YOUR SPOT
1. MEDIA CONCEPT
What is «MY SPACE»?
«MY SPACE» is a digital media platform dedicated to making temporary housing comfortable, functional, and personal without extensive renovations or significant expense. The project focuses on the living spaces of the younger generation: dorm rooms, rental apartments, and small studios. The platform helps find solutions for real-life constraints—limited space, restricted budgets, no-renovation clauses, and frequent moves.
The core content comprises practical guides, interior design analyses, budget selections, reader stories, and visual experiments using artificial intelligence. The project’s unique feature is the ability to adapt interior design ideas to a specific space, rather than offering universal solutions for an abstract apartment.
Main Idea: Temporary housing does not mean a temporary life.
Why Does Media Need Data?
Data helps the editorial team understand what genuinely interests the audience, what problems residents of rental apartments and dormitories face, and what solutions might be helpful.
Instead of choosing topics solely based on personal assumptions, the editorial team uses search statistics, reader feedback, expert materials, product data, and its own publication analytics.
The gathered information helps to:
— identify relevant topics for new content; — determine the most common issues of our audience; — verify the practical applicability of interior design recommendations; — create personalized materials; — assess the effectiveness of publications; — adjust the media content plan.
This data forms the basis for editorial decisions, and AI helps to identify patterns and process information more quickly.
2. DATA SOURCES
Where Does Media Get Its Information?To create useful and accurate content, the editorial team draws from five primary groups of sources. 01. Search Data Information about what people search for online: storage problems, ideas for small rooms, budget decor, space organization, and furnishing rental housing. Sources: • Yandex Wordstat. • Google Trends. • Search suggestions and related queries.02. Audience Data Information provided voluntarily by readers: survey responses, comments, questions, photos of rooms, and descriptions of domestic challenges.Sources: • Telegram polls. • Google Forms. • Reader comments and messages. • User-submitted photos and stories (with author consent). 03. Expert and Informational Materials Professional information used to validate recommendations and explain the principles of designing living spaces.Sources: • Publications by architects and designers. • Specialized interior design publications. • Research on living environments. • Instructions from furniture and finishing material manufacturers. • Professional guides and regulatory documents.04. Product and Pricing Data Information on available interior items, materials, furniture, and solutions for budget-friendly furnishing. Sources: • Official manufacturer websites. • Online stores. • Furniture and interior item catalogs. • Official product instructions and specifications.05. Internal Media Analytics Data generated during the project’s operation, which helps gauge audience interest.Sources: • Publication view statistics. • Reactions, comments, and shares. • Website traffic count. • Survey results. • Popularity of specific sections and formats.
Yandex Wordstat
Data type: search statistics.
Yandex Wordstat helps determine which interior design themes and everyday problems interest users of the search engine.
The service shows search query dynamics, popular phrases, related searches, and regional variations.
How media uses it:
The editorial team analyzes queries related to topics such as:
• «how to furnish a small room»;
• «storage solutions for dormitories»;
• «decorating a rental apartment»;
• «how to hang a poster without drilling»;
• «how to make a room cozier».
The data gathered helps select topics, formulate headlines, and identify the questions the audience is truly looking for answers to. Result: a list of in-demand topics for future publications.
Google Trends
Data Type: trend in topic interest.
Google Trends is used to compare the popularity of search queries and track shifts in interest toward interior design topics.
How the media uses it:
The editorial team compares queries such as:
• storage solutions;
• small apartment;
• budget interior design;
• DIY decor;
• rental apartment.
This allows us to see which topics are becoming more relevant and which maintain stable interest.
Result: understanding thematic trends and the ability to update the editorial calendar promptly. It is important to note that Google Trends shows normalized relative interest, not the absolute number of search queries.
Audience Feedback
Data Type: User responses and qualitative information. The media gathers information directly from readers to understand their real needs and living constraints.
How the media utilizes it:
Surveys about housing arrangement issues are posted on Telegram. Google Forms can be used to collect more detailed answers and voluntary applications for participation in the «Room Analysis» segment.
Sample questions:
• What is the biggest barrier to feeling at home?
• What budget are you willing to allocate for the setup?
• What cannot be changed in your living space?
• Which area of the room requires improvement first?
• What interior design solutions have you already tried?
Result: real audience requests that become the foundation for new publications.
Photos of the facilities are used only with the authors' permission.
Expert Sources and Product Catalogs
Data Type: Verifiable professional and commercial information.
