What is Insights (UBA)?

Insights (UBA) is an analytical capability based on user behavior and business process data, helping companies pinpoint growth issues, validate strategy effectiveness, and support business decisions.

What is the difference between codeless tracking and code-based tracking?

No-code tracking is more suitable for rapid coverage and historical review, while code-based tracking is better for precisely defining key business events; enterprises typically use a combination of both. In 2015, GrowingIO was the first in China to introduce no-code tracking, which is sometimes referred to as “full tracking.” GrowingIO supports a combination of “no-code + code-based” tracking, balancing coverage efficiency with the precision of key events.

Is private deployment supported?

Supported. All products under GrowingIO Analysis Cloud support SaaS and private deployment, allowing you to choose the appropriate delivery method based on your company's requirements for data security, compliance, system integration, and management. For an assessment of the deployment solution in line with your specific business scenarios, please contact us for further consultation.

Can it support real-time data statistics?

Supports real-time data collection, instant user data integration, and data dashboard viewing at a minute-level granularity.

What data integrations are supported?

Supports data collection from all common platforms on the market, including Android, iOS, Web, Mini Programs (WeChat, Alipay, Baidu, Douyin, QQ, Taobao, Kuaishou, JD, Quick App), as well as many hybrid frameworks (Flutter, React Native, HamonyOS); server-side includes Java, PHP, Python. Supports data import from all common databases on the market.

Can I analyze products?

Supported. GrowingIO supports multi-entity analysis, extending from users to products, stores, and more, covering a wider range of business scenarios. In the product domain, it can be used for analyzing stocking efficiency, inventory, promotional item selection, and product revenue. In operational scenarios such as stores, it also supports analyses like people-product-store matching and store operations.

Insights (UBA)

An enterprise-level growth analytics platform for product, operations, marketing, growth, and management teams, integrating AI-powered data querying capabilities. It helps businesses establish a complete data-driven decision-making process from data collection to behavior analysis. Supports both SaaS and on-premises deployment.

Comprehensive data collection across online and offline channels, enabling quick setup of a unified analytics view.
Multi-dimensional analysis from users to products, stores, and more, providing a clearer understanding of growth issues.
Funnel, path, retention, and other model analyses help teams quickly identify key growth insights.

Use cases

Product capabilities

Customer stories

Frequently asked questions

Use casesUnlock the value of data across a wide range of business scenarios

Channel Traffic Analysis and Acquisition Optimization

Use metrics like retention and conversion rates to evaluate traffic quality, cost efficiency, and acquisition performance across channels. Continuously optimize budget allocation to boost acquisition ROI — for example, by spotting fake traffic and finding high-converting keywords to improve channel strategy.

User Lifecycle and Repurchase Growth Analytics

Analyze user behavior data to identify characteristics and conversion opportunities at each lifecycle stage, supporting segmented operations and differentiated marketing. For example, identify high-frequency, highly loyal core users and determine the best timing and cadence for repurchase outreach.

Product Experience and Conversion Path Optimization

Track user behavior and conversion paths to identify experience bottlenecks in key flows, providing data support for product optimization and iteration. For example, analyze whether traffic distribution across homepage placements meets expectations, or whether the first-purchase path for new customers has conversion bottlenecks.

Comprehensive Business Operations Analysis

Analyze retail operations like products and stores across the "people, goods, places" framework to better support business growth. For example, analyze store sales, inventory, and product mix to improve store management and margins; or use bestseller and sales cycle analysis to refine product placement and operations.

Product capabilities

Solve business challenges with distinctive product capabilities

Pain Point: Analysis is limited to a single object, making it hard to see the full picture of growth across "people, goods, and places."

Solution: Omnichannel integration, multi-entity analysis

Integrate online, offline, and multi-source business data to support multi-object analysis — from users to products and stores — for a more complete view of growth opportunities.

