App feature I love: ‘Go Later’ in Waze

Every once in awhile I encounter a feature in an app or service that is so smart I have to, well, write a blog post about it. Today I’m loving Waze’s “Go later” button, an option at the bottom of the destination action sheet that opens a screen that I think is extremely well designed both in terms of feature set and interface.

WazeGoLater

When is the best time to leave? Waze makes it easier to decide.

At the top is a reminder of what the user is trying to do, drive later to AT&T Park, the destination entered before, from the starting point, the current location. Below that is a dropdown for the day with the default set to Today.

It’s the graphic below that and the interaction with it which I think is brilliant: the bar graph on the right clearly shows the times that the journey is expected to take, when it’s worse, and when it improves. The shading of each bar, from yellow to dark red, also indicates the severity of expected traffic and it’s instantly clear that scrolling down will allow selection of a later arrival time while considering traffic. Each arrival time has an expected drive time and, accordingly, when to leave by to make it there on time. Finally, after selecting an arrival time, it can be saved so that Waze sends a reminder to leave on time. What I liked about this screen is that even though the bar format is not a widely used interface, it was instantly clear what information it was trying to convey and how to navigate that information to make the right choice.

DestinationWaze

Where to park – can Waze include costs?

Now, there’s no love without a desire to improve. One thing I’d like is to integrate parking information. Waze already knows where I want to go – I picked AT&T Park as my destination. Then I picked their recommendation for the most popular parking lot. However, that parking lot is, as Waze tells me, an 8 minute walk away from the park itself. So, it would be great if:

  1. Waze would take my original desired arrival time and add the walking distance from the parking lot to the destination (in this case, AT&T Park itself) to the originally stated time.
  2. Is there room at the parking lot? Some lots know how many free spaces they have. Could Waze create an interface for lot owners to update availability?
  3. Pricing of the lots. Sometimes a parking lot a short distance away offers rates that make the extra walking distance worthwhile. Can Waze help make that tradeoff?

Finally, I wonder if the time of the alert changes if a user changes their location? In my example, I set up an alert to get to AT&T Park from my home. But if later in the day I end up closer to the destination, will Waze notify me according to the new location? Also, will the notification time change if actual traffic is worse or better than predicted? Both require constant monitoring of traffic conditions but the former could be extremely valuable to users. After all better to be early than late.

All in all, a really well done feature. Respect to the UI designer that got this right.

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Google’s new photo books: bold product trade-offs with a lot of potential

I’m passionate about photos. Not just taking the perfect photo in terms of composition and lighting, but as mementos of a significant moment, as a door into our parents and grandparents lives, and as keepsakes of the special moments in my and my family’s life. I have an emotional connection to photos and seeing a significant one takes me back to its story. I have always loved sorting through photos and creating keepsakes from them, be they one-off birthday cards, a collage, a photo book of memorable events.

I’ve always loved creating photo books but haven’t actually made that many. It’s, well,  quite a time-consuming process. For those who have never created one, there are three stages of creating a photo book:

  1. Gathering and sourcing: finding all the photos you want to include. This is easier when the scope of the book is a short time period and/or a recent event. A recent vacation, a year-in-review, and a special event are all relatively easy to source with usually one photographer adding photos to a single folder. This task becomes harder as the time period grows larger, especially when the source of the photos is a non-connected digital camera or, in even darker times, printed photos. The former requires going through cloud services and backup drives, while the latter require scanning and cataloguing, as they have no metadata. This takes time.
  2. Selection and sequencing: picking the good ones and trying not to be too repetitive. This is easier for analog photos as not many were taken of a single event, but becomes more difficult in the digital age where the quest for the perfect moment results in a lot of very similar photos, only one or two which are fantastic.
  3. Editing – choosing layouts and adding annotation: picking a book theme/design, placing photos in the book, and adding headers and further information, page by page. With analog and older digital photos this also includes assessing how large a photo can be printed without running into resolution problems and adjusting the page layout accordingly.

