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Getting the edge/ The Magic of Blended Data
Will | @willmcinnes
2
Getting the Edge: The Magic of Blended Data
@willmcinnes @brandwatch
@willmcinnes @brandwatch
Let’s get this
straight.
Simple idea #1
As social moves from a silo to being better through
its connection to everything else in an organisation,
so does social data.
Centralized Distributed Coordinated Multiple
Hub & Spoke
Holistic
@willmcinnes @brandwatch
@willmcinnes @brandwatch
Simple idea #2
That getting an edge matters.
And the best way to get an edge
with social data is to blend it.
Caution!
For every beer and nappies…
@willmcinnes
...there are 17 spurious correlations.
@willmcinnes @brandwatch
3 main risks with social data
1. Sample/selection bias
Assuming people on social are representative of the people you're
interested
Assuming the people you're interested in are posting on social
2. Inference problems
Things like sentiment, gender, location, etc. are inferred with less
than 100% accuracy
3. Being creepy
@willmcinnes @brandwatch
Pic of mike
Raw ingredients
1. Great quality social data you can manipulate
2. Great quality other data
3. Analyst or data science resource
Getting the Edge: The Magic of Blended Data
7 stories to
Enlightenment
Be real.
These are all real examples.
All but one are Brandwatch customers.
Getting the Edge: The Magic of Blended Data
Getting the Edge: The Magic of Blended Data
Goal:
Blend social data with weather data to find insights
How:
Got social data for customers talking about consuming their ice cream
product using
Got weather data for the same period
Outcome:
Found there were meaningful increases in people talking about eating
ice cream when the weather was bad.
Used that to inform their future advertising strategy
@willmcinnes @brandwatch
Getting the Edge: The Magic of Blended Data
Goal:
Jump in to conversations about test drives to signpost potential buyers to local dealers
How:
Queries set up to locate social mentions that mention car model names with ‘test drive’,
dealers names.
Using Rules, Categories and Tags to automatically filter these conversations by Colour,
Model, Brand, Dealer etc.
Then matching CRM details of known customers with social handles to explore the
potential of social CRM at scale (they already have a database of >1m customers on
social).
Outcome:
Increase in car sales from test drives.
Getting the Edge: The Magic of Blended Data
Goal:
More effective ad spend and return visits to their parks
How:
Identified people who met demographic criteria in each of their theme park
DMA region.
Identified topical areas of interest in those demographic segments, by region
Fed those topics into tailored regional advertising campaigns
Outcome:
Uplift in ticket sales + increase in per ticket revenues
@willmcinnes @brandwatch
Getting the Edge: The Magic of Blended Data
Goal:
Change and Adapt Brand Perception
How:
Matching offline physical event check-in data with the social conversations
around each of the physical events
Matching social handles to offline identities and then observing and learning
Outcome:
New evidence and insight into which events drive the most brand favourability
change.
@willmcinnes @brandwatch
Getting the Edge: The Magic of Blended Data
Goal:
Understand which brands and items their existing customers
were talking about publicly
How:
Acquired mentions for the key brands that they sell
Worked with a third party vendor to match social identities to their own
CRM database
Outcome:
Used information to promote those brands and items via the website
and email. ROI ‘made the leaderships’ jaws drop’
@willmcinnes @brandwatch
The point is that it’s not just about social anymore
• It’s about the business
• The customers
• The market
• Social is just part of it
Getting the Edge: The Magic of Blended Data
Getting the Edge: The Magic of Blended Data
What about
the plateau of
productivity?
@willmcinnes @brandwatch
@willmcinnes @brandwatch
Getting the Edge: The Magic of Blended Data
Getting the Edge: The Magic of Blended Data
@willmcinnes
Getting the Edge: The Magic of Blended Data
So what?
@willmcinnes @brandwatch
Come and say
hello
now you know

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Getting the Edge: The Magic of Blended Data

