Content writing training

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Video training:  

  1. Part 1: 
  2. Part 2: 

This is a content writing training program, designed to give some techniques to pointers on how we write killer and insightful content that get rank on Google Search and give us quality leads. Then we will also give you knowledge about the product, explain the ideal customer profile, and explain the reasons why customers buy our product and service. 

We want you to achieve the following:

  1. Blog content writing strategies: The guidelines on how to write the blog articles with insights, maps, charts and with the intent that our business users are looking for. Furthermore, optimize the content in such a way that it should be ranked on search engines.
  2. Publishing of the content on a website: After the draft of your content, you should have the knowledge on how to properly format the content on Webflow with SEO guidelines and then make it LIVE.
  3. Product knowledge: Our customers ask detailed technical questions, our content should answer those questions after studying the product. This will improve the engagement rate of our website on the particular content pages. 
  4. Customer knowledge: Our ideal customer profiles are documented well, our customer pain points and the ROI customers expect to achieve from using this product will help you articulate a strong case to write content for them.

What is is a location intelligence SaaS (Software as a Service) platform that provides a wide range of data sets from multiple industries worldwide. It offers comprehensive insights and tools for spatial analysis, data visualization on maps, and making data-driven decisions. The platform is designed to help businesses optimize store locations, analyze market data, and achieve growth through informed decision-making. prioritizes data quality, security, and seamless integration with a variety of datasets. It also offers advanced features such as spatial analytics, machine learning, and artificial intelligence. The platform is used by businesses in various sectors, including retail, real estate, healthcare, and transportation

What does sell? does not sell physical products. Instead, it offers a location intelligence platform that provides comprehensive insights, spatial analysis, and data visualization tools for businesses. The platform empowers businesses to make informed decisions by visualizing data, managing user access, and utilizing market-ready data for spatial analysis and decision-making.

Content Writing Guidelines:

  1. Choosing the dataset to write an Insights article
    1. In case, your manager didn’t give you the dataset to write about, you should go to xMap data catalog and choose the interesting dataset to write about. For our tutorial, I am choosing “U.S.A Gas Stations Dataset”.
  2. Load the specific dataset on xMap Studio
    1. Open your chosen dataset on xMap Studio (considering you already have signed up for the Studio and you can access datasets).
    2. After loading, you should see the below screen on xMap studio
  1. How to write an effective title of the blog article
    1. Your Blog article is the first thing your reader is gonna see, so make sure its attention-grabber yet concise and accurate.
    2. For example,  for our “U.S.A Gas Stations Dataset”: I would have the title:
      Gas Stations in the United States of America - Everything You need to Know

So in the above title, the title has been divided into 2 sections; first is the basic dataset i.e ‘Gas Stations in the United States of America’ while the second section is something you need to focus on i.e ‘Everything You need to Know’. You can see this sentence is attention grabbing and that’s what your readers will click on first impression.

  1. How to make the featured image of the blog article
    1. All our blog articles featured images have consistency. To make a featured image of your article, you need to edit a template on canva by below link: 
    2. Go to your Studio screen, and capture the screenshot of the screen where the dataset's POIs are visible with different colors and Legend is On. In my case the captured screenshot look like this:
  1. Now Go to canva and upload the screenshot, place it on your template in a way that it looks good. 
  2. Change the heading text on your canva screen to above written article title; after all editing; your canva screen will look like this:
  1. Download the Designed featured image to your computer.
  1. Draft the Blog article
    1. Outlines: First of all, make the outlines of your Blog article; you can make them by analyzing the data on Tabular View and by researching on Google what your competitors are writing about. In my case; my outlines would look like this:some text
      1. Introduction
      2. How many gas stations in the USA? - In its description, It should be written very very explicitly, like "There are 168,000 retail locations in the U.S."
      3. Distribution of U.S Gas Stations by States/Province
        1. States Names ( 5 to 6)
          1. Insightful (Maps, Charts, Tables, Heatmaps etc)
      4. Key Data Insights for Gas Stations in the U.S
        1. Website Urls
        2. Establishments inside Gas Stations
        3. Ratings Data
        4. Number of Reviews
        5. Price Ranges
        6. Phone Numbers
      5. Benefits of Geospatial Data in Gas Station Site Selection
      6. Best Practices for Leveraging Gas Stations Geospatial Insights
      7. Conclusion
        1. How xMap Data Enhances Business Insights
    2. Start Writing your article with Introduction paragraph: Your introduction paragraph should be very engaging which should tell the reader what points you are going to cover in your article and right after your introduction, have 1 strong Fact about your topic in Quotation.
    3. Make sure your headings are engaging yet concise: Write content around your headings and under every heading, include maps, charts, tables, or graphics. Please Note that these elements are necessary to add on your headings, otherwise, your content is not going to rank.

