With the disappearance of traffic dividend, brand marketing has entered the era of stock competition from increment. The problems of high traffic cost, high marketing cost, increasing new cost, low efficiency of private domain operation and so on have always plagued the marketing and operation growth departments of major brands. The impact of the epidemic makes more and more enterprises begin to accelerate the process of digital transformation. Under the trend of the integration of online and offline data, all major brands urgently need to find out a set of effective brand marketing growth logic and path -- all-domain brand digital marketing operation to drive the growth of brand business in the variable market environment.
As a platform for global digital marketing, Whale Strategy focuses on three scenarios: global digital scenario, data business scenario and marketing driven scenario. Through the online and offline whole-domain data embedding layout, the establishment and deployment of data engines, and then the deployment of products according to business requirements, and finally the realization of fine operation, the formation of a closed loop in marketing and business management, optimize business capabilities.
In the closed-loop construction of brand digital marketing, "global data burying point" is indispensable. It is a fast, efficient and rich data acquisition method. It refers to the collection of data from all the contact points that a brand interacts with its users in a business scenario. Online, capture, process and send specific user behaviors or events in websites, apps and small programs. Offline, IOT devices, such as AI cameras, sensors and smart screens, capture, process and analyze user tracks and behaviors outside, inside, in, and on shelves. Global data embedding can help brands provide decision support for different business scenarios, business analysis, product optimization and iteration, refined operation and so on.
Secondly, for brands, the accuracy and integrity of data should be taken into account when deploying the technical solution of all-domain data embedding, which requires continuous testing and verification in the overall data infrastructure project. At the same time, it is equally important to choose a data analysis model that matches different business metrics. In the business scenarios of some brands, when the data infrastructure project is not complete, there are still long data acquisition links, low efficiency, and buried point loss, which ultimately affect the progress of business requirements. Therefore, Whale Strategy launches Analytics analysis cloud, which can help brands build a data foundation platform, enable brand digital marketing in the whole region through data-driven business analysis and decision-making in the whole scene, combined with action and feedback of omni-channel precision marketing.
01 Analytics Cloud, the most comprehensive online and offline data integration platform
The global data Platform provided by Analytics Cloud is an online and offline data fusion platform built based on Whale Open Platform (WOP) system. The Analytics cloud collects One-ID interactive data through AIoT and online data burying points, and makes data reports, notifications, and predictions in real time. Help customers build unified real-time data capabilities, enabling customers to forecast, recommend and automate their core business flows.
Event analysis model
Used to analyze user behavior, event analysis supports multi-dimensional analysis of user behavior through custom indicators, grouping and screening, and a variety of visual charts. Combined with the big data processing capability of Strategy Analytics, it can help us study the value impact and extent of the occurrence of a behavior event on the enterprise.
Attribution analysis model
Attribution analysis supports self-defining attribution-to-attribution events, target events and attribution models to facilitate all-round analysis of the transformation contribution of advertising space and promotion space to target events.
Funnel analysis model
It is mainly used to analyze the transformation and loss of each step in a multi-step process. Strategy Analytics supports custom funnel steps to identify problematic links based on abnormal data indicators to solve problems and ultimately improve the overall transformation.
Predictive function model
By modeling time series data with high-performance AI prediction model, the internal rules of business data can be deeply explored to support enterprises to make scientific decisions. This function is based on the time-sequence prediction line chart in event analysis. Users only need to turn on the switch to use it, which greatly reduces the cost of using the prediction model.
User path model
User path supports user-defined start and end events, enabling product optimization for comprehensive analysis of specific user behavior sequence distribution.
Component analysis model
Analyze what a target user consists of and what are its components. Strategy Analytics provides a custom component analysis function to quickly understand the overall distribution of users' public attributes and help optimize operational strategies.
02 Analytics analyzes six core capabilities of the cloud
Full-end data acquisition capability makes up for the pain points of offline business data acquisition
Full-end data collection for all business scenarios of brands: It has powerful and comprehensive data collection capabilities, covering offline, mobile, PC and other devices, etc., and solves the pain points of incomplete business data such as terminals of offline stores of most brands.
Full contact data acquisition integrates online and offline data
Full contact data collection covering online and offline: connect data from offline to online, integrate data of different granularity, and build a global unified user ID system.
