Tag Archives: Real Time

Marktforschung.de showcase: quick summaries of 5 talks from German research companies #IIeX 

Live notetaking at #IIeX in amsterdam. Any errors or bad jokes are my own.

Realtime research in the digital age by Holger Geibler, YouGov

  • What do people think about research – political polls, representativeness, big data, how slow research is
  • What is real time research – can be from NOW to one week to complete, real time is related to historical timelines
  • We need to be where the respondent is, need to ask less, engage more, connect more – keep surveys under 16 minutes and avoid dropouts, remember than mobile surveys take 10 to 20% longer to complete
  • Let clients access data in real-time but tell them its preliminary, train clients and consultants to use a dashboard, have dashboards that switch between weighted and unweighted data

Reaching millennials via mobile apps and getting superior survey data through gamification by Jonathan Kurfess, Appinio

  • People want to share opinions even if you don’t want to hear it or don’t agree with it
  • #MRX is struggling to adapt to millennial user behaviour – longer questions are good for researchers but not for respondents
  • Money is not a sufficient incentive
  • An app that allows people to interact with each other, compare opinions, create polls and gather opinions is very engaging
  • Ensure questionnaires are mobile optimized

Germans got humor? Only if it’s efficient by Oliver Switzer, September Strategy and Foreshung

  • Do purchasers have emotions about steel? Of course they do. Emotion is involved with everything. Emotion isn’t just anger or disgust.
  • Germans like to be funny not just measure efficiency. Being funner is teh container, the vehicle.
  • Evolution made humans emotional, we used to be emotional about safety and now we’re emotional about product packaging
  • Our consciousness is there just to get orders from our subconscious
  • You can apply KPIs to emotions
  • Our brains is very activated when we see brand names we recognize versus made up brands
  • Our heart beats at different rates for different emotions, fear, trust, anger, skepticism, stress, relelvant, attraction, closeness [ask to see the charts, quite cool]
  • You can feel trust and skeptisism at the same time
  • [never occured to me to treat emotions as KPIs]

Implicit influence explained: how to define and measure the unconscious effects of words and images by Jonathan Mall, Neuro-Flash

  • People who though a zoo is safe even though a gorilla was supposed to have escaped assumed zoo handled the situation properly, these people read a certain type of newspaper
  • Priming means setting you up to feel something, lead to a preference, lead to a purchase
  • We could connect a gorilla to chocolate in a commercials, people who like one will like the other
  • You can’t simply look at one aspect of an ad, you need conscious and unconscious effects
  • people will say something looks good but their unconscious might be noticing the pretty lady on the side, if there is too much attention in the wrong place, then you have an issue
  • The four Ps: primal, priming, preference, purchase

Understanding emotion decision drivers using brain scans by Kai Muller, The Neuromarketing Labs

  • People don’t think how they feel, and they don’t say what they think and they don’t do what they way
  • We can map disgust in the brain as well as other emotions
  • Funny ads engage the heart and the min
  • Annoying ads evoke negative emotions and high attention
  • Positive and negative mentions can impact sales an this is measureable 
  • Were able to match the results of the ad concept with the finished ad

This year’s overused image was the iceberg, two of which appeared in this track. And the second iceberg speaker chuckled over it as his slide appeared. Sorry Homer’s brain, you’re last year. 🙂

 

Viz-Fest Day 3 – Data Visualization and Dashboards #MRX #NewMR

Live note-taking from Viz-Fest, November 2016. Any errors are my own.

Tom Schlak, E-Tabs, Data Viz for the Visually Impaired

  • Most important information visually displayed to achieve objectives and can be monitored at a glance, Charts, graphs, icons, mostly visual
  • How can data visualization be made accessible to someone who is blind
  • Viewing a musical score versus listening to a score, “seeing” a chart can’t be replicated
  • What are the alternatives, Maybe use speech assistive technologies
  • 5% of the world has some visual impairment, 11.5% for people over 50 years of age
  • Good designs benefit everyone even fully sighted users
  • Text and fonts – font size on screen nothing less than 12 to 16 points, Helvetica, Arial
  • Font styles more complicated, must consider legibility and readability, legibility is individual characters, readability is overall appearance including spacing and formatting, good fonts have better spacing, less fancy script, less detailed, filled lettering, less heavy, less thin, less serif, Use display fonts carefully because they aren’t accessible
  • Contrast – sometimes corporate colours are a problem but readability must come first, use an online tool like adobe color CC, let’s you choose colors that match your target color or complement, matters for typography too, forget white on yellow, yellow on red, grey on green
  • Clean user experience – avoid cluttered dashboard, eliminate non-data pixels like background images and watermarks, large logos, etc, think about data-to-ink ratio, avoid dark gridlines or over-labeling, don’t fill up backgrounds just because you can, gradients of grey can be difficult to differentiate, use colors like red and green appropriately, only highlight what must be highlighted, flatten the design by removing shadows and 3D elements that make a flat image look shiny
  • Eg Microsoft logo went from shiny colored circle to four simple boxes
  • What about color deficiency, blindness – 8% of men and .5% of women have deficiencies, the worst forms can distinguish 20 hues but people without can see about 100 hues
  • Avoid red green charts as this can hide the data
  • Traffic light indicators are common, red green yellow, and should be used with caution, consider using shapes as well, arrows, checkmarks, faces, and maybe use them only for one state, just the positives or just the negatives
  • Use cross hatching or fill patterns so you don’t rely just on color
  • Use Colblinder online to test colors, light colors can lose their differentiation, text labels will help, try also ColorBrewer online
  • Much of this applies to good design anyway
  • Is it still beautiful is someone can’t see it? Communicate to everyone

Marta Blankenberger, redaviZ, Data Driven Infographics

  • Infographic is visual representation of data to share information quickly and clearly
  • Need to think about position, size, shape, color
  • Icons help us understand and interpret information
  • Combine a doughnut chart with an icon, or combine a bubble chart with a map behind it
  • Masking – cover or uncover part of a chart but placing a shape in front of it, try that with charts, grey out a section or tone down the color of part of it
  • Combine icons, put stars over circles to mask different areas
  • Try using an arrow as the bars in a bar chart, just paste the image into the bar
  • Try putting a grey bar behind the bars to represent the maximum of the bar
  • Try using copied icons as the bar (e.g., 5 stars, 8 stars, 3 stars), you can use masking to turn 5 out of 10 into 5.3 out of 10
  • Use conditional formatting of data labels, change the color/shape/size of labels if they are less than a specified value, or put checkmarks as the data point
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