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The primary objective was to establish a reliable and accurate digital tracking foundation that could support performance-driven marketing and meaningful decision-making. While Nima lodge was already running Paid Social campaigns, the lack of dependable booking and revenue data meant that optimisation was being done with limited visibility into what was truly driving results.
From the outset, our brief was to move beyond surface-level metrics and ensure that every stage of the booking journey could be tracked accurately. This included understanding where users dropped off in the funnel, how different cabins performed, and how much real revenue could be attributed to advertising activity.
As the project evolved, the objectives expanded to include selecting and implementing a booking platform that could support proper event tracking, enable full-funnel visibility, and align marketing data with real booking outcomes and accurate ROAS. The long-term goal was to create a system where strategy, budgets, and creative decisions were driven by accurate data and attribution.
The biggest challenge we faced with Nima Lodge was the absence of accurate conversion and revenue tracking. Prior to June 2025, the lodge was using RoomRaccoon as its booking platform. While functional from an operational perspective, the platform did not allow us to track user behaviour and purchases in a way that could be reliably connected to Meta advertising or analytics platforms.
This meant that key performance signals such as Add to Cart, Initiate Checkout, and Purchase events were either unavailable or inconsistent. Without these signals, Meta campaigns could not properly exit the learning phase or optimise toward real bookings, limiting both efficiency and scalability.
When InnStyle was introduced in June 2025 as an alternative solution, a new set of technical challenges emerged. The booking journey relied heavily on iFrames, which restricted our ability to track button clicks and funnel progression events. Supporting sales events stopped firing, and purchase testing was initially blocked by configuration issues.
A further layer of complexity was that moving to a new booking platform effectively reset campaign learning. Historical optimisation data tied to the old tracking setup could no longer be relied on, meaning that even strong-performing campaigns had to rebuild momentum from a new data source. This required careful expectation management and a strategy that could absorb short-term volatility in exchange for long-term performance accuracy.
At the same time, we needed to maintain performance momentum during a period where the ad platforms were receiving little to no reliable conversion data. This meant balancing technical troubleshooting with ongoing campaign management, budget optimisation, and creative updates, all while ensuring that Nima Lodge continued to generate bookings during a volatile data environment.
Our strategy for Nima Lodge focused on two parallel priorities: stabilising performance in the short term and building long-term tracking infrastructure that would ensure accurate performance marketing.
In the first phase, Nima Lodge identified InnStyle as a potential alternative. We conducted a comparative review against RoomRaccoon, focusing specifically on tracking capabilities, data reliability, and long-term performance marketing requirements.
Following this evaluation, we aligned with the client on the need to migrate platforms. InnStyle went live in June 2025, after which our focus shifted to diagnostics, testing, and ongoing monitoring to ensure that conversion and revenue data accurately reflected real booking activity.
We implemented and tested purchase tracking, audited funnel URLs, and worked closely with the client and InnStyle to resolve technical barriers caused by iFrame restrictions. Where button-level tracking was not possible, we adapted by creating alternative tracking points such as new thank-you page events, allowing us to measure confirmed bookings and booking values more reliably.
From the outset, we were transparent with Nima Lodge that changing the booking platform would reset Meta’s learning. While this meant short-term disruption, it was a necessary step to build a system based on accurate, future-proof data. Importantly, the momentum built before June 2025 and the structured testing phase with InnStyle created a strong behavioural foundation. As a result, once reliable signals began flowing again, we were able to accelerate learning faster and scale more confidently than if we had started from zero.
While tracking was being stabilised, we protected campaign performance by shifting optimisation strategies. Instead of forcing campaigns to optimise for broken purchase events, we introduced mid-funnel objectives such as Add to Wishlist and interest-based video engagement. This kept Meta’s algorithm learning from meaningful signals while full purchase tracking was under development.
At the same time, we actively managed budgets and creative directions. Seasonal budget increases were phased in, prioritising high-performing campaigns first and supporting underperforming cabins with additional testing. We optimised and refreshed all static, carousel, and video creatives regularly using updated imagery and seasonal messaging to maintain relevance and engagement.
As part of resolving ongoing tracking limitations, we identified challenges with InnStyle’s native conversion tracking. To address this, we proposed the development of a dedicated thank-you page that could serve as a reliable and trackable confirmation point for completed bookings. Following our recommendation, the client implemented this page within the booking journey.
Once deployed, we configured and validated tracking on the new thank-you page, which significantly improved conversion visibility and data reliability. This allowed us to expand the strategy by building remarketing and lookalike audiences based on confirmed booking actions, enabling a return to high-intent optimisation and more confident audience scaling.
By combining technical problem-solving, platform migration, creative strategy, and performance optimisation, we transformed Nima Lodge’s marketing from guesswork into a data-driven system built for sustainable growth.
By the end of the first full cycle with InnStyle fully implemented and tracking optimised, we began to see clear, measurable improvements across key performance metrics. Although data tracking was essentially starting from scratch, the campaigns we were running throughout the process had already built momentum. This allowed us to scale performance far faster than if we had paused activity during the transition. The phased strategy, combined with rigorous testing, budget allocation, and creative optimisation, enabled us to capture data that accurately reflected bookings and audience behaviour.
Comparing the period of December 2025 – January 2026 with October – November 2025, we observed significant growth:
Primary Goal – Bookings & Leads:
Supporting Goal – Contact Conversions:
By establishing a reliable tracking foundation and maintaining campaign activity throughout the transition, we were able to transform Nima Lodge’s marketing from data-limited activity into a fully measurable, scalable system. This approach has positioned Nima Lodge to continue building momentum and scaling efficiently with confidence in the accuracy of their performance data.
