Business Data Operation and Management Final assignment

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Business Data Operation and Management Final assignment
(I) Objectives of final assignment
This assignment is the final assignment of the course, accounting for 60% of the total evaluation results. Students simulate the operation team of e-commerce enterprises in the form of teams, and complete a data-driven business operation analysis report and product selection operation plan around specific products. Examine whether students can integrate market research, data analysis and operational strategies into a complete solution that can guide business decisions.
(2) Topic: Data Operation Analysis of a Chinese Brand Entering a Regional Market
Taking a Chinese Brand entering your home country as a case, uses public data to complete a data-driven business operation analysis report and selection operation plan to form a business decision-making plan, and ultimately demonstrate the feasibility and method of this selection for entering the target market.
(III) Product selection and positioning requirements
Each team must independently select a specific product or product line in a certain industry and make a comprehensive introduction. The contents include but are not limited to: product pricing, model specifications, core features, size parameters, color selection, materials, main functions and recommended use scenarios. The presentation should highlight the unique selling point (USP) of the product, clearly explain how it meets the needs of the specific market, and ensure that all information is accurate and clearly presented.
Selection must be based on in-depth market research and clearly explain the reasons for selection. This includes an understanding of the needs of the target market, how the product is positioned to meet that need, and an analysis of the characteristics and preferences of the target consumer. This section should be presented as an internal proposal that will convince management, not as a random suggestion.
(IV) Research scope and object setting
The research object must be clear and can be analyzed according to the chain of "category-brand/store/website-product-competitive product". It is not allowed to discuss the whole industry or brand group in general. Specifically:
Category level: Choose a mature category (such as cosmetics, personal care, 3C digital, home life, clothing accessories, etc.), and make clear the reasons for the choice.
Product level: Locate one or more core products within the brand as a focal point for sales data, customer feedback, and operational optimization.
Competitive product level: select benchmark competitive stores under this category, and lock in similar competitive products to form a benchmarking relationship.
(V) Report core module
The report can include the following modules: research overview, product selection scheme and product positioning, market environment and trend analysis, category market analysis, store/brand and product data analysis, competitive product and competitive data analysis, user portrait and customer management, data operation optimization and innovation, conclusion and outlook.
(VI) Data source requirements
All analysis must be based on publicly available data, and the use of fictitious data is strictly prohibited. The data should be labeled with the source (platform, report name, release time).
(VII) Submission specifications
Content requirements: cover, charts, etc. Are required
Language and length: Written in English, no less than 15 pages of PDF + PPT.
Submission requirements: PPT presentation in the 16 week（June 17th) class, PPT + PDF document email to yinshi@sspu.edu.cn
Naming format: named by student number, such as: 20260503/20260504 + final assignment
Supplementary requirements: It can be completed independently or in a group of two persons, and the division of labor should be clearly defined in the report.
(VIII) Scoring criteria
	Scoring module
	Score
	Scoring rules
	Integrity of core content
	35
	It covers all modules required by the report, fits the core chapters of the course, and forms a complete closed-loop analysis.
	Depth and practicality of data analysis
	30
	Focusing on the core of data operation, we can interpret business problems and compare gaps through open data, rather than simply listing data and analyzing the actual business scenarios.
	Data compliance and rigor
	10
	All data come from designated open channels, with clear source labels, no fiction or plagiarism, in line with relevant laws and regulations on data security and privacy protection, and to implement the ideological and political objectives of the course.
	Optimization scheme and innovation capability
	15
	Operational optimization proposals can be implemented, and reasonable model innovation, product selection optimization or customer retention measures can be put forward in combination with data to meet the training objectives of curriculum ability.
	Report specification
	10
	The format is standardized, the chapters are clear, the English expression is accurate, the logic is clear, the charts and data are complete, and the labeling is standardized.