Unlock Your Data's Potential By Integrating Qualtrics & Tableau
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Find out what happens when you pair the only enterprise customer experience management platform with the world's most powerful data visualisation software. The new Qualtrics and Tableau Integration allows you to connect your Tableau desktop to Qualtrics so you can gather and view data in real-time. Join Josh Robbins from Qualtrics and Bob Middleton from Tableau for our webinar where you will learn: The easiest and most efficient way to get Qualtrics data into Tableau for both ad hoc or continual analysis. Top tips for engaging your target respondents including keeping surveys mobile friendly, utilizing the survey library (not reinventing the wheel), while making questions easy to understand and much more. Top tips for creating powerful visualisations. High impact use cases from customers using the connector.
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Unlock Your Data's Potential By Integrating Qualtrics & Tableau
- 1. Unlock your data’s potential by integrating Qualtrics with Tableau SM
- 2. Housekeeping • This presentation is being recorded, a copy of the presentation and slides will be distributed within 48 hours • Please chat questions throughout the webinar using the chat window, we will designate time at the end for Q&A • Join the conversation on Twitter by using: @Qualtrics
- 3. Introductions Bob Middleton Product Marketing, EMEA Josh Robbins Strategic Alliances & Partnerships
- 4. Agenda • Introduction to the Qualtrics/Tableau connector • Best practices for data collection • Best practices for data visualization • High impact use cases from customers currently using the connector
- 6. Starts with this One respondent per row
- 7. Need to end with this Each respondent is listed 20 times; one time for each question
- 8. Best Practices for Data Collection • Keep surveys mobile friendly • Keep surveys short • Don’t reinvent the wheel • Screen first • Make questions easy to understand
- 9. Keep Surveys Mobile Friendly
- 10. Keep Surveys Mobile Friendly Reasons why: Organic shift of surveys being taken over mobile device, whether or not the survey administrator wants this to happen (Buskirk, 2013).
- 11. Keep Surveys Mobile Friendly Reasons why: Organic shift of surveys being taken over mobile device, whether or not the survey administrator wants this to happen (Buskirk, 2013). Smartphone ownership, for example tends to be highest among those with incomes above $75,000 (78%), college- educated (70%), and younger adults (~80% of those aged 18- 34 owns a smartphone) (Smith, 2013).
- 12. Keep Surveys Mobile Friendly Reasons why: Organic shift of surveys being taken over mobile device, whether or not the survey administrator wants this to happen (Buskirk, 2013). Smartphone ownership, for example tends to be highest among those with incomes above $75,000 (78%), college- educated (70%), and younger adults (~80% of those aged 18- 34 owns a smartphone) (Smith, 2013). Break-offs are more of a concern in mobile surveys: 5.3% of mobile web respondents dropped-out of the survey, compared to 0.9% for tablet users (Wells, Bailey and Link, 2012).
- 13. Keep Surveys Short • Design your ideal report before you write your survey • Helps you not ask extraneous questions • Helps you not forget an essential question
- 14. Keep Surveys Short • Design your ideal report before you write your survey • Helps you not ask extraneous questions • Helps you not forget an essential question • Randomize questions to separate samples
- 15. Keep Surveys Short • Design your ideal report before you write your survey • Helps you not ask extraneous questions • Helps you not forget an essential question • Randomize questions to separate samples • Knit data from multiple surveys together instead of one HUGE survey
- 16. Don’t Reinvent the Wheel
- 17. Don’t Reinvent the Wheel Use a survey template/library as a starting point
- 18. Don’t Reinvent the Wheel Use a survey/question template as a starting point Combine multiple question templates to make your ideal questionnaire
- 19. Don’t Reinvent the Wheel Use a survey/question template as a starting point Combine multiple question templates to make your ideal questionnaire Tweak your questions, based on the data you will want to collect
- 20. Don’t Reinvent the Wheel Use a survey/question template as a starting point Combine multiple question templates to make your ideal questionnaire Tweak your questions, based on the data you will want to collect Be aware of dependencies, such as routing and piping
- 21. Screen First • Start with screening questions
- 22. Screen First • Start with screening questions • Ask quota-specific questions
- 23. Screen First • Start with screening questions • Ask quota-specific questions • Write a pre-amble giving information about the survey
- 24. Screen First • Start with screening questions • Ask quota-specific questions • Write a pre-amble giving information about the survey • Ask general questions first that introduce the topic
- 25. Screen First • Start with screening questions • Ask quota-specific questions • Write a pre-amble giving information about the survey • Ask general questions first that introduce the topic • Ask specific questions next • Behavioral: past, current, future • Psychographic • Solution-specific
- 26. Screen First • Start with screening questions • Ask quota-specific questions • Write a pre-amble giving information about the survey • Ask general questions first that introduce the topic • Ask specific questions next • Behavioral: past, current, future • Psychographic • Solution-specific • Ask demographic questions at the end – they are both easy and can be sensitive with higher break-off rates
- 27. Make Questions Easy to Understand
- 28. Make Questions Easy to Understand Avoid leading words/questions BAD EXAMPLE Quitting smoking is hard. Do you want to quit smoking for good? Yes/No BETTER EXAMPLE Do you want to quit smoking cigarettes? Yes / No
- 29. Make Questions Easy to Understand Give mutually exclusive choices BAD EXAMPLE
- 30. Make Questions Easy to Understand Cover all possible answer choices If someone makes $20,000 exactly – he or she is going to struggle to find the right response to check. What about the person who uses the Internet every couple of weeks? BAD EXAMPLE
- 31. Make Questions Easy to Understand Use balanced scales Scales should have equal distance between all points on the scale, semantically as well as numerically. BAD EXAMPLE
- 32. Make Questions Easy to Understand One question at a time These two questions might not be asking the same question in the mind of the respondent. BAD EXAMPLE
- 33. Best Practices for Data Visualization • Why visual analytics • What are we good at • What are we bad at • Keep it simple • Testing
- 36. 70% 30%
- 37. What are we good at?
