Discover Marcela, our VP of Client Engagement and Head of our Atlanta office.
Change is a trying time for everyone. Leadership can facilitate it by understanding the micro and macro employee experience.
August 8, 2019
YML's team is diverse, insightful and bound together by a dedication to the agency's mission — make a lasting impact. The "Getting to Know" series shines a light on various members of the YML team.
My name is Adam Talcott, and I’m a software engineering manager at YML.
I’ve been at YML for four years, and during that time I’ve had the pleasure of leading a number of different technology projects. I usually get involved in the early stages of an engagement, even before a client has committed to partnering with us, to bring an engineering perspective to the table. I then get to see that project through strategy, design, development and deployment.
I was born in Chicago, but I grew up in California, splitting my time between the San Fernando Valley in Southern California and the San Francisco Bay Area.
I went to college and grad school in southern California, and, after a brief stint in Austin, Texas, I returned to the Silicon Valley about 20 years ago.
After completing my Ph.D. in electrical and computer engineering, I worked as a computer architect designing microprocessors for IBM, Sun Microsystems and Cisco. In 2008, I started developing iOS (then just “iPhone”!) apps in my spare time.
I started my own consulting company in 2009 working on iPhone apps for a wide variety of customers. I worked at a startup in the machine learning and video space prior to joining YML.
At YML I saw a great opportunity to work with a great team and to partner with amazing clients. I also really love the variety of projects I get to work on and the variety of technologies I get to learn about and use here.
I love to bring great designs and user experiences to life. It doesn’t matter what the technology may be, but nothing gives me more pleasure than having something I’ve helped build improve people’s lives in some way.
Apple is definitely one. I was an Apple fanboy since I first started programming on my parents' Apple II Plus computer. That’s long before it was normal to see everyone in a meeting, classroom or airport with Apple computers or using an iPhone.
It’s been amazing to watch the growth of that company, and I still get inspired by the story of how the first Macintosh computer was developed.
I live in Los Altos, so when I eat in San Francisco, it tends to be for a special event. As a result, my favorite restaurant in the city is Gary Danko, which I’ve been fortunate enough to visit on a few occasions.
Closer to home, and more affordable: I love eating at Patxi’s Pizza in Palo Alto or Estrellita Restaurant in Los Altos.
With my family, usually in the car shuttling the kids between activities. My wife and I have a ten-year-old daughter and and an eight-year-old son, and I always look forward to weekends or traveling with them.
And when I do have a moment to myself, I also love reading history books or getting some video game time in playing Rocket League or a hockey game in NHL 19.
By Sarath Avasarala | July 31, 2019
With rapidly expanding catalog sizes and time-strapped customers with few clicks to spare, recommendations have become essential — a sine qua non — for brands to help reduce decision making complexity and drive business value.
Viewing recommendations as a simple matching exercise between users and items will no longer cut it — brands need to build experiences around recommendations and guide customers on a path to self-discovery, while being sensitive to several pitfalls along this path.
We have a few ideas that we think would help — but first, some context.
In the year 2004, Chris Anderson of Wired wrote an article entitled “The Long Tail”. In his article, he speaks about how the traditional brick-and-mortar retailers — constrained by shelf space — favored the most popular products over niche (“long-tail”) products with low sales volumes. He argues that these long-tail products could potentially outsell the most popular products since they cater to individual tastes and retailers are no longer constrained by shelf spaces or the reach of distribution channels.
It’s 2019 and the “tail” is now longer than ever.
And we’re not just talking about retail. Look at the numbers yourself:
and these counts will only keep getting bigger.
The problem now is not so much on the supply side: the marginal costs of distribution and the costs of inventory have gone down quite significantly.
The challenge is more on the demand (or the “customer-facing”) side, where there is a strong necessity to know the customer and personalize the product to cater to their needs. Therefore, it is important for managers to think about the various touchpoints in the customer journey where recommendations or product personalization can add value.
What follows is a list of key use-cases and goals that one needs to keep in mind to deliver personalized experiences.
The huge assortment of items in any catalog can sometimes be anxiety inducing — this ties to a well documented phenomenon known as the “paradox of choice” — where customers experience stress when presented with large collections of items without any guidance. That is where recommendation systems can be of great help.
When customers visit a website or use a mobile app, there are several implicit signals that can be captured and processed to help them with their decision-making process.
Let us take the example of Uber Eats: when a user opens the app for the very first time, there is little information about the user’s likes and dislikes.
However, the app still makes use of contextual signals such as (i) the location of the user to filter the number of restaurant recommendations and (ii) the time of day to trim down the list of options even further.
In addition to this, users visiting the app communicate intent through (i) search queries (ii) visits to specific cuisine pages or (iii) visits to restaurant pages. These seemingly simple, but powerful signals can be used to push recommendations that save a lot of time for the customer.
