Maven's Marketing Campaign Analysis

This is an analysis of the Maven's marketing campaign. This analysis was done using SQL and Power BI.

After cleaning the data and using some DAX commands to create groups for the various age grades, I used SQL queries to check for null values in the data. The data contained 24 null values in the income column. This means that 24 individuals provided every information except their incomes. These null values do not significantly affect the dataset so I decided to leave them as they were.

The products on this campaign are: Meat, Fish, Fruits, Sweets, Wine and Gold. The total amount spent on these products was $1.36M. Complains received for the period was 21. Which is quite good compared to the total purchases made.

Looking at the number of web purchases show that married people and graduates make more purchases through the web. With 50.81 graduates and 38.6% of married people making their purchases through the web.

Analysis of sales made by the various sales channel shows that the store makes more sales than other channels. The web channel also makes a significant number of sales. This leave catalogue with the least amount of sales made. It is important to note that sales are made through all the sales channels.

Looking at the total spent by country and sales channels show that the highest sales were made in Spain. The sales in Spain for each sales channel are almost the same. However, the sales from the store channel are about 1% higher than the sales from the other channels. This same trend can be seen in other countries. It’s important to note that each sales channel brings in sales, with little differences from each channel across the countries.

Wine sales are the highest among all the products sold. With wine sales making $680k. That is about 50% of the total sales. The sales for meat comes next, with meat making $374k. Fruits make the least sales, with about $59k of sales.

Spending habits by marital status show that married people spend more. Followed by people under the together category and the single people. About $510k are spent by married people, $353k spent by people under the together category and $291k spent by single people. These accounts for about 84.9% of the total amount spent.

Analysis of the marketing campaign shows that the first campaign had a 21.59% success rate, the second campaign had a 4.5% success rate. The 4th campaign which had the highest success rate had a 25% success rate, which isn’t significantly higher than the first campaign. The third and fifth campaigns had the same success rate of 24.44%.

The total amount spent by age group shows that people between the age of 36 to 45 bring in the highest amount in sales. However, Average spending shows that people between the age of 66 to 75 spend more.

Analysing spending across the years show that sales were higher in 2012 and 2013 than in 2014. With 2013 having the highest amount of sales.

Some of my SQL queries identified the total number of purchases made through the web, number of wine purchases made through the web, the total amount spent through the web, and discount received from web purchases.

Further SQL analysis identified the Total product sales from each campaign, number of marital status and kid home, number of marital statuses and teen home. The Number of web visits per year, Income by country, Spending by country, and Total complaints received.

Putting all the visulas together:

RECOMMENDATION

• Spain has the biggest market for all products sold. 84.9% of the total spending comes from married people, people living together and single people. Further marketing campaigns should begin from Spain, targeting people in these categories.

• The first marketing campaign was quite successful. Future campaigns should be designed in such a way that customer follow up can be done after executing the first phase of the campaign.

• Future campaigns could also focus on improving the sales for Fruits and Fish.

• Future marketing campaigns should be designed in such a way that they will improve sales from web and catalogue channels.

• The highest amount from sales is generated from people between the age of 36 to 45. However, average sales tell us that people within the age of 66 to 75 spend more at once. This information should be infused in future campaigns to appropriately target customers.

• The sales in 2014 were quite low. It’s important to review the current marketing campaign to ensure that they are targeting the right customers.

The link to the slide deck I prepared for the analysis is here: https://bit.ly/3v8hYo3

The link to the SQL queries is here: https://github.com/Okaks/Marketing_Campaign