- 39. How many nines are there?
- 40. How many nines are there?
- 44. What are we bad at?
- 45. We are slow comparing numbers
- 46. Colour helps
- 47. We are very fast with visual insights
- 50. Keep it simple
- 51. Best practices: bringing together senses and perceiving
- 52. Mapping to insight: Maps don’t have to be geographic
- 53. Common sense is a pre-requisite
- 54. Testing
- 55. Dashboarding for the 5-second test
- 56. High Impact Customer Use Cases Automation One Hub Minimize Errors Join other Data Flexible
- 57. High Impact Customer Use Cases Automation One Hub Minimize Errors WHY: One central hub for analysis & visualizations Organizations often want to leverage economies of scale and reduce learning curves by using one program, Tableau, as a central hub for all analysis and visualization. Join other Data Flexible
- 58. High Impact Customer Use Cases Automation One Hub Minimize Errors WHY: Join Qualtrics data with other data Organizations have mountains of data. Joining Qualtrics data to other data transactional data helps answer the “why” behind customer behavioral data. Join other Data Flexible
- 59. High Impact Customer Use Cases Automation One Hub Minimize Errors WHY: Flexible data selection Users need ultimate flexibility to create the perfect analysis. With the ability to transpose and select questions, meta data, and embedded data, users can bring the data into Tableau in a variety of configurations. Join other Data Flexible
- 60. High Impact Customer Use Cases Side-by- Side Data AutomationFlexible One Hub Minimize Errors WHY: Minimize errors Exporting Qualtrics data to Tableau or other analysis programs often requires manual reshaping, copying, and pasting that can lead to human error
- 61. High Impact Customer Use Cases Side-by- Side Data AutomationFlexible One Hub Minimize Errors WHY: Automation Once an analysis or dashboard is built, it needs to easily and automatically updated to reflect the most recent user response set.
- 63. SM To learn more, email: partnerships@qualtrics.com
Notes de l'éditeur
- Speaker: Josh (Qualtrics) Introduce participants
- Visual analysis leverages our innate perception skills – but how do we perceive naturally and what perception skills do we humans have that help us understand and gain insights into the world around us? The visual abilities we have are deep rooted, they have been bred into us over hundreds of thousands of years. - Click
- For one of the longest periods of human history we were hunter gatherers, in some parts of the world we still are. We relied on our visual acuity for our very survival. Our ability to differentiate colour and shape allowing our hunters to spot predators, [CLICK] and prey; for our gatherers to distinguish between [CLICK] mayhem, [CLICK] and magic. But why the focus on visual? And why given our evolution, wouldn’t we already be doing just that?
- Given those evolutionary imperatives, it’s hardly surprising that around 70% of the information we take in from the world around us is visual. And given that history there are some things that our visual system is better at picking up than others.
- Visual analysis leverages our innate perception skills – but how do we perceive naturally and what perception skills do we humans have that help us understand and gain insights into the world around us? The visual abilities we have are deep rooted, they have been bred into us over hundreds of thousands of years. - Click
- In fact, your brain is SO good at processing visual data that it actually perceives lots of information about visual data subconsciously, or pre-attentively. Good data visualizations leverage the power of pre-attentive processing, and Tableau is designed to guide users toward building good data visualizations. It’s tough to understand the power of pre-attentive processing until you’ve experienced it. Here your eyes are automatically drawn to ‘the odd one out’ in each of these groups and that single, coloured dot – really jumps out at you. Remember that 70% of the information each of you takes in is visual. So what are we less good at?
- Our brains have to work really hard with packed tables of numbers. Yet how often have you been presented with data in this form and hoped to make sense of it?
