When I design navigation apps and sites I always think how to keep users researches fast, efficient and correct. In my experience, even as common user, the address research is a real complex phase for two main reasons:
1) Typing mistakes caused by complex street names, sometimes even in languages that users don’t know. In Italy for example, a part from the Italian language, we call streets and squares in different ways depending on their dimensions (street= via, viale, vicolo, corso etc; square= piazza, piazzale, largo etc) 2) Inserting the street number using the autocomplete/suggestions drop-down list
While regarding the point 1 I could imagine that a motivated user could type or paste the correct address, the point 2 drives me really crazy.
When I tap on the suggested address the research phase ends brutally locating the pin point in a default position of the map that usually is the street number 1. But what if I’m searching number 299? I must go back modifying the text and risking to invalidate the address, or I must type again everything, street number included, ignoring the suggestions.
That’s the navigation apps street number problem.
In the last weeks I discovedered that Google Map solved the street number problem in a brilliant and simple way. They indeed created a dedicated button for the street number directly on the suggestions/autocomplete drop-down list. Watch the video below.
This solution is available both when the user must chose between a lot of similar addresses or when he/she already typed enough letters for having the correct address. Following the two examples.
Thank to the Google Map new street number button, now I can search “via Durini 15” following theese simple steps:
type “dur” > tap on “street number button” > type “15” > tap “enter” > see my perfect location on the map!
For improving this process I could only suggest to switch to the number keyboard when typing the street number. I know that sometimes, like at our home, street numbers are like 1/a, 1/b etc, but usually these subordinates are not as far to compensate the experience of seeing just numbers when you asked to type the street number.
I hope to use this kind of solution in my future projects, but I’m pretty sure that soon it will be adopted as an industry standard from all the navigation apps decresing the adoption cost.
With 13 billions of passengers per year, the Japan’s railway network is famous for its punctuality and for the stations overcrowding. As everybody should know, the public transportation punctuality is not just a question of planning, vehicles or infrastructure. Often the bad passengers and other vehicle behaviours can cause a strong efficiency decrease.
The behavioural approach of the nudge theory says that the use of some indirect suggestions or reinforcements can change the human behaviour. For example there are the floor stickers for regulating people flows in crowd stations that improved their capacity. Or the “buy now” call to action that we find in the sponsored post on the social networks. I must say that the difference between advertising and behavioural psychology is really thin, but the thing that I liked most about Japan’s nudge strategies is the human approach. They indeed are trying more to take care of the passengers mood than modifying it.
I found ingenious the substitution of the emergency-like sound alert when the train is leaving with a melody composed for reducing the passenger stress and giving a sort of train leaving timing. These melodies had the effect to calm down the passengers reducing the overcrowding and decreasing the last second jumps that cause doors problems and delates. Following the video with all the melodies that obviously have a really strong manga approach.
The other nudge strategy that at first seems banal is regarding the suicides containment using some led lights installed at the ends of the platforms. According some studies the blue color has a calming effect, but what seems just a neuro-marketing concept, in that country had incredible results. Japan has the highest suicide rate of the world’s most advanced country and the blue led light installation decreased this rate of the 84%.
Concluding I think that the nudge theory in Italy could be used, but adapting it to our particular approach to transportation and public spaces. I found really interesting that some stickers or sound alerts could improve the transportation efficiency with a really low investment.
This will surely change the way I’ll work in the future.
Google has started its self-driving project in 2009 and in 2016 it funded a completely new company called Waymo. Google today is one of the first company that put on the road level 4 autonomous vehicles and that says to have driven 3.5 million of autonomous kilometers in public roads.
In the autonomous vehicles arena there are many other interesting competitors like Bosch, Nvidia, Apple, Tesla and Navya that opened the orders for its Autonom Cab. We can’t even forget all the other traditional automakers like Ford, GM, Toyota, Honda and Daimler that are working on autonomous cars as the only future possible for their business. So, even if the competition is really high, for me Google will dominate self-driving market like it is dominating Internet but let me explain how starting from a schematisation of what Google did for the web.
As you can see Google created an ecosystem based on technologies, services, contents and advertising more or less in the same way it is doing with its mobility company Waymo. Waymo indeed created its own technology that is supposed to be designed “just” to drive autonomously around the city like Gmail was designed just for sending emails, Google Search just for indexing the web and YouTube just for sharing videos.
Waymo has a proprietary combination of self-driving hardware and software that besides going alone around the city, I’m sure that will distribute personalized and localized advertising for passengers and pedestrians installing external displays. In the near future Google will sell targetized advertising aggregating data from our Android account, our web/video history, our interests, our purchases and lastly our daily commuting and the places we live!
“The detail we capture with our custom LiDAR is so high that not only can we detect pedestrians all around us, but we can tell which direction they’re facing.”