Omni-channel user touch real-time interaction with users
It can realize all-channel user access: connect with the offline store shelf, APP, SMS, email and other channels, and interact with users in real time in all channels to improve the efficiency of brand marketing management.
Multiple data analysis models match different business indicators
For different business indicators, it provides a variety of data analysis models, including application event analysis, funnel analysis, user path, forecast model analysis and other more than 10 analysis models, real-time and flexible business analysis; Among them, the prediction model can help better control the cost, plan the deployment in advance, refine the operation and set the KPI reasonably, so as to "reduce the cost and increase the efficiency" for brand marketing.
Supports flexible combination of multiple collection modes and burial modes
Multiple collection modes are supported: Full buried: Used to collect more user data for user-defined analysis and other data mining scenarios. The whole domain buried point of Analytics analysis cloud is the integrated SDK, which completes all data collection with one click, which is simple, fast and low development labor cost; Code buried point, often used in the scenario of complex service data. The agent buried point adopted by Analytics analysis cloud supports user behavior data collection of small programs, Web and apps, which can collect data according to demand, complete business information, and more focused on data analysis.
Enable the global data service scenario to generate actual service value from data
There are three main sources of data: server-side own business data, buried point tracking behavior data, and third-party data summary. The Analytics cloud collects these three types of data through AIoT and online data burying, then integrates data of different granularity, and finally makes data integration analysis and prediction, so as to open up the whole data business scenario and continuously optimize the brand business capability.
Take the business scenario of customer flow operation in stores as an example. The collection of "server's own business data" is mainly based on AloT devices such as AI cameras, sensors and smart screens. It mainly captures the user trajectory and user behavior in the route area of the store, including key data such as customer flow in and out of the area, average length of stay, and number of commodity interactions. Then, based on the passenger flow analysis model at the entrance and exit, the marketing efficiency of the display contents was further analyzed through data tools such as A/B test.
Taking serving a global beverage chain giant as an example, it is necessary to combine the "service side's own business data", "embedded point tracking behavior data" and "tripartite data" to connect online and offline data and conduct full-contact data collection. Because of the large number of stores in the chain, the supervision of user journey is a huge operational challenge, such as the unified implementation of marketing activities management in stores across the country, how many people are queuing in the stores, how many drinks are being made, how to match online orders with offline capacity, and so on. If the brand wants to have a comprehensive view of the effect of the marketing operation in the whole region, it must collect the "whole region data buried" in every touch point and every channel involved in the private domain traffic such as the shop assistant applet, client applet, client APP, offline store terminal, so as to integrate the users, commodities and spatial information collected online and offline, so as to realize the fine user operation and intelligent marketing.
Take opening up the global data service scenario and optimizing the marketing operation cost as an example. Xibei, a well-known domestic catering chain brand, has about 4000+ offline screen contacts in China, with an average of more than 1000 consumers per screen watching the marketing content pushed in different periods of time every day. Due to the large number of stores, the variety of screens, the delivery and use of advertising content is extremely complicated, resulting in high operating costs.
Now, through Whale Strategy Analytics analysis cloud, Xibei has unified data collection and operation management for offline screen contacts and online mini program contacts. Combined with DAM digital asset management system, headquarters and shop staff can simultaneously manage private traffic advertisements through MAP. And push different marketing contents through the customer flow labels of different stores. For brands, through the global data platform of Analytics cloud, open up the global data business scenarios, through MAP to automate marketing scenarios, such as the establishment and operation of user journey, dynamic intelligent marketing content delivery, recommendation system, etc., truly achieve "cost reduction and efficiency" for brands.
For different business scenarios, the Analytics cloud integrates online and offline data to help brand marketing operation form closed-loop management, open up the all-domain digital scenario, and make the data generate actual business value.
All-round enabling brand digital marketing
First of all, it establishes a comprehensive data collection and content distribution system through offline intelligent equipment and online buried tools. Secondly, data precipitation is completed through the establishment and deployment of data engine. Deploy products (MAP, CDP, CRM, etc.) based on business requirements. Finally, through a closed loop of data and business management, we continuously optimize our business capabilities as we serve our various customers.
In a practical application scenario, the Analytics cloud meets the following common marketing business requirements.