Notice how the app has several widgets stitched into the core user experience. What’s more interesting is the fact that each widget in the experience has a purpose and caters to a different user persona:
It is important to note that the personalization journey doesn’t end with implicit signals: there is a strong need to capture explicit signals about users' preferences, and this can be done through purchase data, item and category-level ratings, favorites, and reviews. These signals are fed back into the system to create a strong personalization engine that knows the customer very well and serves the most relevant recommendations.
It is easy to fall into the trap of using implicit and explicit signals to only recommend items with a high probability of purchase.
However, with enough user data, this can create a “filter bubble”, where a user is repeatedly exposed to recommendations from a small set of categories.
This phenomenon is particularly pervasive on social media where a user watching certain category of videos is exposed to the same type of videos over and over again.
While this is a hard problem to solve, several brands have shown that this problem can be handled to a certain extent through editorial intervention (“featured”, “editor’s picks”), making recommendation diversity an explicit goal of the recommender system, or providing avenues for the customer to independently explore content through a “discover” space.
Spotify, for instance, uses an intelligent combination of personalized playlists (“Daily Mixes”) and curated content (“Editor’s Picks”), along with multiple categories of playlists (“Discover Weekly”, “New Music Friday”). This approach has reportedly led to a lift in listening diversity by close to 40% (Source: Spotify Insights)
Twitter lets the users choose between an algorithmically ranked feed or a reverse chronological feed. The same holds for trends, where the user can choose between personalized or non-personalized trends. These kinds of additions provide avenues for users to step outside of the filter bubble and help them discover new content.
There are several occasions where users visiting an app or a website browse for content but are unable to complete the purchase flow (or perform a "success action") within a session.
One can observe drop-offs on category pages, product pages, or after a product is added to the cart; this presents a chance to take recommendations outside of the core product experience and into email or notification campaigns, where a user can be gently nudged to finish an incomplete flow and be presented with similar product recommendations for purchase consideration.
On similar lines, there are occasions where users communicate intent through a search query, but the exact item is not available in the product catalog. On such instances, one can measure similarity between search query and the items in the catalog to surface similar items which are already in the catalog.
For instance, even when Netflix does not have a title related to your search query, it surfaces titles that are similar in some respect (the genre, actors, etc.) so that the user has alternative viewing options.
A critical part of recommender system design is to evaluate the cost of an inaccurate recommendation. This becomes all the more important in domains like healthcare, where an inaccurate recommendation can potentially cause a lot of harm.
The only way to solve this would be to have an open discussion involving a diverse group of people and build feedback mechanisms into the product to mitigate potential downsides.
Building simple feedback mechanisms to capture dislikes or offensive content goes a long way in improving the recommendation system.
Common implementations include (i) downvotes or thumbs-downs (ii) “see less often” options in social feeds (iii) close buttons in recommendation spaces to hide specific recommendations or (iv) full-fledged reporting modules which capture details about why a user didn’t like a certain recommendation.
Recommendation systems can span the whole gamut from popular to hyperpersonalized and context-unaware to context-aware.
A well-designed recommendation system can add a lot of business value in terms of increased frequency of product use to increased cart value and retention. On the customer side, it can reduce decision-making complexity and lead to moments of customer delight.
At the same time, understanding the limitations (bias, filter bubbles, cost of inaccurate recommendations) is extremely important and it is vital for system designers to ensure that the product has enough checks and feedback loops in place to protect the customer from potentially harmful or divisive content.
As we said before, providing a good recommendation is more than just matching a user with an item - it is about guiding the customer on a path to self-discovery!
Sarath Avasarala - Product Manager @ YML Bengaluru
Sarath is a Product Manager at YML. With hands-on experience in design and a keen understanding of business and tech, Sarath loves to talk to customers, get his hands dirty with design, dive deep into data, and do whatever it takes to deliver customer delight.
July 18, 2019
YML's team is diverse, insightful and bound together by a dedication to the agency's mission — make a lasting impact. The "Getting to Know" series shines a light on various members of the YML team.
I’m Hamish, which is a Scottish name pronounced “Hey-mish”, but in the US by necessity I will respond to Hammish, Hameesh, Amish, Shamus and occasionally Angus.
I’m a UK qualified Chartered Accountant, and I’ve been working as a CFO / COO for professional services agencies for most of my career.
Despite the extremely Scottish name, I was born and raised in South East England and spent the first two decades of my career in London. When the agency I was the CFO for in London expanded into the US in 2003, I took the opportunity to move with it to the San Francisco Bay Area where I’ve been living and working since 2006.
Tell us a little about your background.
My time at school and university was dominated by mathematics – almost all of my high school qualifications are mathematics subjects, and my bachelor’s degree is in mathematics. So after graduating, becoming a Chartered Accountant was a natural route into the business world for me.
Why did you choose to come to Y Media Labs?
