ArashLari Week 11

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Development Terms

  • Read: The Data-Driven Design Era in Professional Web Design
  • By: Lassi A. Liikkanen

This article introduced me to many terms I hadn't heard in respect to design before, but the author did a good job of explaining them so I didn't need to consult outside sources very much. I had heard of most of the analytics products before but there were a few I wasn't familiar with. The following terms are defined according to my understanding after reading their definitions.

  • Generative Design
    • A development process that is akin to evolution. The process is to set out design goals and an initial schema, and then go through several permutations of variation until arriving at the best option. (Flake, 1998)
  • Heat Maps
    • Heat maps in regards to design are basically the same as heat maps in terms of population movement. It is a visual representation of where the average users cursor hovers and clicks and for what amount of time. (Liikkanen, 2017)
  • User Screen Recordings
    • A user screen recording is a literal video of the individual user's screen during their session on the application. (Liikkanen, 2017)
  • A/B Tests
    • A controlled test with two variants. This is used to compare different potential design layouts and choose the most effective elements from them. (Kohavi, Longbotham 2015)
  • Behavioural Analytics
    • The contextual information around a users session on an application, including information such as the usage log, click-stream data, average time spent on each page, etc. (Liikkanen, 2017)
  • Assistive Tools
    • Tools that make tasks easier for humans but still require a human interaction. (Liikkanen, 2017)
  • Agentive Tools
    • Tools that do tasks for humans and eliminate the need for the humans to do anything related to the task. (Liikkanen, 2017)
  • Net Promoter Score
    • A measure from -100 to 100 of a customer's willingness to refer a product or company to a peer. (NetPromoter, 2017)
  • KISSmetrics
    • A behavioural analytics service that provides automated tools for interpreting data from customers. (Kissmetrics, 2017).
  • IBM TeaLeaf
    • A company that IBM acquired that is focused on bettering customer experience through behavioural analytics. (IBM, 2017).

Outline and Presentation

File:Data Driven Design.zip

What is Data Driven Design?

  • Traditionally, products were designed by the designers intuition and opinion
    • This is because collecting information about user activity has been difficult until recently
  • The rise of technology and internet based services has led to evidenced-based design
    • Companies and developers want to know that their intended users will be able to easily use their service before it affects sales
  • Designing based off of results empirical user evidence is called data driven design
    • There are assistive and agentive generative tools to help creative tasks
      • A generative design process basically means designing and redesigning based on how the previous iteration was received
    • It’s basically an assortment of tools at the disposal of the designers and the developers that they can use in a multitude of ways to gauge how effective their design is.
    • The basic idea of this design philosophy is to collect data, combine it with other data, and analyze it for implementation in the final design

Data Driven Design of Web Services

  • Web interaction design is a field that utilizes data design driven solutions frequently
    • Major internet companies often build their own experiment-management platforms so they can run many different experiments in parallel with automation
  • Data-collection can be separated into two types of solutions: Active and Passive
    • Active data collection is reliant on user input, and as such it’s considered qualitative
      • It doesn’t really fit the mold of DDD very well if the scale is large
      • Surveys are often plagued with many issues such as reluctance to participate and low quality answers that don’t provide very much insight
      • In smaller cases it is very useful, such as using an online focus group to get detailed reactions and responses
        • This is costly, which is why large corporations don’t often do this
    • Passive data collection, or passive tracking is any kind of recording of user activity
      • Screen recordings, heat maps, experiment management, and descriptive behavioral analytics are some passive tracking tools
        • Screen recordings are full recordings of the users screen for later analysis.
        • Provides a very detailed view and a lot of useful implementation
        • However, raises privacy and ethical concerns and can’t really be automated to gain insight
    • Heat maps are a way to visualize the most frequently clicked on and hovered on spots of a page
      • It isn’t always very clear because some pages might be context specific, but it still can provide enough information to help optimize the design of the page
    • Experiment management is basically having 2 or more types of designs be tested on to find which features and design choices should be kept or removed
      • It allows developers to find fail new ideas quickly so they don’t have to waste time with subpar designs
      • They can be automated but their shortcoming is the numbers aren’t always that insightful
    • Behavioral analytics are the precursor to all current DDD solutions
      • It’s all the contextual data related to the visit, such as the amount of time spent and on what pages, what elements were clicked and in what order, etc.
      • This information is more useful for business and marketing decisions rather than design decisions.
        • Many companies offer analytics solutions for developers
          • Google is the biggest by far, but there are others such as Adobe Analytics, KISSMetrics, and IBM Tealeaf

Conclusion

  • Data driven design provides designers a strong incentive to adopt a hypothesis-driven approach to design research
    • Having a clear hypothesis is important as it will affect the way one interprets data and identify which results are the most significant
    • The age of Data Driven Design draws heavily upon designer moral, integrity, and candor.
      • Ethics of how data is collected and used is very important, and consent is key in ethical data acquisition.
  • The future of data driven design will be with tools that couple seamlessly with design processes, be adaptive to change, and show maturity in addressing ethical questions.
    • Designers will embrace more quantitative data as tools that allow for scalability become available
    • Design will introduce assistive and agentive tools that do things with us and for us
  • What will we use for our project?
    • We won’t use any of the passive tools directly
      • Although useful, we do not have the means to get enough different users to get fruitful information using these methods
      • Although we might implement experiment-management within our own small group and see what we collectively thinks works best
    • We will be using active data collection, and ask our fellow classmates to browse our site and give us feedback as they use it
      • This level of interactivity with the end-user provide useful insight

Electronic Notebook

Our group met thursday after class to schedule a time to meet over the weekend. Unfortunately we didn't meet in person over the weekend due to scheduling conflicts. We updated each other over the phone and Nicole and I went over what the article and presentation where about over the weekend and worked on it digitally on monday night. I also kept in contact with Hayden and he and Mary filled me in on their part and helped Nicole and I out for the presentation.

Acknowledgements

  • I worked with my homework partners Hayden, Mary, and Nicole. We mostly communicated via phone call or text message.

While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source. ArashLari (talk) 01:21, 14 November 2017 (PST)

References

Links

Arash Lari

BIOL/CMSI 367-01: Biological Databases Fall 2017

Assignments


Journal Entries:

Shared Journals:

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