CYBAEA is the “more than analytics” company that not only delivers the insights from your data but also helps you execute on that knowledge to drive the results that make a difference.
Analytics is not the goal. You may want to increase profits or revenues, treat your customers better, or improve people’s lives or their security. Whatever your goal is, it is our goal too, and we will work tirelessly with you to achieve your ambition, giving you all the support you need (and getting out of the way when you don’t need us).
Yes, we “do” Big Data, predictive models, customer segmentation, and all the other elements of data analysis and machine learning. We really understand data and what it can do; we can make your data talk. But we also understand business, making money and getting results, and we understand customers and how to treat them.
We know how to put it all together. The data, the business, the people. We know how to make it work, we understand how to get the results and how to sustain them.
Learn from us. We have decades of experience. Browse our site for thoughts, inspiration, case studies, white papers, and much more. Contact us and let us talk about the specific situation you face. We have worked with many companies big and small.
What we do
We help you make money and achieve breakthrough business results. We understand business; we understand customers; and we understand data. We do analytics-as-a-service, projects, and interim management; we build Customer Insight and Customer Value Management (CVM) functions; and we like the R platform for statistical computing and its related ecosystem. See our services for how we do it and read our Journal for examples of our current thinking.
Contact us now and let us help you achieve lasting success.
Recent articles from our Journal
Consumer-facing companies in developed economies have experienced little or no growth since the global recession of 2008 and 2009. This is the damning introduction to a recent article from Boston Consulting Group. Consider it for a moment. It has been eight years. During that time we have seen an explosion of data becoming available about our markets and about our customers and their behaviours from a multitude of channels and devices; this includes both data internal to the organization and information from third-party providers. Cloud computing platforms are now readily available from vendors like Amazon, Microsoft, and others, making storage and analysis of this data possible for everyone. Data mining and analytics software and has progressed tremenously making everyone a potential data expert. And yet we have seen no growth? Not even from the very companies that should have benefitted the most from these changes. What has gone wrong? BCG points the finger at the immaturity of the Customer Insight function.
If you had asked me two years ago if Microsoft was a serious vendor for data science and analytics infrastructure and tools, I would have laughed. At the time their offering seemed to me to consist of Excel against SQL Server. There is nothing really wrong (or exciting) about SQL Server, but friends don’t let friends use Excel for data analysis or indeed for anything that matters at all, so that whole proposition was a non-starter. But things have moved on, so how does Microsoft stack up now (mid-2016)? (You can skip right to our conclusions if you are impatient.)
We looked at a rule of thumb for confidence intervals and what that means for a business manager in our previous post. Now we do the maths, stats, and R code for the practitioner.
The 2016 conference on R in Insurance will be held on Monday 11 July 2016. This year we are back at Cass Business School in London, UK. This is the fourth time the conference is held and CYBAEA is proud to have sponsored all four conferences.
How many responses do you need in order to have an accurate measure of the Net Promoter Score? What is the confidence interval on your score? Do you really know if it has changed since last measure? If you are going to use the score for anything, you need to know the answers to these questions.
For the very impatient, a good rule of thumb is that with 1000 responses you (only) know your Net Promoter Score to within 10 points (±5) and it takes fully 100,000 responses to know the score to one point (±0.5).