Measuring Quality

At the end of last year, Cassie raised the question of ‘how to measure quality?’ on our metrics mailing list, which is an excellent question. And like the best questions, I come back to it often. So, I figured it needed a blog post.

There are a bunch of tactical opportunities to measure quality in various processes, like the QA data you might extract from a production line for example. And while those details interest me, this thought process always bubbles up to the aggregate concept: what’s a consistent measure of quality across any product or service?

I have a short answer, but while you’re here I’ll walk you through how I get there. Including some examples of things I think are of high quality.

One of the reasons this question is interesting, is that it’s quite common to divide up data into quantitative and qualitative buckets. Often splitting the crisp metrics we use as our KPIs from the things we think indicate real quality. But, if you care about quality, and you operate at ‘scale’, you need a quantitative measure of quality.

On that note, in a small business or on a small project, the quality feedback loop is often direct to the people making design decisions that affect quality. You can look at the customers in your bakery and get a feel for the quality of your business and products. This is why small initiatives are sometimes immensely high in quality but then deteriorate as they attempt to replicate and scale what they do.

What I’m thinking about here is how to measure quality at scale.

Some things of quality, IMHO:

axeThis axe is wonderful. As my office is also my workshop, this axe is usually near to hand. It will soon be hung on the wall. Not because I am preparing for the zombie apocalypse, but because it is both useful as a tool, and as a visual reminder about what it means to build quality products. If this ramble of mine isn’t enough of a distraction, watch Why Values are Important to understand how this axe relates to measures of quality especially in product design.

toasterThis toaster is also wonderful. We’ve had this toaster more than 10 years now, and it works perfectly. If it were to break, I can get the parts locally and service it myself (it’s deliberately built to last and be repaired). It was an expensive initial purchase, but works out cheap in the long run. If it broke today, I would fix it. If I couldn’t fix it for some extreme reason, I would buy the same toaster in a blink. It is a high quality product.

coffeeThis is the espresso coffee I drink every day. Not the tin, it’s another brand that comes in a bag. It has been consistently good for a couple of years until the last two weeks when the grind has been finer than usual and it keeps blocking the machine. It was a high-quality product in my mind, until recently. I’ll let another batch pass through the supermarket shelves and try it again. Otherwise I’ll switch.

spatulaThis spatula looks like a novelty product and typically I don’t think very much of novelty products in place of useful tools, but it’s actually a high quality product. It was a gift, and we use it a lot and it just works really well. If it went missing today, I’d want to get another one the same. Saying that, it’s surprisingly expensive for a spatula. I’ve only just looked at the price, as a result of writing this. I think I’d pay that price though.

All of those examples are relatively expensive products within their respective categories, but price is not the measure of quality, even if price sometimes correlates with quality. I’ll get on to this.

How about things of quality that are not expensive in this way?

What is quality music, or art, or literature to you? Is it something new you enjoy today? Or something you enjoyed several years ago? I personally think it’s the combination of those two things. And I posit that you can’t know the real quality of something until enough time has passed. Though ‘enough time’ varies by product.

Ten years ago, I thought all the music I listened to was of high quality. Re-listening today, I think some of it was high-quality. As an exercise, listen to some music you haven’t for a while, and think about which tracks you enjoy for the nostalgia and which you enjoy for the music itself.

In the past, we had to rely on sales as a measure of the popularity of music. But like price, sales doesn’t always relate to quality. Initial popularity indicates potential quality, but not quality in itself (or it indicates manipulation of the audience via effective marketing). Though there are debates around streaming music services and artist payment, we do now have data points about the ongoing value of music beyond the initial parting of listener from cash. I think this can do interesting things for the quality of music overall. And in particular that the future is bleak for album filler tracks when you’re paid per stream.

Another question I enjoy thinking about is why over the centuries, some art has lasting value, and other art doesn’t. But I think I’ve taken enough tangents for now.

So, to join this up.

My view is that quality is reflected by loyalty. And for most products and services, end-user loyalty is something you can measure and optimize for.

Loyalty comes from building things that both last, and continue to be used.

Every other measurable detail about quality adds up to that.

Reducing the defect rate of component X by 10% doesn’t matter unless it impacts on the end-user loyalty.