- Now is it easy? Yes it is – we used a preattentive attribute, colour, to “pop out” the 9s. Our brain starts processing differences in colour before we begin to make conscious understanding of the data.
- Pause for a few seconds OK, 3 things just happened Your brains, without your consent or any real conscious effort, did colour and shape - it then kicked it up a notch and counted maybe to 9, maybe via a 5 + 4. Did any of you draw a D shape around it and think 9-pin D, or is that my inner geek showing.
- How many 9s. No just joking. Here is a small table and you WILL be getting some useful information out of it immediately. Pre-attentive position helps you see quickly that North America has the largest numbers and Latin America the smallest. You then see that there is some growth in all areas. Beyond that, it gets tricky
- Now we get a lot more information very quickly North America and Europe took a dip in July but have put on very healthy growth since Something caused a ‘relatively’ major uplift in Latin America through June and that new level has been maintained, what happened and can we do it again? The line chart makes it so much easier to compare regions and spot trends, the colours help us keep track of each region when lines cross.
- Visual analysis leverages our innate perception skills – but how do we perceive naturally and what perception skills do we humans have that help us understand and gain insights into the world around us? The visual abilities we have are deep rooted, they have been bred into us over hundreds of thousands of years. - Click
- Let’s do that exercise one more time. Which 3 product subcategories are the most unprofitable? Which are the three best performers? Not impossible but tricky.
- Using colour can help with simple questions the 3 lowest and 3 highest would still be hard to do just with colour In this case, as humans, we effortlessly know that red means “pay attention” and in this data set, our eyes – completely subconsciously – are drawn to the red numbers. We’re able to perform visual analysis on this data set in a matter of milliseconds to hone in on the 5 rows with unprofitable customer segments. The amount of data we’re processing is much smaller and further analysis is easier. But we’re still comparing numbers…
- Now … which product subcategory is the most unprofitable? You can instantaneously see that Tables for the Home Office customer segment are the least profitable. In this instance, there are visual analysis cues that supported human’s nature perception triggers – in this case, both color and size comparison. While the previous data set helped us hone in on the important numbers through color, in this case, we aren’t being asked to do any number comparisons – and remember, numbers are actually very complex and largely theoretical, in this instance we are able to visually perceive insights without having to do any numerical comparison or in-depth processing. The comparisons we are doing are around the relative length of the bars in the chart, the color differences. And as with the math problem, when we’re given the right tools, our ability to get to the “answer” in this case –the analysis – is much, much faster. In fact, I’m sure for most of you, the answer to which product category is the most unprofitable you’ve already moved on to thoughts like, wow, office machines for the corporate segment are doing really well! Or, technology is by far our most profitable product category regardless of customer segment.
- Bars and colour are a great way to display differences in data that can be grouped in some way, But beware of relativity! Here is a solid grey bar that is telling us nothing.
- Here is the same solid grey bar with a nicely shaded background. It confuses our eyes into seeing shading in the grey bar that isn’t there. So keep it simple, don’t add unnessesary clutter that might confuse.
- Visual analysis leverages our innate perception skills – but how do we perceive naturally and what perception skills do we humans have that help us understand and gain insights into the world around us? The visual abilities we have are deep rooted, they have been bred into us over hundreds of thousands of years. - Click
- In addition to an understanding of our hardwired pre-attentive visual attributes and the way we assign importance, being sensitive to other sensing pitfalls – like the difficulty visual interruption presents – is important. So too are standards – time on the x-axis, location on a map, a using a bar char to compare values. In this dashboard it’s easy to understand the area (size/scope) of the data, the time frame (day of the week, the work day) and what we’re comparing (different ticket types) The red makes the data pop but it’s not overly complicated with different colors that would only confuse the viz – for example, marking the days of the week in in alternate colors would be meaningless here.
- Another easy to understand example is seating for large venues like stadiums or concert halls, or congressional seats
- Visual analysis leverages our innate perception skills – but how do we perceive naturally and what perception skills do we humans have that help us understand and gain insights into the world around us? The visual abilities we have are deep rooted, they have been bred into us over hundreds of thousands of years. - Click
- Most of us start at the top left and scan across to the right. That’s where your title and your key information go. Legends need to be where they are needed We try to put filters at the top or on the right Simple is good clutter is bad. In this dashboard I seem to be breaking the 5 views rule but those simple charts at the bottom are just breaking down my traffic by type so it works in answering ONE question, what’s my web traffic Users have three ways to filter so they can ask and answer their own questions The overall effect of this dashboard goes beyond function – it’s beautifully laid out
- Tableau Questions: Suppose I want to bring in additional data, like population data. Can I do that as well within Tableau. Can I create those maps with Tableau or do I have to import them. Qualtrics Questions: How do I get the connector enabled on my account? Can I use a survey library from another organization?