SPSS users often want to know how they can combine variables together. In this video Jarlath Quinn demonstrates how to use the compute procedure to calculate the mean of a number of variables to create one combined variable, and also how to use the count values procedure to count how many times a particular value occurs across a series of variables in order to create an overall count.
Can you start off just by talking a little bit about your background and how you came to be working in analytics in the first place? Yes, I did research methods at university and was experienced at using spreadsheets and things like that, and that’s where I picked up SPSS, and then I got into …
Expert insight – Nick Di Paulo, Lead Customer Researcher, Hyde Housing Group Read More »
I have been in the business of delivering software applications and solutions that have advanced and predictive analytics at their core, in one form or another, for last 25 years. In a recent conversation with colleagues we were discussing how the wider market has changed and, more specifically, how this has affected the way that …
5 key trends affecting technical training provision in predictive analytics Read More »
Could you start off just by telling us a bit about your background and how you came to be working in the area that you’re working in with analytics? I studied statistics with economics undergraduate level, then I went on to do a Masters in statistics at the LSE part-time whilst I was working at …
Expert insight – Karsten Shaw, Director of Analytics, Populus Read More »
What’s your background? How did you come to be working in analytics? I came from an accounting background and then moved into retail where I worked across a variety of teams in finance, marketing analytics and strategy for various different retailers. I then left that to join a consultancy working with loyalty card data. I …
What’s your background? How did you come to be working in analytics? I suppose accidentally really. I studied politics at university, then I happened upon a short-term contract for a market research company doing data entry and progressed from there. I found the work interesting and enjoyed the projects I worked on. I moved to …
Expert insight – Emma Brooker, Customer Insight Manager, L&Q Read More »
In most businesses it’s not enough to simply be measuring outcomes like customer satisfaction, sales, customer churn rates, subscription renewals, customer loyalty, cancellation rates and so on. To gain competitive advantage you also need to know what’s driving those outcomes. Which aspects of the service you provide most influence how likely someone is to renew …
7 things you need to know about key driver analysis (KDA) Read More »
Surveys remain one of the most popular forms of market research, and consequently we regularly work with customers on large survey-based market research projects. Most commonly this is customer satisfaction surveys, and these can be one of the most valuable forms of data that a company has. We also have clients who conduct broader market …
As it is the end of the year I’ve decided to devote this blog post to some thoughts on where we see the analytics market going in 2018. Unlocking the analytics potential of unstructured data Enterprises are collecting ever greater quantities of unstructured data. A recent survey by Forbes showed that the number of organisations …
Most companies these days are aware of the potential value that advanced analytics could offer them. Lots of people are talking the talk of advanced analytics, hiring data scientists and investing in sophisticated analytics technologies. But these things on their own aren’t going to give you the competitive advantage that you’re hoping for. It’s not …
How to ensure advanced analytics gives you a concrete competitive advantage Read More »
In this video Jarlath Quinn introduces the popular TURF analysis technique and demonstrates how to apply it in IBM SPSS Statistics. TURF analysis is used in many industries to find the optimal sub-group of options from a wider portfolio in order to maximise their appeal to an audience or market.
In this video Jarlath Quinn explains what cluster analysis is, how it is applied in the real world and how easy it is create your own cluster analysis models in SPSS Statistics.
With less than a year to go until it comes into effect, organisations are really starting to get to grips with what GDPR will mean in practice. We’ve talked to lots of customers who are concerned about the implications that GDPR might have for the way in which they collect and analyse customer data. Much …
Sometimes you may have problems with your data issues not related so much to the values of the data but to the fields themselves, such as awkward field names. The filter node is a really useful tool that offers a bunch of tricks for dealing with awkward fields.
In this video we explore variable sets – a procedure in SPSS that allows you to generate subsets of variables or fields for display within dialogue boxes and in the data editor itself.
Used correctly, the generate menu offers analysts some substantial time saving benefits. Watch this video to learn more about how you can use the generate menu effectively.
