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A Quick DataCracker Predictive Tree Tutorial

Welcome back to our tutorial video series. In this video, we’ll show you how to use one of DataCracker’s advanced data analysis tools – Predictive Modelling (or Predictive Tree).

A predictive tree, or decision tree, is a visual model that shows how some input data predicts the value of target data. For example, a predictive tree could show that age and gender can predict the value of attitude data.

A series of charts will be displayed in a tree format, showing how the chart values (the target data) change according to the input data.

Check out our blog post Implementing the 80:20 Rule with Predictive Modeling for more information on how you can use Predictive Modelling for your business.

Having more questions on how to dig deeper into your survey results? Visit our DataCracker Knowledge Base or leave your questions in the comments below.

 

A Quick DataCracker Segmentation Tutorial

In this video, we’ll show you how to use one of DataCracker’s advanced data analysis tools – Segmentation.

What does it do? Segmentation will help you identify whether there are different groups of people in your customer base and how each group differs from others.

Why do you need to know? There are many reasons why you should segment your customers – focusing your resources, re-packaging your product/service offer and developing more effective marketing campaigns to name a few.

Check out our blog post Speak Your Customer’s Language: How You Can Use Segmentation to Create Effective Customer Profiling for more information on how you can utilize segmentation to be a smarter marketer.

Don’t forget to check back here for even more useful tips on analyzing survey data.

Having more questions on how to dig deeper into your survey results? Visit our DataCracker Knowledge Base or leave your questions in the comments below.

How Many False Discoveries Have You Made? Putting Rigor Into Stat Testing

How Many False Discoveries Have You Made? Putting Rigor Into Stat TestingIf you look hard enough, surveys are filled with “insights”. There are always differences that could be interesting.  Men may like your product more than women.  Older people may buy your product less frequently.  Awareness may lift when you rejig your website.

The challenge with analyzing surveys is that many things that look like insights are probably wrong.  Statistical testing has been developed for just this problem.  The purpose of a “stat test” is to work out if a result in a survey that seems to be interesting is likely to be a one-off fluke, or, is a true insight. [Read more…]

You’re not still using cluster analysis are you? Do you wear a seatbelt when you drive?

Some short cuts are good. A faster way to drive to work. A delicious meal in five minutes.

You’re not still using cluster analysis are you? Do you wear a seatbelt when you drive?Some short cuts are bad. Driving without a seat belt. Failing to proof read. Cluster analysis. Yep. You read it right. Cluster analysis. [Read more…]

The Almost $64 Question: Road-testing Google Consumer Surveys and Toluna QuickSurveys

In the olden days – and by “olden” I mean the last century – it was expensive to conduct market research. Even if you only asked a single question you were generally looking at spending at least $1,500. Today, you can ask a single question, and get a heap of profiling data, for around $100.  And, you get your results much faster.

The almost $64 question Survey Analyzer: road-testing Google Consumer Surveys and Toluna QuickSurveysTo get a feeling for how this works in practice, I  road-tested a couple of the new super-cheap services: Toluna QuickSurveys and Google Consumer Surveys. I tested Google because it is the new kid on the black, doing things completely differently to everybody else. There was no particular science behind my choice of Toluna and I suspect I would have had broadly similar experiences if using any one of the other “traditional” DIY market research services. [Read more…]

Clouds with Silver Lining: Freemium Text Analytics

Tom CruiseWorking out how to analyse text data is one of the most difficult problems in data analysis.  To get your head around how difficult it is, look at the table below.  This shows the answers of 20 people to the question “What do you dislike about Tom Cruise?” [Read more…]

Analysing Survey Data: Conducting Market Research Surveys on a Shoestring Budget

Cutting cost - Image courtesy of David Castillo Dominici - FreeDigitalPhotos.netMaybe you’ve been contemplating doing some market research for your business. You could be looking at analysing survey data to create customer profiles. Tweak your product offering. Or improve your marketing message. Jumping into market research can often appear daunting though. Both costly and time consuming.

This can be true. Especially if you engage the services of a professional market research firm. Luckily for you the internet has opened up a new set of cost effective alternatives for survey research.

Read on below for a step by step guide to carrying out your survey research on a shoestring budget. [Read more…]

They Say “Know Your Target Market”, but Which Target Market? (Market Segmentation)

Market segmentation with DataCracker

“Know your target market” is one of the mantras of modern business.  It is shorthand for saying that its a good idea to design your product and communications so that they can be found by, and appeal to, the customers that you think are the best prospects.

If you are an established product working out your target market can be as simple as profiling your customers and can be done using predictive modeling.  However, if you have a new product, or, are struggling and suspect you are targeting the wrong target market, you need to segment your market prior to deciding who to target.

Market segmentation is the term that marketers use for breaking a market up into parts and developing different strategies for the different segments.  Almost all businesses segment their markets.  Nevertheless, there are two quite different logics of segmentation and it is important to have a clear view of which you are trying to employ. [Read more…]

DataCracker Tutorial – How To Analyze Survey Data

  • Have you ever freaked out when it comes to working with data?
  • Did it take you unreasonably long to get so little insight from your customer data?
  • Have you ever dreamed of an app that can automatically analyze your surveys, tell you the golden nuggets of your data, and even better – write a report for you?

If you answer yes to any of the above questions. This video is for you.

Welcome to our first tutorial video on survey results analysis. In this video, we will show you how easy it is to make DataCracker do the hard work for you.

Visit our DataCracker Knowledge Base or leave your questions in the comments below for more tips on making the most out of your customer data.

Implementing the 80:20 Rule with Predictive Modeling

80:20 rule, predictive modelingIt has lots of names.  The 80:20 rule.  The pareto principle.  HVC.  Power Laws.  Zipf laws.  Whatever we call it, the idea is that around 20% of our potential customers will account for 80% of our upside.  While the numbers can move around a bit, this basic idea applies in all aspects of customer management.  It applies among your customers: a small proportion of your customers will provide most of your profit.  It also applies among your prospects: a small proportion of the prospects have the potential to deliver much more profit than the rest.

If the 80:20 rule describes your market, how can you leverage it?  Fortunately, it is pretty straightforward! [Read more…]