SOMDEEP SEN; Business Analyst: Trimax Analytics
(e) [email protected]; (p): 09748229123
LinkedIn: http://linkd.in/1ifqs3x
• XYZ Consultants have been the task to analyze a sample bill of Vodafone
• The analysis should contain the following details:
Call:
– Total no. of calls made; Called numbers & destinations
– Duration of calls (Total & Avg.); Time of call (Peak, Off-Peak);Cost of calls; Breakup: Day & Date
wise
SMS:
– Total number of SMS sent; Breakup: Day & Date wise
Data Usage:
– Total amount of usage(in KB), Breakup: Day & Date wise
• Determine the type of Usage (Roaming, Local or International Roaming)
• Review the plan to determine overall fitness of the plan for this person
• Recommend an alternative plan based on the comparison with 3 other plans
• Predict certain demographic details(age, occupation) & type of phone being used
Note: One may justify the present plan as the best one too
Type Rate
Local CallMobile(In-Network & Off-Network), Landline: 0.3/Min.
Free Qty: 400 minutes
STDIn-Network & Off-Network Mobile: Rs. 0.5/Min
Local Landline: Rs. 0.5/Min
Roaming CallsIncoming: Rs. 1.0 / minute; Local: Rs. 1.5/ minute
STD: Rs. 0.5/ minute
SMSLocal SMS: Rs. 1.0/ minute; National SMS: Rs. 1.5/ minute
Roaming SMS (National & Local): Rs. 1.5/ minute
Data GPRS Data & GPRS Roaming (0.1 / 10 KB)
Understanding the Data
Data Cleaning
Analysis
Comparison with other plans
Providing recommendation
Prediction
Note
• The information mentioned above is provided for the billing cycle: 10.12.13 to 09.01.14
• The information scattered over multiple excel sheets
Particulars Details
Call
•Date(DD/MM/YY) , Time, Duration (Min : Sec)
•Called Number (Vodafone or Non-Vodafone)
•Type of call (Local or STD) & Charges
SMS
•Date(DD/MM/YY) , Time
•Destination Number (Vodafone or Non-Vodafone)
•Type of SMS (Local or STD)
Data Usage•Date(DD/MM/YY) , Time
•Type of Usage (VF Mob Connect/ VF Live)
Problems Encountered
• Date & Time for the particulars were given together one cell
• Information regarding Conference Call wasn’t specified
• Format of some of the mobile numbers were not in symmetry
• Data usage was scattered in over 10 sheets
Tool Used for cleaning, organizing & analyzing the data: Ms-Excel
• Advanced Filtering
• Pivot Table
• V-Lookup
• This excludes conference call (40 minutes), as the details of con-call was not provided
0
5
10
15
20
25
10
-Dec
11
-Dec
12
-Dec
13
-Dec
14
-Dec
15
-Dec
16
-Dec
17
-Dec
18
-Dec
19
-Dec
20
-Dec
21
-Dec
22
-Dec
23
-Dec
24
-Dec
25
-Dec
26
-Dec
27
-Dec
28
-Dec
29
-Dec
30
-Dec
31
-Dec
1-J
an
2-J
an
3-J
an
4-J
an
5-J
an
6-J
an
7-J
an
8-J
an
6
16
34 3
5
9
1415
14
2 2
25
18
8
24
20
14
5
1
3
1
23
Du
rati
on
(M
ins)
Date
• Total duration: 235 mins; This includes night speak of 11 mins.
• Average duration: 10 mins/day; 23 days have been considered
• No calls were made on 14th Dec, 16th – 19th Dec, 27th – 28th Dec
• Only night calls were made on 25th & 26th Dec
• Drop in average duration weekends suggests that primary purpose of use professional
• Calculated duration(235 minutes) doesn’t match with the billed duration (335 mins)
• Therefore, either some call details might be missing or it might be a case of over billing
• However, both billed & calculated duration is less than 400 mins
• As per the bill 5 minutes STD call was made; but the data didn’t seem to have the details
• All calls made seemed to be Local
• Almost 96% of the calls just lasted <= 3 minutes
• Short duration of calls reemphasizes that the calls might have been professional in nature
0
20
40
60
80
100
120
140
1 minute calls 2 minute calls 3 minute calls 4 minute calls 5 minute calls
123
31
84
2
Nu
mb
er o
f ca
lls
Call Duration
• ‘10:30 AM-7:30 PM’ can be tagged as the peak time as it contributes 180 mins out of 235
• ‘10:30 AM-1:30 PM’ may also be the office time for the person leading to the steep rise
• Interestingly no calls are made between 12:04 PM to 1:04 as it might be the recess time
• Steady drop in call duration suggests that the person might be on the way back home from office
• The before 10:30 AM & after 8 PM can be tagged as off-peak time
17
28
53
99
26
12
0
20
40
60
80
100
120
7:30 AM-10:30 AM 10:30 AM-1:30 PM 1:30 PM-4:30 PM 4:30 PM-7:30 PM 7:30 PM-10:30 PM After 10:30 PM
Du
rati
on
(M
ins)
Time range
• Local Vodafone number clearly occupies the majority of the duration breakup
• The analysis also showed that majority of the numbers were called multiple times in a day
• This suggests that the calls might have been made to the colleagues
• Others included: Local Landline & Toll-free numbers
• Landline numbers also suggested that calls might have been made to different branches of the organization
78
52
105
In Minutes
Non-Voda_Loc_Mob Others Voda_Loc_Mob
This analysis is useful keeping in mind that Vodafone has to pay a termination fee
to end the call made to a Non-Vodafone number
65
43
6
In Minutes
Airtel
Reliance
Docomo
MTS
0
5
10
15
20
25
30
35
40
45
10
-Dec
11
-Dec
12
-Dec
13
-Dec
14
-Dec
15
-Dec
16
-Dec
17
-Dec
18
-Dec
19
-Dec
20
-Dec
21
-Dec
22
-Dec
23
-Dec
24
-Dec
25
-Dec
26
-Dec
27
-Dec
28
-Dec
29
-Dec
30
-Dec
31
-Dec
1-J
an
2-J
an
3-J
an
4-J
an
5-J
an
6-J
an
7-J
an
8-J
an
14
41
44
6
11
33
86
13
810
28
1
20
1 1
Nu
mb
er
Date
• Total no. of SMS sent: 234; Avg. no of SMS sent/day: 14; Days considered: 17
• All the SMS sent was local
• No SMSs were sent on 14th Dec– 19th Dec & 1st – 6th Jan.