From the start, I’ve wanted to work with business leaders to help them build and grow their organizations. Fast-growing businesses are the most fun and challenging to work for, and I’m a professional services agency specialist and a technology enthusiast – so Y Media Labs checked every single box for me. I couldn’t have been more excited when Ashish and Sumit asked me to join.
What about this industry are you most passionate about?
I’ve always been a tech geek – before computers I was a gadget guy, in the early 80’s I was programming an 8-bit computer with machine code, and I love the things that technology enables. I keep in touch with friends and family all over the world using social media. I listen to just about any book in the world or any music I want to during my commute using a wireless super-computer that fits in my pocket. I can deal with my anxieties by checking my garage door is closed from anywhere in the world – all these things I love with a passion and muse on with awe on a daily basis, and I’m excited for the things to come too.
What are some other companies you admire?
I admire people more than companies, and it’s the people behind them that drive inspirational companies. Coming from the UK I grew up being inspired by Richard Branson, and his values of fairness, inclusion and humility, which infuse the Virgin brand. And people like Roger Federer, who despite his phenomenal success and domination of his sport for years, maintains a humility and kindness to all which is an example for everyone.
What are your favorite spots to eat in San Francisco?
I worked for several years on the Embarcadero, in what is now Google’s San Francisco office. Favorite places around there are Ozumo for sushi, and Boulevard for a splurge. Where I live in Marin, I have to give a big shout out to Insalata’s.
How do you spend your spare time?
Living in Marin, our family does a lot of outdoors stuff – tennis, hiking with our dogs, swimming, and mountain biking which was invented in Fairfax the town next door to us. We love movies too, and being able to stream HD movies on demand onto a projection screen in our living room is amazing – just another reason I love technology!
By Shayna Stewart / July 17, 2019
A people-first approach is neither easy to create or quick to implement. But it is the secret sauce at the core of the biggest and best brands in the world today.
Customer experience is a strategy that all digital insiders know has to be a focus if they want to have a lasting impact in their industry. However, the execution of customer experience isn’t as easy as just coming up with a plan to leverage emerging technology and building digital products. It’s as much about igniting cultural change within a company as it is about planning for the evolution of the experience.
At YML, we’ve designed a dynamic and thorough people-first strategy built to cultivate cultural change.
That people-first approach is what is missing from the majority of CX initiatives — and it shows.
What differentiates the Silicon Valley behemoths and startups is the people-first approach.
A people-first approach comes with a shift in mindset that is drastically different from the historical business executive mindset. You suddenly are talking about the broad spectrum of all people, internally and externally, instead of just customers, and ultimately revenue. You are talking about emotions as opposed to products. Instead of technology solutions, you are building conversational tools. Lastly, whereas a business-centric mindset is one that optimizes based on minimizing risk and maximizing revenues, a people-first mindset is one that optimizes for transparency and intrinsic value.
In the short term, when first making this cultural shift, these optimization goals can constrain each other. In the long run, a people-first approach will maximize revenue, reduce risk, build loyalty with your team, and, quite frankly, keep your business relevant.
But this is a very difficult story to tell when in a boardroom meeting. Often times a savvy executive can make the initial case for investing in CX, but isn’t able to clarify the full scope of that CX investment, which includes a gradual and tangible, cultural change to people-first. What ends up happening is that the first part of the project may go well and the customer may come first, but then the returns on revenue and reduced risk are not immediately recognized and therefore the mindset shifts back to business as usual.
The trick is to trust the strategy. Trust consistency of message and approach.
Here are some examples of companies optimizing for people-first.
In both of these instances with Netflix and McDonalds, the immediate impact on the business metrics (revenue, profit) went down. In the long run, these CX strategies resulted in heightened retention over time. Brand perception and revenue drastically improved. They illustrated how creating a people-first culture will help mitigate the initial shock of investment and reduce risk over the long run because the investments made are directly informed by people’s emotions.
At YML we have created a step by step hierarchy to help you understand what actually goes into creating a people-first cultural mindset. Breaking it down into steps can help your teams understand where they are in maturity. The plan is also a tool to understand what steps were missed in the past. The key to this model is that it implies a high level of collaboration from stakeholders from historically siloed teams at every step.
Levels to Creating a People-First Culture:
Each step is crucial, and completion of a step without completing the one before it will invalidate all steps. In addition, the investment in each level is additive and represents a cost that is continuously incurred. This means the investment does not go away once a team has leveled up. The result for each step will be unique to every brand and even the approach to all steps is not a one-size fits all. Even if you meet the requirements in each step there are still some cultural habits that will undermine this entire investment.
Habits to Avoid in Order to Preserve a People-First Mindset
A people-first mindset should permeate the underlying thinking of all teams. It should be an iterative process that produces long term business results.
It should unite and empower all employees to stand up for what’s right for the customer.
