as a range, never presented as fact. Worked examples on this page are Modelled.
03
Momentum
Directional and forward-looking: the compounding effect of citations earned today on answers generated tomorrow. Used to frame trajectory, never to justify a fee.
WORKED EXAMPLE · MODELLED TIER
What does this look like in practice?
A worked example built around CANSO's Airspace World — the global air traffic management event — using agreed, conservative-to-base assumptions (Modelled tier). The model produced a band of AI-influenced value per year:
Conservative inputs
≈ $24,000/yr
Base-case inputs
≈ $143,000/yr
Pilot engagement fee
$4,900
On those inputs, the $4,900 pilot breaks even at roughly a third of a single exhibitor decision. The band is Modelled, not Measured: the assumptions are agreed with the client, stated as ranges, and replaced with recorded figures as the engagement produces them.
COMMON QUESTIONS
Frequently asked questions
How much revenue is at risk when AI engines don't cite your brand?
Revenue at risk is the annual value of buyer decisions influenced by AI answers that cite your competitors instead of you — calculable, per the MAXIFI model, from six numbers a business already has. In the aviation-event worked example above (Modelled tier), the band ran from roughly $24,000 to roughly $143,000 per year against a $4,900 pilot fee.
What is the MAXIFI model?
The MAXIFI model is Maxifi Digital's framework for valuing AI visibility. It multiplies six factors — Market, Ask-AI, eXposure, Influence, Finish, and Income — to estimate the annual revenue influenced by AI answers. The revenue-at-risk variant swaps your exposure for the citation gap between competitors and you.
How do you calculate break-even on an AEO engagement?
Break-even equals the fee divided by (Finish × Income): the number of AI-influenced buyer decisions needed to pay back the engagement. In the worked example, the $4,900 pilot broke even at roughly 0.3 of one exhibitor decision.
Where do the numbers in the MAXIFI model come from?
Your figures come from your records; the influence rate is agreed, never asserted. Every output is labelled Measured, Modelled, or Momentum so it is always clear how firm each number is.
START WITH THE X
The model needs your citation share. Measure it first.
The free Visibility Snapshot tests real buyer questions across five AI engines and scores where you stand today — the eXposure number the model runs on.
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