How to add Maps on your content: 

First, you will take a screenshot of the map from xMap Studio, make sure that your map should have the Legend ON. Other steps is to add the lines to explain a) What is this Map POIs for b) What these POIs represent on this map: Below is the example for your Map:

How to add Table:

Head over to Tabular View, apply filters if needed. Rearrange the columns. Now select the columns you need to have data for, and copy the data with the Copy command. 

You can go to any Sheets/Excel platform, paste your data from clipboard and your table is ready. 

How to add charts:

Charts are something that can make your reader stay on to interpret the data so it's very important to have charts in your article. To add charts, follow these steps:

  1. Go to Tabular View and Group by your choice i.e Provinces.
  2. Expand the columns section from the right side and add the relevant data for your chart.
  3. Reorder your columns and select the number of rows you want to have a chart display.
  4. Right click on your selected column and click on your desired chart to have your visualization.

In our case: by following the steps, we able to make the following chart:

  1. Write the Conclusion of your article: The last step of your article draft is to conclude your article in a single paragraph of 4 to 5 lines. After the conclusion, you must have the subheading to write some points on how xMap can help.
  1. Publishing of the content on a website:

To publish your article, you have to head over to the Webflow for Blog CMS. But first you have to make sure that the formatting of your article is correct. 

  1. Your title of the article is by default the H1 heading. 
  2. So every heading of your article should be H2 and every subheading should be H3 and so on.
  3. Your tables should be in the HTML format, you can make HTML of your table through any Online HTML editor.
  4. Make sure your charts, maps are visible.

Content Article Checklist

  1. The title of an article should be engaging yet catchy. (Can be great if you include keyword in it)
  2. The keyword should be on your first paragraph of the article. Also try to include your keyword in your subheadings or in the content 3 to 4 times.
  3. After your first paragraph, you should have relevant "Stat" or "Quote".
  4. Every article should contain basic query as a heading H2 i.e "How many gas stations in U.S.A?"
  5. Every article must have relevant maps. Sometimes you can add multiple datasets to make relevancy i.e Gas Stations with Road Traffic or Restaurants with Road Traffic.
  6. Every article must have relevant and designed charts extracted from xMap Studio.
  7. Every article must have relevant tables where applicable.
  8. You must have to follow the Formatting of every article i.e H2, H3 & H4 headings in proper order.
  9. To ensure readability to the user, make sure your paragraph isn't exceeding 3 to 4 lines.
  10. Your article will be checked for duplicate & AI generated content. So make sure, you are writing your draft smartly.

2. Understanding the Product

Datasets sales: offers a location intelligence platform specializing in delivering high-quality, up-to-date data related to points of interest (POIs) across various segments such as restaurants, bakeries, cafes, and groceries. This data is updated monthly and is available through a data subscription service, catering to a broad range of clients including major corporations like Coca-Cola and Unilever, consulting companies, government entities, and more.

Our data here: 

Key Features Offered to Customers:

  • Comprehensive POI Data: XMap provides detailed and segmented data on points of interest, useful for businesses looking to target specific markets or understand changes in geographic areas.
  • Monthly Updates: The data is refreshed every month, ensuring clients have access to the most current information for making informed decisions.
  • Customizable Data Solutions: XMap is flexible in how it packages its data, offering subscriptions based on geographic area or specific data attributes to meet diverse customer needs.
  • Quality Over Quantity: While XMap focuses on delivering high-quality data, it continually seeks to improve the depth and accuracy of its offerings.

Problems XMap Solves for Customers:

  • Market Analysis and Expansion: Companies looking to expand into new markets or understand changes in existing ones can leverage XMap's data to identify new leads, track market changes, and prioritize targets for B2B sales.
  • Sales and Marketing Optimization: With detailed POI data, companies can better strategize their marketing and sales efforts, targeting potential leads more effectively to improve their closing ratios.
  • Operational Efficiency: By outsourcing POI data collection to XMap, companies can focus on their core business operations instead of investing time and resources in data acquisition and cleaning.
  • Data-Driven Decision Making: Access to accurate and up-to-date POI data enables businesses to make informed decisions based on current market trends and consumer behaviors.

1. Comprehensive Data Acquisition:

  • USP: XMap collects data from over 200 sources, using artificial intelligence (AI) and machine learning (ML) to consolidate and refine this data. This approach ensures a more comprehensive and accurate dataset than competitors who may rely on fewer sources or less sophisticated technology.

