conversation about maximising value from customer insight

Listening to 31 Data Scientists and Seeing 10 companies’ applications

To complement the perspectives of our recent guest bloggers, today I’m sharing three ways of listening to data scientists. These will include a (potentially) free recommended eBook, an engaging blog post and a punchy video. Peter, Robert & Francesco have made a case for data & AI potentially transforming businesses & sectors. As part of our month focussed on applications of data & analytics, I also want to share real.. Read More

InsurTech: bucking the trend of cautious insurers with AI innovation

How close are you to the AI innovation happening within the InsurTech sector? To promote debate, and deeper thinking amongst Customer Insight Leaders, this post balances our last one. Apparently contrary to that review (shared by SMA), in this post we look at lots of insurance innovation. The reason for the difference is a focus on the InsurTech sector. But, there are notable examples beyond InsurTech too, including recent use.. Read More

Is that tempting technology really useful to your business?

Unless it proves useful to your business, it was a distraction. Recent posts have focussed on advice when using Data Science or Data Visualisation. Now it’s time we returned to focussing on commercial realities. One lesson, I learned as a senior customer insight leader, was not to get distracted by what one CEO called “hobbies”. By that, he meant ideas, passions or technical innovations that, whilst interesting, are not relevant.. Read More

On the Bank Holiday, here’s a variety of topics for Insight Leaders

Sitting at my desk on a Bank Holiday, before taking a break, I’ve been reflecting on a variety of topics for Insight Leaders. One of the reasons I found Customer Insight Leadership such a rewarding career and still find it fascinating to help such leaders, is the diversity. One day your focus may need to be on improving specific Analytics skills, or complex Data problems, the other it could be.. Read More

Data Science programming languages: (2) Resources for Python

As 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.. Read More

Ethnographic research is still evolving and relevant for business

This 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.. Read More

Advancing on Blockchain Analytics, more investment & collaboration

Since our previous post, raising questions for Blockchain to answer, I have seen more news on Blockchain Analytics. It seems many individuals and firms are working in this space. To bring together the power of analytics (sometimes plus AI), to help both analyse blockchain data and enable new types of analytics. We raised, in that previous post, the unanswered questions on whether blockchain could help overcome current data challenges &.. Read More