This means that Waymo’s cars can count the “views” exactly like AdWords, AdSense and Google Analytics do on the web. From the advertisers point of view this targeting option is absolutely incredible and it opens to the most effective and distributed local/real-time marketing of the digital era but is not enough. The neutrality of the Waymo’s platform means that all the traditional automakers will have the opportunity to deploy the bigG self-driving technology paying for the full package, or paying a fee and letting Google use their data and their space for advertising. If this sounds disturbing, well, if you used at least one Google product Android included, you are already in the system!
What could be defined the Google’s Digital business model will give to Waymo two solid revenue sources that will make affordable and viral its technology like happened with Android, AdSense, Adword, Analytics, Maps, Office Suites, Webmasters Tools, Wallet and yes, even YouTube.
The Waymo’s integration with other Google services will be amazing and will make taking a ride as easy as searching for a website or zooming a map. Privacy will have to be taken really seriously but we all see in the future how the market winner will manage this issue.
In the meanwhile I’ll continue to read and design, so if you liked this post, share it and come back on my site.
When I wrote about the Tesla Model 3 I focused on design , infotainment system and its pre-order success. Today indeed I write about the production approach that, reading the recent news about skipping the beta testing, is going to be assimilated to the agile software development framework.
In the last days I read many articles about the Model 3 pre-production beta testing skipping. This news was so curious that I needed to retrieve the source, so link after link I landed on the Anton Wahlman articles on Seeking Alpha “The Secret Tesla Investor Call To Which You Were Not Invited” and “Tesla Selling Model 3 Test Cars: Accounting Questions“. Considering that at the moment none knows how these “test cars” will be sold, which quality level they will have and what kind of refinement will be done by the testers/customers, I’ll focus on what I define the Tesla’s agile car development framework.
Agile software development describes a set of principles for software development under which requirements and solutions evolve through the collaborative effort of self-organizing cross-functional teams. It advocates adaptive planning, evolutionary development, early delivery, and continuous improvement, and it encourages rapid and flexible response to change.
For understanding how this applies to Tesla and Model 3, you don’t need to be a Software Engineer or a Digital Product Manager like me. Read just the words that I put in bold and then think how normal is buying a videogame or a smartphone and immediately update it online. Is it possible for a Tesla? The answer is yes, but why?
Tesla isn’t a traditional carmaker, not only for the charismatic presence of Elon Musk and not only because its investors are continuing putting money in. Tesla actually is the unique car producer that together with a car produces a software Operative System that, thanks to the car’s hardware, can manage remotely things that any other carmaker couldn’t control neither at its official assistance network. The most impressive Tesla OS back-end updates are: the battery capacity, the engine power and the self-driving functions.
Whatch this overview video where the deep hardware and software integration is demonstrated.
Reading the Tesla OS official page is easy to understand that the Musk’s car are disrupting the automotive industry because they shifted the core of their products from mechanics to software development. It doesn’t mean that the Teslas hardware (chassis, shocks, body, glasses etc) aren’t good enough the other carmakers or that they didn’t need the same R&D and pre-production tests. What Musk said is that the knowledge-base that they have accumulated from the development of the Model S and Model X will give them the opportunity to jump directly to the production lines skipping the beta test and leaving the “final testing” to the first users (read this Wahlman article for in-depth analysis).
Skipping the beta testing for a traditional car-maker is a sort of suicide, but if you are Tesla it is the first application of its agile car development framework approach. The Tesla’s cars are really different from the other cars. Its engines, chassis, interiors and all the other components are a way simpler from the other cars so, once tested and standardized, they don’t need to be tested again for all the models. I suppose that the electric engines and the batteries can be scaled in a easiest way than the combustion engines, and that the chassis architectures simpler and less stressed than traditional cars. Moreover the Tesla Model 3 will be really more simple than the Model S like this official press release states and the dashboard (absence!) suggests.
Above this, for sure Tesla has other three big advantages. The first one is the big amount of real usage data that users need to share with the company for having the OS updates; the second is the capacity to absorb a lot of physical/software recall/updates thank to its low volume production, its dealers network and its over the airOS updates; the third is the customers base that is composed by engaged and motivated fans that are healthy, techies, early-adopters, green contingent and sports car lovers (read “Elon Musk and the cult of Tesla” by Hope Reese).
So the Model 3 beta test skipping shouldn’t be interpreted like a dangerous move for accelerating the mass production and keeping the investors happy (during the investors call Musk admitted a delay in the mass production plan). It is more like an iteration of a product with the most important hardware parts already tested, while the easily replaceable components and the less critical front-end functions are still in development.
To be simple. Tesla is like Facebook launching its new app. The core is always the same but the design improves fast and in an iterative way. For this reaason Tesla presented the Model 3 as the next company model, not as a concept car.
