SOTTOSOTTO

The industry measures viewing.Sotto measures intent.

Existing measurement tells you what happened. Whether someone started an episode, whether they finished it, how long they stayed and when they dropped off. It does not tell you why.

A conversation does. When fans spend real time asking questions in their own words, what they ask is a direct account of what they care about, and you do not have to infer it from vague data points.

A dashboard, in your hands, updating as conversations happen.

Not a quarterly deck and not a data export somebody on your team has to interpret. Written in the language your marketing and creative teams already use, and built to answer the questions they already ask.

Where you want it feeding an existing system rather than sitting in another tab, custom integrations are possible.

The panel, on sample data

01

Conversation topics

Themes fans raised on their own, ranked by how often they came up and coloured by how they felt about them.

#TopicMentionsSentiment

What fans actually said

Why did nobody on that boat argue with her? It made no sense after everything in episode two.

The ferry scene is the one bit of this season I would rewrite.

I have watched it three times and I still think the crossing was a cheat.

214 of 892 mentions questioned the character logic

PositiveNeutralMixedNegativeSelect a topic to read the fans' own wording

02

Trending characters

Characters ranked by mentions, with how fans spoke about each one.

1Wren Halloran4,482-0.02 Neutral
2Sela Voight3,004+0.13 Mixed
3Marcus Tey2,761-0.04 Neutral
4The Warden2,750+0.03 Neutral
5Ada Rook2,588-0.42 Negative
6Nils Halloran2,571+0.15 Mixed
7Pell2,560+0.44 Positive

03

Creative signal

What fans invented, misread or asked for, unprompted, inside the conversation.

1The radio signal is coming from inside the eastern camp411
2Sela took the seat to protect Wren, not to hold power307
3The Warden knew about the parentage from the first season288
4Pell survived the collapse and the body was never confirmed246
5Tey is working to an instruction we have not been shown195

04

Sentiment

Overall fan sentiment, how far it swings, and the moments that moved it

-0.29

Average sentiment · Slightly negative

0.33

Emotional volatility · Medium

100%

Answer coverage · in canon

Emotional peaks

Wren learning of her family's sentence372
The knighting on the eastern wall331
The mine collapse264
The ferry crossing251
Tey's arrival at the winter camp244
Pell's last stand196

05

Tone of voice

Emotional tone inferred from language patterns across every session

Casual23%
Sceptical21%
Enthusiastic18%
Frustrated18%
Emotional13%
Analytical8%

Detected emotions

Disappointment1,450
Frustration1,410
Curiosity1,200
Anger1,090
Boredom1,020
Surprise970
Melancholy950

06

Engagement and fandom depth

How deeply fans engage, how much they already know, and who is in the room

61%

Return within seven days

52%

Ask a follow-up question

43%

Knowledge level · Familiar

Conversation depth

42%35%24%
SurfaceModerateDeep

Fan type

42%41%18%
CasualFanSuperfan

07

Episode engagement

Sessions and sentiment by episode, in airing order.

Episode 13,120-0.19 Mixed
Episode 22,970-0.17 Mixed
Episode 32,920-0.32 Negative
Episode 42,890-0.45 Negative
Episode 52,780-0.53 Negative
Episode 62,400-0.14 Mixed
Episode 71,980+0.11 Mixed
Episode 81,760-0.10 Mixed

08

Activity over time

Daily session volume. Hover a column for the day.

Peak 2,300 sessions

06.04.2603.05.26

Where fans are talking from

GB1,840
US1,620
DE760
AU640
IT480

Sample panel. Property names, figures and fan quotations are illustrative. Live deployments report on the rights holder's own titles inside their own environment, and fan records are held under the terms of the access grant.

Sample data, two properties

Passive and active

What measurement gives you today

Did they start it.

Did they finish it.

How long did they watch.

When did they drop off.

The output is historical. A report on something that already happened.

What a conversation gives you

What are they asking.

What confused them.

What are they obsessed with.

What theories are forming.

The output is live. It arrives while you can still act on it.

Imagine an always on, real-time focus group at scale. Say hello to Sotto

Current measurement understands whether people finished an episode. This tells you why.

The four things you learn

01

Mood

How a fandom feels, and how sharply that changes. Which episode landed and which one caused an argument. Sentiment across a season, and the volatility inside it, drawn from what fans actually said rather than from a sample who agreed to be surveyed.

02

What holds attention

Which parts of a world people stay with, and for how long. Which threads they return to unprompted weeks later. Where a conversation deepens and where it stops. Attention measured in engagement rather than in exposure.

03

Where your depth is

Who your most engaged fans are as a group, what distinguishes them, and what they do differently. Useful for knowing which parts of a fandom will carry a new title, and which will not, before you spend against them.

04

What to try next

Fan theories forming in real time. Questions asked so often they amount to a request. Direct routes to ask your audience something and get an answer, without commissioning research. The fastest available read on whether an idea will land.

Data privacy at the core.

Individual fan identity stays with you. The first-party relationship stays with you. Nothing about an identifiable person moves to us or to anyone else, and nothing crosses between rights holders.

What comes back to you is aggregated and de-identified. Patterns across a fandom, not a file on a fan.

We can show you what this looks like against with a demo of Sotto's data platform.

Book a demo →