It’s harder to measure, but this is true even for things which are specifically designed not to last. In particular, “experiences”; a once-in-a-lifetime trip, a festival, a learning experience, etc, etc. If these experiences are of high quality, the memory lasts and you re-live them and re-use them many times over. You tell stories of the experience and you refer your friends. You are loyal to the experience.

Bringing this back to work.

For MoFo colleagues reading this, our organization goals this year already point us towards Quality. We use the industry term ‘Retention’. We have targets for Retention Rates and Ongoing Teaching Activity (i.e. retained teachers). And while the word ‘retention’ sounds a bit cold and business like, it’s really the same thing as measuring ‘loyalty’. I like the word loyalty but people have different views about it (in particular whether it’s earned or expected).

This overarching theme also aligns nicely with the overall Mozilla goal of increasing the ‘number of long term relationships’ we hold with our users.

Language is interesting though. Thinking about a ‘20% user loyalty rate’ 7 days after sign-up focuses my mind slightly differently than a ‘20% retention rate’. ‘Retention’ can sound a bit too much like ‘detention’, which might explain why so many businesses strive for consumer ‘lock-in’ as part of their business model.

Talking to OpenMatt about this recently he put a better MoFo frame on it than loyalty; Retention is a measure of how much people love what we’re doing. When we set goals for increasing retention rate, we are committing to building things people love so much that they keep coming back for more.

In summary:

  • You can measure quality by measuring loyalty
  • I’m happy retention rates are one of our KPIs this year

My next post will look more specifically about the numbers and how retention rates factor into product growth.

And I’ll try not to make it another essay. 😉

2015 Mozilla Foundation Metrics Strategy(ish) & Roadmap(ish)

I wrote a version of this strategy in January but hadn’t published it as I was trying to remove those ‘ish‘s from the title. But the ‘ish’ is actually a big part of my day-to-day work, so this version embraces the ‘ish’.

MoFo Metrics Measures of Success:

These are ironically, more qualitative than quantitative.

  1. Every contributor (paid or volunteer) knows at any given time what number they (or we) are trying to move, where that number is right now, and how they hope to influence it.
  2. We consider metrics (i.e. measures of success) before, during and after after each project.
  3. We articulate the stories behind the metrics we aim for, so their relevance isn’t lost in the numbers.
  4. A/B style testing practice has a significant impact on the performance of our ‘mass audience’ products and campaigns.

1. Every contributor (paid or volunteer) knows at any given time what number they (or we) are trying to move, where that number is right now, and how they hope to influence it.

  • “Every” is ambitious, but it sets the right tone.
  • This includes:
    • Public dashboards, like those at https://metrics.webmaker.org
    • Updates and storytelling throughout the year
    • Building feedback loops between the process, the work and the results (the impact)

2. We consider metrics (i.e. measures of success) before, during and after after each piece of work.

  • This requires close integration into our organizational planning process
  • This work is underway, but it will take time (and many repetitions) before it becomes habit

3. We articulate the stories behind the metrics we aim for, so their relevance isn’t lost in the numbers.

  • The numbers should be for navigation, rather than fuel

4. A/B style testing practice has a significant impact on the performance of our ‘mass audience’ products and campaigns.

  • This is the growth hacking part of the plan
  • We’ve had some successes (e.g. Webmaker and Fundraising)
  • This needs to become a continuous process

Those are my goals.

In many cases, the ultimate measure of success is when this work is done by the team rather than by me for the team.

We’re working on Process AND Culture

Process and culture feed off of and influence each other. Processes must suit the culture being cultivated. A data driven culture can blinker creativity – it doesn’t have to, but it can. And a culture that doesn’t care for data, won’t care for processes related to data. This strategy aims to balance the needs of both.

A roadmap?

I tried to write one, but basically this strategy will respond to the roadmaps of each of the MoFo teams.

So, what does Metrics work look like in 2015?

  • Building the tools and dashboards to provide the organisational visibility we need for our KPIs
  • ‘Instrumenting’ our products so that we can accurately measure how they are being used
  • Running Optimization experiments against high profile campaigns
  • Running training and support for Google Analytics, Optimizely, and other tools
  • Running project level reporting and analysis to support iterative development
  • Consulting to the Community Development Team to plan experimental initiatives

Plus: supporting teams to implement our data practices, and of course, the unknown unknowns.

