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Sep 22, 2024, 5:59 PM

Data sheet - April - Sept 2020 - GRPs Spends.xlsx

Missing file

I would like to understand the ad spends and Spending Trends: You can analyze the relationship between spend allocation on different channels or time slots and the GRPs (audience reach).

Prime-Time vs Non-Prime-Time Performance: Investigating if certain genres (like news or religious content) perform better in non-prime-time slots in different regions could help in optimizing future media spend.

Regional Breakdown: Compare the effectiveness of campaigns in different markets (e.g., Bihar vs. Kerala) based on GRP data, adjusting future campaigns for region-specific preferences.

Let's start by loading the Excel file and examining its structure. This will help us understand the data and proceed with the analysis.

I'll first display the sheet names to understand the structure of the file.

The Excel file contains the following sheets:

Raw Dataset
Dataset analysis implications
Info

To proceed with the analysis, we will focus on the Raw Dataset sheet, as it likely contains the primary data for ad spends and GRPs.

The Raw Dataset sheet has been loaded successfully. Here are the first few rows of the dataset:

Channel	Genre	Market	Date	Month	Week Day	Start Time {Av(Tm)}	Hrs	PT / NPT	Time Band	...	Kerala.1	TN/Pondicherry.1	Bihar/Jharkhand.1	MP/Chhattisgarh.1	Pun/Cha.1	Har/HP/J&K.1	HSM.1	HSM Urban.1	HSM Rural.1
Aaj Tak	News	HSM	2020-04-01	Apr'20	Wednesday	14:50:43	14	NPT	12:00-17:59	...	0.11	0.06	0.150	0.18	0.23	0.50	0.220	0.27	0.170
Aaj Tak	News	HSM	2020-04-01	Apr'20	Wednesday	15:24:00	15	NPT	12:00-17:59	...	0.00	0.00	0.370	0.14	0.26	0.04	0.120	0.13	0.120
Aastha	Religious	All India	2020-04-01	Apr'20	Wednesday	06:50:33	6	NPT	0:00-06:59	...	0.00	0.00	0.135	0.00	0.00	0.00	0.015	0.03	0.015
ABP Ananda	Bengali Sat	WB	2020-04-01	Apr'20	Wednesday	07:16:14	7	NPT	07:00-11:59	...	0.00	0.00	0.000	0.00	0.00	0.00	0.050	0.05	0.050
ABP Ananda	Bengali Sat	WB	2020-04-01	Apr'20	Wednesday	09:13:47	9	NPT	07:00-11:59	...	0.00	0.00	0.000	0.00	0.00	0.00	0.100	0.15	0.060

The dataset contains information on various channels, genres, markets, dates, time slots, and GRP data for different regions.

Next, we will analyze the relationship between spend allocation on different channels or time slots and the GRPs (audience reach).

It seems that there was an error because the column 'GRPs' was not found in the dataset. This might be due to a different column name or a typo.

To resolve this, let's first inspect the column names of the dataset to identify the correct column names for spend allocation and GRPs.

The dataset contains the following columns:

Channel
Genre
Market
Date
Month
Week Day
Start Time {Av(Tm)}
Hrs
PT / NPT
Time Band
Length [sec] {Sum}
Rate/Budget
Spends
Master Programme
Advertiser
Brand
Brands
India
UP/Uttarakhand
Rajasthan
Delhi
Assam / North East / Sikkim
Odisha
West Bengal
Guj / D&D / DNH
Mah / Goa
AP / Telangana
Karnataka
Kerala
TN/Pondicherry
Bihar/Jharkhand
MP/Chhattisgarh
Pun/Cha
Har/HP/J&K
HSM
HSM Urban
HSM Rural
India.1
UP/Uttarakhand.1
Rajasthan.1
Delhi.1
Assam / North East / Sikkim.1
Odisha.1
West Bengal.1
Guj / D&D / DNH.1
Mah / Goa.1
AP / Telangana.1
Karnataka.1
Kerala.1
TN/Pondicherry.1
Bihar/Jharkhand.1
MP/Chhattisgarh.1
Pun/Cha.1
Har/HP/J&K.1
HSM.1
HSM Urban.1
HSM Rural.1

It appears that the GRP data is spread across multiple columns for different regions (e.g., HSM.1, HSM Urban.1, HSM Rural.1).

Next, we will sum the GRP data across all regions to create a total GRP column and then analyze the relationship between spend allocation and GRPs.

The scatter plot above shows the relationship between spend allocation and GRPs (audience reach) for different channels, genres, and time slots.

Key insights:

Each point represents a combination of channel, genre, and time slot.
The size of the points indicates the total GRPs.
The color represents different channels.

Next, let's investigate the Prime-Time vs Non-Prime-Time Performance to see if certain genres (like news or religious content) perform better in non-prime-time slots in different regions.

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