2. Monthly Data Updates:

  • USP: The commitment to monthly updates guarantees that customers have access to the most current information, a critical factor for businesses that rely on up-to-date market intelligence to make informed decisions. This frequency is a significant advantage for customers in fast-changing industries.

3. Customization and Flexibility:

  • USP: XMap offers unparalleled flexibility in its data subscription services, allowing customers to tailor their subscriptions based on geographic areas or specific attributes of the data. This customization ensures that businesses only pay for the data they need, optimizing their investment and reducing unnecessary costs.

4. Quality over Quantity:

  • Proprietary Approach: While many competitors focus on the sheer volume of data, XMap prioritizes the quality and relevance of its data. This focus is supported by sophisticated data cleaning and processing methodologies that enhance the value of the information provided to clients.

5. Enterprise-Level Credibility:

  • Superior Service: XMap's reputation and track record of selling to multiple enterprise accounts, including notable companies like Coca-Cola, Unilever, and Lavazza, underscore its reliability and the trustworthiness of its data solutions. This credibility is a significant asset in attracting and retaining customers.

6. Solution-Oriented Approach:

  • USP: Beyond just selling data, XMap positions itself as a partner in solving customers' business challenges. Whether it's market expansion, operational efficiency, or strategic planning, XMap works closely with clients to ensure the data they receive translates into actionable insights.

7. Agile and Customer-Centric Sales Process:

  • USP: XMap's aggressive and flexible approach to sales, combined with a readiness to offer demos and samples, ensures that potential clients can quickly see the value of its product. This agility is a differentiator in industries where speed to market and rapid decision-making are crucial.

8. Global Reach with Local Expertise:

  • USP: While offering a global perspective, XMap provides data that is locally relevant, ensuring that businesses operating in or expanding into specific markets receive data that is accurate, culturally sensitive, and highly applicable to their needs.

9. Platform Usability:

  • Proprietary Technology: XMap's platform is designed for ease of use, making it accessible to users with varying levels of technical expertise. The ability to integrate XMap's data into existing systems or workflows with minimal friction is a clear competitive advantage

3. Knowing Your Audience

  • Target Market:

1. Large Enterprises with B2B Focus:

  • Examples: Coca-Cola, Unilever, Lavazza
  • Needs: These companies require detailed POI data for market analysis, expansion strategies, and to refine marketing and sales efforts, especially in the HORECA (Hotels, Restaurants, Cafés) sector.

2. Consulting Firms:

  • Examples: Companies producing industry reports for governments or private sectors, decoration and hospitality consultants.
  • Needs: High-quality data for market research, trend analysis, and strategic planning. They prioritize data accuracy and comprehensiveness for advising their clients accurately.

3. Government Entities and Public Sector Organizations:

  • Needs: Data to support urban planning, infrastructure development, and policy-making. These customers value data accuracy, geographical coverage, and the ability to subscribe to updates.

4. Retail and Distribution Companies:

  • Examples: Gas station networks, retail chains
  • Needs: Identifying new locations for expansion, understanding market dynamics, and optimizing distribution strategies. They require granular data that includes geographical spread and segment-specific insights.

5. Real Estate and Development Firms:

  • Needs: Market analysis for site selection, investment decisions, and trend tracking. These customers need up-to-date data reflecting current market conditions and opportunities.

6. Technology and Platform Developers:

  • Examples: Companies building digital twins, location-based services, or specialized platforms requiring POI data.
  • Needs: Continuous, reliable data feeds to power their platforms and ensure their offerings are based on the latest information.

7. Academic and Research Institutions:

  • Needs: Data for studies, publications, and research projects, especially in urban planning, geography, and market trends. Budgets may be lower, but data accuracy and accessibility are critical.

8. Proptech and Fintech Companies:

  • Needs: Innovative startups and tech companies looking for niche market data to develop solutions in property technology, financial services, and more. They prioritize data freshness and innovation.

Characteristics of the Ideal Customer:

  • Decision-making Authority: Entities where the decision-makers understand the value of data-driven insights and have the authority to invest in data subscriptions.
  • Budget Allocation: Organizations that allocate a specific budget for data acquisition and analytics as part of their operational, marketing, or strategic planning processes.
  • Innovation-Driven: Companies that prioritize innovation and are looking to leverage new technologies and data to gain a competitive edge.
  • Growth-Oriented: Businesses with a clear focus on expansion, whether geographically or in terms of market share, and see data as a tool to facilitate this growth.

1. Need for Comprehensive and Accurate Data:

  • Pain Point: Customers often struggle with incomplete, outdated, or inaccurate data, which can lead to poor decision-making and missed opportunities.
  • Solution: offers data collected from over 200 sources, refined through AI and ML, ensuring high accuracy and comprehensiveness.

