Excel to Power BI

Tittle: Analysis of Top Uk Youtubers

excel-to-powerbi-animated-diagram

Table of contents

Objective

The Head of Marketing wants to find out who the top YouTubers are in 2024 to decide on which YouTubers would be best fit to run marketing campaigns throughout the rest of the year.

To create a dashboard that provides insights into the top UK YouTubers in 2024 that includes their

This will help the marketing team make informed decisions about which YouTubers is best fit to collaborate with in the upcoming marketing campaigns.

User story

As the Head of Marketing, I want to use a dashboard that analyses YouTube channel data in the UK.

This dashboard should allow me to identify the top performing channels based on metrics like subscriber base and average views.

With this information, I can make more informed decisions about which Youtubers are right to collaborate with, and therefore maximize how effective each marketing campaign is.

Data source

We need data on the top UK YouTubers in 2024 that includes their

Stages

Design

Dashboard components required

To understand what it should contain, we need to figure out what questions we need the dashboard to answer:

  1. Who are the top 10 YouTubers with the most subscribers?
  2. Which 3 channels have uploaded the most videos?
  3. Which 3 channels have the most views?
  4. Which 3 channels have the highest average views per video?
  5. Which 3 channels have the highest views per subscriber ratio?
  6. Which 3 channels have the highest subscriber engagement rate per video uploaded?

For now, these are some of the questions we need to answer, this may change as we progress down our analysis.

Design mockup

Some of the data visuals that may be appropriate in answering our questions include:

  1. Table
  2. Treemap
  3. Scorecards
  4. Bar chart

Dashboard-Mockup

Tools

Tool Purpose
Excel Exploring the data
SQL Server Cleaning, testing, and analyzing the data
Power BI Visualizing the data via interactive dashboards
GitHub Hosting the project documentation and version control
Mokkup AI Designing the wireframe/mockup of the dashboard

Development

Pseudocode

  1. Get the data
  2. Explore the data in Excel
  3. Load the data into SQL Server
  4. Clean the data with SQL
  5. Test the data with SQL
  6. Visualize the data in Power BI
  7. Generate the findings based on the insights
  8. Write the documentation + commentary
  9. Publish the data to GitHub Pages

Data exploration

This is the stage where you have a scan of what’s in the data, errors, inconcsistencies, bugs, weird and corrupted characters etc

  1. There are at least 4 columns that contain the data we need for this analysis, which signals we have everything we need from the file without needing to contact the client for any more data.
  2. The first column contains the channel ID with what appears to be channel IDS, which are separated by a @ symbol - we need to extract the channel names from this.
  3. Some of the cells and header names are in a different language - we need to confirm if these columns are needed, and if so, we need to address them.
  4. We have more data than we need, so some of these columns would need to be removed

Data cleaning

The aim is to refine our dataset to ensure it is structured and ready for analysis.

The cleaned data should meet the following criteria and constraints:

Below is a table outlining the constraints on our cleaned dataset:

Property Description
Number of Rows 100
Number of Columns 4

And here is a tabular representation of the expected schema for the clean data:

Column Name Data Type Nullable
channel_name VARCHAR NO
total_subscribers INTEGER NO
total_views INTEGER NO
total_videos INTEGER NO
  1. Remove unnecessary columns by only selecting the ones you need.
  2. Extract Youtube channel names from the first column.
  3. Rename columns using aliases.

Transform the data

/*
# 1. Select the required columns
# 2. Extract the channel name from the 'NOMBRE' column
*/

-- 1.
SELECT
    SUBSTRING(NOMBRE, 1, CHARINDEX('@', NOMBRE) -1) AS channel_name,
    total_subscribers,
    total_views,
    total_videos

FROM
    top_uk_youtubers_2024

Cleaning-data-1

Create the SQL view

/*
# 1. Create a view to store the transformed data
# 2. Cast the extracted channel name as VARCHAR(100)
# 3. Select the required columns from the top_uk_youtubers_2024 SQL table 
*/

-- 1.
CREATE VIEW view_uk_youtubers_2024 AS

-- 2.
SELECT
    CAST(SUBSTRING(NOMBRE, 1, CHARINDEX('@', NOMBRE) -1) AS VARCHAR(100)) AS channel_name, 
    total_subscribers,
    total_views,
    total_videos

