Whale Analytics Cloud
Whale Analytics Cloud
Data quantitative drive + Product intelligent decision-making = one-stop digitalintelligent decision-making platform

「Whale Analysis Cloud 」 provides a one-stop digital decision-making solution for brands. Based on brand data, business scenarios and best practices, through configurable components such as indicator library, data model library, feature library, visual data dashboard and categorization label library, etc., to solve enterprise needs smoothing, greatly promoting efficiency, experience optimization, sales forecasting and other complex business decision scenarios.

Brand Dilemma

  • Difficult Chain Store Management

    Difficult Chain Store Management

    - Lack of standard index system

    - Poor quantification of improvement effects

    - Store optimization has no direction

  • Difficult Advertising Pit Optimization

    Difficult Advertising Pit Optimization

    - Can't trace user path

    - Behavioral contribution difficult to assess

    - Optimization test method old-fashioned

  • LIVE Review without Breakthrough Point

    LIVE Review without Breakthrough Point

    - LIVE changes are not easy to detect

    - Re-disc data indicator single

    - Topic heat is difficult to trace

  • Long Explosion Build Cycle

    Long Explosion Build Cycle

    - Product positioning is not accurate

    - Lack of basis to match people and goods

    - Data reflow difficult to diagnose

Data Collection

multi-terminal SDK , professional event tracking solution.

Data Cleaning

cloud database access, data set configuration.

Data Visualization

indicator library management, embedded analytics.

Data Analytics

omni-directional scanning insights into people and freight yards.

Data Modeling

prediction, evaluation, classification, attribution.

  • Sort

    Rooted in actual business scenarios, design standardized data specification processes, create a complete data index system, and clarify data flow links.

    Combing data indicatorscombined with the user journey graph model, the business indicator system is divided.

    Identify One Metric That MattersFind key metrics and tap their core values and operational guidance.

    Open up the context of the index systemdefine goals, determine strategies, clear metrics, and open up the context of the index system from top to bottom.

  • Collect

    Build a global One-ID system, realize online and offline consumer touchpoint management, and realize comprehensive collection and global integration of user data.

    Demand InterpretationCollect, sort out and interpret the business needs of the brand.

    Event tracking designDesign specific, measurable, achievable, and pragmatic event tracking schemes.

    Online and offlineBuild a One-ID system, connect online and offline consumer touchpoints, and realize global data integration.

  • Check

    Gain insight into the status quo, trace the source, predict the future, and realize data-driven business growth through real-time analysis and decision-making of data.

    Whole-link visualizationadvanced charting + analysis model to achieve instant insights into data lake visualization.

    Automatic warningThe data cockpit supports custom indicators, thresholds, and abnormalities automatically trigger warnings.

    Data sharingcard service + report doc, realize data collaborative editing and flexible sharing.

  • Use

    Disassemble business scenarios, and realize data model-driven, brand intelligent decision-making, and business quantitative growth through global insights, strategies, and operations.

    In-depth business scenariosBased on brand data, business scenarios and best practices, combined with cutting-edge technologies, algorithms, etc. to disassemble business scenarios.

    Model quantificationresource level attribution analysis, LIVE quantification attribution, member life cycle management, brand intelligence diagnosis, etc. are carried out through the model.

    Intelligent decision-makingBased on data model analysis, it drives product intelligence and business decision-making, helping the brand to truly penetrate the hearts of the people and face the future.


Data model-drivenquantitative business growth

  • Store Evaluation

  • Attribution Reasons

  • LIVE Analysis

  • Hot Spot Creation

Store Evaluation

Customer Problem

or catering brand D with 200 + stores, there are large differences in dine-in and takeaway in different regions, and it is difficult for brands to grasp the situation of local stores in real time and conduct unified management.

Customer Demand

quantify the weather/holiday of on the performance of each store impact and adjust it in time;

Realize the comprehensive assessment of multi-store health inspection ;

Master the regional stores dine-in takeaway pricing, to achieve efficient performance.

Use Effect

Through the WAC - store health evaluation model,the brand pays close attention to the dynamic operation of each store, realizes the integration of chain store evaluation, monitoring and operation, implements problem store positioning and scientific cultivation of seed stores, and indirectly guides the cultivation of 25 + seed stores.

Attribution Reasons

Customer Problem

Well-known clothing brand T has always paid attention to private domain operations, and needs to continuously upgrade the Mini Program homepage, theme page layout & atmosphere to optimize the consumer link experience and promote the conversion rate.

Customer Demand

screening and positioning the most conducive to the transformation of brand materials ;

Insight into different consumers 'behavioral preferences and operating habits ;

Understand how each link of consumer behavior contributes to the final transformation.

Use Effect

Brands useWAC data capability-attribution modelto guide pit optimization, improve conversion rate & repurchase rate, and achieve data analytics increase in 150%,efficiency and 22% increase in transaction conversion rate in daily and large promotion marketing.

LIVE Analysis

Customer Problem

a domestic beauty brand is very focused on online LIVE channel, need to achieve LIVE cost reduction and efficiency, and precipitate a set of reusable LIVE methodology.

Customer Demand

realize data abnormal fluctuation reminder in LIVE ;

Analyze, refine and precipitate hot topic LIVE in the process of topics and keywords ;

After LIVE, the performance of different products/hosts is analyzed.

Use Effect

Brands use the WAC LIVE quantitative attribution model,combined with "semantic recognition ability" to build an algorithm model to help build brand Knowledge Graph and LIVE single-store models, making brand LIVE simpler and more efficient Quantify attribution and output the correlation between LIVE video keywords and LIVE traffic and transaction conversion key business indicators, so that the LIVE re-disk efficiency can be improved by 200%+

Hot Spot Creation

Customer Problem

shoes and clothing brand T new product research and development in trouble, iterative on new products is difficult to get consumer love , market performance decline.

Customer Demand

refined brand core user portrait ;

Insight into the relationship between sub-categories of goods ;

Look alike Customers seek and reach .

Use Effect

The brand builds models through WAC explosions, conducts cross-category cross-penetration mining , product correlation analysis, realizes opportunity insight , product expansion, and cooperates with cold start laboratory to monitor and return test brand data in real time and value label verification . Finally, the explosion building cycle is shortened by 60%,and the new brand population is greatly promoted to 150W+

Empower Business Growth