This document discusses opportunities for conducting conjoint analysis on mobile devices. It begins by introducing mobile conjoint and its benefits for exploring new research areas and contexts. It then presents three examples of mobile conjoint opportunities: 1) A 3x3 mobile choice-based conjoint survey that reduces tasks and concepts for mobile usability; 2) Integrating conjoint into a real-life online shopping app to test attributes like prices and promotions; and 3) Using conjoint beyond just products and prices to optimize aspects of the online shopping experience like website filters and search functions. The document emphasizes how mobile research allows incorporating context and realism to take conjoint applications to a new level.

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Mobile research is a rapidly growing addition to the traditional ways of performing research. In the new world, where the attention span of consumers is getting shorter and shorter, mobile conjoint provides the opportunity to explore fields previously unknown to choice modeling. This creates unique research opportunities, but it also comes with limitations. During this workshop, we will take you through a couple of those opportunities and show you how a ‘3-by-3 mCBC’ approach enables us to receive as valid results on mobile as with a traditional conjoint survey.

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At SKIM, we are choice modelers - always curious about understanding consumer decision making. We take a look at consumer decision making in three different contexts:
•Pricing and Portfolio;
•Communication; and
•Innovation.
Since we use conjoint as methodology in many of our projects, we often get asked by clients: Can we also execute this conjoint survey on mobile devices?

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Mobile is an established research method by now and it is here to stay. There has been so much discussion about mobile research in the past that tips and tricks on how to use it can now even be printed in a book: for example, the Handbook of Mobile Market Research.
In this book, you can find a checklist on technical details to keep in mind when doing market research on mobile devices:
•Adjust the length of your survey
•Use ‘responsive design’ to optimize your survey for various devices
•Fit questions onto small screens (using less text, fewer answer options)
•Consider the usability of the device: Zooming, panning, and swiping
•Keep in mind the available bandwidth of a mobile user on the go
At SKIM, we have spent much of our time working on the technical details of how to fit a conjoint survey, as we know it, onto mobile devices.

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Now that we have clarified all technical issues up until the point that we can print recommendations in a book, it is about time to take a look at what else can be done with ‘Mobile‘ in the future:
•Is there a paradigm shift in research now that ‘mobile’ is happening?
•What can we do with mobile research beyond what we do now? For us at SKIM, ‘mobile research’ is about more than bringing Desktop surveys onto mobile devices. Mobile research is a chance to rethink the way we execute studies and discover entirely new research avenues.
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The really exciting new thing about ‘Mobile’ is the addition of context as a variable:
•It is no longer only about WHO you survey  target groups, demographics, etc. …
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•…instead you can move on to think about WHERE and WHEN you want to survey consumers  shopping occasions, context, reality virtue
Mobile research comes along with a special reality virtue: with the addition of context, occasions, and locations, mobile offers opportunities to bring our research onto a whole new level of realism. That is exactly the point where it gets interesting for us as conjoint users: with conjoint we always want to do an experiment (what would happen to the market if product X were available?). Now, with mobile, we can make experiments even more realistic; getting to even better insights.
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We will present you with 3 examples of new opportunities to discover with conjoint research on mobile devices.
Some of these ideas are today’s current reality; others look less like conjoint experiments as we know them today. These ideas offer a sneak peek into what conjoint research on mobile devices can look like tomorrow or further into the future.
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Opportunity #1: 3x3 mobile CBC – close to home
Our first idea is close to home: We started with the question of how to bring conjoint exercises - as we know them from desktops - onto mobile devices.
We realized quickly that this is not trivial: Try to fit this this conjoint task onto the display of a smartphone…

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The motto for mobile research clearly is: ‘Doing More With Less’. We realized quickly that we would need to develop solutions with fewer conjoint tasks, fewer concepts on small mobile screens, and shorter surveys overall to get to even better insights.
This made us start with the end in mind. We forced ourselves to think through what mobile research is really all about and how we imagine the ideal mobile conjoint exercise: no more than 3 taps on a smartphone.

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Ideally, a mobile conjoint exercise would take no more than:
•3 tasks,
•3 options per task, and
•no more than 60 seconds of a respondent’s time.