• Interestingly no calls were made on 14th Dec, 16th – 19th Dec & only 3 calls were made on the 15th
• This may infer that the person might have been on leave during 14th- 19th December
• However, despite low call duration from 4th to 6th Dec the person seemed active
• Also just like calls Calculated number (236) doesn’t match with the billed one 294)
• The person had an SMS pack of 100 free SMS FOR Rs. 50
13
18
Average Number of SMS
Weekday Weekend
9.5
10.5
Average Duration of Calls
Weekend Weekdays
• Average duration & number is closely matched for calls; whereas for SMS weekend has won the race
• Such stats may infer that due to workload the person may have to work on weekends too
• Assumption: The person uses the phone for professional purpose only
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
• Total usage: 2.08 GB, Avg. data download/day 0.08 GB
• There were no internet usage on 14th Dec, 16th -19th Dec
• Interestingly during these time periods SMS sent & calls made was also very low
• This indicates that the person might have been on a leave
• Maximum usage: 0.79 GB on22ⁿᵈ Dec followed by 27th,23rd 21stand 20th Dec
• There was a modest use of VF Live leading to a negligible consumption of 70 KB
0
5000
10000
15000
20000
25000
30000
35000
40000
12
:00
AM
12
:34
AM
1:0
5 A
M1
:35
AM
2:0
7 A
M2
:42
AM
3:1
6 A
M3
:51
AM
4:2
4 A
M4
:57
AM
5:3
3 A
M6
:06
AM
6:4
0 A
M7
:05
AM
7:3
0 A
M7
:55
AM
8:2
1 A
M8
:53
AM
9:2
8 A
M9
:58
AM
10
:26
AM
10
:59
AM
11
:27
AM
11
:43
AM
12
:02
PM
12
:19
PM
12
:48
PM
1:1
8 P
M1
:46
PM
2:1
3 P
M2
:43
PM
3:0
9 P
M3
:40
PM
4:0
8 P
M4
:39
PM
5:0
4 P
M5
:32
PM
5:5
6 P
M6
:19
PM
6:4
1 P
M7
:07
PM
7:2
8 P
M7
:51
PM
8:2
0 P
M8
:44
PM
9:0
4 P
M9
:22
PM
9:4
1 P
M1
0:0
8 P
M1
0:3
7 P
M1
1:0
6 P
M1
1:3
6 P
M
• Three significant time slots are observed
– 6:30 AM - 8:00 AM, 11:00 AM – 12:30 PM and 8:30 PM – 10:00 PM
These three time slots probably signify:
The starting of the day with checking mails and leads for planning the day ahead
Assigning work and communicating for work purpose
Provide feedback, reviews and instruction for the next day
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
09
-12
-20
13
10
-12
-20
13
11
-12
-20
13
12
-12
-20
13
13
-12
-20
13
15
-12
-20
13
20
-12
-20
13
21
-12
-20
13
22
-12
-20
13
23
-12
-20
13
24
-12
-20
13
25
-12
-20
13
26
-12
-20
13
27
-12
-20
13
28
-12
-20
13
29
-12
-20
13
30
-12
-20
13
31
-12
-20
13
01
-01
-20
14
02
-01
-20
14
03
-01
-20
14
04
-01
-20
14
05
-01
-20
14
06
-01
-20
14
07
-01
-20
14
08
-01
-20
14
09
-01
-20
14
FALSE
TRUE
• Data usage wasn’t very high on weekends except for 21st and 22ⁿᵈ Dec
• It pulled the total usage during weekends higher than the total usage during weekdays
• We can conclude, that this person was working on a certain weekend due to increase in work-load
1. Occupation: High or Mid Level Executive
Justification:
• Relatively short length, but high frequency of calls
• Steep rise in call durations in 10:30 to 7:30
• Spike in 4:30-7:30 indicates that the calls might be used to take reports or feedback at the end of day
• Closely matched stats for avg. no. of calls & SMS on weekdays & weekends suggest high work-Load
• The person may belong to the domain of marketing & sales
2. Age: Greater than Equal to 30
Justification:
• Usually high level executives belong to the age bracket of 30+
3. Type of phone : Blackberry or Smartphone
Justification:
• The customer had access to internet starting from 6:30 AM to 11:30 PM
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