Tesla has commoditized the cars hardware focusing on user experience, green technology, autonomous driving, products distribution and customers engagement.
That’s agile, but it is even a strategic move for conquering the electric vehicle supremacy and restarting, in 5 or 7 years, the traditional research and the tests for a real new product.
Looking at the recent Mercedes-Benz Concept A Sedan, I was impressed by the led headlamps colour. At first I thought that it was only a show car like other concept at the Auto Shanghai Motor Show, but then its design was so evolutive that I understood that Daimler was introducing and testing a relevant design innovation.
The headlights are one of the most important part of the car’s design. Since when led technology was incorporated in headlights introducing the “day-light” concept, I was pretty impressed by the light signatures that the automotive companies were creating. Today any modern car in any advanced market could be sold without day-light led in the headlights, but even if the lighting market has a multitude of technologies, what puts in common all the solutions is the color. All led lights are white. No exception. No creativity. No innovation.
I think that this decision is obvious because the “white ice” color is the most visible, but considering that leds today have more a design function than a functional function is time to innovate.
The Mercedes-Benz Concept A Sedan indeed isn’t just a concept car: it is a beautiful led headlights innovation test that will change all the automotive industry. I’m pretty happy that finally an automotive company disrupted the evolutive lighting design, bringing a new concept in one of the most visible design part of their car. It is one of the more interesting “ready to production” exterior design innovation that I’ve seen in the last two years and the fact that a luxury company like Mercedes-Benz launched a project like this, make me really confident about the creative future for the cars led lights design.
Following what Merceded-Benz writes on its website talking about the core innovation of the Concept A Sedan:
Guideline: “Stimulating Contrast”.
The headlamps with their eyebrows as a typical feature of the brand as well as the striking grid structure on the inside guarantee a confident look – and a simultaneously high recognition value. The structural sculpture that has been broken down in detail represents a technically based counterpole to the sensual exterior – “stimulating contrast” is one of the six guiding principles of Mercedes-Benz design. The grid structure in the lamps has been coated with a UV paint and it is exposed to ultraviolet light. As a result, the headlamps “glow” in different colours, depending on the light medium – the daytime running lamps, for instance, are white
In my memory, recently only Suzuki and Chevrolet put colors in the headlights, but not using the led technology. Instead they just put some coloured plastics inside the headlights giving to the car a really differentiating design that indeed is helping the commercial succes of the Suzuki Vitara and of the Chevrolet Onix.
Intead of Bots, in these months I used many times a lot of Chat Customer Services on some companies web sites and on Messenger. As all the studies say, communicating with a company through our favourite instant messaging app is smarter than downloading any branded app or using the old-fashioned email. My experience was great and these companies increased loyalty and my admiration.
Using Whatsapp, Messenger, Telgram or WeChat for companies is a great challenge for many technical and communicational factors:
Technical, because CRMs should access to IM platforms for identifying users and managing the requests trafic.
Communicational, because some contents should be always and easily available for customers instead of lose in the chat’s flow.
As a Product Manager I focused on the second problem and, starting from a Whatsapp-like layout, I designed the “Featured contents” function. The scope of this function is to enrich the discussion between the customer and the company saving the requested contents in a reserved area of the app.
Watch the “Featured contents” gif animation for understanding how it function in the direct relationship between a Hotel and its customer.
I’m following the evolution of the self-driving technologies with a lot of interest. Many automotive companies say that by 2020/2022 they will commercialize autonomous cars that will reach the level 4 or 5 of the SAE International Automated Driving standards.
Below the table that is commonly adopted by all the automotive industry.
Wired points the level 3 human problem in a very clear way: humans are not capable to maintain their attention if they are not interested or required to. For simplifying, a crash in self-driving mode cannot be avoided thanks to the intervention of the driver that in the meanwhile could be reading a newspaper or watching a video. Humans are just too slow and in that case even too distracted for recognizing the risk and avoiding a crush.
In the last months automotive world is talking a lot about autonomous and self-driving vehicles both for private and public transportation. During my day researches one day I found the exciting call for collaboration for Olli, the self-driving vehicle produced by Local Motors.
Designing the autonomous bus user experience is a complex task: for first because self-driving buses will serve the traditional public transportation diversified and multi-age target; second because without the driver and, in some cases, without a fixed route, passengers will have some new functional and informational needs.
The first part of my project started with a Service Design session focused on what kind of transportation services a self-driving bus can serve.
Personal on-demand shuttle
It’s like a Taxi/Uber, but less exclusive and more spacious. It brings one or more people from A to B. It can be reserved days in advance and can make various stops during a single dedicated service. The served area is restricted.
Shared on-demand shuttle
It’s like public transport service except for the fact that passengers can add a personalized stop to the route within the bus pertaining area. The route is dynamically optimized depending on users destinations and pick-up calls. The high level of complexity makes this service ideal for closed areas like small districts, big companies, entertainment parks etc.
