DEV Community: Aryan Zingade

Stake.com A Case Study

Aryan Zingade — Tue, 05 May 2026 16:27:45 +0000

Objective

The objective of the case study is to understand the rise of Stake.com, which emerged from nothing but a niche crypto casino platform to a global gambling platform with an increased number of users. The case study will also analyze the unique strategies Stake.com took up to see how it stood out in the industry.

Background & Context

Before the emergence of Stake.com, the gambling industry was dominated by established casino giants with decades of experience and brand recognition such as the Las Vegas casinos and online platforms like BetMGM and Caesars.

Year 2009, Bitcoin burst onto the scene, and caught people's eye. It started growing more and more into the crypto world. Cryptocurrencies promised decentralization, anonymity, and faster transactions, capturing the imagination of tech-savvy individuals.

The popularity of cryptocurrencies (Bitcoin) presented a unique opportunity to tap into a rapidly growing and engaged audience.
Stake.com was founded in 2017, by Craven and his US co-founder Bijan Tehrani, when the founders saw an opportunity in the promising world of crypto-gambling.

The founders in 2013 started off by creating Primedice, an online dice game that allowed players to bet in crypto. Since this worked well, they officially formed Stake.com as a fully-fledged gambling platform.

They positioned themselves as the premier platform for players seeking a seamless and secure experience using their digital assets. The primary objective was to stand out and grow larger than the giants of the industry.

Challenge & Opportunity

The opportunity Stake.com saw was the increased popularity of cryptocurrencies. It is quite interesting because the challenge was also along the lines of the same statement. Even though popularity increased, building trust and overcoming skepticism towards crypto based gambling was the crucial hurdle which had to be overcome for establishing a brand in the middle of a crowded market.

Since crypto is unregulated, it had its pros and cons; the pro being that there was freedom and less legal regulations, the con being that due to less regulations, there was scope of uncertainty and things going south. Maintaining a balance between this was a big challenge Stake.com had to face.

Strategy & Approach

The opportunity Stake.com saw over here was using the credibility of popular icons, influencers and streamers as there were many avid figures who fell under this category. Partnering up with them and building a brand was an excellent way to gain customer trust. One such incredible partnership was with the Global Rap Icon, Drake, who himself was a huge crypto enthusiast. Drake signed a $100,000,000/year endorsement deal with the company. Drake posts regularly about his gambling bets and how he has earnt millions on a single deal. The massive fan following of drake brought in an enormous number of customers to the platform.

Stake.com made high-profile sponsorships, which included huge collaborations with events such as UFC, football clubs such as Everton FC and Watford FC, and finally getting the title sponsorship with the Formula 1 team Alfa Romeo - Sauber. This showed Legitimacy.
Stake.com invested heavily in building a platform which is engaging. They built a user-friendly and appealing platform with a variety of betting options for the customers to pick from. Lastly, they also had reward programs for customers who did sign up.

Execution

Stake's influencer partnerships was the primary form of execution to gain popularity. Streamers broadcasted live gameplay sessions, showcasing the platform's features and generating excitement among viewers. Engagement increased by the incentives offered to the customers in the form of reward programs. Title sponsorships such as UFC and the Football and F1 teams was a good way to catch the eye of customers.

Metrics & Measurement

Stake.com became the world's seventh largest gambling platform by revenue touching nearly $2.6 Billion.

Revenue figures:

2020: $105 Million
2021: $1.2 Billion
2022: $2.6 Billion
2023: $4.3 Billion

Analysts expect its revenue to reach $145 Billion by the year 2030.
Number of registered users: 5 million+
Year On Year growth: 400%. This figure shows the impact of marketing campaigns in reaching new audience
Social media followers: 200% increase
Repeat User Rate: 80%
Average session duration: 30+ minutes
Stake.com's impressive growth, user engagement, and financial performance stand as strong evidence of their successful marketing strategies.

Creative Elements: Advertisements

Stake Your Claim: Own Your Game.
Link

Stake.com launched this ad as a form of publicity. The ad has symbols like dice, cards, and digital avatars, showing the background of gambling and representing the concept of taking control and "owning your game".