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Try our example of a mobile choice-based conjoint survey on your mobile phone or tablet!

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This is what a mobile conjoint task looks like.

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As researchers - we asked, of course: How valid is it to run conjoint surveys from a mobile phone? We ran several validation studies comparing the results from desktops and mobile phones. This taught us a whole lot about the necessary conditions for running choice-based conjoint studies on mobile devices:
•Sample: A larger sample allows for asking fewer questions while still arriving at robust model estimates. You can use the rule of thumb of having twice the sample you would use in a desktop study when running your survey on mobile.
•Statistical design: Reduce the complexity of your model. 3*3 mCBC works best with perfectly balanced designs – don’t waste conjoint tasks on exclusions, prohibitions, or alternative specific attributes.
•Layout: Make use of the space you have - max. 5 attributes, concise level descriptions, work with icons and brand logos where possible.

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Where could you apply 3*3 mCBC? Think about context and the reality virtue:
•Conjoint surveys as we know them, but now on the go;
•Conjoint surveys at the shelf (“You are currently in the supermarket in the candy aisle. Which candy would you choose, if there were this new variant of chocolate on the shelf as well?”);
•Exit-surveys on (non-)purchases in the store.

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Opportunity #2: Conjoint in real-life online shopping App
The 3*3 mCBC seen previously still looks a lot like a standard conjoint – just on a smaller screen. This does not need to be the end of the road, though: What else can we imagine doing with mobile and conjoint that will be driving business insights in the future?
One application that suggests itself: online shopping - continuously growing, running on ever more mobile devices. Imagine you are sitting on your couch at home, with your tablet at hand, browsing Amazon’s pages…

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Use the URL or QR-code to browse our online shopping app from your mobile or tablet!

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What you will see, may not look like a conjoint task anymore, but – trust us – it is one:
•Try adding a product to your shopping cart and click on ‘Next’;
•Prices, promotions, shipping costs will change.
•Also: the product order and the products placed on the first page (of several) will change.

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New attributes that we can test:
•Product ratings and reviews,
•Prices and promotions,
•Product descriptions and visuals,
•Also: Shipping options and costs.

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Now what kind of business questions can we tackle with this online shopping app and conjoint?
Think back to the addition of context and realism:
•Optimizations of product and price in the context of online shopping;
•Optimization of ‘In App’-Purchases;
•Optimize in the context of various sales channels and purchase occasions (different devices – desktop, tablet, mobile phone – all have different purchase occasions).

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Opportunity #3: Besides product and price, let’s re-think what else we can optimize with Conjoint
In examples 1 and 2, we take on typical conjoint research questions:
•What to do with the price of product X?
•What will happen if product Y enters the market?
We can also use conjoint as a method for other types of research questions. Imagine again your home, your couch, your tablet in your lap, roaming the Internet looking for a new laptop to buy: What are you looking for when researching laptops online? Which webshop is giving you the best variety and the best information? Which webshop do you prefer to compare laptops? Which one offers the best checkout process?
From conjoint in a mobile shopping environment, it is a small step to the question: How do consumers make purchase decisions in a mobile shopping environment?

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We apply the concept of conjoint (attributes and levels) to a new research area: the virtual shopping environment of a webstore. Attributes to vary can be:
•Filter options,
•Ranking options,
•Search options,
•Product portfolio.

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And more: we can explore the entire search process respondents go through and compare possible product options in a conjoint exercise at the same time.

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Take a look at our prototype of a webstore optimization using conjoint (optimized for tablets – it’s a prototype)!

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Now what can we do with this webshop ? Think again about adding context and the reality virtue:
•Optimize webstores and online shopping channels using conjoint;
•Also: Use it like ACBC to explore the decision making of online shoppers;
•Segment online shoppers and determine specific target-group requirements for webstores.

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The key takeaways about mobile research and conjoint on mobile devices:
1.Learn to use context as a variable,
2.Start appreciating the reality virtue of mobile,
3.Think beyond what we know are conjoint applications today.

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You have questions or new ideas for applications of mobile conjoint?
Contact us or follow us online!
We look forward to hearing from you!