I’ve recently had the chance to complete this process with one of the more customizable photo book editors out there, Mixbook, and with Google, who introduced photo books at I/O earlier this year (and gave a free one to every attendee.) It’s interesting to compare the two processes and results of these two, especially since it looks like Google started from scratch and tried to reimagine the process at every step.

How Mixbook does layouts: lots of options, endless customization, as much text as necessary.

In a recent project, an anniversary book that spanned years, the gathering stage took me about 25 hours… over three weeks! To make the second step easier, I organized photos in folders by years. This worked really well for my Mixbook project as I uploaded photos and added them to the book grouped by year. Mixbook has a great feature that can hide photos that have already been used in a layout so it’s easier to focus on the current batch. The third step, however, again took me a long time, about 15 hours because I had to further edit my selection and make layout and add text for every single page of the project. I had to pay attention to photo quality, the photo actual photo size vs the space allotted in the

Google, on the other hand, takes a different approach. First, all photos have to be on Google Photos. Second, users can just choose between 20-100 photos, the maximum allowed per book. Finally, there are no layout or text options. It’s one photo per page, white background, no text.

Let’s start at the beginning: users have three different ways to start a book.

  1. Automatic selection: picking 77 photos out of an album of 140. This is more significant when albums are larger.

    Pick an existing folder/album with any amount of photos and let Google select what it considers the best ones. For example, I did this with a folder with 140 photos and it chose 77. After that selection users can manually add and remove selected photos from the same folder only. This is good for those working on a recent, focused event such as a recent vacation or party. It’s not great when a vacation has many photos split up into several folders by day, as I usually do. For the book I created on Google I had to merge all the photos into one folder before letting the selection algorithm work its magic. This means that even though Photos thinks the process is quick, there is more prep work to be done to adapt to that process. Also, I had to manually go through all the photos that were chosen and in about half the cases replaced them with either a similar photo of the same scene, a similar photo but with different people to ensure all participants were represented, or with an important moment that was not represented by Google’s selection. The problem is that liking only half of them means I don’t really trust the algorithm to choose the best, but it’s a rather good shortcut.

  2. Manually pick photos by scrolling through all your Google photos organized by date. This is more tedious than MixBook’s traditional upload-as-you-work process because scrolling through one long, long scroll of photos doesn’t give an option to pause and save the work and to asses the collection amassed so far. Also, it makes replacing difficult since only 100 selections can be made. That means the user has to scroll back and find a photo to unselect before continuing. Even with a long scroll, it’s easier to select every photo at once and then whittle down to 100. Of all three options, this was the one I liked least. It has no benefits over Mixbook’s process.
  3. Best of Spring 2017 – automatically created by Google.

    Start with one of Google’s Suggested Books. I had “best of spring” suggested for me which included 37 photos. The problem was is that while it included some great ones and some that represented important events this spring, it also included a photo of a medical device, of irrelevant people, of insignificant events. It also chose photos with only a place over a photo of people I care about in that place. When I narrow down a season to 37 photos, every photo counts. Anway, as in option A, it’s a nice shortcut but the selection needs to be monitored and modified.

Yet, let’s look at the bigger picture. What’s interesting here is that Google is trying to take my 25-hour gathering stage and reduce it to minutes. The drawback is that each shortcut has a tradeoff that Google hopes won’t be significant to the user.

In option A, the tradeoff is that each option has the paradigm of “one album/folder = one book” isn’t inclusive enough, but when it is, the automatic selection is a very powerful tool. Even with the algorithm’s not-quite-there selection – it still saves a significant chunk of time. The selection algorithm will improve over time as it learns who is important to me and what kind of mix of photo types I like to include (i.e. portraits, group shots, landscapes, etc.) Also, for cases where paradigm doesn’t hold, and the user needs to do significant prep work to create that one album, make it easier to merge several albums (eg: not just cut and paste.) Perhaps it means allowing users to select more than one album before the selection algorithm gets to work.