…ish

Webmaking in the UK, and face-to-face events

One of this week’s conversations was with Nesta, about Webmaker usage within the UK and whether or not we have data to support the theory that face-t0-face events have an impact getting people involved in making on the web. These are two topics that interest me greatly.

I’m basically copying some of my notes into blog form so that the conversation isn’t confined to a few in-boxes.

And the TL;DR is our data represents what we’ve done, rather than any universal truth.

Our current data would support the hypothesis that face-to-face time is important for learning, but that would simply be because that’s how our program has been designed to date. In other words, our Webmaker tools were designed primarily for use in face-to-face events, which meant that adoption by ‘self-learners’ online is low because their is little guidance or motivation to play with our tools on your own. This year we’re making a stronger push on developing tools that can be used remotely, alongside our work on volunteer led face-to-face events. This will lead to a less biased overall data set in the future where we can begin to properly explore the impact on making and learning for people who do or don’t attend face-to-face events at various stages in their learning experience. In particular I’m keen to understand what factors help people transition from learners, to mentoring and supporting their peers.

I also took a quick look at the aggregate Google Analytics location data for the UK audience which I hadn’t done before and which re-enforces the point above.

Screen Shot 2015-01-30 at 11.14.29

Above: Traffic to Webmaker (loosely indicating an interest in the topic) is roughly distributed like a population map of the UK. This is what I expect to see of most location data.

Screen Shot 2015-01-30 at 11.17.25

Above: However, if you look at the locations of visitors who make something, there are lots of clusters around the UK and London is equaled by many other cities.

To-date, usage of the Webmaker tools has been driven by those who are using the tools to teach the web (i.e. Webmaker Mentors). But we also know there are large numbers of people who find Webmaker outside of the face-to-face event scenarios who need a better route into Webmaker’s offering.

The good news is that this year’s plans look after both sets of potential learners.

The week ahead: 19 Jan 2015

January

If all goes to plan, I will:

  • Write a daily working process
  • Use a public todo list, and make it work
  • Catch up on more email from time off
  • Ship V1 of Webmaker Metrics retention dashboard
  • Work out a plan for aligning metrics work with dev team heartbeats
  • Don’t let the immediate todo list get in the way of planning long term processes
  • Invest time in working open
  • Wrestle with multiple todo list systems until they (or I) work together nicely
  • Survive a 5 day week (it’s been a while)
  • Write up final testing blog posts from EOY before those tests are forgotten
  • Book data practices kick-off meetings with all teams

To try and solve some of the process challenges, I’ve gone back to a tool I built a couple of years ago (Done by When) and I’m breaking it a little bit to make it useful to me again. This might end up being an evening time project to learn about some of the new tech the Webmaker team are using this year (particularly rewriting the front end with React). I find it useful to have a side-project to use as a playground for learning new things.

Anyway, have a great week. I’ll try and write up some more notes at the end.

“Conclusions”

Mile long string of baloons (6034077499)

  • Removing the second sentence increases conversion rate (hypothesis = simplicity is good).
  • The button text ‘Go!’ increased the conversion rate.
  • Both variations on the headline increased conversion rate, but ‘Welcome to Webmaker’ performed the best.
  • We should remove the bullet points on this landing page.
  • The log-in option is useful on the page, even for a cold audience who we assume do not have accounts already.
  • Repeating the ask ‘Sign-up for Webmaker’ at the end of the copy, even when it duplicates the heading immediately above, is useful. Even at the expense of making the copy longer.
  • The button text ‘Create an account’ works better than ‘Sign up for Webmaker’ even when the headline and CTA in the copy are ‘Sign up for Webmaker’.
  • These two headlines are equivalent. In the absence of other data we should keep the version which includes the brand name, as it adds one further ‘brand impression’ to the user journey.
  • The existing blue background color is the best variant, given the rest of the page right now.

The Webmaker Testing Hub

If any of those “conclusions” sound interesting to you, you’ll probably want to read more about them on the Webmaker Testing Hub (it’s a fancy name for a list on a wiki).

This is where we’ll try and share the results of any test we run, and document the tests currently running.

And why that image for this blog post?

Because blog posts need and image, and this song came on as I was writing it. And I’m sure it’s a song about statistical significance, or counting, or something…

Something special within ‘Hack the snippet’

Here are a couple of notes about ‘Hack the snippet‘ that I wanted to make sure got documented.

