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I got fed up with Google Maps’ 20-result limit…so I built my own.
r/SideProject
8/15/2025
Content Summary
The post discusses the frustration of working with Google Maps' 20-result limit when prospecting local businesses. The author built DensOps, a tool combining ChatGPT and Google Maps for sales, allowing complex queries beyond what Google offers. They also mention using a graph database for efficient data relationships and share technical details about their approach. Users in the comments discuss challenges with API costs, data enrichment, and alternative solutions like OpenStreetMap and scraping techniques. The author plans to launch DensOps in September with a flat-fee pricing model aimed at making business prospecting more affordable and accessible.
Opinion Analysis
Mainstream opinions in the discussion revolve around the need for better tools to overcome Google Maps' limitations and the high cost of API usage. Many users agree that the 20-result cap is a major hindrance for sales and marketing efforts. There's strong support for DensOps as a potential solution, especially given its focus on natural language queries and graph database architecture. However, some users argue that over-engineering with graph databases may not be necessary, suggesting relational databases or NoSQL solutions could be sufficient. A few users also question the legality of scraping data from Google Maps, highlighting the importance of legal compliance. Overall, the discussion reflects a mix of excitement for innovative tools and caution about implementation and legal risks.
SAAS TOOLS
| SaaS | URL | Category | Features/Notes |
|---|---|---|---|
| DensOps | https://densops.com | Business Prospecting Tool | Combines ChatGPT and Google Maps for sales, allows complex queries like "Find every boutique gym in Berlin with an Instagram account". Uses a graph database for efficient relationship traversal. |
| Clay | - | Data Scraping / API | Mentioned as a tool that was too expensive for the user's needs. |
| PhantomBuster | - | Social Media Scraping | Used for scraping Instagram handles. |
| Apollo.io | - | Email Outreach | Used for contact data collection. |
| Merchynt | - | Lead Enrichment | Mentioned as improving cold outreach templates. |
| RushDB | - | Graph Database | Suggested by the author as a fast solution for graph-based queries. |
| ClickHouse | - | Data Analytics | Used for handling large datasets and updates. |
| ElasticSearch | - | Search Engine | Mentioned as problematic for the user's use case. |
| OpenStreetMap (OSM) | - | Mapping Data | Suggested as an alternative to Google Maps. |
| LeadMint | - | Business Prospecting | Mentioned as a tool that fixed the 20-result limit for some users. |
USER NEEDS
Pain Points:
- Google Maps limits results to 20 per search, making it inefficient for business prospecting.
- High costs of API calls for data extraction from Google Maps.
- Inconsistent or incomplete categorization of businesses on Google Maps.
- Difficulty in enriching data with social media and other signals.
- Challenges in building scalable tools for business prospecting.
Problems to Solve:
- Overcoming the 20-result limit on Google Maps.
- Reducing costs associated with API usage.
- Improving data accuracy and completeness for business listings.
- Efficiently managing and querying large-scale local business data.
- Building tools that allow natural language queries for business discovery.
Potential Solutions:
- Using custom-built tools like DensOps to bypass Google Maps limitations.
- Implementing graph databases for efficient relationship traversal.
- Utilizing third-party APIs like PhantomBuster and Apollo.io for data enrichment.
- Employing scraping techniques and distributed IP systems to avoid API rate limits.
- Exploring alternatives like OpenStreetMap for less restrictive data access.
GROWTH FACTORS
Effective Strategies:
- Solving a clear pain point: overcoming Google Maps' 20-result limit for business prospecting.
- Leveraging graph databases for efficient data relationships and scalability.
- Focusing on user-friendly interfaces that simplify complex queries (e.g., using natural language).
- Offering flexible pricing models (flat fee instead of credit-based systems) to improve user experience.
- Engaging with communities (like r/SideProject) to gather feedback and build early interest.
Marketing & Acquisition:
- Sharing success stories and technical insights (e.g., graph database benefits) to attract developers and data enthusiasts.
- Building a community around the product through discussions and open-source sharing.
- Using Reddit as a platform to promote the side project and generate buzz.
Monetization & Product:
- Pricing model based on time-limited access (24-hour pass, weekly pass, monthly subscription) rather than credits.
- Emphasizing affordability and ease of use to differentiate from competitors.
- Focusing on product-market fit by solving real-world problems faced by sales teams and marketers.
User Engagement:
- Encouraging user participation through AMA sessions and technical deep dives (e.g., explaining graph database architecture).
- Creating a sense of community by responding to comments and engaging with potential users.
- Offering early access and beta testing to build loyalty and gather feedback.