Another drawback to option A is the assumption that all photos were taken on a phone and backed up to Google Photos automatically. This would, indeed, shorten the process significantly. However, many photographers still use dedicated cameras, especially for special events and vacations. This site claims photos taken by Nikon, Canon, Sony, and Fulifilm cameras make up over 80% of all photos shared online on sites including Flickr, 500px and Pixabay. Despite the glaring absence of sharing on social media platforms, this is still a significant number. What this means in Google’s process is that more prep work is required to get those photos into online. It’s not a dealbreaker.

In option C the tradeoff is that for the short time it takes to review Google’s selection, the result could be a really cute keepsake. What I liked in this scenario is that it’s based on a certain time period that Google identified to be significant for me. It could do the same for a day, weekend, or even an event over a few hours. That’s powerful.

After making shortcuts in gathering and selection, in step 3, editing, Google has gone all out: only one photo per page, white background, no text. The only choice is the photo’s original shape on white, square on white, and full page. There is no editing. All that’s left is selecting a title for the book. While this absolutely saves time, it’s a bit too harsh on the creative soul. No way add descriptions, dates, location, and, perhaps most important, people?  

I, for one, can live with the simpler design with no theme choice. I might even be persuaded that one photo per page is not so bad, even though my photo book philosophy is more is best. What I can’t live with is no text at all. A photo book is a story. It’s me telling a story to my friends and family now and in the future. My story needs text. What I did to overcome this limitation is add photos of signs of the places we visited for the road trip photo book I created. It took away from my overall photo limit which meant less photos of people were included.

What Google did is make photo book creation very easy for a very specific use case. It automated parts of the process but in doing so made the manual one more difficult. By taking away design options, it also shortened creation time significantly. But at what price? For someone like me, who loves photos, has a huge collection, and wants to delight friends and family with personal keepsakes, then this isn’t the right product. While I love the shortcuts, the prep work is significant, the AI isn’t quite there yet to pick out the absolute best photos and the lack of any customization goes too far.

That said, Google getting this right is an intriguing option. The AI will improve, the photos selected will be more relevant. Instead of not allowing any text, captions for locations, dates, and people could be added automatically. It could do more, add more photos per page that have a connection between them, such a the same day, event, or person. It could make creating a book from several albums easier with an overarching selection algorithm. It could really tell a story, which is more than just the photos, and it could do that in less than an hour.

I can’t wait.

My top three takeaways from the Women in Product conference

Yesterday I was lucky enough to attend the second annual Women in Product conference that took place in San Jose. Around 1,500 product managers, all women, all working at some tech-related product, at many, many different stages of their career. I was inspired not only by the women on stage but also by the women sitting next to me, listening, asking questions, and sharing their knowledge. Some of the talks I heard had familiar content but each one managed to teach me something new. That said, at the end of the day, these three talks are the ones I’m still thinking about.

Go-Jek‘s approach: beyond ride-sharing. Multiple features in one app.
Source: From Ms Chan’s slides,

First, Connie Chan’s lightning talk titled “Cross-Border Innovation” and focused on how the Asian app developers approached mobile product  delopement. In Silicon Valley, current wisdom is to have a different app for each function or activity. For example, Google has over 100 Android apps, some with obviously close affinity and others with functionality overlap. Yet each has to be downloaded, installed and used on its own. The Asian approach, which Ms Chan called the Super App, melds different and varying functionalities into one app and leverages the existing audience to introduce new functionality. The assumption is that users will find what they need while gaining benefits such as a single login and identity without the need to re-enter payment credentials for each. To paraphrase Ms Chan, each functionality within the app shares distribution and traffic with the others, while maintaining mindshare and relevance. The Super App approach is so different than current Silicon Valley thought but yet makes so much sense from the marketing and growth perspectives. Bonus: extra insights from Ms Chan.

