a large-scale characterization of user behaviour in cable tv
TRANSCRIPT
A Large-Scale Characterization of User Behaviour in Cable TV
Diogo Gonçalves, Miguel Costa, Francisco CoutoLaSIGE @ Faculty of Sciences, University of Lisbon
RecSysTV 2016, Boston, USASeptember 15, 2016
• Today, there are many services from which to choose contents to watch:• Live TV• Video on Demand (VOD)• Catch-up TV• Over-the-top (OTT) from 3rd parties (e.g. Netflix)
• Understanding how users interact with such services is important to increase:• user satisfaction • user engagement • user consumption
(this knowledge helps to enhance the recommendation systems of Cable TV providers)
• We didn’t find any study comparing usage patterns between Live TV, VOD and Catch-up TV in an integrated way from a large scale Cable TV operator.
2
• Live-TV• a client can watch any video content that is being broadcast live (e.g. a live
soccer game).
• VOD (video-on-demand)• a client can watch any video content anytime that was pre-recorded and made
available, usually a movie or series.
• Catch-up TV• is a type of VOD, where a client can watch any video content that was broadcast
live up to a few days before (e.g. up to 7 days).
Contents are delivered via Set-Top Boxes (STB) installed in users‘ homes.
3
Live Catch-up VOD Total
Users 896,000 806,000 220,000 897,000
Programs 24,000 24,000 15,000 39,000
Episodes 330,000 330,000 15,000 345,000
Programs per moment (avg.) 160 6,000 15,000 21,000
Episodes per moment (avg.) 160 35,000 15,000 50,000
Views (>10 min) 617,000,000 56,000,000 9,000,000 682,000,000
User views (avg.) 688 70 40 758
User views per month (avg.) 327 33 19 360
October to December 2015 (9 weeks)160 channels available to the user
4
Some
Results
5
Number of users per day
0
100
200
300
400
500
600
700
1 8 15 22 29 36 43 50 57
# u
sers
(th
ou
san
ds)
DaysCatch-up TV Live TV VOD
Live TV has muchmore users than
Catch-up and VOD together, but less
research.
Should we focus more in improving the user
experience for Live TV?
6
0
2
4
6
8
10
12
14
16
18
1 8 15 22 29 36 43 50 57
# vi
ews
(mill
ion
s)
Days
Catch-up TV Live TV VOD
Number of views per day Number of watched hours per day
Live TV has much more views and watchedhours than VOD & Catch-up
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
1 8 15 22 29 36 43 50 57
# h
ou
rs (
mill
ion
s)
Days
Catch-up TV Live TV VOD
7
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
# vi
ews
(mill
ion
s)
hour of day
Live TV Catch-up TV VOD
Number of views per hour
The graph shows the typical work/rest cycle of users for the
3 TV services.
sleepingworking
@home
8
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 51
01
52
02
53
03
54
04
55
05
56
06
57
07
58
08
59
09
51
00
# vi
ews
% program watched
Live TV Catch-up TV VOD
The average percentage of content watched in Live TV is small (27%) when compared with Catch-up TV (50%) and VOD (60%)
stop watchingsooner
most peopledo not watch
the full content
9
0%
20%
40%
60%
80%
100%
0 51
01
52
02
53
03
54
04
55
05
56
06
57
07
58
08
59
09
51
00
# vi
ews
% program watched
News TV Series Entertainment
Kids Documentaries Sports
Movies Adults
kids categorywas more watched
adults categorywas less watched
Live TV
10
Distribution of program types perday made available by the Cable TV operator
Distribution of program typeswatched by users on live and catch-up TV
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1 8 15 22 29 36 43 50 57
# p
rogr
ams
DaysRecurring Programs (Repeats)
Recurring Programs (New Episodes)
New Programs
0%
20%
40%
60%
80%
100%
1 8 15 22 29 36 43 50 57
# p
rogr
ams
DaysRecurring Programs, Recurring for User, Repeat
Recurring Programs, Recurring for User, New Episode
Recurring Programs, New for user
New programs
~20% of watched episodes are repeated.These are mostly kids programs.most users watch
new episodesof programs already seen
not having feedback from the specific user11
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 91
01
11
21
31
41
51
61
71
81
92
02
12
22
3
# vi
ews
hour of dayNews TV Series EntertainmentKids Documentaries Sports
Views in Catch-up TV per category over the day
users watch differentcategories in different hours
12
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
0 24 48 72 96 120 144 168
# vi
ews
(mill
ion
s)
hours after broadcast
Views in Catch-up TV
most users watch contentsfrom the last hour 13
• The characterization of Live TV, Catch-up TV and VOD on a large-scale Cable TV provider shows usage differences between these 3 services. These insights enable to adapt and create better recommendation algorithms depending on the TV service.
• Live TV receives the majority of views. Still, Catch-up TV and VOD accumulate a large amount of views and hours watched. The 3 services should have recommendations.
• Users tend to watch Catch-up TV and VOD programs for longer, when compared to Live TV. The implicit feedback provided by the program views should be adjusted to the TV service.
• Users tend to watch some categories (e.g. Kids) for longer than others (e.g. Adults). The implicit feedback provided by the program views should be adjusted to the content categories.
• Users prefer to watch different types of programs depending on the hour of day. We should adjust the recommendations for the time period.
• Users prefer to watch new episodes of programs previously watched by them. Should we recommend the programs that users usually watch or should we suggest new programs?
• Users prefer to watch programs recently broadcast in Catch-up TV. Should we recommend the most recent contents first?
14
