Why Multi-Reviews for High-Level LGs are Essential for Data Quality?
I am well aware that Google Maps operates on the principle of ‘one review per Local Guide (LG) per POI.’ However, this rigid restriction creates significant issues for dedicated LGs who visit the same place across different seasons.
Currently, to record a new visit, we must edit our previous review. This results in a chaotic mix of photos from different time periods, making the information confusing for users. Furthermore, a single review is limited to 50 photos. Once that limit is reached, any additional high-quality photos get buried and mixed with thousands of other random uploads. Eventually, even the most dedicated LGs lose the motivation to contribute further. This is a significant loss for Google Maps because these are the very contributors providing the most accurate, high-purity, and reliable data—data that could serve as a benchmark to filter out lower-quality information. Wouldn’t it be more beneficial to prioritize these ‘Power Users’?
Some might argue for ‘simplicity.’ However, the system I am proposing is already conceptually present in various parts of Google Maps. Implementing this wouldn’t require a massive structural overhaul; from a programming perspective, it could be as simple as adding a few ‘IF’ conditions based on LG levels. For instance: IF Level 8, allow 2 reviews; IF Level 9, allow 5 reviews; IF Level 10, allow 10 reviews.
Such a minor technical adjustment would encourage our most loyal LGs to be even more devoted. How could this possibly be a disadvantage for Google? Anyone with even a basic understanding of programming knows that this does not demand a ‘tremendous’ systemic change. Nor would it lead to an exponential increase in data costs, given how few LGs actually reach Level 8 and above.
Lastly, this feature wouldn’t even need a massive public announcement. Only those who truly need it would discover and utilize it. This isn’t about deceiving anyone; it’s about Google providing the right tools for its top-tier contributors, who in turn have the expertise to use them effectively.
As for concerns about rating manipulation (spam), isn’t that mostly a concern for the private sector? If we were to start applying this to the public sector first, those concerns would be virtually non-existent.