Employee thinking should be able to shift seamlessly between their executive persona and people persona. And most importantly, it should allow employees to feel like people feel because, at the end of the day, all of us are just people.
By Shayna Stewart & Amit Garg | July 8, 2019
To say the stakes with voice interactions are high would be an understatement. This is the moment for voice technology.
Voice has the power to capture attention like never before because it hooks directly into the mechanism for how people think. It removes the friction of reading, clicking and translating like with other technologies.
However, voice-based AI is highly constrained in terms of what it can and cannot do:
These constraints make the design of voice one with little room for error.
At YML, we think about building products (including voice projects) in the form of an infinity loop, a repeated steps of moments that are continuously optimized as you learn more.
Below we outline how UX and Data Strategists can partner in each moment for a voice-based AI project to reduce risk of voice AI going terribly wrong.
Having a clear, distinct vision is essential for voice.
The utility of the conversation is the most important part of the vision. At this point in time, the voice-based AI has not mastered the art of casual conversation where it can react to what the person has said and feed them what they are anticipating to hear through compliments and relatability.
AI is programmed to learn in smaller verbal tasks and take the learning of the smaller tasks and associate learnings to other tasks (though progress is being made there).
UX should define the utility, personality and context of the conversation. Why is this interaction important to have? At what point should the conversation happen, particularly if the conversation is prompted by another interaction? What is the intended outcome of the conversation? What qualities of our brand will this voice represent?
We must provide evidence for why voice is the right channel to design for in a given interaction, especially by understanding its context. For example, a bedroom voice interface that reduces volume to 25% at late night and is less wordy understands we don’t want loud robotic voices at midnight. Practically, a feature like that could be documented in a user flow.
Understanding the tone and the personality is not something a data person typically creates (or even understands in the real world), however, in voice this is a critical element because the personality is actually a data requirement. For example the answers to the following questions are data requirements:
They should also start identifying any current or potential datasets that may be relevant to help train the AI in the subsequent product phases. They will need to work with a variety of teams to collect and get it into a format that can be easily used during training.
Fundamentally, the way we think about the design of sound is different from sight.
Of course there’s overlap, but it’s interesting to take a closer look. For example, a designer strives for visual consistency. Repetition and visual hierarchy help us stay organized when looking at an interface.
But with speech, that kind of repetition gets rather annoying. Therefore, we should think of the journey as a carefully crafted conversation full of familiar variety.
In an app or website, the way people interact is relatively constant. GUI interaction occurs in a fairly regular rhythm of cognitive load. Mentally navigating the interface, reading text, and executing tasks requires a sustained level of attention through out.
It’s a very different situation for voice.
People make the first move, unprompted, and the system responds immediately. And, due to the transient quality of sound, people need to give their full attention to process the response. The luxury of closing an alert dialog without reading it on a GUI is not afforded by voice, nor is the action of reading and re-reading information. Instead, our full attention is required during voice interaction, and absolutely no attention when not interacting.
Therefore, voice experiences should feel like a conversation - an interaction that we want to give more of our attention to when it matters - in order to have the highest likelihood of re-engagement.
UX should define a framework for the desired flow of the conversation.
Similar to designing for GUIs, the overall flow of the interaction needs to be designed, as well as defining the user intent the system should be recognizing.
UX should be asking questions like:
How can we remove friction in the process? Is this how someone would actually think about this interaction? Is the system doing everything possible to pick up on the nuances of speech and trying to move the conversation forward?
Even in the case that the engineering team leverages machine learning techniques to let the AI learn the conversation flow on its own, this framework will help the team identify if it is producing the intended results.
For example, at YML we recently worked with a Fortune 500 insurance company to reimagine their self-service digital strategy, which involved a concept for using in-home voice assistants to handle basic transactions like paying a bill.
Along each step of the conversation, we outlined how the system should move the conversation forward by capturing user intent, setting the variables of intent, and the next action to be taken - all packaged into a helpful and professional voice that emanates confidence and security.
The data strategy team should partner with UX to understand the basic conversation framework and then work with the engineering team to understand their methodology for building the dialog model.
The data strategy team member will need to be able to translate the constraints of each methodology whether its’ rule-based or machine learning-based.
For example, Amazon Alexa skills experts recommend that the conversation has no hierarchy.
This makes sense when designing skills - which typically are a one use product. This is because it prevents questions to have to go through a menu-like conversation (think pretty much any credit card company call centers first line of defense, having to answer a multitude of yes’ or nos before just getting directed to someone).
Though the implications of having no hierarchy mean that:
This synthesis of the UX framework and engineering approach is important in this step because it will provide input on how to evaluate the success, the learning methodology and optimization strategies post-launch.
This step is owned by the engineering teams, but this step should entail having regular meetings with both UX and data strategy to ensure that the assumptions they are making are in line with the overall vision from UX and data strategy.
This is also where the AI starts to learn from the team.