The second talk I liked was by Jen Dante of Netflix who talked about the importance of failure when building products. As PMs, we tend to focus on success so much that we often forget that we can learn from building products, features, and experiences that users don’t like. The consequences of rewarding only successful products or features doesn’t mean that failure won’t happen. Rather, failures will be hidden and the opportunity to learn from them will be lost. Fear of failure discourages bold product initiatives and will most often result in what Ms Danta called “consensus-driven decision making” which ends up being political and discourages bold moves. She introduced the audience to Netflix’s culture of discussing, measuring and yes, celebrating failure. Ms Dante’s closing statement: “when you fail, you learn.”

My third takeaway was from a talk by a PM I have long admired and gotten to know through her posts, Julie Zhou. She introduced us to the three questions product managers should ask at product reviews to figure out not whether we can build something, but whether we should.  

  • 1st question: “What people problem are we trying to solve?” where the focus is on people. Will the product or feature benefit actual users? Is there an emotional or social benefit aside from the functional one? What is the simple, human benefit?
  • 2nd question: “How do we know it’s a real problem worth solving?” Well, the “know” part drives the collection of both qualitative and quantitative data about the product, while the “real” part means to ask if it is something significant to our users and if it’s worth solving.
  • 3rd question: “How will we know if we solved this problem?” Which leads not just to acceptance criteria or the definition of a set of success metrics, but rather a softer, more intuitive approach. Ask yourself what will be different in the world if we do?

What I liked about Ms Zhou’s and Ms Dante talks is that both are working on complex products in large companies, both with a large number of users and revenue driven by those users, and both are in charge of major product decisions. Yet Ms Dante’s talk focused about the importance of numbers, Ms Zhou focused on more big-picture questions. For me, both are important to consider as part of the product development process and great to have in my toolkit.

Gartner’s emerging technology hype cycle – 2017 edition

For the past few years I’ve taken a look at Gartner’s Emerging Technologies Hype Cycle as a way of following what products and technologies make it out of the Silicon Valley bubble and into the real world. It’s an interesting yet in some way humbling exercise to see what products that we think are the best thing since sliced bread never make it out of the Trough of Disillusionment. Quick reminder: Gartner maps technologies on its Hype Cycle as Expectations as a function of time. They describe the first, exciting part of the Hype Cycle as the Innovation Trigger, which peaks at the second stage, aptly named the Peak of Inflated Expectations. The third, downward slope is called the Trough of Disillusionment. The successful technologies and products slowly make their way out onto the Slope of Enlightenment and graduate to widespread market adoption in the Plateau of Productivity.

Gartner’s Hype Cycle for Emerging Technologies, 2014-2017
Sources: Gartner 2014, Gartner 2015, Gartner 2016, Gartner 2017

First thing I looked for this year was what Gartner thinks of voice-activated smart speakers such as Google Home, Amazon Echo, and the yet-to-be-released Apple HomePod and Facebook’s Aloha. Since last summer’s report Home and Echo have seen a jump in sales and in the 2016 holiday season, “US sales jumped nearly 1,000% from the same period a year earlier. But even outside the holidays — when about three out of every four smart speakers was sold last year —sales have been up 39 percent on a year-over-year basis… Google Home topped US online sales of smart speakers during the holidays, Amazon’s Echo Dot — which sells for less than half the price — held that title in the first quarter.” Yet what’s interesting about that report, from only two months ago, is that “49% of U.S. consumers don’t use voice assistants. Half of the potential market still needs convincing that voice assistants are the wave of the future, and companies need to ensure that newcomers have a positive first impression.”  

Cat listening to cat sounds on Google Home

The Hype Cycle reflects this spurt in adoption. In 2016 Natural Language Question Answering, what I see as one component of smart speakers, was sliding into the Trough of Disillusionment but expected to reach mainstream adoption. This year, it’s off the chart which I take to mean it has reached adoption faster than predicted. The other component of smart speakers are Virtual Assistants, which remain just under the Peak this year. This could indicate that Gartner believes that while smart speakers are becoming more widespread, it’s their capability to interact and answer questions via voice that are more valued by consumers than assistants. This will change as assistants become more versatile and voice interactions become easier. Google, at least, placed an emphasis on creating more apps for Assistant at their annual I/O conference, which bodes well for this technology.

