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Do you need research that will drive your business forward?

Whether you want to understand how to nudge more people towards your brand, or how to make communications work harder, we can help.

We are a behaviour, brand and communications research agency using our experience of research, psychology and behavioural economics to design tailor-made, effective research solutions. This may include ethnography, qualitative or quantitative research or a combination, whatever will be the most effective.

At the end rather than drown you in information and charts, we focus on the key findings and what they mean for your business

Charities/Voluntary, Drinks (Alcoholic), Finance/Investment – Personal, FMCG – General, Internet/New Media, Online, Property/Construction/Housing, Retail, Travel/Tourism, Wellness/Fitness
Consultancy, Continuous, Copy Testing, Creative development research, Diary Studies, Ethnography, Event Evaluation, Qualitative, Quantitative, Tracking
Advertising, Behavioural Change, Brand/Branding, Communications/PR, Concept Testing, New Product Development, Packaging/Design, Usage & Attitude
Republic of Ireland, UK
Senior Contacts

Alexa Arrowsmith (Partner)
Helen Law (Partner)
Helen Nuki (Partner)

Breakdown of Personnel

Total Number of Employees: 1 to 5

Address

53 Queen's Drive
London
N4 2SZ
Tel: 020 3397 3773
Email: info@monkey-see.co.uk
Establishment date: 2011

Five Reasons Why Big Data Needs Research

When I first started working as a researcher in a big advertising agency, one of my jobs was to 'mine the data'.  I always wanted to reply ‘what am I looking for?' but assumed I should know.

 

Today’s companies, especially those operating in the digital arena, have access to increasing amounts of data - plus entire teams to ‘mine the data’.

 

But are the data analysts always getting the most out of what is at their fingertips - and coming to the right conclusions?

 

With more experience under my belt, I know that such large data sets only really sing when combined with small data, in the form of specialist quantitative surveys and qualitative research.

 

But why? What additional insights can the combination of big and small data bring you?

 

It is our belief that this combination will help by:

 

1.    Identifying the core behavioural challenge
Understanding the real opportunity for a brand comes from pinpointing the specific behavior that needs to be changed.

For example, in one study we found that many of those identified on the client’s database as ‘one-time users’, were actually ‘multi-time users’, driven to use different sign-ins by a generous sign-up incentive.  This meant their Behavioural Challenge was not about getting users to come back as first thought.  It was about rewarding repeat usage.

 

2.    Identifying and sizing the triggers and barriers to different behaviours
The beauty of most databases is they allow the identification of people adopting different behaviours (eg: ‘loyalists’ v ‘occasional users’ v ‘lapsed users’) - but not the reasons underlying that behaviour.
Researchers can speak to groups of people in each category, and try to understand what might nudge them towards the desired behaviour.

 

3.    Minimizing the risk of getting correlation confused with causation.
In a large dataset it is easy to find correlations between different measures (i.e. different measures moving together) but statistics cannot tell you if these correlations are meaningful.  Combining with qualitative research or perhaps a few experiments allows a deeper exploration of these relationships.

 

4.    Bringing the data to life
By giving the stories behind the behaviour, people find it easier to remember and relate to the subtleties of what is going on.  This helps them empathize and think of possible solutions.
For example, in one study the client could not understand why a competitor was doing better despite having a seemingly inferior product.  Getting deep into the individual stories behind how they chose brands in the category suggested that while people said they wanted rational product benefits such as low interest rates etc, they actually chose the brand they had heard of before and they believed would quickly accept their application rather than a careful analysis of all the product’s benefits.

 

5.    Giving new hypotheses from which you can then go back and reanalyze the larger dataset.


So in summary, big data and research need each other!

 

Big data should be looked at with a questioning hat, instead of a solution hat, providing patterns of what is going on - and sparking questions from which research can go in to do deeper explorations.

Monkey See are different. They get to the nub of what I'm trying to achieve quickly, they ooze experience and perspire to deliver exactly what I need. And crucially they tell me what it all means and where & how they think it should direct action

James Burgess, Squadron Venture Media

 Thanks for such a useful deck – it clearly defines the strategy we should pursue in terms of product and marketing.  Also simple and easy to distil, which reminded me of how good you guys are – you know how to keep it simple which is rare in your world

Charlotte Harper, Zoopla 

 Monkey See never fail to impress. And, as well as being brilliant thinkers, they’re delightful people to work with too

Kate Waters, ITV 

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