Maven Tech Sales Performance Dashboard

MavenTech Project Description

1. Introduction

MavenTech B2B sales company which sells computer hardware, including information on accounts, products, sales teams, and sales opportunities worldwide. The main goal of this project is to create an interactive dashboard using PowerBI for sales managers to track their team's performance.

2 Objectives

1. A comparative analysis of individual performances of the teams, including regional areas, taking into account contextual data.

2. Present a summary of the MavenTech enterprise with respect to its product offerings and sales performance.

3. An analysis of the company's sales distribution across different geographical regions.

With the focus on these specific objectives, the dashboard will be designed and analysed to accomplish the project.

3 Data Preparation, Data modelling & Quality issues:

Five data tables were uploaded to the power query editor, renamed the tables were renamed according to facts and dimensions, and finally the data types. The data was clean enough to proceed. There were four CSV files available for data modelling. The data_dictionary table was given to describe the other four table parameters, and that was not the part of modelling or analysis.

At first, the fact tables and dimension tables were identified. For identification, I used primary and foreign keys for the given table. Sales_pipeline was the fact table and other three were dimension/look-up tables. Usually, the dimension table holds one column that is considered as primary key of the table and consists of all distinct values. I developed many relations between fact and dimension tables. Generally, the fact table contains multiple foreign keys in different columns which are not distinct in nature. As the tables were not complex, I followed the star schema to perform data modelling.

The quality for the data of all four tables was checked using column quality, column distribution, and column profile from the view tab of the power query editor. The data set was 100% valid with no errors.

4 Data Analysis:

A substantial amount of time was invested to understand the nature of the data. Understanding the context of the data is the most important part of the projects. Mostly, I used some bar chart, table, and matrix to define the whole context of the problem.

In any project, the fact tables are the main point of the whole analysis. Consequently, to my understanding, I started to develop data measures and a calculated column. Using the power query editor, the start of quarter, start of month, and start of week columns were created based on the close_date column to track the time-sensitive distribution of sales. Another column, ‘Deal Preparation Days’, was added by subtracting close_date from engage_date to track the number of days required to reach a deal. In the table per head, revenue of employee was added using the divide function.

In this project, the performance of the sales team depended on how many deals they won in 2017. Also, the final sales were pretty much related to the number of deals won. More specifically, I prepared an expression for Deal Won, lost, engaging, and prospection and also found the percentage of the respective deal stages. total number of deals and total sales were calculated using DAX measures. After developing each measure, it is essential to check the value of the measure using a card to justify the expression and also check for errors.

A line chart was developed to follow the distribution of sales over time in the year 2017. A bar graph described the product category of Maven Tech in terms of sales.

5 Dashboard Development:

The dashboard was developed in 3 pages, and one page was added for tooltip. To make a colourful and attractive background, I imported background images from FREEPIK (https://www.freepik.com/free-photos-vectors/dashboard-background). I also made a layout using paper and pen, considering the most vital data and graphs.

Featured dashboard

The first page describes the overall performance of the company in terms of product types, their revenue, sales data over time, Top 100 company based on sales, and revenue retention% per employee. Key performance indicators (KPIs) were included at the top of the dashboard to understand the whole scenario of the company. I created a text card based on the measures developed for all KPIs. One filter was added to segment visuals for three regions, namely east, centre, and west. All the charts and visuals were formatted based on my selected colour (yellow, light green, Purple) from format menu. I used three colours that refer to the dashboard for making the visual appealing. I also use tooltips for the area chart and bar chart to get specific detail data. To define the 100 company, I used Top N of the filter pane to filter out the top. Line and stacked column chart is used to establish a relation between revenue retention% with average deal days; however, there might be a relation between these two parameters.

Sales team performance

A two-doughnut graph was added to show the percentage of deals stages and manager’s performance. 49.3% of the deak won by Maventech and almost similar performance was observed for all six managers. The formatting was done carefully to conform to the theme color of the projects. Tooltips background, value, and level colours were adjusted for all visuals. The top 20 sales agents were listed in the stacked column chart to show their contribution to winning or losing a deal. The interactions among the visuals were edited to get specific information.

Geographical distribution

In this page, the slicer is added to filter out countries and the background colours were adjusted and formatted. A visual map was added to represent the geographical distribution of sales and their respective percentage.