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.
Internet has already posted a lot about the new Tesla Model 3. I want to say something since the launch’s day, but first to start writing down this post, I read dozens of articles and their comments for understanding exactly what happened in the automotive industry and what kind of innovation is really bringing the Model 3.
Why Model 3 is a design success?
Tesla built an incredible brand. Tesla is the youngest automotive company that consumers remember like the older and biggest ones like Toyota, Wolkswagen, Nissan, BMW or Daimler. But unlike them, Tesla made the miracle of giving a desirability aura to electric vehicles and it did it not only making fast, efficient and advanced vehicles, but even having the courage to revolutionize the design of its (future) best-selling model.
Generation Z is composed by young that are actually between 12 and 17 years old. For the automotive industry they are evaluated 3.2 trillion of dollars by 2020, so it’s really interesting to understand what they will look into their future cars.
The most important insights that I read are:
92% wants to own a car
they don’t care a lot about style and design
they remind some old-fashioned brands like Ford, Chevrolet and Honda for their solidity
they care more about saving money (in the purchase and running costs) than in saving the environment
they care more about safety than infotainment
they’d like to have autonomous vehicles for increasing security, but they don’t trust in that technology at all
they’ll buy a car in a car dealer, not online
Looking with attention the slide where the generations are described, I found some new interpretative keys of the Gen Z’s purchase intentions.
Drivin‘ is a Car Pooling and Neighbourhood social platform that I designed almost three years ago for sharing car’s rides with people that have similar transportation needs, and for creating a trusted network for empowering the local sharing economy.
I presented the project many times to many developers and Startup events but as usual, being just an idea, nobody cared about it. Actually I abandoned the desire of developing the service because the concept was realized by many many other startups, plus some big companies like Lyft with its Lift Lyne. I sincerely don’t know if these apps are having the success that a service like this should merit. The Instant Car Pooling (or ride sharing) is the real alternative to the private car and to the public transportation but the security issues, the business model and the critical mass needed for creating a real instant service are really big challenges.
By the way, I’m proud that a 3 years old project is still actual and has a lot of potential. All the world’s Transportation Authorities together with the car manufacturer (and Google and Apple) are looking forward for creating the mobility pattern of the future. Not only because of the pollution or the metropolitan congestion, but because cities and citizens have changed their concept of mobility. Because thank to the social networks we have lost anonymity and we trust more one to each other (we know that we are monitored). Because we don’t like to lose time and money for daily commutes. Because we trust that technology could do things that we don’t like to do.
During the last years I developed a strange professional syndrome.
Everytime I use an object I analyze usability and functions trying to learn or imaging improvements. Today the interaction between humans and machines is powered by all kind of sensors that can interpret imput like natural voice commands, objects movements, touch and hand free, etc.
Today I want to introduce you my concept for an in-ear headphones touch gestures. As you can see in the following gifs, I imagined to turn the headphones cables in a control device dedicated to the four most common commands used during the music listening: volume up, volume down, next song and last song.
For designing the in-ear headphones touch gestures I was inspired by the “traditional” touch pattern gestures and by the emerging smart clothing technology. I admit even that sometimes during my trainings or in a crowded metro I’d appreciated these gestures because I didn’t have how to switch that shitty song that everyone have on its library.
Following the in ear headphones touch gestures concept.
Volume up: thumb + index finger down on the right cable