  1. It significantly changed peoples’ predisposition to Webmaker before they arrived on the site
  2. Its ‘post-interaction’ click-through-rate was equivalent to most one-click snippets

Behind these observations, something special was happening in ‘Hack the snippet’. I can’t tell you exactly what it was that had the end-effect, but it’s worth remembering the effect.

1. It ‘warmed people up’ to Webmaker

  • The ‘Hack the snippet’ snippet
    • was shown to the same audience (Firefox users) as eight other snippet variations we ran during the campaign
    • had the same % of users click through to the landing page
    • had the same on-site experience on webmaker.org as all the other snippet variations we tested (the same landing page, sign-up ask etc)
  • But when people who had interacted with ‘Hack the snippet’ landed on the website, they were more than three times as likely to signup for a webmaker account

Same audience, same engagement rate, same ask… but triple the conversion rate (most regular snippet traffic converted ~2%, ‘Hack the snippet’ traffic converted ~7%).

Something within that experience (and likely the overall quality of it) makes the Webmaker proposition more appealing to people who ‘hacked the snippet’. It could be one of many things: the simplicity, the guided learning, the feeling of power from editing the Firefox start page, the particular phrasing of the copy or many of the subtle design decisions. But whatever it was, it worked.

We need to keep looking for ways to recreate this.

Not everything we do going forwards needs to be a ‘Hack the snippet’ snippet (you can see how much time and effort went into that in the bug).

But when we think about these new-user experiences, we have a benchmark to compare things too. We know how much impact these things can have when all the parts align.

2. The ‘post-interaction’ CTR was as good as most one-click snippets

This is a quicker note:

  • Despite the steps involved in completing the ‘Hack the snippet’ on page activity, the same total number of people clicked through when compared to a standard ‘one-click’ snippet.
  • We got the same % of the audience to engage with a learning activity and then click through to the webmaker site, as we usually get just giving them a link directly to Webmaker
    • This defies most “best practice” about minimizing number of clicks

Again, this doesn’t give us an immediate thing we can repeat, but it gives us a benchmark to build on.

Who’s teaching this thing anyway?

This is an idea for Webmaker teacher dashboards, and some thoughts on metadata related to learning analytics

This post stems from a few conversations around metrics for Webmaker and learning analytics and it proposes some potential product features which need to be challenged and considered. I’m sharing the idea here as it’s easy to pass this around, but this is very much just an idea right now.

For context, I’m approaching this from a metrics perspective, but I’m trying to solve the data gathering challenge by adding value for our users rather than asking them to do any extra work.

These are the kind of questions I want us to be able to answer

and that can inform future decision making in a positive way…

  • How many people using Webmaker tools are mentors, students, or others?
  • Do mentors teach many times?
  • How many learners go on to become mentors?
  • What size groups do mentors typically work with?
  • How many mentors teach once, and then never again? (their feedback would be very useful)
  • How many learners come back to Webmaker tools several days after a lesson?
  • Which partnership programme reached the greatest number of learners?

And the particularly tricky area…

  • What data points show developing competencies in Web Literacy?

Flexible and organic data points to suit the Webmaker ecosystem

The Webmaker suite of tools are very open and flexible and as a result get used by people for many different things. Which personally, I like a lot. However, this also makes understanding our users more difficult.

When looking at the data, how can we tell if a new Thimble Make has come from a teacher, a student, or even an experienced web developer who works at Mozilla and is using the tool to publish their birthday wishes to the web? The waters here are muddy.

We need a few additional indicators in the data to analyze it in a meaningful way, but these indicators have to work with the informal teaching models and practices that exist in the Webmaker ecosystem.

On the grounds that everyone has both something to teach and to learn, and that we want trainers to train trainers and so on, I propose that asking people to self-identify as mentors via a survey/check-box/preferences/etc will not yield accurate flags in the data.

The journey to identifying yourself as a mentor is personal and complex, and though that process is immensely interesting, there are simpler things we can measure.

The simplest measure is that someone who teaches something is a teacher. That sounds obvious, but it’s very slightly different from someone who thinks of themselves as a teacher.

If we build a really useful tool for teaching (I’m suggesting one idea below) and its use identifies Webmaker accounts as teacher(s) and/or learner(s) then we’d have useful metadata to answer almost all of those questions asked above.

When we know who the learners are we can better understand what learning looks like in terms of data (a crucial step in conversations about learning analytics).