Part of defining conversation flows requires defining trigger words in order to move forward in the task. These are documented in the user flow, and are launching points for a task.
During development, UX can conduct usability testing. The classic task-based metrics (effectiveness, efficiency, and satisfaction) are still relevant here, in addition to qual research (in-home ethnography, surveys, interviews, etc.) to learn how customers respond to the design in context.
Data strategy should be listening in to how the AI is progressing over time. If it is not producing the anticipated results, the data strategy expert will need to evaluate why. It may be because the dataset is biased, it may be due to the training dataset not being reflective of the task at hand.
Once the issue is identified, the data strategy expert can make recommendations as to how the dataset should be modified.
Also in this phase the data strategy expert should be outlining a measurement strategy for how the AI will be evaluated based on its current progress. Datasets that will evaluate the performance also need to be built into the development phase. This measurement strategy should include workflows and resources needed to update the AI as it encounters new phrases, as this can be a manual process post-mvp launch.
Voice-based AI is a product that needs constant optimization to not only ensure that it continues to work as anticipated, but also to keep audiences engaged.
If the experience starts to lose it’s initial utility or becomes repetitive, the usage of the product will plummet. Teams should be monitoring and optimizing based on the workflows outlined in the data strategy to ensure the sustained quality of the product.
In addition to refining the design, UX can provide insight into why any failures may be happening.
Was there an insight missing from the define period that changed the perspective of the utility of the conversation? Or is there a technical failure happening? Is the developed conversation mismatched from what was designed? Maybe the personality feels off.
All of this needs to be caught as soon as possible and translated into any new requirements for refinement.
To get deeper insight, UX should review transcripts from all conversations had, as these will provide rich qualitative data to help understand how the product is performing.
The data teams should be analyzing the number of failed conversations, understanding why they failed and making recommendations on how to teach the AI based on these conversations.
This is when the measurement strategy workflow outlined in “Develop” is working.
The data strategy team member will likely need to ensure that the work flows are increasing in efficiency overtime through monitoring the AI KPIs. This is what will lead to continuous optimization of the product infinity loop.
The qualities of voice-based AI defined in this process result in the underlying identity of a brand.
It’s a high impact touchpoint, that when it goes wrong, goes really wrong.
Though, it also has the potential to reach people in new ways. It is the personification of a brand and has the potential for businesses to create new relationships with their customers.
To protect your brand from a potentially high-risk situation, partner your UX and Data Strategy teams together.
By Shayna Stewart | July 2nd, 2019
Omni-channel — it's one of the most overused terms in our day, and one we should all agree to sunset.
I respect what it was trying to explain when it was first coined in the early 2000s (or before?) — to be on all channels, all the time — but so much has changed since then that the concept is obsolete.
In the context of the best strategies out there today, to be “Omni-Channel” is a HUGE mistake for two critical reasons:
What you really need is a Smart Consumer Experience (Smart CX for short).
Let's see why.
Presenting your brand on all channels all the time is a highly inefficient way to gain eyeballs. While it may boost impressions, it won't lead to desired actions.
An omni-channel approach is often what brand use when they don’t know how to reach their customers or potential customers.
Smart CX is the anti-omni strategy, challenging brands to know where their customers or potential customers are and come up with a curated strategy around reaching them.
The best way to uncover how to reach customers with the lens of Smart CX is to root your product strategy in a custom consumer journey. In this work you will uncover the broad steps someone will take to a desired action (most likely a purchase in the space your brand is in).
Within each broad consumer journey step, you should outline the customer's needs, motivations, and their emotional highs and lows to empathize with what your potential customer will go through each step of the way.
Being everywhere at once is inauthentic. That's why omni-channel feels automated. Customers today have an amazing bull***t radar. So to be there for your customers when they need you most is the sweet spot.
Have you ever said outloud, or even thought, “I’m now entering the Facebook channel.” No, because people don't think in 'channels,' and brands shouldn't either.
The main issue with a channel strategy is that people don’t necessarily discern between a website or finding information from a post or blog. Information is information. It needs to be served up when it’s relevant, not hidden or confined to a specific channel.
Employing Smart CX means carefully creating a system for the information that is provided, when it is provided, and in the best experience to provide that information. Consider these tools with regard to information delivery:
You can think of your Smart CX strategy as well curated art shows. You put thought into the artists that were chosen, the diversity of art mediums, the specific walls where the art is hung, the types of attendees you will invite, and the flow of the attendees throughout the space during the main event.
There's process. There's intentionality. And there's a desired result.
In order to innovate, you need a framework to help benchmark yourself against industry standards. This is where defining Smart CX components becomes important.
It can be used to evaluate your current product and your upcoming feature list so that teams can understand if the product is adhering to best practices (in this industry, this means customer expectations).
Here’s how the best practices shake out.
