A 1000-page data-driven site had features not working at final testing; what's the most probable cause?

• A. Data driven sites are best suited for smaller sites and may cause errors in larger projects.
• B. The team failed to build and test a prototype of the site early on in the project.
• C. The customer had set unrealistic expectations that could not be met by the design team.
• D. The wireframe of the project was modified throughout the project creation, causing inconsistencies.

Answer: (B)

Prototyping and early testing are essential to validate how data-driven features actually work with real data and workflows. In a large, 1000-page site, many features depend on data formats, integrations, and sequence of user actions. If you skip building and testing a working prototype early, you won’t catch mismatches between design intent and data handling, or identify where performance or integration bottlenecks will occur. That means issues can accumulate and only show up during final testing, when fixing them is expensive and risky. By prototyping early, you simulate real usage, validate critical paths, and iterate on design and data flows before full development, dramatically reducing late-stage failures. The other options don’t pinpoint a root cause as directly: a data-driven approach can scale beyond small sites, unrealistic expectations don’t inherently produce unusable features, and wireframe drift is risky but typically surfaces through early validation as well.