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Data Analytics
Marketing Dashboard
A marketing dashboard reveals everything which improves your business and profit.
June 21, 2024
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Client
Based in the UK, our client is Marketing company . They provide services across sectors such as education, Health, Retail, Banking
Industry
Marketing and Consulting Services
Overview
Need to Analyze their Marketing Data.
Business Requirements
Client need a solution to connect multiple data sources Centralization of Data and Centralized Report.
Analytic Insights
Used Tableau Servers, Python for predictive models.
Correlation of products shows which products are frequently sold together. Highest revenue earned product category is descendible shown in a tree map. Purchasing behavior shows the segmented product combinations and values. There is no severe increase in revenue with date.
By comparing the years there is a slight increase from 2016 to 2017 but a steep decrease from 2017 to 2018.
Key Features
Easy Data Management Live stream Data Analysis and Dashboard Personal dashboard for different level of Management
Revenue
Revenue is the amount of money that a company actually receives during a specific period, including discounts and deductions for returned merchandise. It is the top line or gross income figure from which costs are subtracted to determine net income. Revenue is calculated by multiplying the price at which goods or services are sold by the number of units or amount sold.
Transaction Lines
Transactions consist of at least one or more transaction lines. Transaction lines represent details, such as quantity, pricing and description, of the products sold.
Business Benefits
Increase production of frequently brought items. Increase production of highly earning product categories. From the table find out the product combinations which are highly sold and increased revenue, and concentrate on them. Improve marketing skills and thereby revenue.
Result and Analysis
Enhanced Performance
METAL achieves improvement over the current best result in the chart generation task. For the LLaMA base model, the average F1 score of METAL improves by 11.33% over Direct Prompting with 5 test-time compute recurrences. Similarly, for the GPT base model, METAL outperformed baselines by a considerable margin, achieving an average F1 score of 86.46%, which is improved 5.2% in average over Direct Prompting.
Tech Stack
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Tableau
MySQL
Google Analytics
Google BigQuery
CASE STUDIES
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