conversation about maximising value from customer insight

Data Science programming languages: (2) Resources for Python

Resources for PythonAs promised in our previous post, for the R programming language, this one will focus on resources for Python.

Although R may have a longer heritage within the Statistics and Data Science community, Python could be described as a more complete programming language.

In my conversations with clients and Data Science leaders, I’ve also heard a number praise Python as much quicker to learn. So,although both languages are proving popular with analytics teams, there is perhaps a choice between the more statistically grounded R and the easier programming in Python.

But, even that distinction is now less clear, as both benefit from the kind of support/resources ecosystem that I mentioned in my post on R.

So, enough introduction, let me share some resources that I’ve found to help Python coders (and would be coders). Enjoy diving in, at the risk of getting bitten by the coding bug.  (more…)

Data Science programming languages: (1) Resources for R

Resources for RThis month, let’s turn our attention to Data Science programming languages; today, resources for R.

Ever since the rise of R as an alternative to traditional statistical packages (like SAS, IBM Analytics etc), there has been a growing focus on coding.

In the past I have tended to avoid these programming languages as a topic for this blog, as I have some concerns. Namely that the role of insight analysts, in the migration to job title of Data Scientist, is being reduced to that of a programmer. Too much focus on coding skills & the capabilities of new packages, can reduce the needed focus on interpretation, insight generation & influencing a business.

However, working with clients, I am seeing that a majority are now embracing this new generation of analytics tools/languages. So, I thought it would make sense to (hopefully) help readers by sharing the resources I have found online for a few of the most popular options.

In this post we will focus on the R programming language. (more…)

3 perspectives on how to use research and what they teach us

how to use researchTo complement the research industry perspectives we have shared so far this month, I’m going to share 3 perspectives (on how to use research) from outside the insight community.

After sharing so much material to digest, in that Behavioural Economics guide, this post will be shorter.

I’ve taken the approach of browsing recent news stories, for commentary on use of consumer research. Beyond the stories commentating on recent research findings, 3 news items struck me.

What they had in common was an outsiders’ perspective of how to use research. Each of these perspectives usefully highlights the misconceptions or challenges that insight leaders can face when seeking to secure investment for the research they see as needed.

(more…)

Results of survey for Data Insight Leaders Summit 2017

Data Insight Leaders Summit 2017During our month focussed on research, it seems appropriate to share with you my latest research for Data Insight Leaders Summit 2017.

This annual survey is the second of its kind and is published as part of the run-up, to the Data Insight Leaders Summit 2017, in Barcelona on 18-19 October.  A great conference that I will again have the privilege of chairing this year; you may recall my brief reflections on benefits of event last year.

Following on from the success of the report published by Worldwide Business Research (WBR) in 2016, this survey also provides comparison with last year’s results. I was honoured to be asked to provide the expert commentary, on the implications of survey findings, for leaders working in this area. (more…)

The state of Behavioural Economics in 2017, your handbook

state of behavioural economicsWhat is the state of Behavioural Economics (BE) in 2017? Is it past the ‘hype cycle‘ and settling into common usage, or gradually being assigned to the dustbin of once popular ideas?

Behavioural Economics is one of those topics that regularly comes up in conversations with clients & about this blog. In fact, I’m reminded it’s one of the topics for which readers asked for more coverage in our latest readers survey. My own experience is that it is still very relevant, especially for both Customer Insight teams and B2C businesses.

So, I’m delighted to be able to share with you the best online update on the current state of BE that I have found online. (more…)

Ethnographic research is still evolving and relevant for business

ethnographic researchThis week, following another wonderful wedding (my daughter this time), I’ve been thinking about ethnographic research.

A variety of circumstances, including the wedding, have meant I’ve reflected on the continued importance of human interaction and the power of observing people.

It’s easy, in our increasingly technology-focused world, to assume the future of any industry lies in increasing automation and use of AI to reduce reliance on humans.

But, what separates the technology that people adopt as part of their lives, from that which quickly goes out of fashion, is usability. Designing digital experiences, or human computer interaction, that is both easy & satisfying, requires not just technical skills but genuine insights into people and what works for them. (more…)

Longer reflections on subjective reality, comics and research

Longer reflectionsA number of our previous posts have quickly curated short blogs posts with tips for researchers, this time I’ll share longer reflections.

In addition to my own (and guest blogger) opinion pieces, some of our past research-related collection include:

But, as promised, this time I’ll share some longer form content, akin to what the Financial Times likes to call their “Big Read“.

Given the current bias, towards more articles being published on topics of data, analytics & data science, than research – it was good to find this content.

I hope this (totally subjective) selection helps inform your research practice and CPD as a research leader. (more…)