The Rocky Road to Prototype Delivery

SrProjectBlogPost4ImageAgainst what often felt like all odds, my team and I finished a prototype of Senior Care Share — a niche social network for caregivers.  To some extent, it’s like a newborn — alive but ‘sleeping’ most of the time and with only the inkling of a fully animated personality.

There were a few challenges along this birth canal.  Some of the anticipated challenges, such as developing a technically viable solution, adhering to privacy and other legislation and building an engaged user community, have yet to come. Instead, the journey was challenged by:

  1. Defining a clear scope and avoiding the temptation to let it creep
  2. Striving to produce a compelling interface—without having every best practice nailed down
  3. Rapidly learning a tool to bring a concept to life and integrating output from another tool

Keeping the Scope in Check

Fortunately, my concept was an easy sell to anyone who was within or close to my target audience. However, with interest comes ideas and there was plenty. What about a live chat? Online seminars? People ranking products? Giving commercial entities a piece of the action?

Research, such as comparative analysis, audience needs’ assessment and optimal card sort, played an invaluable role in weeding out component contenders and uncovering gaps. These insights helped me set a sane scope of three modules: a Q & A forum (versus a live or open chat); a facilities review; and a section for rewarding participation and nurturing the community.

Striving for a Compelling Interface

As I’m still green at UX and a perfectionist, I scour the Internet for best practices on the shape, position and size of every element when faced with a wire frame task. This dilemma leads to ‘writers’ block’ but fortunately I found a UX mentor who encouraged my early ideas and designs, nudging me forward with a few principles at a time.  I also engaged a team member, initially pegged as an editor, to take UX ownership of one module, which eased the load. His work also gave me new ideas to adapt and iterate across the platform.

Rapidly Learning a New Tool: Axure

My initial plan was to complete wire frame in either Axure or Omnigraffle and then transfer to a specific prototyping tool like Invision.  When my mentor suggested completing it all in Axure, I thought I’d found a ‘shortcut.’  I quickly learned how wrong I was.

I signed up for Axure training videos to help learn this tool, while using it for these critical steps.  My colleague stayed with Omnigraffle and it took a few extra steps to merge the two wire frame types into a unified look and feel.  Fortunately, I was able to cut and paste sections over, which I knew were not perfect but looked blended through most eyes. I also cut corners by opting for the simplest interactive technique: linked pages/widgets, which proved effective to my surprise.

Before this experience, I envisioned a prototype as something more robust with more fully formed content and crystal clear transitions…but time ran out. Like a newborn that’s thrust into the world after nine months to be raised by ‘a village,’ there’s a point where a concept needs to take form and evolve with a community’s input.

Without a forced schedule, ‘my baby’ might be have been internally refined forever, possibly with lame limbs and extra appendages. With a prototype in place, I now need to explain less and the feedback I receive is focused, primarily within scope, and helping this baby grow.

Drilling Down on UX Design Details

Screen Shot 2015-04-02 at 10.55.49 PMI met D., my UX mentor, last Saturday afternoon for two hours in a coffee shop near his home. The pre-agreed purpose of the meeting was to introduce him to my senior project and walk him through my preliminary work on it.

He quickly grasped the project’s concept and purpose to enable caregivers to share proven recommendations and resources with each other. I had various documents on aspects of the project but not surprisingly, he was drawn to the visual materials. D. wanted to start with my personas. He said they were well thought out and looked professional. For future scenarios, he recommended breaking each into smaller chunks, which are easier for a UX designer to reference when developing wireframes.

I showed him process flow diagrams for the Q&A module user path and housing review user path. I also showed him the first wireframe for the Q&A screens.

He reviewed the user flow diagrams in detail and made several suggestions, including:

  • Grouping ‘Yes’ options together and separate from ‘No’ options stemming from the same decision point
  • Limiting rating scale options to three to avoid user fatigue
  • Highlighting the most positive outcomes on the chart with a background tone or colour.
  • Exploring design additions to offset the user’s disappointment in negative areas of the path, such as when they don’t find an immediate answer to their question.

For my wireframes, D suggested limiting horizontal buttons on mobile screens to three and to strive for more white space. He recommended Designing Social Interfaces, by Christian Crumlish and Erin Malone, as a great reference for social solutions. This is particularly helpful as early on I searched for UX resources specific to social and came up dry.

My biggest challenge with senior project is time, as I thought we would have more time this semester to focus on development.  D. suggested shaving time by using Axure for the prototype instead of formatting it in a separate tool, as I’d initially planned.  He also recommended proposing varied stages for the solution to manage breadth of scope and avoid scope creep.