Many of our clients regularly hire new analysts and we’re often involved in discussions about what the core skills are that they should be looking for. Similarly, I often talk to people looking to build a career in analytics who want to know what skills they need to develop. The most skilled analysts are in …
Thinking of hiring a data analyst? What skills should they have? Read More »
We often talk to people who are unsure whether they need SPSS Statistics or whether SPSS Modeler might be more suited to their needs. In fact, it’s not always a clear cut choice as to which tool is more appropriate as it depends on the context in which the technology might be used. With that …
Do I need SPSS Statistics or Modeler? How to choose the right product for your needs Read More »
SPSS enables quite a high level of customisation so you can set up the software in a way that enables you to be a lot more productive, however many people are unaware of just how powerful these customisation options are. In this video we explore the options edit menu.
The data audit node is a powerful tool you can use to help understand the shape and structure of your data before your analysis begins. You can also make some decisions here regarding how you might want to clean up your data, for example by dealing with missing values or extremes and outliers.
Over the past two years I’ve noticed a steady stream of articles in the mainstream press and business journals centred on the themes of a) the dangers of machine learning 1 2 or b) the limitations of machine learning 3 4. Many of these articles refer to incidents where machine learning initiatives have echoed and …
The real world, whether it be the physical world, for example machines, or the natural world, for example human and animal behaviour, is very complex with many factors, some unknown, determining their behaviour and responses to interventions. Even if every contributory factor to a phenomenon is known, it is unrealistic to expect that the unique …
I’ve blogged several times now about different aspects of data science. A conversation I’ve been having more and more frequently now is about what tools people should learn if they’re hoping to develop a career in data science. Obviously there are many different factors to be taken into account here. You’ll want to think about …
Contemporary analytical platforms like SPSS and SAS represent the some of the earliest and yet longest-lived examples of proprietary software in the industry. When we think of the tectonic shifts the technology landscape has witnessed in last four decades, through the mainframe era, the rise of the PC, browser wars, the dotcom bubble, the smartphone …
How alternative interfaces can help you get more out of R Read More »
Many of the analysts we speak to are being pushed over to R, primarily because it’s open source and therefore a free alternative to commercial data analytics packages for which the costs can sometimes run into tens of thousands of pounds (or more). However, even experienced analysts often find that getting to grips with R …
It’s not uncommon for people to say to us that they don’t understand why they should pay for industry standard analytics products like SPSS or SAS when there are strong open source alternatives freely available such as R. Indeed the development of R has really transformed the analytics marketplace in many ways. It’s tempting to …
Six questions to ask before you opt for open source software Read More »
It’s not uncommon to talk to potential clients who consider themselves to already be very much data-driven in the way that they operate. However it’s very rare to find a potential client that truly is exploiting the full potential of the data that they hold. That’s because companies often confuse business intelligence with predictive analytics, …
What’s the difference between business intelligence and predictive analytics? Read More »
As we help our clients get up and running with the predictive analytics tools and skills they need, we see some trends emerging in terms of the kind of applications for which clients tend to use predictive analytics most commonly. These are what we call ‘repeatable application templates’. In my previous post I outlined the 4 …
In part one of this video series Jarlath Quinn explains how operational analytics works, what data sources may be utilised and introduces the example case study that forms the basis of the subsequent videos in the series.
In part two of our predictive operational analytics video series, Jarlath Quinn introduces the IBM SPSS Modeler Software before showing how to explore the example data from the case study and carry out text analytics of engineer logs to categorise the information and create key fields for further analysis.
In part 3 of this predictive operational analytics guide Jarlath uses the results from the previous analysis stage to show how to build and assess a predictive model that identifies whether or not a part replacement will be required during a maintenance visit.
In this final part of our predictive operational analytics video series Jarlath shows how we can use the predictive technology to go further by predicting the actual outcome of the visit including which part is likely to require replacement.
