o The objective of the project was to do time series modelling of the sales data and predict future trends and sales values. The project also involved identification of key cost incurring are for the company and factor that affect the sales according to their importance. o The project involved cleaning of the raw data present in the company database. Finding out the relevant field from data and then to structure the data in format that would be fit for time series modelling.

1. Sales Prediction and Anomaly Detection
System
Presentation on
Summer Internship Project
At
TRIAD Marketing Services
Presented by :-
Apoorv Parmar
FMG-25

2. TOPICS OF DISCUSSION
• Company Overview
• Objectives
• Sales Forecast System
• Cleaning data
• Creating Time Series
• Visualizing Time Series
• Identifying Sales Trend
• Forecasting
• Anomaly Detection System
• Use data to forecast any anomaly in the Addes System.

3. COMPANY OVERVIEW
• TRIAD Marketing Services is a full service trade-marketing firm committed to provide our
clients a one-stop solution for all their trade and consumer marketing requirements.
• Founded in the year 2009.
• Shortlisted for ‘20 Most promising Marketing Technology Companies 2017’ by CIOReview.
• Client base consists of:
Triad Marketing Services

4. OBJECTIVES
Develop Sales Forecast System
Identify the various factors affecting the Sales
Identify the Sales Trend.
Develop the Anomaly detection Systems.

5. Resource
(Data)
Working on
the Data
Results

6. SALES DATA BY DAY

7. AVERAGE SALES DATA BY DAY(WITH OR WITHOUT SCHEME)

8. AVERAGE SALES DATA BY DAY(WITH OR WITHOUT SCHEME)
Monday 2.18,
Tuesday 2.57,
Wednesday 2.76,
Thursday 2.78,
Friday 1.95,
Saturday 2.08,
Sunday 2.29

9. Sales Factor for specific daySales Value
Sales Factor for specific daySales Value

12. ANOMALY IN DATA

14. RECOMMENDATIONS
• Encourage Retailers to use the app Timely.
• Provide Training to KRE’s to increase the usability of app.
• Provide greater incentive to Retailers to input the data in the app.
• Increase communication between Amazon and Triad Employees.

15. THANK YOU

16. Composition of Time Series DataDecomposed Time Series DataFiltering out the noise or Residual values in the System