Second technology I’ve been following is AR. At their F8 conference this year, Facebook demoed fun VR products but it was their talk about AR that I found most interesting. Michael Abrash, the chief scientist for Oculus, talked about some potential uses for AR that have some fascinating implementations, especially when enhanced by the social graph. He talked about near term applications such as seeing your friends dish recommendations on a restaurant menu and some (very) far but amazing applications such as adding name labels for people you know in a crowd. Yet Abrash added that “real, always-on augmented reality glasses are at least five years away. And that was his early estimate. He also said it’s possible we’re 10 years out.” Interestingly, adoption is moving faster than predicted for VR. Gartner places VR well on its way to adoption on the Slope of Enlightenment for 2017, where it was last year as well, but this time with an expected time to reach the Plateau in 2-5 years as opposed to 5-10 last year.  AR has spent the last few years slowly sliding into the trough and Gartner placed it at lowest point of the Trough for 2017, with expected time to reach plateau in 5-10 years, matching Abrash’s prediction for glasses.

Third, IoT. I’m rather surprised that Gartner still sees IoT platforms and the connected home at the Peak of Inflated Expectations where I see them somewhere in the Trough of Disillusionment. That said, last year Gartner moved IoT itself (meaning devices?) off the Cycle and into the Plateau but left these two at the peak. It seems that IoT is at a crossroads of sorts. Devices themselves have been “smartened” in various ways, with varying success but the platforms connecting them into a usable tool aren’t quite there yet. Moreover, there is a disillusionment from what a connected, smart home will eventually be capable of and it may be that consumers aren’t quite ready to pay a premium for connected devices vs those that do their job.

Fourth, self-driving or, as Gartner calls them, Autonomous Vehicles. These are one of the few items on the Cycle with a 10 year or greater adoption prediction but the only one on the way down from the Peak into the Trough. Interestingly enough, in 2015 and in the years before, Autonomous Vehicles were slowly climbing up the cycle but had a prediction of 5 to 10 years to reach the plateau. In 2016 and 2017, they have not only started sliding down, but their adoption horizon has been pushed back. It’s interesting to note, though, that almost every major car company now has offices in Silicon Valley and is working on some version of this.

Finally, I’m surprised drones are still on the Cycle – they seem to have been widely adopted by everyone from ecommerce giants to wedding photographers. Everyone seems to know what they are and how they’re used and they’re so common there is already government regulation on where and how to use them. Maybe next year they’ll be firmly in the Plateau of Productivity?

Till next year!

My inadvertent Facebook experiment & what it might mean for the future of social apps

It started with a trip abroad, with limited connectivity. It continued with an unexpectedly dead phone and a forced edit of apps, and continued for a few more weeks mostly because I was just too busy to get back to it. In the end, I stayed off Facebook for almost two months, which included my birthday, a day I’m usually happy to spend time on Facebook.

I didn’t go back because the Facebook “experience” was wearing me down. What I wanted was to stay in touch with a close circle of friends that I cared about and to receive updates about significant life-moments from those a not as close. What I got was page after page of in-stream ads, “suggested posts” that had no meaning for me, articles that someone more distant to me liked, a distant friend who connected with someone I have never met, and more. What’s worse, all of these irrelevant distractions hid the updates I did want to see. Now, this isn’t new. All of those irritations have existed for a while and I was still on Facebook. What tipped the scales for me were the political posts – their frequency, their extremism, and their clickbait headlines.

And you know what? I didn’t miss it. I found that cutting Facebook from my day saved me frustration and time. I figured that I could stay in touch via email, WhatsApp and Slack, and I felt that it worked. During this period Facebook sent me twice daily emails with attempts to draw me back, but the content they chose to highlight just served to show me that not logging in was a good idea. Examples included “[distant friend] commented on her photo” and “[a coworker from 10 years ago] shared an update” which did not really interest me.