This can be a difficult one for people who are experts in their respective fields. Often times what’s important to an expert is not important to a layperson. In fact, details that are important to experts typically detract from the decisioning with a layperson.
There are two pillars that fall under simplicity:
Robinhood is a new player in the online trading industry. They built their experience around making it easier for young people to get into trading by removing barriers to entry and an exceedingly simple design.
Their insight was that the current companies make it difficult for new-to-be traders to understand how to trade, therefore, keep people out of the market.
Robinhood's business strategy was going after those people who wouldn’t have entered the market, but what ended up happening was that 75% of their user base were already traders on other platforms.
So how was it that they cannibalized their competitors market share, given that wan't part of their original business strategy?
The key was their sleek, intuitive designs along with plain and simple English. You can see within their trading flow that there is minimal information provided and the screens are broken up so that the trader can process one step at a time.
When directly compared to eTrade, there is an extreme language and visual difference:
eTrade has a cluttered interface chock full of highly technical terms and visual elements that are important only to the likes of day traders.
It is important to also note that simplicity can go against legal regulations as just seen in the failed launch of Robinhood’s latest product.
Robinhood wanted to offer a checking account that earns interest. That’s what they communicated to their customers, which was likely the simplest way to explain what the actual product was. They ran into major legal issues because the account was not a checking account, but rather a Certificate of Deposit account.
In this case, it’s important to understand why you cannot have the most simplistic language and work around that.
The best way to have a contextual experience is to make sure the content triggered tees up the answers to the questions a person is asking themselves at the time they are asking.
This becomes difficult in practice if:
But it’s not impossible to create a contextual experience when going up against these barriers.
Take Delta for example.
While it's likely one of the most complicated backend implementations, Delta only shows the customers what’s important to them in specific, triggered moments of time. Delta has many inroads to purchase a ticket, but once someone has searched for a flight they offer up the custom experiences tailored to the person’s search results. They do this by using a combination of persistent, user-declared data location and time-based business rules.
Here’s a typical contextual communication log from Delta:
What changes about these communications from person to person is the city they are traveling to, frequent flyer status, notification preferences, and location.
They aren’t with the traveler throughout his/her entire trip, just for the moments when the traveler needs Delta.
Delta zeroed in on those moments and flawlessly executes this strategy, so much so they have been recognized as industry leaders in innovation.
Automated decisioning can be done via predictive analytics or machine learning, but it is not exclusive to advanced analytics: filling out form fields ahead of time, mobile payments, and package options are all examples of automating decisions.
Think of it as anything that helps lighten the mental work that goes into making a decision.
Much of this rests on collecting persistent customer data and tracking behavioral preference data. Once the right data is being tracked, automated decisioning can be built by creating business rules on the backend or from leveraging advanced analytics. This goes beyond simplicity and goes into the psychology of helping people make decisions.
Fewer options, in this case, equates to Costco’s way of automating decisions, making grocery shopping more pleasant.
Once you stop thinking in terms of channels and start thinking in terms of behavioral triggers and consumer journey moments, you can start to build coordinated experiences.
This all starts from a solidified customer journey map that contains emotional highs, lows, task-based mindsets and gaps in content with the current experience.
From there you need to plan out how marketing and the experiences move the potential customer through that flow. Below is an example template that YML created to help outline how the experiences need to be coordinated around the customer experience.
Marcela Lay, YML's VP of Client Strategy, lays out her step by step “How To” complete this research.
Once this framework is outlined, you can use it as a basis for diagnosing the coordination across all of your touch points.
The omni-channel strategy may once have had value, but the evolution of consumer behaviors and product experiences means moving away from this outdated format. 'Always on' is out.
Smart CX represents a vital transition for businesses intent on building lasting relationships with their customers.
By Stephen Clements — June 25, 2019
Talking about good customer experience is easy. It’s just doing it that is hard.
You’d think it’d be easy for me to talk about it because I have spent the last 15 years talking about it to people who do it every day — clients and designers.
And I have often wondered why is it that all these hours get spent — often on conference calls or in long meetings — by people trying to do the same thing, but in constant disagreement about how it should be done.
A colleague of mine, his wife works as a United flight attendant. That's not her below 🙂
His wife says that on every trip, without fail, at least one customer complains. And they are so bitter, so vitriolic, and they get so angry that they say things like:
“United is the worst.”
“You have just lost yourselves a customer.”
“I am never going to fly United again.”
But she smiles professionally, all the while thinking:“Of course you will. You will go on Kayak and you will pick the cheapest option—you will consider your milage plan—and I will see you next time.”
In short, improving the customer experience sounds cool, but it will no doubt raise the cost of a United flight. And this might actually turn off more customers than it’s worth.
I was recently having dinner with my wife, and she asked me, “What are some of the questions you have been asked a lot by clients recently?” (A fun date night, right?)
