How about looking for a house in Zhuge? Analysis of hot topics and real user reviews on the entire network in the past 10 days
With the fluctuation of the real estate market and the diversification of home purchase needs, real estate information platforms have become an important channel for users to obtain housing resources. As a well-known real estate big data platform in China, Zhuge Zhaofang has once again become the focus of heated discussion recently. This article combines hot topics and user feedback across the Internet in the past 10 days to analyze Zhuge’s actual experience in finding a house from multiple dimensions.
1. Analysis of the correlation between hot topics across the Internet and Zhuge’s housing search (data in the past 10 days)
| Ranking | hot topics | Related platforms | Number of discussions (10,000) |
|---|---|---|---|
| 1 | Second-hand housing listings surge in first-tier cities | Zhuge House Search/Lianjia | 28.6 |
| 2 | School district housing price fluctuation monitoring | Zhuge House Search/Anjuke | 19.2 |
| 3 | Controversy over real estate agency fee reform | Shell/Zhuge house search | 15.8 |
| 4 | Rental market peak season data analysis | Zhuge House Search/58 City | 12.4 |
2. Core Function Experience Evaluation
1.Authenticity of property: Based on user sampling feedback, the authenticity rate of officially certified housing listings on the platform is about 89%, which is significantly higher than the industry average. However, some users still report that there is a problem of "sold but not removed".
2.Big data analysis tools: Its featured "House Price Map" and "Rise and Fall Ranking" functions are the most discussed, with 73,000 interactions on related topics in the past 10 days. In particular, the early warning function for housing price fluctuations in school districts has been well received.
3.Service coverage: Currently covering 200+ cities across the country, but the update speed of housing listings in third- and fourth-tier cities is slow, with an average lag of 2-3 days.
| Function module | User satisfaction | Industry comparison |
|---|---|---|
| Property search efficiency | 86% | 5% ahead of similar platforms |
| Price monitoring accuracy | 91% | Leading similar platforms by 8% |
| Broker response speed | 78% | On par with the industry |
3. Focus of dispute among users
1.Member service cost-effectiveness: Some users believe that the exclusive data provided by premium membership (298 yuan/year) is of doubtful value, and there have been 43 new related complaints in the past 10 days.
2.Advertisement push frequency: About 32% of Android users reported that the APP startup advertisement lasted more than 5 seconds, which significantly affected the user experience.
3.Data update delay: Especially during weekends, about 15% of listing status updates are delayed by more than 6 hours.
4. Key Indicators for Comparing Competitive Products
| indicator | Zhuge looking for a house | Shell house hunting | Anjuke |
|---|---|---|---|
| Average daily active users (10,000) | 142 | 310 | 286 |
| Number of duplicate listings (10,000) | 850 | 1200 | 980 |
| Average response time (minutes) | 23 | 18 | 35 |
5. Suggestions for use
1.Price monitoring scenario: It is recommended to give priority to its big data tools, especially the "historical transaction price comparison" function, which has an industry-leading accuracy rate of 93%.
2.Preparation for house inspection: Although the authenticity of the properties displayed as "for sale" on the platform is relatively high, it is still recommended to confirm by phone in advance to avoid about 23% of invalid viewings.
3.Member service options: Ordinary users can meet their needs by using basic functions. Only investors who need in-depth market analysis need to consider paid membership.
Taken together, Zhuge Zhaofang has obvious advantages in big data analysis and housing price monitoring, but there is still room for improvement in service response speed and some detailed experience. It is recommended that users make a comprehensive comparison based on their own needs and combine multiple platforms to obtain the best housing search experience.
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