Data science is everywhere at the moment. Nearly as everywhere as big data, but not quite. Books out there are making the concepts behind statistics and predictive analytics more and more accessible not only to those in business making decisions everyday but also to the average man or woman on the street. Try Super Crunchers …
Data science is everywhere, so why no data scientists to be seen? Read More »
Jarlath provides a brief history of the concept of net promoter score before introducing the case study whereby Predictive Promoter was applied to data from the guests of a major hotel chain.
In this video Jarlath shows how to automatically produce a model that predicts customer’s recommendation scores based upon transactional and operational data.
In this video Jarlath shows how easy it is to take a previously built model that has been generated based on known outcomes and apply it to customer data where the outcome is not known.
In this final part of our predictive promoter video series, Jarlath Quinn tackles the project’s most ambitious task: mining the open-ended guest comments to uncover important insights. Here you can discover how we can use text analytics to extract a series of concepts and sentiments from customer comments in order to categorise the guests’ responses.
A is for Automation Why bother trying out loads of modelling techniques to see which one works best when Modeler can do that for you? Modeler can test many permutations of the same algorithm and multiple instances of different methods before selecting the best performers according to a pre-specified criteria. Oh and it will also …
An in depth guide to using the chi-squared test to determine statistical significance.
What is correlation? Correlation is a term that we employ in everyday speech to denote things that appear to have a mutual relationship. In the world of analytics correlations are specific values that are calculated in order quantify the relationships between variables. This kind of analysis is powerful because it allows us measure the association between …
This post describes how to use Python scripts to create and modify Modeler supernodes, and control the execution of the nodes within the supernode. If you’re after a basic overview of Python scripting in Modeler then this post may be of interest, and I’ve also written about how to write standalone Python scripts in Modeler here. As …
We spend a great deal of our time at Smart Vision helping our clients to establish the use of predictive analytics in their business. For many organisations, getting started with predictive analytics can feel like a real departure from more traditional and familiar areas of activity. That said, organisations in almost every industry sector are becoming …
Four reasons why getting started with predictive analytics is simpler than you think Read More »
The concept of the net promoter score was introduced to the world in Frederick Reichheld’s seminal Harvard Business Review article The One Number You Need to Grow in 2003. Reichheld’s research led him to believe that there was a deep and intrinsic link between profitable growth and customer loyalty. Two years of research revealed that, for most industries, …
Understanding what drives your net promoter score – how data science can help Read More »
Data science is on the rise. A couple of years back Harvard Business Review suggested that ‘data scientist’ is the sexiest job title of the twenty first century and the hype around data science shows no sign of abating. The term ‘data scientist’ itself was only coined in 2008 but since then the number of data …
Data science projects – what skills do you need and where can you get them from? Read More »
In this short video Jarlath Quinn demonstrates how to use the powerful simulation tools within IBM SPSS Modeler to perform What If analysis (also known as ‘Scenario Planning’). What if analysis allows business-focused analysts to go beyond simple predictive modelling to evaluate the impact of different choices and scenarios on predicted outcomes.
This video shows you how organisations with substantial capital assets can use IBM SPSS Modeler to predict when asset failure is most likely. Predicting asset failure can prevent problems before they happen and enables organisations to save money, reduce asset downtime and increase efficiency.
This video shows you how you can analyse customer comments or indeed any free-text data, using the power of the text analytics engine contained in SPSS Modeler Premium
Learn how to exploit the power of the text analytics engine contained in SPSS Modeler Premium (video 2 of 3)
Learn how to exploit the power of the text mining engine contained in SPSS Modeler Premium (video 3 of 3).
This short video shows how you can perform a simple affinity analysis using IBM SPSS Modeler. Affinity analysis can be used to understand interconnected relationships between key factors. For example, in retail it can be used to perform basket analysis, whereby retailers can identify which products are most commonly purchased together by customers in a single transaction or over a given period time.