The animation style gives a feel like it's from the 90s showing how gambling was in the past and how much it has evolved.
The ad features a mix of individuals from different backgrounds and ethnicities, reflecting Stake.com's global audience and inclusivity message.

The central message revolves around empowering individuals to take control of their lives and opportunities, symbolized by "staking your claim."

Drake x Stake
Link

This campaign was made due to the immense fan following of Drake. The ad has a soundtrack in the background which is a genre the current generation loves listening to. That is somewhat enough to pull audience towards Stake. At the end of the ad, Drake says "Trynna play some Roulette to be honest" which is again a gambling game, and tries to deliver the message that Stake.com has multiple gambling games.

Customer Feedback
This is an overlook of the average customer feedback after using Stake.com.

Some reviews of customers:

Key Takeaways

This growth of Stake.com can teach several businesses a lot. Some of the prime takeaways are:

Embracing innovation and catering to niche markets.
Leveraging strategic and huge partnerships and influencer marketing.
Building a user-centric and engaging platform.
Maintaining a strong community focus.

Future Recommendations

Maintaining and addressing regulatory concerns on a time-to-time basis is something that should be looked after proactively. Responsible gaming practices should be encouraged and promoted to the users using this platform. Bringing in more products and games on the platform, and also introducing more cryptocurrencies to gamble with is another aspect Stake should look into. Lastly, maintaining customer relations by offering good reward programs and constantly trying to improve the user experience is crucial.

Bringing Together Containers & SQL

Aryan Zingade — Tue, 07 Jan 2025 06:08:46 +0000

Having read about it in theory, I used Docker and understood how containerisation actually works in one of my recent mini projects. This mini project is a combination of some tools and technologies that are new to my knowledge (Docker and Flask) and tools such as SQL and Python that I have used in the past. The application builds visualisations based on the queries it asks the users to input on the dashboard; a dashboard for data stored on SQL databases.

Architecture

Flask API & connecting to SQL

First, I established the connection to the SQL database using the mysql.connector written within a function. Depending upon your database, user and host, the credentials need to be updated.

def get_connection():
    try:
        logger.debug("Connecting to MySQL database...")
        connection = mysql.connector.connect(
            host='db', user='root', password='yourpassword', database='hotel'
        )
        logger.debug("Successfully connected to MySQL database")
        return connection
    except mysql.connector.Error as err:
        logger.error(f"Error connecting to database: {err}")
        return None

The heart of the application is built using Flask. The Flask API works with the endpoint /run_query which is programmed to handle both GET and POST requests. The GET request is in charge of retrieving the input from the users and POST is in charge of sending the requests to the server.

@app.route('/run_query', methods=['GET', 'POST'])

The functionality defined at the API endpoint is a simple retrieval and visualisation process. Query validation is done to check if the query is empty or not and is then executed on the databases. Flask uses the cursor to access the results, which are then stored as a list of rows, along with which column names are extracted, for plotting purposes.

def run_query():
    chart_image = None 
    if request.method == 'POST':
        query = request.form.get('sql_query') 

        if not query:
            logger.debug("No query entered by the user")
            return render_template('index.html', chart_image=None)

        connection = get_connection()
        cursor = connection.cursor()

        try:
            logger.debug(f"Executing query: {query}")
            cursor.execute(query) 
            result = cursor.fetchall() 
            columns = [desc[0] for desc in cursor.description] 
            logger.debug(f"Query Result: {result}")
            logger.debug(f"Columns: {columns}")

            if not result:
                logger.debug("No results returned from the query")
            x = [row[0] for row in result]
            y = [row[1] for row in result]

            if not x or not y:
                logger.debug("X or Y values are empty, no chart will be generated")