I’m now busy implementing D.’s recommendations, which means making some time-consuming structural adjustments to my user flows.

D. has agreed to meet me again but as his best time is weekends, we can’t meet again until April 11. This is two days before my senior project is due for my semester mark. However, as I’m looking at phases, I consider this the deadline for phase one. I can iterate further for phase two, which is when I will show it as part of a digital show’s student exhibit in early May.

I also heard back from M. with a date to meet with her and a content expert just after the semester deadline for senior project. However, I can apply any advice I glean from this meeting to phase two.

Measuring ROI and Success with Analytics

SONY DSCOur 11th Analytics class was about ‘how’ to measure an online strategy’s return on investment (ROI) — which sounds much simpler than it often is.

Some of the many challenges are:

  • Assessing SEO  – It’s hard to estimate the SEO’s ROI because you can’t estimate the full impact of the long tail. A workaround is to multiply the search volume for top key words by 3.3 (or 30% of the possible clicks) but this is just an estimate.
  • Defining Social Media ROI – You can’t always definitively tie a social conversion to a specific financial metric.  Subsequently, you need to assign a financial value for each social engagement metric by testing and validating social activity. For example, if you generate a $1,000 sale for every 10,000 Twitter re-tweets (RT), each RT is worth $10
  • Attribution Analysis Quandary – There is no definitive answer on which brand/campaign touchpoint ‘wins a visitor over’ and prompts them to complete the desired action (e.g. purchase, sign-up or send an email inquiry). It may be the fourth visit to the website or seeing the item in the store after after reading about it once on the website. As an alternative, Sofia outlined a blend of Media Mix Modeling and Marginal Attribution Analysis. Specifically, this means measuring your baseline, allocating part of the budget to one marketing channel, run tests with/without it and track impact until the value declines. Repeat for each channel until you find the most cost-effective combination with the highest returns.
  • Offline Impacts – Offline promotions and external events (e.g. new competition, scandal, market crash) can skew results. You need to take extra steps to track offline promotions, such as setting-up vanity URLs to track coupons, and find rationale for traffic patterns.
  • App ROI – Apps aren’t cheap to make or run. To measure their ROI, you need to consider the Total Cost of Ownership (TCO), including development and ongoing operation costs, which can fluctuate over time.

So while measurement is a finite science, measuring online ROI is part art because it requires some subjective decisions.

Sofia provided comprehensive best practices and a number of formulas, which I think will give me long-term value — or ROI on the cost of her college course. However each campaign and scenario is different and there is no ‘cookie cutter’ solution.

What does this mean to me?

For example, the business model for my senior project generates revenue by selling online advertising. If I need 10,000 page views per month to sell a $1,000 ad but I currently only get 9,000 views per month, I might use a keyword upgrade to drive traffic to my site. The resulting formulas might look like:

For SEO Revenue:

18,000 (people searching for my keywords) X 10% (average success rate, where I define success as clickthroughs with page views) = 1,800 new page views

$1,000/1,800 = $0.50 value per page view

For ROI:

$1,000 (July SEO Ad Revenue)/$200 (Contractor to identify keywords and incorporate them into site) = ROI of 5

Illustration Source: Lisa Solonynko /Haml via Morgue File.

Connections Prompt Plan Adjustments


It’s week two of the mentor process journey and I’ve finally heard from all my prospects.

Unfortunately, ′L,′ a subject matter expert (SME) in the topic and audience of my senior project, won’t be able to meet me until she completes an all-consuming major office move in mid-April. I will follow through and eventually meet her but it won’t be until after this term ends. As a back-up, I’m reaching out to ‘N,’ another SME who oversees communications and stakeholder relations for one of Ontario’s CCAC and is a former employer.

I had my first meeting with ′M′ on Tuesday morning. In the high level agenda I sent the Sunday before, I outlined the overall purpose of the meeting as to get a preliminary overview of her background and transition to digital. I also expressed an interest in learning about recommendations for boosting my analytics knowledge/skills.  M’s reputation precedes her and so as predicted, she was warm, congenial and professional. (Off the top, she inquired about my professor, who she knows, and thought teaching and yoga were great fits.)

M said her transition to digital was back in 1996 (earlier than I initially thought). In the early days, she explained how she made sketches with buttons and draft screens to outline to developers how she wanted a solution to look and act. Today, she works for a global agency with very specialized divisions and experts to handle those details, leaving her to oversee clients and accounts.