-- 3.
FROM
    top_uk_youtubers_2024

Cleaning-data-2

Testing

Row count check & Column count check

/*
# Count the total number of records (or rows) are in the SQL view
*/

SELECT
    COUNT(*) AS no_of_rows
FROM
    view_uk_youtubers_2024;

/*
# Count the total number of columns (or fields) are in the SQL view
*/


SELECT
    COUNT(*) AS column_count
FROM
    INFORMATION_SCHEMA.COLUMNS
WHERE
    TABLE_NAME = 'view_uk_youtubers_2024'

Data-quality-check

Data type check & Duplicate count check

/*
# Check the data types of each column from the view by checking the INFORMATION SCHEMA view
*/

-- 1.
SELECT
    COLUMN_NAME,
    DATA_TYPE
FROM
    INFORMATION_SCHEMA.COLUMNS
WHERE
    TABLE_NAME = 'view_uk_youtubers_2024';

/*
# 1. Check for duplicate rows in the view
# 2. Group by the channel name
# 3. Filter for groups with more than one row
*/

-- 1.
SELECT
    channel_name,
    COUNT(*) AS duplicate_count
FROM
    view_uk_youtubers_2024

-- 2.
GROUP BY
    channel_name

-- 3.
HAVING
    COUNT(*) > 1;

Data-quality-check

Visualization

Results

Visualization This shows the Top UK Youtubers in 2024 so far.

Dax measures

  1. Total Subscribers (M) ```powerbi Total Subscribers (M) = VAR million = 1000000 VAR sumOfSubscribers = SUM(view_uk_youtubers_2024[total_subscribers]) VAR totalSubscribers = DIVIDE(sumOfSubscribers,million)

RETURN totalSubscribers


2. Total Views (B)
```powerbi
Total Views (B) = 
VAR billion = 1000000000
VAR sumOfTotalViews = SUM(view_uk_youtubers_2024[total_views])
VAR totalViews = ROUND(sumOfTotalViews / billion, 2)

RETURN totalViews
  1. Total Videos ```powerbi Total Videos = VAR totalVideos = SUM(view_uk_youtubers_2024[total_videos])

RETURN totalVideos


4. Average Views Per Video (M)
```powerbi
Average Views per Video (M) = 
VAR sumOfTotalViews = SUM(view_uk_youtubers_2024[total_views])
VAR sumOfTotalVideos = SUM(view_uk_youtubers_2024[total_videos])
VAR  avgViewsPerVideo = DIVIDE(sumOfTotalViews,sumOfTotalVideos, BLANK())
VAR finalAvgViewsPerVideo = DIVIDE(avgViewsPerVideo, 1000000, BLANK())

RETURN finalAvgViewsPerVideo
  1. Subscriber Engagement Rate ```powerbi Subscriber Engagement Rate = VAR sumOfTotalSubscribers = SUM(view_uk_youtubers_2024[total_subscribers]) VAR sumOfTotalVideos = SUM(view_uk_youtubers_2024[total_videos]) VAR subscriberEngRate = DIVIDE(sumOfTotalSubscribers, sumOfTotalVideos, BLANK())

