In one of Both&’s recent projects, we were approached by a client operating in the luxury travel and property management space, curating a global portfolio of high-end properties through an international supplier network. As their business evolved, the importance of structured, high-quality data became increasingly central, not only for managing listings and bookings but also for enabling more precise matching between travellers and properties.
Their technology stack was built around Zoho CRM as the system of record, with Zoho Forms used as the primary interface for supplier-driven data capture. While this foundation had supported the business effectively in its earlier stages, the growing scale and complexity of its portfolio began to expose limitations in how data could be captured, structured, and maintained.
Business Challenge
What initially appeared to be a straightforward data capture requirement quickly became a deeper structural challenge. Each supplier could manage multiple properties, and each property required highly detailed, multi-layered information, spanning bedroom configurations, bed types and quantities, bathroom relationships, amenities, and service-related data. This introduced a level of hierarchy that traditional form tools are not designed to support.
The existing process became increasingly fragmented as complexity grew. Suppliers were required to repeatedly enter similar information; updates were difficult to manage, and there was no effective way to revisit and refine previously submitted data. Simultaneously, internal teams lacked confidence in the dataset's consistency and usability.
Zoho Forms, while effective for simple use cases, presented clear constraints. It does not support nested subforms, offers only limited native prefill capabilities, and lacks mechanisms for structured updates over time. These limitations created friction not only in data capture but also in ongoing data maintenance.
Critically, the business required more than just collecting data. It needed a structured, filterable, and scalable dataset capable of supporting complex booking requirements and serving as the foundation for future capabilities, such as automated property matching.
Solution Overview
Zoho CRM was positioned as the central data layer, responsible for storing and structuring all information, while Zoho Forms was reimagined as a dynamic interface sitting on top of it.
A key component of this approach was the development of an API-driven prefill mechanism. Each property was assigned a unique identifier embedded within a reusable link. When accessed, the form triggers a call to Zoho CRM, retrieves the relevant data, and reconstructs it into a format that can be rendered within the form. This allows the same interface to function as both a capture and editing environment, enabling suppliers to return at any time, view existing data, and make targeted updates without restarting the process.
To manage complexity, the onboarding journey was divided into four interconnected stages, each representing a logical segment of the data-capture process. While technically separate, these forms are daisy-chained to create a continuous, guided experience. Data is written back to Zoho CRM at each stage, ensuring persistence and continuity throughout the journey.
Hierarchical data structures were modelled directly within Zoho CRM using custom related lists. This made it possible to represent real-world relationships, such as properties with multiple bedrooms, each with associated beds and bathrooms, despite Zoho Forms lacking native nested capabilities. The result is a system capable of capturing highly granular, relational data in a structured and queryable format.
Implementation & Technical Complexity
Although the end experience is intentionally simple, the implementation required overcoming several non-trivial platform constraints. One of the primary challenges was simulating nested data structures within a tool that does not support them. This was achieved through careful replication of field groups, supported by conditional logic that controls when and how fields appear, along with defined limits to ensure usability.
The Zoho CRM data model required equal attention. It needed to accurately represent real-world property configurations, including multiple layers of relationships and optional dependencies, such as linking bathrooms to specific bedrooms. Ensuring consistency across these relationships was critical to maintaining data integrity.
The prefill engine introduced additional complexity. Data retrieved from CRM had to be transformed from relational structures into flat inputs compatible with form fields, and then effectively reconstructed each time the form was loaded. This created a stateless interface experience, supported by a fully stateful backend.
Continuity across the multi-step process was achieved by writing data back to CRM at each stage, enabling a draft-like experience where progress is preserved. This design introduced some trade-offs, including a short delay before newly submitted data becomes available for prefill, and the need to manage media assets externally to maintain quality.
The most complex aspects of the solution, particularly the data modelling and prefill logic, required approximately two months of iterative development and refinement.
Results & Impact
The solution transformed a fragmented process into a unified, structured onboarding experience. Suppliers can now move through a guided workflow, with existing data pre-populated and easily editable, significantly reducing friction and improving data accuracy.
From a data perspective, the organisation now has access to a highly structured and granular dataset, enabling advanced filtering across multiple dimensions, including room configurations, amenities, and location-specific attributes. This has improved the ability to support complex client requirements and increased confidence in the data.
Beyond immediate operational gains, the solution has established a strong foundation for future capabilities. With structured and reliable data in place, the business is now positioned to explore more advanced use cases, including automated matching and intelligent recommendation systems.
Key Takeaways
This case demonstrates that the perceived limitations of tools like Zoho Forms can be reframed as design challenges. By introducing an API-driven architecture and repositioning forms as a dynamic interface rather than a static input tool, it becomes possible to support complex, relational data use cases within an existing platform.
The approach reinforces the importance of placing CRM at the centre of the architecture, enabling scalable and structured data modelling. It also highlights a broader principle, that investing in backend sophistication can significantly simplify the user experience, even in complex scenarios.
Ultimately, the project illustrated how Zoho Forms can be extended beyond its typical use case, evolving into a flexible and scalable solution for capturing and maintaining deeply structured data.