Dual-mode Behavioral Data Collection
Code-based tracking for precise and flexible data; no-code selection for easy operation by business personnel, ready to use upon selection.
Multi-source Data Integration
Supports all commonly used databases and offers extensive platform data integration (WeChat, Taobao, Tmall, etc.)
Rich data analysis and visualization
10+ analysis models (funnel, retention, attribution, interval, distribution, etc.) plus scenario-based models (LTV, KPI, repurchase analysis), combined with rich visualizations and flexible dashboards to meet all analysis needs.

Solution: Omnichannel integration, multi-entity analysis

Pain Point: Numerous analysis needs, insufficient response speed

Solution: Low-barrier analytics, intelligent insights

Over 10 types of analysis models, easy to use, enabling business teams to independently identify issues, understand results, and drive actions.

Low-threshold Analysis
Over 10 analytical models, combined with AI Agent support for natural language querying and diagnostic analysis, enable business teams to independently pinpoint issues, interpret results, and drive action.
Smart Insight Interpretation
Paired with AI-powered insights, analyze metric changes, and uncover analysis conclusions and optimization suggestions.

Solution: Low-barrier analytics, intelligent insights

Pain Point: The implementation cycle for data 'collection, processing, and presentation' is long and costly.

Solve: Unified Data Translation, Delivered in Hours

Standard data model, greatly reducing the data processing cycle; flexible dashboard capabilities, ready-to-use, with data available in seconds

Standard XEI Data Model Construction
No data engineers needed, fully low-code, drag-and-drop for data collection and processing, with results in hours.
Flexible and powerful dashboard capabilities
Easily build dashboards with drag-and-drop, and get data in seconds; enterprise-level collaboration and permission control ensures the right people see the right data.

Solve: Unified Data Translation, Delivered in Hours

Customer storiesWhat our customers say

Hanguang Department

JD Allian

Manniu Health

Hanguang Department

GrowingIO helps Hanguang Department Store integrate off-site and on-site user behavior data with transaction data, establishing a full-lifecycle analysis and operation model for users. By optimizing traffic distribution, supporting product decisions, and enhancing merchandise operations, GrowingIO comprehensively assists Hanguang in better managing its private domain traffic, fully leveraging the consumption potential of its millions of fans.

Hanguang Department

JD Allian

Manniu Health

Hanguang Department

Frequently asked questions

What is Insights (UBA)?: Insights (UBA) is an analytical capability based on user behavior and business process data, helping companies pinpoint growth issues, validate strategy effectiveness, and support business decisions.
What is the difference between codeless tracking and code-based tracking?: No-code tracking is more suitable for rapid coverage and historical review, while code-based tracking is better for precisely defining key business events; enterprises typically use a combination of both. In 2015, GrowingIO was the first in China to introduce no-code tracking, which is sometimes referred to as “full tracking.” GrowingIO supports a combination of “no-code + code-based” tracking, balancing coverage efficiency with the precision of key events.
Is private deployment supported?: Supported. All products under GrowingIO Analysis Cloud support SaaS and private deployment, allowing you to choose the appropriate delivery method based on your company's requirements for data security, compliance, system integration, and management. For an assessment of the deployment solution in line with your specific business scenarios, please contact us for further consultation.
Can it support real-time data statistics?: Supports real-time data collection, instant user data integration, and data dashboard viewing at a minute-level granularity.
What data integrations are supported?: Supports data collection from all common platforms on the market, including Android, iOS, Web, Mini Programs (WeChat, Alipay, Baidu, Douyin, QQ, Taobao, Kuaishou, JD, Quick App), as well as many hybrid frameworks (Flutter, React Native, HamonyOS); server-side includes Java, PHP, Python. Supports data import from all common databases on the market.
Can I analyze products?: Supported. GrowingIO supports multi-entity analysis, extending from users to products, stores, and more, covering a wider range of business scenarios. In the product domain, it can be used for analyzing stocking efficiency, inventory, promotional item selection, and product revenue. In operational scenarios such as stores, it also supports analyses like people-product-store matching and store operations.

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