It’s exactly the same public transport service as we know it.
It’s like sending objects using a shipping company, but instead of giving the package to a human, users will schedule the shipment using an app or a dedicated device in the bus, and then they store the package in a secured housing inside the vehicle. The recipient will track the shipment in real-time and will be alerted when the bus is at the delivery point (or in front of his door). This service can be added to the “Shared on-demand shuttle” one, or it can be configured as an automated delivery service with customized buses and dedicated physical hubs.
This delivery service model is useful for companies that need to transport small parts within a relatively big space, or in modern cities creating a sort of fully automated shipping/delivery hubs for connecting wholesale shops and retails stores.
After this first Service Design session, I started a User Centered Analysis focused on the self-driving bus passengers needs. For designing a real accessible service, I defined only “analogue” needs excluding all the information/functions that a smartphone app could have. What you read is what my grandmother or a manager with a dead smartphone could need for using an autonomous bus.
What self-driving bus passengers need outside the bus
– Passengers need a purchase and reservation system that should be both digital (app), physical (street’s stops signs) and gestural (raising the hand for asking to catch the bus).
The assumptions from where I started my reasearch are:
Users don’t want conversations. Users want pertinent and timely contents within the app that they use most.
Chatbots have the reason to exist because users don’t like to download lot of apps and because mobile sites are slow or difficult to navigate.
Chatbots are a communication channel with an interaction pattern in a sort of way similar to the natural language. They aren’t virtual sales agents.
Chatbots have the difficult mission to bring together contents and services within messaging apps.
The best chatbots performances aren’t based on conversations. Interacting with them requires new functions and a standardized command language.
So I can say that Chatbots are an important technology because:
they represent a way for engaging users within their favorite apps
they can replace apps and websites for simple and recurrent tasks
they are the only direct marketing channel comparable with the email
they revolutionize the smartphone’s push communication marketing
they are the entrance point for advanced data building programs
users interest in downloading branded apps is decreasing
mobile navigation sometimes is frustrating
users are accustomed in making Google searches in a conversational way
But this importance bring with it some threats:
chatbots can’t really understand natural language
chatbots can’t replace the all the other apps functions
chatbots could decrease the users curiosity and research capacity
chatbots will struggle for visibility
chatbots can’t wrong a lot of answers and they can’t ask too much questions
chatbots must care a lot about language, style, frequency and relevancy of their push contents
chatbots aren’t a branded channel
Chatbots are the future of Customer Relationship Management (CRM) and Direct Marketing for the following reasons:
because they deliver profiled offers and contents, receiving immediate feedbacks
because they are an effective support for the human-based customer care
because they will build accurate customers profiles analyzing the interactions and asking for information, ratings etc
Thinking about all these incredible opportunities, I examined the standard instant messaging apps user experience and I realized that Chatbots should have a dedicated set of functions that designed as following.
At this point I tried to go practical matching my Chatbots functions and experience with some generalistic companies.
So please, stop dreaming about a J.A.R.V.I.S.-like Bot. AI will never be like a personal assistant that knows everything about you, that understands the environment, your feelings and your needs. AI assistant will be for ever a digital system that gives complex and nice outputs just because someone coded all kind of linguistic inputs that a human can produce; this kind of assistant will never really understand what’s happening. The most advanced AI possible is the one that has the biggest relational and semantic database tested (manually!) by real operators (read “The Humans Hiding Behind the Chatbots” by Ellen Huet).
Natural language isn’t the key
Machines that understand some plain language commands and that can anticipate some users needs are possible, but computers that are able to understand all kind of phrases that a human pronounces, sorry, but aren’t near to come.
Like everybody us today can understand icons on expensive glass-plates called smartphone, in the same way we must create a simplified language for communicating and using Bots.
For me nobody wants to lose his time talking with a Bot even if companies would love the idea that millions of virtual and assertive sales people talk 24h/7 with customers. Instead, the most amazing feature of the Bots AI isn’t their humanity, but the fact that users can treat them without any courtesy, that they will memorize users tastes and credentials, that they will anticipate users needs thanks to some “natural language” commands and some Facebook profile analysis.
All this doesn’t mean that companies shouldn’t care about language per se, but that they should drive users to use a simplified language for the following reasons:
a simple language is easier to explain in a sort of tutorial during the first chats
a simple language is faster and more efficient than the natural one. If the number of taps for receiving an information on a chat is a way more than searching it on a website, the chatbot is going to fail
creating a sort of standard simplified language for all the Bots will ease exponentially their usage.
The users fruition model will be like the one that today drives sites like Yahoo Answers, Quora or the common FAQs pages where contents are organized and required using the “How to…” and “What is…” format.