A key feature I have integrated is converting the outputs as graphs. The application is good for scenarios when more than one variable is being fetched, which means the variables can be plotted against one another. The charts are created using Matplotlib, and the choice of chart can vary as per the data being fetched. For the purpose of demonstration, I have implemented a bar chart. The chart is then saved as an in-memory image, encoded into base64 format, and sent back to the frontend. This ensures the chart can be displayed on the dashboard without saving any files locally.

            fig, ax = plt.subplots()
            ax.bar(x, y)
            ax.set_xlabel(columns[0])
            ax.set_ylabel(columns[1])
            ax.set_title('Query Result')

            img_io = BytesIO()
            fig.savefig(img_io, format='png')
            img_io.seek(0) 
            img_data = base64.b64encode(img_io.getvalue()).decode('utf-8') 
            chart_image = img_data

        except mysql.connector.Error as err:
            chart_image = None 
            logger.error(f"Error executing query: {err}")
        finally:
            connection.close() 
    return render_template('index.html', chart_image=chart_image)

Frontend

The frontend is rather basic for this application but does the job. The form (input of SQL query) collects the queries via a POST request. The frontend also displays a section for the chart, depending upon whether the query was executed or not. If a query is successfully executed, the chart is displayed in the form of an embedded image encoded in Base64 format. This ensures seamless integration without the need to store image files locally, making the application lightweight and efficient.

<!DOCTYPE html>
<html lang="en">
<head>
    <title>Data Dashboard</title>
</head>
<body>
    <h1>SQL Query Data Dashboard</h1>
    <form method="POST" action="/run_query">
        <textarea name="sql_query" rows="4" cols="50" placeholder="Enter your SQL query here..."></textarea><br><br>
        <button type="submit">Submit Query</button>
    </form>
    {% if chart_image %}
        <h3>Query Result Chart</h3>
        <img src="data:image/png;base64,{{ chart_image }}" alt="Chart">
    {% endif %}
</body>
</html>

Docker Components

First, the Dockerfile - A set of instructions that serves as an image for the Flask app. It includes specifications and commands that need to be run in the container. It automates and takes away the hurdle of manually having to install each and every dependancy. An important part of this file is to set the working directory (/app in this case), which is where all subsequent commands that come later in the file, will be run.

FROM python:3.9-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
CMD ["python", "app.py"]

Next, the compose file - Essentially specifying the services that contain the multiple containers present in the application. In this case, I have specified two containers - Flask and SQL. Other than configuration details such as ports and environments, the containers are linked for the application to run. Here, the flask container depends on the SQL container for the data.

services:
  db:
    image: mysql:8.0
    environment:
        - MYSQL_ROOT_PASSWORD=${DB_PASSWORD}
        - MYSQL_DATABASE=${DB_NAME}
    ports:
        - "3307:3306"
    volumes:
        - db_data:/var/lib/mysql

  web:

    build: .
    ports:
        - "5002:5002"
    depends_on:
        - db
    environment:
        - FLASK_ENV=${FLASK_ENV}
        - DB_HOST=${DB_HOST}
        - DB_USER=${DB_USER}
        - DB_PASSWORD=${DB_PASSWORD}
        - DB_NAME=${DB_NAME}
    volumes:
        - .:/app
volumes:
  db_data:

Data population - A Learning

During the development of this app, I faced the error of queries not being executed due to 'data not existing'. This kept me wondering, because the connection with the SQL database was successfully established. Here is when I realised that using SQL while containerising the application was slightly different and needed some more setups.

A container is nothing but a virtual machine which works only when it has all its dependancies and data. While integrating containers and SQL, a separate container is created for the SQL database, which is where data will be extracted from. Something to note here is that, even though a container is created, does not mean the data has been copied into it. This is something that has to be done manually. Data from the local device can be copied into the container by creating a .sql file, which is a portable file and can be pasted by accessing the container in bash mode. Now that the container has been populated, we can get results as per queries.

Conclusion

Throughout the development, challenges such as managing SQL data within containers offered me valuable learning experiences, further solidifying my understanding of containerisation and database interactions. The project lays a foundation for building more robust and feature-rich applications in the future, with opportunities for scalability, improved frontend design, and enhanced user engagement.