Then came last Friday, when out-of-town friends and former neighbors posted that they were enjoying the Giants game at AT&T Park. My husband saw it and wondered how it was that they were in San Francisco and that we didn’t know. After a short exchange in the comments, I logged in and noticed that they had, indeed, contacted me on Messenger over a month ago. All this led me to spend some more time on Facebook to see what else I had missed. Turns out – another biggie: friends visiting from Europe left a wall message, along with a birthday wish, that they were in the Bay Area for a few days…. two weeks ago! I had missed them completely. On the bright side, I had several wonderful birthday greetings which were fun to go through.

So what’s going on? Does this mean Facebook is impossible to quit? Kind of. Facebook exclusively owns many of my lesser relationships and it created an easy, person-based way to contact them, one where I don’t need to know their current email or phone number. Once a connection is established, that friend is reachable forever. That’s a very potent draw, and a huge competitive advantage. Sure, Snapchat can entice the teens with cool features, stories, and streaks, but they still connect on Facebook because they can easily get in touch with each other when they need to coordinate a homework assignment.

Facebook’s welcome screen. It’s all about friends.

What’s intriguing is whether Facebook’s ownership of these relationships means game over for any other company that tries to implement a social application. Is this a barrier that no other competitor will ever overcome? In our age of constant innovation I want to doubt that. After all, Yahoo was well established when Google came along. Yet take a look at voice-operated speakers. Already, Facebook is playing catch up with Amazon and Google, but their upcoming home video-chat device is one that has social interactions already built in. Will Facebook be the only company to ever own our meaningful social graph?

I want to wrap this up with a recommendation to listen to a Forum episode from earlier this week with Tristan Harris, a design ethicist. He argued that the social media companies, including Facebook and Snapchat, aren’t behaving ethically because they are intentionally preying on “very deep human evolutionary instincts.” Says Mr Harris: “It’s very useful and very important to know what other people are thinking about you and saying about you, [such as] if other people in your social group are hanging out and you are not invited. The ability to know at any moment where I am in the social hierarchy is new and is being deliberately manipulated to get attention. They’re playing with the delicate and vulnerable parts of the human psyche.” So when we find ourselves unable to resist Facebook’s pull, now at least you we know why.

A few musings on notifications in iOS by a long time Android user

This week, after my Android phone died again, I decided to venture into the world of Apple and borrowed an old iPhone 6 from a friend. I’ve spent the last few days fighting with my muscle memory (where do I swipe?) and Googling “how do I…” when I can’t find an essential setting. Since my Android died abruptly, I couldn’t use Apple’s Move to iOS app, so I’m installing apps only as I remember that I need them. This is actually turning into an interesting purge as there were apps on my Android that it turns out I really haven’t been using. But I digress.

Aside from the changes in UI that were predictably hard to get used to, and I’m not holding a grudge against Apple for this, I’m truly exhausted by one thing: notifications.

  1. iOS alerts: so many, each its own, large-ish message.

    The sheer number: there are so many alerts and each one is its own message. Android encourages notification bundling but iOS seems to do nothing of the sort, and doesn’t seem to offer it in their settings. This means that I get an alert for every news item, every email, every Twitter like, and every new post in every WhatsApp group, including multiple posts in the same group.