  • 1. Getting the edge/ The Magic of Blended Data Will | @willmcinnes
  • 2. 2
  • 7. Simple idea #1 As social moves from a silo to being better through its connection to everything else in an organisation, so does social data.
  • 8. Centralized Distributed Coordinated Multiple Hub & Spoke Holistic @willmcinnes @brandwatch
  • 10. Simple idea #2 That getting an edge matters. And the best way to get an edge with social data is to blend it.
  • 12. For every beer and nappies… @willmcinnes
  • 13. ...there are 17 spurious correlations. @willmcinnes @brandwatch
  • 14. 3 main risks with social data 1. Sample/selection bias Assuming people on social are representative of the people you're interested Assuming the people you're interested in are posting on social 2. Inference problems Things like sentiment, gender, location, etc. are inferred with less than 100% accuracy 3. Being creepy @willmcinnes @brandwatch
  • 16. Raw ingredients 1. Great quality social data you can manipulate 2. Great quality other data 3. Analyst or data science resource
  • 19. Be real. These are all real examples. All but one are Brandwatch customers.
  • 22. Goal: Blend social data with weather data to find insights How: Got social data for customers talking about consuming their ice cream product using Got weather data for the same period Outcome: Found there were meaningful increases in people talking about eating ice cream when the weather was bad. Used that to inform their future advertising strategy @willmcinnes @brandwatch
  • 24. Goal: Jump in to conversations about test drives to signpost potential buyers to local dealers How: Queries set up to locate social mentions that mention car model names with ‘test drive’, dealers names. Using Rules, Categories and Tags to automatically filter these conversations by Colour, Model, Brand, Dealer etc. Then matching CRM details of known customers with social handles to explore the potential of social CRM at scale (they already have a database of >1m customers on social). Outcome: Increase in car sales from test drives.
  • 26. Goal: More effective ad spend and return visits to their parks How: Identified people who met demographic criteria in each of their theme park DMA region. Identified topical areas of interest in those demographic segments, by region Fed those topics into tailored regional advertising campaigns Outcome: Uplift in ticket sales + increase in per ticket revenues @willmcinnes @brandwatch
  • 28. Goal: Change and Adapt Brand Perception How: Matching offline physical event check-in data with the social conversations around each of the physical events Matching social handles to offline identities and then observing and learning Outcome: New evidence and insight into which events drive the most brand favourability change. @willmcinnes @brandwatch
  • 30. Goal: Understand which brands and items their existing customers were talking about publicly How: Acquired mentions for the key brands that they sell Worked with a third party vendor to match social identities to their own CRM database Outcome: Used information to promote those brands and items via the website and email. ROI ‘made the leaderships’ jaws drop’ @willmcinnes @brandwatch
  • 31. The point is that it’s not just about social anymore • It’s about the business • The customers • The market • Social is just part of it
  • 34. What about the plateau of productivity?

Editor's Notes

  1. Social data is valuable commodity that dept needs and wants
  2. A quick update for you Brandwatch now has clients in 51 countries. And just since Dec 2014 users have logged in from 93 different countries! 30% of Fortune 100 use Brandwatch data to drive business decisions – about campaign performance, about product feedback, on supply chain and inventory Crisis comms and command centers
  3. ARTHUR C CLARKE – Magic quote OR, engagement doubles with dog tweet
  4. Picture of cute dog- mymessgage – I’m not going to stoop that low
  5. Be much clearer. Think about other industries that went through this. My personal story – I’m much better at hyping than at this stuff, but this reflects where the world is.
  6. One of our Phd / Doctors
  7. Small data – not millions of customers – the 1,500 who were actually talking about test driving their cars
  8. May, 50,000 tweeted ‘I want to go to [theme park] – so not general tweets, but indicating some kind of desire or intent.
  9. Make it more exciting, go for it. People remember experiences!! You don’t remember names but they remember experiences. The reason that photos are so popular is because…
  10. Have a look at IFTTT
  11. latitude and longitude coordinates of the message locations have more than 5 decimal places of precision
  12. Every dept needs it
  13. Shingy // Hype is gone // Most of the gurus are gone – it’s REAL BUSINESS NOW