Part Three · Execution · Section 13
Measurement
The first task is to record the starting state before any activity scales, so that change can be read against a zero line.
13.1
Baseline now
No structured measurement exists today (Part One), so the first task is to record the starting state before any activity scales, so that change can be read against a zero line. The baseline captures the three dominance proxies from Section 1 through Ahrefs: share of category branded search, share of organic and direct traffic across the competitive set, and share of AI citations. Alongside them it records current enquiry and booking volume and their sources, the referring-domain profile, and search rankings. This is the line every later result is read against.
13.2
Why last-click attribution fails here
The purchase is considered, long and relationship-led, and referral is its main source (Part One). Last-click attribution credits the final touch, usually a branded search or a direct visit, and misses the brand-building and relationship work that created the demand in the first place. Judging the strategy that way would repeat the Part One error of reading channels through a signal that does not capture what they do. The integration principle sharpens the point, since a single film shoot or event feeds several channels at once (Section 12), and crediting the one channel where a booking surfaces misreads activity built to work across all of them. The measurement model is built instead on leading indicators and incrementality, read across the connected effort, and last-click attribution is set aside as the basis for decisions.
13.3
What to measure: three layers
Layer one
Mental availability
Share of search, the brand’s branded searches measured against competitors, stands as the behavioural proxy for how readily the brand comes to mind. The finding that share of search tracks and can lead market share comes from the work of Les Binet, and the strength of the link varies by category, so it is treated as a strong indicator and read with that limit in mind. Share of search carries particular weight here, because the audience is small and hard to reach, so a survey panel would return wide error, and a behavioural measure drawn from real search demand holds steadier. Where brand-tracking surveys are used, they measure the brand’s association with the category entry points (Section 8), and their sample limits are kept in view when the results are read.
Layer two
Physical availability
Ranking share, organic and direct traffic share, AI citation share, and the site’s enquiry rate show whether the brand is present and easy to reach when demand arrives. Two of these, traffic share and citation share, are also dominance proxies, so this layer and the north-star measures overlap by design.
Layer three
Business outcomes
Enquiries and their quality, bookings, revenue, and the contribution of referral become visible through the CRM. The CRM is the instrument that lets referral and relationship activity be attributed at last, which is the gap that left the earlier spend unreadable.
13.4
Incrementality and cadence
The question underneath all of it is whether the activity causes bookings. Small numbers and a long lag make classic conversion-lift testing hard, so the approach is staged.
Stage 01 · First
Leading indicators
Leading indicators that move faster than bookings, share of search and enquiry volume, are read first.
Stage 02 · Where volume supports
Holdout tests
Geo or time-based holdout tests are run where the volume supports them, turning a channel on in one region or period and holding another for comparison, with their limits stated honestly given the base rates.
Stage 03 · A later stage
Contribution modelling
Contribution modelling across the mix becomes possible once enough history exists, which places it at a later stage.
For the high-attention brand channels, the attention metrics from the media buys (Section 11) serve as a quality check on the inputs, read against brand-health movement over time.
Avoiding a claim of precision the data cannot carry.
The stance holds to measuring contribution and leading indicators, running incrementality tests where the numbers support them, and avoiding a claim of precision the data cannot carry.
Cadence: leading indicators monthly, the dominance proxies and brand health quarterly against the competitive set, and incrementality and contribution reviewed as the history builds.
13.5
Operational measures
The measures above track whether the strategy is working. A second set tracks whether the work is being done. These are the operational measures, the activity the team controls directly, and they move month to month while the outcome measures take longer to turn. They anchor the monthly review and hold the plan to a visible pace.
| Component | Operational measure | Cadence |
|---|---|---|
| Events and hospitality | Events hosted, guests attending, guest-to-enquiry conversion | Monthly |
| Partnerships | Active partnerships, new partnerships opened, joint activities run | Monthly and quarterly |
| The owned fleet | Content captured per sailing; hosted events aboard counted under events | Monthly |
| Digital PR | Placements landed, links earned, referring domains gained | Monthly |
| Brand and editorial PR | Features and placements landed | Monthly |
| Online video | Films and cut-downs published, delivery against attention benchmarks | Monthly |
| Podcasts and audio | Placements or sponsored episodes live | Monthly |
| Organic social | Posts published, follower and engagement growth | Weekly and monthly |
| SEO | Content published, keywords gained, rankings moved | Monthly |
| AEO | Content shaped for citation, citation share moved | Monthly |
| Referral | Referrals prompted and captured, referral-sourced enquiries | Monthly |
The target level for each, the number of events in a month or placements in a quarter, is set against team capacity and budget in Section 14, since the pace the plan can hold depends on the resource behind it.