We talked about what I see as the challenge of being a generalist in a competitive world where experts are held in high esteem. I explained that in the PR world (where I cut my teeth), you had to master strategy to execution across the board. Ideally, you also had to keep a hand in tactics, even as you rose in seniority. M suggested that large teams with specialists/experts are great but also expensive. In contrast, smaller teams with more generalists are more cost efficient. M prefers them as you get fewer but more committed people on the team. She sees account teams shift between both types, as accounts evolve and budgets often need to scale back.

I suggested that I’m particularly interested in content strategy but also want to work toward roles where I’m engaged in developing digital strategy — or as M described it the “why” of digital. M deemed either goal feasible and saw them as integrated. She stressed the value of an effective CMS and content strategy in the projects she manages for financial service clients, as well as a large retailer.

Specifically, M said an effective content strategist can:

  • Identify and reuse consistent content across platforms
  • Develop a foundational content library with just the ‘right’ quantity of consistent assets for effective use across platforms.
  • Manage the ‘how’ components of the customer’s journey along a smooth path to purchase.

She also asked me about Centennial’s program, which gave me the opportunity to weave in my senior project, along with other highlights.  M quickly grasped the value of my project and appeared interested. She asked me if I had a field placement yet and proactively volunteered to look into options at her agency but cautioned there may be an age bias. She wants to introduce me to one of her content strategists, who can give me more insight and look at my work. As for analytics, she admits to only scratching the surface but may be able to connect me with an expert who can offer more in-depth advice.

As per action items discussed, a sent her a link to an overview of Centennial’s program, field placement dates, my available meeting times and resume. I did not expect her to express an interest in me as an intern at this stage but it’s wonderful that she did. So I’ll do my best to follow through and see what happens.

I was also recently in touch with ‘MH’ a web designer, who I’ve hired and referred on several occasions. When he learned I was studying interactive media management, he suggested we meet.  So although MH was not part of my original mentor plan, I think meeting with him will complement it.

Illustration Source: Godidwlr via Morgue File.

Analytics Success Lies in Digesting Related Segments


Our 10th analytics class focused on how to best analyze and understand data.

The top-level message I came away with is a data metric shouldn’t be evaluated in isolation, which is meaningless.  For example, knowing only that users spent an average of five minutes on a page offers no insight to validate or adjust your strategy. It may mean only users from a paid referral on one day of the year spent this much time on the site and on other days or referrals from organic/social/direct bounced after 10 seconds.  This would call for course corrections to improve results but without looking at the ‘big picture,’ these issues might go undetected.

Specifically, you should assess data metrics:

  • In context with the organization’s goals, what competitors are doing, industry information, internal initiatives, external events/trends…
  • Ideally in related segments, such as: referral sources (paid/social/organic/direct), days of the week (weekends and weekdays), times of the day or platforms used to access a site.

Sofia cautioned against comparing unrelated data metrics, such as tablet use with social referrals or creating compound or ‘super’ combinations like Alexa page rank with inbound links.

I found it interesting to note that higher numeric data (e.g. 10,000 contact page exits on every 100,00 visits), might deliver exactly the same statistical significance as smaller data (e.g. 1,000 contact page exits out of 10,000 visits) but is more effective when expressed as a clear outcome, such as 10%, versus a ‘muddy’ ratio like 10,000:100,000 or 1,000:10,000. However, I think higher numbers do strengthen a metric’s value.

For the class exercise, we re-examined the metrics set for our senior project, identified segments to be assessed and ways they might be visually depicted.

For my project, here are some KPI segmentation and visualization options:

  • Percentage of conversions by each referral source, such as social (fb, Twitter, Reddit), organic, paid and direct in a specific month, compared to non-conversions by referral sources in the same month.  (Visual depiction – 2 pie charts or a bar graph)
  • Specific Senior Care Share modules engaged in a specific month by referral sources. (Visual depiction – segmented bar chart)
  • Page views for a specific month, segmented by weekdays versus weekends. (Visual depiction – segmented bar chart, pie chart or even infographic with other metrics)
  • Page views in a specific month, segmented by referral sources. (Visual depiction – segmented bar chart)

However, as with all analysis, you should:

  • Find out what’s happening across the organization, such as other initiatives; business changes or help desk calls.
  • Consider external events that might impact data, such as holidays, market trends or even weather/power outages.
  • Possibly do surveys, click density analysis or other research….

….to get the full picture and extract maximum value from your data.

Illustration Source: Haml via Morgue File.