2. Market Expansion and Strategy Development:

  • Pain Point: Companies looking to expand into new markets or refine their strategies lack the localized and sector-specific data needed to make informed decisions.
  • Solution: Monthly data updates and customization options allow businesses to receive relevant, up-to-date information tailored to their target markets and sectors.

3. Operational Efficiency and Focus:

  • Pain Point: Businesses waste resources collecting, cleaning, and analyzing data in-house, diverting focus from core activities.
  • Solution:'s subscription service offloads this burden, enabling companies to concentrate on their core offerings and strategic objectives.

4. Competitive Intelligence:

  • Pain Point: Keeping up with competitors and market trends is challenging without access to current and detailed market data.
  • Solution: provides monthly updates, helping companies stay ahead of market trends and competitor movements.

5. Optimizing Sales and Marketing Efforts:

  • Pain Point: Companies lack the detailed geographic and demographic insights needed to target marketing efforts and optimize sales strategies effectively.
  • Solution: delivers granular POI data that supports highly targeted marketing campaigns and sales strategies, improving ROI.

6. Cost and Risk Management:

  • Pain Point: Investing in data collection and analytics involves significant upfront costs and risks, particularly for businesses exploring new markets or products.
  • Solution: Flexible subscription models and customizable data sets from minimize financial risks and reduce upfront investments.

7. Data Integration and Usability:

  • Pain Point: Integrating external data into existing systems and workflows can be technically challenging and time-consuming.
  • Solution: offers data in user-friendly formats, ensuring easy integration with clients' existing systems and workflows.

8. Scalability and Flexibility:

  • Pain Point: As businesses grow, their data needs become more complex, requiring scalable and flexible data solutions that can adapt over time.
  • Solution:’s scalable data solutions and flexible subscription services ensure that businesses can easily adjust their data access as their needs evolve.

Success Stories

1. Coca-Cola's Market Expansion in Japan:

  • Challenge: Coca-Cola needed detailed insights into the changing landscape of restaurants and cafes in Japan to refine their marketing and sales strategies for the HORECA segment.
  • Solution: By subscribing to’s monthly updated data, Coca-Cola gained access to precise, localized information, enabling them to identify new sales opportunities and optimize their distribution strategy effectively.
  • Outcome: Improved market penetration and a stronger presence in the Japanese HORECA sector, leading to increased sales and revenue.

2. Unilever's Marketing Strategy in the Middle East:

  • Challenge: Unilever sought to expand its market reach and enhance its marketing efforts across Dubai, Saudi Arabia, and Egypt but lacked the targeted data to do so efficiently.
  • Solution: Utilizing’s detailed POI data, Unilever was able to identify and prioritize high-potential leads, tailoring their marketing efforts to maximize impact.
  • Outcome: Enhanced sales capabilities, better lead prioritization, and significantly improved marketing ROI in the targeted regions.

3. Consulting Firm's Industry Report for UAE Government:

  • Challenge: A consulting firm needed comprehensive and up-to-date data on the restaurant industry in the UAE to produce a detailed market report for the government.
  • Solution: The firm leveraged’s data subscription service to access the latest information on restaurant openings, closures, and trends.
  • Outcome: The production of a highly accurate and insightful industry report that informed government policy and strategy regarding the hospitality sector.

4. Retail Chain’s Site Selection Strategy:

  • Challenge: A multinational retail chain was exploring potential locations for expansion but required detailed local insights to make informed decisions.
  • Solution: With’s granular POI data, the retail chain could evaluate potential sites based on market density, competitor presence, and consumer demographics.
  • Outcome: Successful selection of optimal locations for new stores, leading to stronger market presence and increased customer footfall.

5. Digital Twin Platform Development by Tonomus (Neom):

  • Challenge: Tonomus, a subsidiary involved in building Neom’s digital twin platform, needed continuous, accurate POI and traffic information data to build comprehensive digital models.
  • Solution: supplied consistent, detailed data feeds, enabling Tonomus to integrate real-world accuracy into their digital twin platform.
  • Outcome: Enhanced platform functionality with real-time data integration, supporting urban planning and infrastructure development projects in Neom.

6. Proptech Company's Solution Development:

  • Challenge: A Proptech startup required up-to-date POI data to develop a new property technology solution but lacked the resources to collect and process this data internally.
  • Solution: The startup utilized’s data on a subscription basis, integrating it into their platform to offer customers innovative property insights and analytics.
  • Outcome: Accelerated product development, reduced go-to-market time, and a competitive edge in the Proptech industry.

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