RETURN subscriberEngRate

6. Views per subscriber
```powerbi
Views Per Subscriber = 
VAR sumOfTotalViews = SUM(view_uk_youtubers_2024[total_views])
VAR sumOfTotalSubscribers = SUM(view_uk_youtubers_2024[total_subscribers])
VAR viewsPerSubscriber = DIVIDE(sumOfTotalViews, sumOfTotalSubscribers, BLANK())

RETURN viewsPerSubscriber

Analysis

Findings

Here are the key questions we need to answer for our marketing client:

  1. Who are the top 10 YouTubers with the most subscribers?
  2. Which 3 channels have uploaded the most videos?
  3. Which 3 channels have the most views?
  4. Which 3 channels have the highest average views per video?
  5. Which 3 channels have the highest views per subscriber ratio?
  6. Which 3 channels have the highest subscriber engagement rate per video uploaded?

1. Who are the top 10 YouTubers with the most subscribers?

Rank Channel Name Subscribers (M)
1 NoCopyrightSounds 33.60
2 DanTDM 28.60
3 Dan Rhodes 26.50
4 Miss Katy 24.50
5 Mister Max 24.40
6 KSI 24.10
7 Jelly 23.50
8 Dua Lipa 23.30
9 Sidemen 21.00
10 Ali-A 18.90

2. Which 3 channels have uploaded the most videos?

Rank Channel Name Videos Uploaded
1 GRM Daily 14,696
2 Manchester City 8,248
3 Yogscast 6,435

3. Which 3 channels have the most views?

Rank Channel Name Total Views (B)
1 DanTDM 19.78
2 Dan Rhodes 18.56
3 Mister Max 15.97

4. Which 3 channels have the highest average views per video?

Channel Name Averge Views per Video (M)
Mark Ronson 32.27
Jessie J 5.97
Dua Lipa 5.76

5. Which 3 channels have the highest views per subscriber ratio?

Rank Channel Name Views per Subscriber
1 GRM Daily 1185.79
2 Nickelodeon 1061.04
3 Disney Junior UK 1031.97

6. Which 3 channels have the highest subscriber engagement rate per video uploaded?

Rank Channel Name Subscriber Engagement Rate
1 Mark Ronson 343,000
2 Jessie J 110,416.67
3 Dua Lipa 104,954.95

Notes

For this analysis, we’ll prioritize analysing the metrics that are important in generating the expected ROI for our marketing client, which are the YouTube channels with the most

Validation

1. Youtubers with the most subscribers

Calculation breakdown

Campaign idea = product placement

a. NoCopyrightSounds

b. Dan TDM

c. Dan Rhodes

Best option from category: Dan Rhodes

2. Youtubers with the most videos uploaded

Calculation breakdown

Campaign idea = sponsored video series

a. GRM Daily

b. Manchester City

c. Yogscast

Best option from category: Yogscast

3. Youtubers with the most views

Calculation breakdown

Campaign idea = Influencer marketing

a. DanTDM

b. Dan Rhodes

c. Mister Max

Best option from category: Mister Max

Discovery

We discovered that

  1. NoCopyrightSOunds, Dan Rhodes and DanTDM are the channnels with the most subscribers in the UK.
  2. GRM Daily, Man City and Yogscast are the channels with the most videos uploaded.
  3. DanTDM, Dan RHodes and Mister Max are the channels with the most views.
  4. Entertainment channels are useful for broader reach, as the channels posting consistently on their platforms and generating the most engagement are focus on entertainment and music.

Recommendations

  1. Dan Rhodes is the best YouTube channel to collaborate with if we want to maximize visbility because this channel has the most YouTube subscribers in the UK.
  2. Although GRM Daily, Man City and Yogcasts are regular publishers on YouTube, it may be worth considering whether collaborating with them with the current budget caps are worth the effort, as the potential return on investments is significantly lower compared to the other channels.
  3. Mister Max is the best YouTuber to collaborate with if we’re interested in maximizing reach, but collaborating with DanTDM and Dan Rhodes may be better long-term options, considering the fact that they both have large subscriber bases and are averaging significantly high number of views.
  4. The top 3 channels to form collaborations with are NoCopyrightSounds, DanTDM and Dan Rhodes based on this analysis, because they attract the most engagement on their channels consistently.

Potential ROI

  1. Setting up a collaboration deal with Dan Rhodes would make the client a net profit of $1,065,000 per video.
  2. If we go with a product placement campaign with DanTDM, this could generate the client approximately $484,000 per video.
  3. NoCopyrightSounds could profit the client $642,000 per video too (which is worth considering).

Actions plan

Based on our analysis, we beieve the best channel to advance a long-term partnership deal with to promote the client’s products is the Dan Rhodes channel.

We’ll have conversations with the marketing client to forecast what they also expect from this collaboration. Once we observe we’re hitting the expected milestones, we’ll advance with potential partnerships with DanTDM, Mister Max and NoCopyrightSounds channels in the future.

  1. Reach out to the teams behind each of these channels, starting with Dan Rhodes.
  2. Negotiate contracts within the budgets allocated to each marketing campaign.
  3. Kick off the campaigns and track each of their performances.
  4. Review how the campaigns have gone, gather insights and optimize based on feedback from converted customers and each channel’s audiences.

Conclusion

Base on the findings and analysis of the viewership and views per subscriber, Dan Rhodes appears to be the best option to advance with due to higher returns of investment compared to other channels. Hence the conclusion was that the head of marketing, will work with Dan Rhodes to run it`s current marketing campaing throughout the rest of the year as per the analysis.