Making the next opportunity visible.

Campaign activity was distributed across markets, internal teams and agency partners, and the status of that activity was not always represented consistently in the existing reporting.

A campaign might have been booked but never launched, which meant planned activity could make a market appear more active than it really was.

Without a consistent view of genuine adoption, it was difficult to see which markets were established, where activity was stalling and where meaningful whitespace remained.

The first step was establishing the fields required to understand activity properly, including market, agency, campaign status, booked value, launch status, product usage and timing.

I then worked with the data team to bring those inputs into a central cross market view that distinguished activity that had merely been planned or booked from activity that had genuinely launched.

This gave the account team a repeatable way to understand adoption across the organisation and created a common view of what “active” actually meant.

Campaign and financial reporting relied on structured data and deterministic rules, but some of the information surrounding those records was less consistent.

Campaign names, market references, agency naming conventions and free text status descriptions could vary between sources, making it harder to analyse activity cleanly across the entire account.

I used AI assisted classification to help normalise ambiguous records into consistent categories before they entered the cross market view, while the structured reporting remained the source of truth.

The same approach helped surface recurring patterns, including markets where campaigns repeatedly reached booking but failed to launch, giving account teams a clearer starting point for understanding where adoption was getting stuck.

At the beginning of the programme, meaningful live activity existed across 16 of the 27 markets.

Among the remaining markets, some had demonstrated interest but had failed to activate, while others showed little meaningful adoption. That distinction mattered because a market with evidence of previous intent presented a different growth opportunity from one where the relationship was still at an earlier stage.

Once those differences were visible, we could prioritise markets based on the evidence available rather than treating every inactive market as the same kind of whitespace.

The number of markets with active campaigns increased from 16 to 23, representing a 44% increase in the number of active markets.

Across the 27 market opportunity, that moved active penetration from 59% to 85%.

The new workflow also reduced the time required to reconcile global activity by approximately 90%, turning a process that previously consumed several hours each week into a view that could be reviewed in less than 30 minutes.

The visibility also changed how we could think about growth within the account. We could see where adoption remained incomplete, understand the nature of the gap and make a more deliberate decision about which markets represented the strongest opportunities for further penetration.

The cross market view turned differences in adoption across the account into something we could observe and act on. Instead of treating expansion as one broad objective across 27 markets, we could identify where the relationship had room to deepen and prioritise those opportunities accordingly.