1) The document discusses using online data to understand behaviors and context, which it argues provides richer insights than just content alone.
2) It emphasizes the importance of considering factors like who created or curated the content, how many people paid attention to it, and differences between active online participants versus casual viewers or bystanders.
3) As an example, it outlines how tracking behaviors, geographical and social contexts around mothers' use of camcorders with young children could provide insights beyond just the content itself.
2. Going to be talking about
? What does online data deliver best
content vs
behaviours vs
Internet content is poor grade content
But outstanding contextual and behavioural data – so
let’s treat it as such
And it’s a Knowing resource..
Cloud of free
8. Dictionary definitions
The part of a text or statement
that surrounds a particular
Source businessdictionary.com word or passage and
Cloud of Knowing determines its meaning.
10. Thinking about advertising you
have seen in the last 2
weeks..
When you make gravy.. What
do you usually?
Cloud of Knowing
11. Why focus on context?
Because found online content
doesn’t match offline
research content
What people spontaneously
post is richer in behavioural
and contextual data
Play to your strengths
Cloud of Knowing
12. Ocean vs jellyfish
Jellyfish 99% water and mostly transparent –
people are unreliable at reporting recall,
behaviour, let alone culture changes
Are we researching the jellyfish – or are we
using the jellyfish to understand the ocean?
Cloud of Knowing
13. Wineglass vs Mattress
Remarkably difficult to start a movement
that travels the length of the mattress –
LOTS of post rationalisation – mostly with
non commercial virals
Behaviours and contextual data spread faster
than content
Cloud of Knowing
14. Not everybody online is equal
Creators
Curators
Fans
Viewers
Bystanders
Cloud of Knowing
15. Grading data: the curator curve
Some people know a lot more than others,
Some post a lot more content than others
A significant proportion of non commercial web
content is published by a relatively few sources
How much you have posted affects the content you
post – and what you say.
We need to factor in a measure for curation for
every piece of data we examine
And identify those who create and the fans who link
comment and forward
Cloud of Knowing
16. Grading data: the attention curve
We pay a lot more attention to some information
than others
Currency comes from lots of people perceiving that
others are perceiving it too
It affects how we talk about it
Much of the desire to reach large numbers of people
comes from brand manager’s desire to locate and
aggregate an audience
When we track how many people have paid
attention we need to identify creators and fans
separately from audience and bystanders
Bystanders received it but didn’t pay attention
Cloud of Knowing
17. camcorders
Usage: Mothers with babies and toddlers
Behaviour
Stills uploaded – where uploaded
uploaded clips: clip length, number
Verbatims about trips with young children –
camera mentions
Camcorder vs mobile usage/repertoire
Geographical context
Geotagging – where clips being shot
Geo distribution of images/clips
Cloud of Knowing
18. More usage..
Social Context
Subject matter
What the children are doing
What is said about what the
children are doing
Social media context
Who photos clips are mailed to
Who comments
Who forwarded to
Keywords used
Cloud of Knowing
19. Purchase
Triggers to purchase
Camcorder/camera repairs search enquiries
Visits to camera camcorder websites
Competitor models considered, sort criteria
Features searched for
Social media context
Asking for advice about cameras used
Who comments
Who forwarded to
Keywords used
Cloud of Knowing
20. Social media currency
for each item of data
Social metrics
Audience curve:
Size and scale of audience – index against
other types of clip
Curator curve:
Frequency and regularity of posting or
commenting on this topic compared with
others.
Cloud of Knowing
21. Conclusions
Contextual and behavioural data is so much
more than online behaviour
Probably needs an offline research study to
Disc
identify interesting behaviours us s
!!
Once identified behaviours and context can
be tracked.
Frequency and change over time can be
automatically monitored
Cloud of Knowing