Scenario 1: Optimizing advertising channels Greatly improves marketing efficiency
Taking a beauty brand as an example, the Analytics cloud collects and analyzes data on the advertising channel delivery scenarios of the brand: Based on the data performance of advertisements on platforms such as Douyin, wechat mini program and Weibo collected, data analysis of the attribution of advertising value is carried out according to the correlation between advertising channels and marketing activities, data analysis reports are made, and the mix of media channels is adjusted, thus helping the brand to increase the effect of advertising by 21% and greatly improving the efficiency of brand marketing.
Analytics analysis cloud can realize omni-channel marketing scenario analysis, channel quality assessment, landing page analysis, product analysis, advertising channel optimization, store layout display analysis, business potential analysis and other comprehensive and multi-angle marketing analysis, fully help the brand to improve the efficiency of marketing operation.
Scenario 2: Full cycle customer journey management in-depth optimization of operations
Taking a global well-known intelligent electric vehicle brand as an example, it comprehensively upgraded and optimized the store marketing customer journey through the Analytics cloud, increased the number of goods displayed in offline stores by three times, and doubled the duration of consumers' stay in the store, thus improving user stickiness and retention.
Taking the user marketing of a top 500 FMCG brand as an example, Analytics analysis cloud can help the brand online mall to carry out real-time marketing management monitoring, through the automated marketing management platform, through SMS notification to wake up sleeping users, encourage customers to favor again, and increase the purchase conversion rate of 12%;
The Analytics cloud helps brands comprehensively evaluate the operation effect of activities; Carry out detailed operation and hierarchical management of users, optimize user paths, improve user engagement and retention, and help brand marketing operation management in the whole process.
Scenario 3: Product optimization iteration improves the repurchase rate of explosive models
Taking a new brand in the cake industry as an example, the Analytics analysis cloud is used to analyze consumers' real usage of its best-selling cakes, which helps the brand truly understand consumers' preferences in different consumption scenarios, and then continuously optimize and iterate the product taste, accurately grasp consumers' demand pain points, and help customers find problems in the product. Constantly refine selling points and optimize product display details, improve conversion rate and re-purchase rate through A large number of A/B tests, and finally increase the re-purchase rate of this popular product to more than 40%.
The Analytics cloud helps brands understand how products are actually used, drill down and attribute. Find the problem in the product through the protective gear, obtain the user behavior path, and improve the smoothness of the product.
Scenario 4:360 User view Real-time user analysis management
Taking a beer brand as an example, real-time risk control management is carried out for the brand through Analytics analysis cloud to monitor the gross profit of products in real time. With the help of 360-degree user view, information such as consumer preferences and trading conditions can be obtained to control and monitor abnormal risks, so as to reduce malicious brush orders during marketing activities and reduce brand operating losses.
The Analytics cloud helps the brand realize 360-degree user view, obtain user information, preference, distribution, trajectory, transaction and other user information for follow-up analysis; Flexible user groups can help brands find high-value users and refine user management.
Under the joint support of technology, capital and consumption upgrading, the omni-domain digital marketing operation with the integration of online and offline modes has been the general trend, and the digital transformation layout of major brands and brands is in full swing. As a service provider of all-domain brand digital operation, Whale Strategy provides digital capacity building and application layer solutions for brands and retail brands through artificial intelligence (AI), large-scale Internet of Things (IoT) and Data model innovation, efficiently integrates resources and deeply integrates brand digital technology, product business and operation management. The Analytics cloud helps the brand to integrate offline and online business data, further refine the operation of the overall traffic, and reshape the growth mode of the brand.
About Whale strategizing
As a professional omni-digital marketing operation platform in China, Whale, through key technological innovations in artificial intelligence (AI), large-scale Internet of Things (IoT) and Data model (Data), provides future-oriented retail brands with data-driven, collaboration-first, simple and easy to deploy omni-brand marketing solutions. It aims to enable sustainable fine operation and lean growth of retail brands and open up the "last mile" of MarTech. At present, Whale strategy service system has widely covered food and beverage, beauty makeup and skin care, fashion shoes and clothing, light luxury jewelry, digital electrical appliances, catering and tea drinking, business super convenience, automobile service, medicine and health and other industries. It has accumulated benchmark customers such as Unilever, Watsons, Sibei, Midea, Paopamart, Nextev, Carrefour and more than 300 Top brands in the industry. The company was founded in 2017 in Hangzhou, and has offices in Shanghai, Shenzhen and Beijing.