Well, I thought, something I have been asked a lot is,“Yeah, yeah, yeah. This customer experience thing sounds cool. But how will it move the needle?” I have been asked this question in many different ways. By many different clients. At many different organizations.
And, look, I get it. No one wants to invest in all this trendy customer experience goodness, but not see any actual results. Or worse still, see negative results, and they get fired.
For example, I was at a meeting with the head of e-commerce from a major airline, and he said to me that their most vocal customers — the ones who complain the most bitterly — are in fact the ones that are most profitable.
Probably because they have to pay extra for all the things they didn’t plan for—extra bags, extra legroom seats, extra food, etc. Which got me thinking.
First-of-all, is all revenue good revenue? And is it worth putting short-term profits ahead of long-term customer lifetime value?
It has taken me many years as a designer to reach this state of business-minded enlightenment. And finally I have come to the conclusion: Clients don’t actually hire us to make their customers happy. They hire us to make their businesses better.
*And sometimes (sometimes) it’s the same thing.
Now, I realize this might strike you as a little odd. I mean, is this a creative person giving us a business lecture? Just please stick with me.
You see, in the beginning — when I was a young and idealistic designer — I wanted to make things that were beautiful. I wanted them to be just drop dead gorgeous. And I didn’t care about much else.
I call this my aesthetic design phase.
All I wanted to do was create porn. Not real porn. Visual, aesthetic, product porn — and I was lucky to get to do this for brands like Nike and Xbox.
Then, as my career matured, I began to develop more empathy for people. I wanted to create experiences that helped people, were loved, and talked about. Experiences that tackled really high-value life moments, like shopping for a car — like the work I did with Audi, or buying a house — like work I led with Trulia.
I call this my experience design phase.
And then, when I matured again, I developed a deeper understanding for the clients I served. I began to appreciate and better understand their decision making process, and how they are optimizing to make more money.
I wanted to create experiences that solved real business problems — which we proudly did here at YML by doubling The Home Depot’s mobile revenue in one year.
I call this my business design phase.
I think all great designers must go through this evolution. It is the holy trinity of design.
First it was aesthetic problems.
Then, experience problems.
And lastly, now it’s business problems.
Designers that don’t graduate along this path… well usually, they fall short of their promise, and their careers are stunted. They aren’t opening their minds to this business imperative.
Some years ago, I was given some advice to buy my clients’ stocks on Robinhood — a beautiful, designer friendly app, if you don’t know it. I bought just a hundred bucks worth, here or there. I bought Nike. I bought Activision. I bought NVIDIA (that one went gangbusters). I’m definitely not a power-investor, by any measure, but it gave me valuable insight into my clients’ world — the business of business.
At YML we did work for First Data on their Clover point-of-sales system, and a year ago I bought some of their stock. It’s been quite a ride, but I have nearly doubled my money.
Now, I am no expert in macro-economics, but that trough on the right of the graph pretty much happened all across the stock market — because of the China tariffs, the fed raising interest rates, reports of economic slowdown, and maybe the Mueller investigation, too.
Right at the bottom of that trough we had a meeting with the head of the Clover team. It didn’t go too well. She was obviously distracted and when she was engaged, she was asking very tough, business-minded questions. Maybe it was bad timing, but it was also a reminder of how significant business realities are, each and every day.
In the past, I have heard promising designers, sometimes Creative Directors even, saying things like:
"Money is evil."
"Business is for other people."
Clients...they just don't think like us." (But, of course, they all still want a raise, come review time.)
And it is true, most clients don’t think — or talk — like us. Or real people, for that matter. Imagine if they did.
I mean, I don’t know about you, but as a real person, I often find myself wishing there was more info.
Or, looking for a solution that is more scalable.
And, who isn’t absolutely thrilled when they fall into the correct user segment?
But designers aren’t any better.
They are just different.
I mean, that must be an awesome Kleenex site!
What I have learned, over the years, is that clients and designers are often talking about the same thing. But they come at it from different angles.
It's like they are speaking different languages. It leads to a lot of disconnects, frustration, lengthy meetings, and rather cantankerous conference calls.
Let me tell you a true story. Many years ago, I was on an hours long conference call to discuss a website with a client. And we were talking round in circles when this happened.
"I want you to uplift the branding quotient," the client said.
"Do you mean make the logo bigger?" one of our designers asked.
"Yes" the client said.
And that is a true story.
It’s a perfect example of where we are talking about the same thing in different ways. And it’s this sort of disconnect that makes it a lot harder for anyone to actually buy or sell work. Therefore, I find my day job is partly to play the role of translator.
As translator, I have spent years helping clients understand designers, and I help designers understand clients. And I have discovered it works like this.
Designers love to create simple, human, 1:1 experiences. They obsess over all the small details, crafting quality experiences that connect with people on a personal, emotional level.
And clients, well, they love scalable, enterprise-ready solutions that are 1 to many. They, quite rightly obsess over how it will make them a gajillion dollars.
