BIG DATA BRAINSTORMThe Results!

YourName You will see a star with your name

on.

For 10 Seconds!

This is your cue to step up to the mike ;)

Our Insight

Our Reasons Why… And more reasons why…

You have 1.30‘‘!

Feels like ages?(30 seconds…)Still time to go!(60 seconds…)

On the home run!(15 seconds

to go…)

If you haven‘t said it now…

Bert Hendricks

who is interested in big datawhy the interest in big data

every organization that want to be/stay competitive SHOULD be interested in big data. This does not only concern product brands, but as well employer brands for example. So 'WHO' - every organization, 'WHY' - to be/stay competitive, as the consumer has taken over the control about the brand name / brand community / brand image.qual analytical techniques can be used on big data- split massive data into smaller observations

understand the story of the customer

Qual research connects the dots where big data informs without explanation. Qual gives you the why behind the story.

By combining qual and big data I can picture today's story faster and better, so I can spend more time & budget on the story of tomorrow (ideation).

key: qual techniques can use big data to set a stage/current context and qual analysis can help set the whats & so whats to build hypotesis for now whats.

Gregg Fraley

Karin Jorgensen

Our key insight was it would take a HYBRID approach, blending quantitative tools (such as search engines and text processing engines) with open ended questions such as those used in qualitative. Clearly, we all need to tolerate ambiguity and de-mystify BIG DATA in order to move forward with actually using it. What led us there Our concerns were related to context, sorting out the trash, finding gems, and anonymity, And our answers to address those concerns had to do with following up the massive scans with qual "verification studies" where traditional qual techniques can be used. Ultimately, a narrative, a story needs to be the output, a result of the hybrid approach. And...wouldn't it be nice if clear business success stories were created.

Vartika

90 Sec Insight

Qualitative analysis can work on BIG data to :•Understand the ‘what’s’ •Derive the ‘so what’s’ •Hypothesize the ‘now what’s’

Q &A• Who is interested in Big data ? What are they

interested in?• Anyone (marketer, researcher, brand

custodian, organisation, businesses), who wish to make informed decisions, in order to stay competitive

What helped us derive this ?• As a user, would prefer investing (money, time,

energy) on ‘future’, rather than existing scenarios

• Current scenario and historic context– Loads of data out in the open– Define efficient starting points– No need to re invent the wheel

Someone fromPieter Paul’s Table

Otomi

Key insights :

Qualitative research makes it possible to sort BIG data into different blocks of attitudes and motivations.What led us here :

- Emotional aspects- Psychological effects - Short term : understand needs (+)

manipulation (-)- Long term : human beings are not objective (+)- value of personality (-)- Understand “Why” / anticipating

Name of presenter : Ottomie

CiceroBaggio

Give Big Data Face!What led us: People do not have a choice regarding privacy (if they want to be connected to for example social media). People have to pay the price of privacy in order to connect with their friends (facebook) or search on the internet (google). Transparancy: tell me that you take my dateWe need to be capable of seeing the bigger picture. Less = more.

Lookingat the Borders

Key insight :

For new insights and trends on your market, don’t look at the most typical representatives of your clusters , but look at the borders and dive deeper at that point

Lisa Elder

Key insight: Qualitative ‘techniques’ are not enough – the challenges presented by Big Data can only be turned into opportunities with qualitative skills.{It is not the tools you use but how you use them.}

What led us here:• We have unique skills to apply to data:

• The skill of collaboration to create action plans.• The skill to bring together diverse sources of information to identify

themes of learning.• The skill to transfer learning into meaning within the human condition.

Presenter name: Lisa Elder

Indy &Co

What is qualitative research• Focus groups, in-depth interviews, ethnographics• Understand the why & how, quant more for the “what, where & when”• Discussion & Observations• Analyzing and interpretation• Understand the reason why people are behaving or thinking in a certain way and transforming it to action• Finding pattern from small piece of data• Getting to the emotion of people, getting to the subconsious of the people• Understand the motivations of people• More words than numbers, as in big data• Getting deeper details• Understanding what’s behind it• Small sample, often local• Transforms questions into meaningful hypothesis• Find out what is relevant, eliminating the “noise”

What is qualitative research• Insight: Both, big data and qualitative research is about finding patterns, results are words and not numbers. In the end it’s about eliminating the “noise” and drawing relevant conclusions.

Presenter: Indy Neogy

Erin &Scott

How can we apply qualitative techniques to the challenges of BIG Data?

How can we generate big data insights?Key Insight: • There is a place for qualitative researchers in Big Data analysis because of our intuitive nature,

explorative orientation , process, and mindset.

What Lead Us Here:• Fulfill a need• Cast a wide net• See emotional & rational patterns• Open to exploratory• Insist on context, “the why”, not just satisfied with the “what”• Flexibility - useful in various stages

“Seeing the tree through the woods”

Presented by: Erin Althage, Sommer Consulting & Scott Hayward, heads up! research inc.

JonathanGable

How are Big Data people different from Qual people?

“I can find the needle in a haystack.”

“I make sense out of unstructured data.”

“At the start of a project, I know what

I’m looking for.”

“I can use what I learn as a valid basis for

decisions.”

Bonus Question:

Mac or PC?

Thank You!