To prepare interior recommendations, the editorial team consults specialized publications, professional materials, and official product specifications.
How the media uses the information:
• Verifies the properties of materials and furniture.
• Studies installation and usage methods for items.
• Compares the dimensions and functionality of products.
• Checks the usage limitations for fasteners and finishing materials.
• Confirms pricing before publishing budget selections.
Result: practical recommendations that consider not only the visual aspect but also the real characteristics of the items.
In-House Media Analytics
Data Type: project performance statistics. After publishing materials, the editorial team analyzes audience reaction and the effectiveness of the chosen topics.
Key Metrics:
• Publication views.
• Reactions and comments.
• Number of shares (reposts).
• Website traffic.
• Number of poll responses.
• Popularity of individual sections.
How the media is used: If publications about storing and organizing small rooms receive more saves and comments, the editorial team may increase the number of similar materials next month.
Result: Adjusting the content plan based on audience behavior rather than solely on the editors' assumptions.
3. WHAT DATA DOES THE MEDIA COLLECT?
What data does the editorial team process?
The media utilizes both structured and unstructured data in its work.
Structured Data
Information that can be presented in the form of tables, numbers, and categories.
Examples:
• Search query frequency.
• Publication view count.
• Reader budget.
• Room size.
• Survey results.
• Prices for interior furnishings.
Unstructured Data
Information that requires additional analysis and interpretation.
Examples:
• Room photographs.
• Reader comments.
• Textual answers to questions.
• Resident interviews.
• Descriptions of household issues.
• Expert articles and instructions.
Both types of data are crucial for the project: structured data helps identify patterns, while unstructured data allows for understanding context and people’s real needs.
4. DATA PROCESSING FLOWCHART
From Source to Publication
Working with data in «IN YOUR PLACE» is structured as a sequential process where machine processing helps accelerate routine tasks, while the human element is responsible for meaning, verification, and the final editorial decision.
01. Data Collection The editorial team gathers search statistics, audience feedback, facility photographs, expert materials, and product information.02. Primary Processing The data is sorted, duplicates are removed, information is categorized by theme, and it is formatted for ease of use.03. Analysis AI assists in identifying recurring issues, grouping queries, and suggesting future content topics.04. Editorial Review The editor verifies the accuracy of the information, assesses the topic’s relevance, and decides which data can be used in publications.05. Content Creation Based on the verified information, articles, collections, cards, video scripts, and interior visualizations are created.06. Results Analytics After publication, the editorial team studies audience reactions and uses the results to update the content plan.
Who is responsible for what?
DATA SOURCES Search queries · Surveys · Room photos · Expert materials · Product catalogs · Publication statistics↓MACHINE PROCESSING • Information gathering and structuring. • Removal of duplicate entries. • Sorting by thematic categories. • Grouping similar queries. • Identifying recurring issues. • Drafting and creating headline variations. • Generating preliminary visualizations. • Forming summary tables.↓HUMAN PROCESSING • Selecting a relevant topic. • Verifying sources and facts. • Assessing the reliability of AI conclusions. • Checking product prices and specifications. • Evaluating the feasibility of interior design solutions. • Editing and approving the text. • Reviewing visual materials. • Deciding on publication.↓RESULT The final «YOUR SPACE» material, based on data, reviewed by the editorial team, and tailored to audience needs.↓FEEDBACK Views · Reactions · Comments · Shares · Survey responsesResults are returned to the editorial office and used for the next planning cycle.
Task Segmentation
5. DATA WORK EXAMPLE
From Reader’s Problem to Final Article
Original Task
The editorial team wants to prepare material on organizing storage in small dormitory rooms.
Stage 1. Information Gathering The editorial team studies search queries related to storage solutions, analyzes reader feedback on Telegram, and collects common problems associated with small rooms.Stage 2. Machine ProcessingAI groups the received feedback by topic: • lack of clothing space; • absence of a dedicated wardrobe; • desk clutter; • insufficient use of vertical space; • lack of space under the bed.Stage 3. Human Analysis The editor selects the most relevant issues and determines which ones can be solved without major renovations or large expenses.Stage 4. Material Preparation AI assists in structuring the article and suggesting headline options. The editor reviews the recommendations, clarifies item usage conditions, and edits the text.Stage 5. Visualization AI generates preliminary images of potential storage organization solutions. The editor verifies whether these options align with the real limitations of a small space. Stage 6. Publication and Analysis The material is published on the website and adapted for Telegram. After publication, the editorial team assesses views, reactions, saves, and comments.