But, of course, these things aren’t at odds. They are 2 sides of the same coin, and they have mutual benefit. Each one makes the other better.
It was this realization that has led me to not only be a better consultant to my clients — because I learned to speak their language — but it also made me a better designer — because I learned to understand their business.
The business of business.
It might seem obvious, but design is a tool for making businesses better.
We are not artists. Plain and simple.
At Y Media Labs — where I am the Chief Creative Officer — we have this way of thinking built into our DNA. And every day, we strive to use our superpowers of strategy, design and technology to make a lasting impact.
A lasting impact on the people that use our experiences. And on our clients’ businesses, too.
1 to 1. And 1 to many.
Formerly co-founder of Junior: the Rapid Invention Company, a product design accelerator for big brands, and before that, Executive Creative Director for AKQA, San Francisco, Stephen has over 15 years industry experience working at the top of the game. An accomplished product design and innovation leader, he created breakthrough work for brands such as Activision, Anheuser-Busch, Audi, eBay, Jordan, Levi’s, NVIDIA, Verizon, Visa, Xbox, and YouTube to name a few.
By Shawn Murphy-Hockett | June 20th 2019
June. It’s a month filled with color. Nature is inviting, nurturing, and allowing of all things different. It’s as if Mother Earth is begging us to celebrate her multicolored world. Vibrant flowers bloom. Warm sunshine clears the air.
And, in most places, rainbow flags sway in the breeze.
Throughout the month of June it’s becoming more and more common that people across the US, and the world, recognize Pride; a social movement rooted in commemorating the 1969 Stonewall Riots, a turning point in our country's LGBTQ+ history dedicated to promoting the self-affirmation, dignity, and equal rights of this historically marginalized group.
This colorful flag has gone through many revisions over the years but is now internationally recognized as the common symbol of the Pride movement.
It’s a significant, powerful moment each year.
But the way I see it, why should we limit ourselves to recognize Pride only one month out of the year?
It’s incredible that this singular event has garnered so much support, attention, and recognition for what PRIDE aimed to do — promoting equal rights, building an alliance for the LGBTQ+ community, and celebrating sexual diversity. And it continues to evolve, now a giant festival in cities across the world. Pride has become a party — maybe the best one of the year (If you haven’t been out in the Castro yet, I 100% guarantee you will have one of the best nights of your life).
I’m grateful to have always felt safe, included, and wanted whenever I’ve walked into a gay bar. And the gay community doesn’t have to be welcoming to outsiders like me. If you think about it, I’m the one that is ‘invading’ their safe space.
Now - imagine that the entire world doesn’t feel safe for you to be your true authentic self.
What does this basic cis-gender straight white girl know about inclusivity when it comes to the LGBTQ+ community? Not enough.
I grew up in a very liberal, albeit, hippie household where my brother and I were always told that it didn’t matter the sex, race, socio-economic status, nationality, etc. of the HUMAN we loved. That doesn’t mean my parents still didn’t ask me all of the naive questions about my brother marrying a man. They meant no harm, they were honestly just curious about how this whole “gay-marriage” thing works. I am so grateful to my parents for being open-minded and loving their children no matter what, as I know that a lot of my friends were not so lucky.
Which is why as an adult, I’ve made it a personal goal that wherever life takes me, both personally and professionally, my environment must feel like home.
This is exactly why I chose to grow my career with Y Media Labs.
I knew it was right for me as soon as I finished my interview. Y Media Labs has an unconventional hiring philosophy. While hiring for fit is the norm, YML insists on hiring people who don’t fit, but rather come in and add to the culture through their differences.
This is all rooted in the idea that our culture is constantly evolving, and that while change can be hard, it’s vital to growth. The same culture of inclusivity and celebrating diversity that reverberates through the Pride movement lies at the foundation of YML.
There are three new projects specifically in place to help pursue, identify, and celebrate our differences more so than ever before.
Our newly established ‘Women’s initiative’ meets once a month to listen and learn from a fellow member’s presentation with topics such as confidence, culture, and women in the tech industry.
‘Passion Projects’ invites employees into the more unknown talents, backgrounds, and hobbies of their fellow co-workers. This can be anything from holding a wine tasting to learning about someone’s past life in a traveling circus (hasn’t happened yet, but a girl can dream).
Finally, we will be reigniting ‘Listening Sessions’ to have a safe place for those deep conversations about topics such as LGBTQ+ rights and safety in the workplace. The goal is to gather the team and create allies around how we can ALL do better to achieve foreseeable outcomes.
So, I’m challenging you to make a lasting impact. Make it a point to care. Openly. Colorfully. Lovingly. And not just in June. By observing our differences, we form a rainbow each day. For each other. For ourselves. For our values. Let’s hold ourselves accountable.
Together we can, and we will find a way to make the world a little more proud.