First Foray into My Mentorship Strategy

Untitled design

I sent out three meeting requests to three prospective mentors in the past week (on March 11, 12 and 13), through three distinct approaches/channels: a referral, a cold call and a continued LinkedIn conversation.

  • The first was a referral request a friend sent via LinkedIn on my behalf to ‘M,’ a digital sector veteran, who happens to be her cousin.
  • The second was a cold call email to ‘L,’ a subject matter expert in caregivers, my senior project’s target audience.
  • The third was shifting a LinkedIn conversation I had previously began with ‘D,’ a UX designer, to the meeting ‘ask’ stage.

Then, I had a nail-biting week waiting to see if any of these prospects would respond and for awhile, it looked somewhat grim. As life often throws off the best laid plans, M took a week to response because she was away in Salt Lake City. After waiting three business days for L, I followed up by phone, discovered she’s on vacation until March 23 and left a voice message. D responded after four days.

So I now have my first meetings tentatively set with M for this coming Tuesday (March 24) and with D on Saturday, March 28. The later first meeting with D gives me time to work up draft wireframes of my senior project, which he previously agreed to look at.

In the interim, I’m planning for these meetings and learning what I can about these individuals.

M’s facebook profile tells me she’s a skier and a mom with two little girls but I can’t see into much of her recent life, as she wisely tightened her privacy settings last spring. Her LinkedIn profile seems to show her major transition into digital came in 2000, about six years into her career, when she worked in the Toronto office of a US digital agency. She also has strong staying power, having stayed a minimum of two years in all her roles and nine in her current role as an Account Director for a global agency.

I’ve committed to send her an overview (i.e. agenda/POAD) on the weekend. One of the first things I’d like to learn is how she made the leap from ‘intense’ hard copy government/financial services account management to digital. I think it may also be safe to add enquiries about tools/training to boost my analytic skills to the agenda for this first meeting.

As for D’s background, he’s pretty quiet on social media. From what I can tell, he has a LinkedIn profile and Twitter account, which he’s set aside for a couple of months. Still, his tweets tell me he’s interested in classical music, Toronto trivia and its congestion challenges, plus innovative apps, designs and data visualizations.  I re-tweeted his post on a data visualization project from MIT to help build support and because it was interesting. His background is a mix but I really want to learn about best practices in UX to incorporate in my senior project and elsewhere.

Telling the Visual Story of Data

Screen Shot 2015-03-19 at 4.45.19 PMIn our ninth analytics class, we focused on data visualization, which is used to visually depict a project’s results or analytics.  Seeing a visual representation of data helps people to understand its meaning. It also makes the information more memorable as it helps to tell a story.

Data visualization is particularly effective for conveying a project’s ongoing results, particularly KPIs, to stakeholders and showing them where they need to pay attention or course correct.

There is a huge variety of data visualization formats you can use to tell the visual story of data — from conventional bar and line graphs to golden ratio depleting charts and intricate infographics.  Fortunately, there are a range of tools available for creating them. We took some time to experiment with Tableau. I think this is a really versatile tool but it comes with a steep learning curve.

I think it would be really useful for showing KPIs for my senior project, such as conversion rates from various social and organic referrals, possibly in a pie chart, to show which are most effective.  I might also use a bar graphic to compare the time users spent on each of the niche social media network’s pages.

However, in the interim, I wanted to try this tool on existing data. Last summer, I managed a youth shelter’s eight week fundraising campaign that was heavily promoted on social media. I used a tool called ‘SumAll’ to track Twitter results for this campaign and exported them into an excel sheet. I imported this into Tableau and experimented with the tool.

One challenge was getting the weeks to display from oldest to latest. I re-labelled the weeks from a ‘week of Mon 08 Sept’ format to ‘week 8 (08 Sept)’ format in Excel to make the sequencing clearer. Latterly, I also found that in some views, you can click on the Dimension value to reverse the order.

There is much more formatting I need to do but, the above bar graphic is a start at showing the stats from this campaign. In this example, I used a side-by-side bar chart format to show the growing momentum of three measures (tweets, mentions reach and retweets reach) over the last six weeks of the campaign leading up to a September 6 event date. I filtered out the first two weeks, as the Mentions and Retweet reaches were minimal during this early part of the campaign.

A graph like this could be used to demonstrate to a stakeholder the value of a campaign of several weeks, versus expecting comparable results with a one or two week period (which some might think adequate).

I need to learn much more — but can’t even begin to visually imagine the data I must absorb to proficiently use these tools.