Seolly vs DataChat

Seolly is an analytics dashboard that pulls read-only Google Search Console data into one place for agencies managing many sites. You connect your GSC properties, see clicks and impressions across every domain on a single overview page, and drill into popular, growing, or decaying pages without clicking through Google's interface. It shows the same underlying numbers as Search Console, not traffic estimates from third-party crawlers.

Rank trackers and all-in-one SEO suites store your performance data on their servers. Seolly markets a privacy-first model where it does not store or resell your GSC metrics, only the Google OAuth key needed to render dashboards until you revoke access. Branded keyword filtering and custom content groups are built for client reporting where you need to strip branded queries or compare landing page clusters quickly.

SEO agencies, consultants, and affiliates with multiple Search Console properties are the core audience. Teams that export CSV reports for clients benefit from unlimited exports and a Privacy Blur mode that hides URLs in screenshots. Lifetime pricing at $49.99 targets freelancers who want to avoid another monthly subscription.

DataChat is a no-code conversational analytics platform that lets business users ask natural language questions to explore data instantly. It removes the need for SQL or scripting, turning plain English queries into actionable insights. Users can refine queries on the fly and dive deeper into data without waiting for technical support. The platform automatically documents every step, ensuring transparency and trust in the results. It integrates with major data warehouses like Snowflake, Google BigQuery, Databricks, and Amazon Redshift, making it easy to connect and analyze large datasets. Collaboration is built-in, allowing teams to work together in real time without overwriting each other's work. DataChat also prioritizes security and compliance by keeping data on-premises and restricting access based on permissions. Its AI and machine learning features automate data exploration, trend analysis, and forecasting, helping users make smarter decisions faster. The platform supports reproducible workflows, so analyses can be saved and rerun on updated data, ensuring consistency across teams. Overall, DataChat accelerates data-driven decision-making by simplifying access to insights for non-technical users while maintaining enterprise-grade security and scalability.