  2. They pop up everywhere, repeatedly, in multiple locations. Whereas in Android they’re only on the lock screen in the same format as in the notification drawer and requiring the same action, on iOS they’re on the lockscreen, the notification center, and as alerts, as temporary banners, and as badges. Speaking of the variety…
  3. At every app install, permission is requested by the app to send notifications. I agreed to most, especially the messaging and mail apps, as these are notifications I want to receive. I was then summarily overwhelmed. Going into settings I realized that there were many different aspects of notifications that I could control, such as badges, banners, sounds and alerts. After looking up what they meant, I realized that I have lots of control but not for what I need: minimizing and grouping alerts.
  4. Dismissal of notifications takes a swipe, to get available actions, and a click, to choose view or clear. Why not just a swipe? Each notification has to be dismissed individually, there’s no dismiss per app or per group. Update: Notifications can be dismissed for the entire day, I missed this.
  5. The badges stick until actively dismissed, which drives me crazy. Email, for example, keeps telling me I have 38 unread emails. Yes, I know, but these are not new unreads, they are ones that I already know about and decided not to read or delete for now. The badge is useless, which is why I downloaded the Gmail app, where badges are not for total unread but only for new unreads. I get that this is decided on an app by app basis but this doesn’t make sense to me, especially for iOS’s default mail app.
  6. Choosing channels in Apple’s News app – why are so many on by default?

    There is no hierarchy of notifications in the general settings, only in some individual apps, who mostly don’t offer additional options. Gmail is one exception and allows notifications settings for different types of email, where I can chose to be notified only for Primary emails, not Updates or Social. It helps minimize notifications without a risk of missing important messages. I also cannot set how many notifications I’d like to receive from an app daily (Nuzzel does this well.) The good is that some apps, such as Apple News, do offer customization abilities so that I can choose what channels I want to hear from. The drawback to this is that it’s in the News app and not reachable from the News notifications from Settings, so it needs to be discovered independently. 

So, is it just a question of me getting used to a new UI or are iOS notifications really that stressful? I’m in the process of customizing and maybe, by next week, I’ll feel more at home in this new OS. Meanwhile, I am more appreciative of the changes that Android has in store for Notifications in O: more granular control and the realization that too many notifications cause anxiety and not all notifications are equal.

Finally I love how every iOS app puts the back button in a different place, but that’s a post for another day.

Citymapper integrated bike-sharing and it looks great

Going on vacation is my way to see what Citymapper has been up to. It’s pretty much the only app that continues to surprise me every time I update with some new, useful feature. Last time it was the journey companion (hitting Go on a chosen route provides cards throughout the trip and reminders when to get off) and this time around it was integration with the local bike-sharing service.

 

Paris, like many cities, has a bike-share program with multiple docks throughout the city. Like many of their counterparts around the world, the Paris bike-share system has its own app, which shows docks with their available bikes and empty slots. Like the advantage of a complete route planning app over a static Metro map, bike-only apps are good at a providing bike information, not information on what transportation option is overall better given user preferences. Citymapper offers not only bike routes but also combines bike segments with other public transport options like the Metro. It also has updated information on the number of bikes available at a pickup dock and the number of empty spaces available at the destination dock.

What I don’t know, because I didn’t actually use the bike-sharing option in Paris, was whether the app has the ability to change the destination bike dock en route based on the closest bike dock to the user’s final destination that actually has available slots for checking in a bike. On several occasions in Paris I saw riders cycling towards a dock only to discover that there were no available slots, pulling out their phones and then cycling away in frustration. This is one situation where Citymapper can offer more value, like Waze and other navigation apps, by changing planned routes due to changed conditions along the route.

One other feature I could see use for is predicting availability ahead of time by looking at and studying docking patterns throughout the day and week, similarly to how Google Maps considers historical traffic patterns when predicting times and routes for future travel. This could be useful during periods of high demand for bikes and slots during rush hour, when bike traffic can be more unbalanced and demand higher for bikes and open slots in certain locations.

Finally, and I know this isn’t a simple request, but it would be so useful for those users with no international data plans (ahem) that need route planning on the go. The Paris Metro has dense (in the city center) crisscrossing lines, with trains arriving every few minutes. Helping tourists find just one, optimal route even when they are not connected could be extremely helpful. Another lesson learned in Paris is that there are some stations (Châtelet-les-Halles as the the most obvious) that should really be avoided for transfers between lines because they are so huge. I haven’t seen Citymapper offer routes that specifically avoid large stations and it could be a helpful option, and doable seeing as it already offers routes that aim to be rain-safe.