If anyone can use this proposed tool as part of their teaching process, and students can engage with it as students. Then anyone can teach, or attend a lesson in any order without having to update their account records to say “I first attended a Maker Party, then I taught a session on remixing for the web, and now I’m learning about CSS and next I want to teach about Privacy”.

A solution like this doesn’t need 100% use by all teachers and learners to be useful (which helps the solution remain flexible if it doesn’t suit). It just needs enough people to use it to use it that we have a meaningful sample of Webmaker teachers and learners flagged in the database.

With a decent sample we can see what teaching with Webmaker looks like at scale. And with this kind of data, continually improve the offering.

An idea: ‘Teacher Lesson Dashboards’

I think Teacher Lesson Dashboards would catch the metadata we need, and I’ll sketch this out here. Don’t get stuck on any naming I’ve made up right now, the general process for the teacher and the learner is the main thing to consider.

1. Starting with a teacher/mentor

User logs in to Webmaker.org

Clicks an option to “Create a new Lesson”

Gets an interface to ‘build-up’ a Lesson (a curation exercise)

Adds starter makes to the lesson (by searching for their own and/or others makes)

e.g. A ‘Lesson’ might include:

  • A teaching kit with discussion points, and a link to X-ray goggles demo
  • A thimble make for students to remix
  • A (deliberately) broken thimble make for students to try and debug
  • A popcorn make to remix and report back what they have learned

They give their lesson a name

Add optional text and an image for the lesson

Save their new Lesson, and get a friendly short URL

Then point students to this at the beginning of the teaching session

2. The learner(s) then…

Go the URL the mentor provides

Optionally, check-in to the lesson (and create a Webmaker account at the same time if required)

Have all the makes and activities they need in one place to get started

One click to view or remix any make in the Lesson

Can reference any written text to support the lesson

3. Then, going back to the mentor

Each ‘Lesson’ also has a dashboard showing:

  • Who has checked-in to the lesson
    • with quick links to their most recent makes
    • links to their public profile pages
    • Perhaps integrating together.js functionality if you’re running a lesson remotely?
  • Metrics that help with teaching (this is a whole other conversation, but it depends first on being able to identify who is teaching who)
  • Feedback on future makes created after the lesson (i.e. look what your session led to further down the line)

4. And to note…

‘Lessons’ as a kind of curated make, can also me remixed and shared in some way.

Useful?

I’m not on the front-lines using the tools right now, so this is a proposal very much from a person who wants flags in a database 🙂

  • Does this feel like it adds value to mentors and/or learners?
  • Do you think is a good way to identify who’s teaching and who’s learning? (and who’s doing both of course)

 

Weeknotes 5 – Webmaker Workweek

View from Mozilla Space Toronto
View from Mozilla Toronto

As I’m halfway into the following week I’m writing these notes quickly rather than losing them completely. I apologize in advance 🙂

Week 5 was spent in Toronto with the Webmaker team and it will be hard for a quick write-up to do this week justice. I got to hack and hang-out with about half of the total Mozilla Foundation staff, which is hugely valuable four weeks into a job where you mostly work remotely. IRC handles turned into real people, and the people turned out to be very special. So first, thanks to this amazing team for welcoming me so kindly. I think we crammed a year’s worth of social activity into a week’s worth of evenings and across the whole week, I almost got a whole night’s worth of sleep.

I signed more that one waiver in the name of fun this week
I signed more than one waiver in the name of fun this week

There’s a test that goes something along the lines of “people you wouldn’t mind getting stuck at an airport with”, and everyone I met last week would pass that test. Genuinely.

I thought this week might have been a lot of talking and leaving with too many ideas to implement, but from the start it was structured to create measurable output.

Sunday in the office, the bugzilla tickets were transformed into a physical scrum board:

Webmaker Scrum Board

And during the week, these discrete tasks moved from To Make > Making > Made

In the metrics track, I was lucky to work closely with Scott Downe who taught me a tonne of useful things, and we shipped some stuff too. Including a brand new process to make continual testing and optimisation of the Webmaker tools practical.

You can see the new testing process here, and our tests and the results will be open for you to follow along as we learn more about our tools and how people use them.

Onwards…

I like this Canadian alternative to the UK's "One Way"
I like this Canadian alternative to the UK’s “One Way”

And I would be negligent not to include the gif of the week: