September 12, 2019

Why Consumer-Centric Strategies Need the Right Datasets

By Shayna Stewart | September 12th

You deserve a big pat on the back if you have successfully shifted your Product and Executive teams to a consumer experience driven mindset — one that prioritizes empathy for the consumer in the product experience.

However, after all that work educating teams and setting up new processes, your Product and Analytics teams are likely experiencing a little bit of friction.

The growing pains occur because the datasets are not evolving as the questions are evolving from business-centric to consumer-centric:

  1. Analytics teams get stuck operating only within the business analytics and marketing analytics paradigms.
  2. Consequently, they have a tough time getting into product and consumer-centric analytics paradigms.

Obsessing over customer satisfaction is a good thing — and a proven game changer for brands across the spectrum.

Often, teams that switch to the consumer experience mindset, accidentally mistake business or marketing data for product data, so you’ll need to stop focusing on quantitative behavioral data.

Here’s how.

Consumer-centricity is tough on data structures

This mostly has to do with when the way data structures were built:

Data structures are a function of the questions you ask.

Historically, the business data sets are the oldest. They were built to answer questions like, “How much money am I making and how many paying customers do I have?

Marketing data sets were introduced to answer questions revolving around campaign performing, reach and impact.

Most companies stopped building data structures beyond those two. Now, brands across the spectrum are struggling through an obsolete system attempting to answer key questions for both marketing and business development teams.

You might be wondering:

How it is possible that we are lacking data sets in a day in an age where the amount of data is increasing exponentially by the second?

Another great question! 🧐

The reality is that data needs a particular structure to answer specific questions. Typically the data is being captured in an unstructured way, and then needs to re-structured to answer critical product and consumer-centric questions.

Evolving Your Data Set

Building these data sets is a cross-functional team sport. It’s a sport because it requires coaching, practice and can create a bit of rivalry across the teams to create a great dataset.

Step 1

👉 Have a clear and concise consumer-centric strategy.

Consumer-centric strategies need to have a consumer journey that is informed by consumer feedback and consumer need based states as the user moves through the consumer journey. Once this is done, make sure that everyone is aware and agrees with this strategy.

The consumer-centric analytics will fail if people start to waver on how much they agree with the strategy, as analytics is meant to provide feedback on how well the strategy is performing.

If people start to disagree with the strategy or follow a different strategy, then the consumer-centric analytics framework will not provide information on how well the strategy is performing.

Step 2

👉 Build your KPI structure from the ground up, starting with consumer-centric KPIs first.

Your consumer-centric KPIs should be descriptive of your consumer’s need based states you identified as a strategic play in your consumer journey research. They also should be predictive of your business and marketing KPIs.

Step 3

👉 Identify the differences between the business, marketing, product and consumer-centric questions.

We recommend that an analytics team member categorize the questions that they get asked on a regular basis. Even further, start to categorize which teams are asking what questions.

This will help set up your data democratization strategy later on. Not everyone is interested in receiving answers to all categories of questions. For a refresher of the different types of analytics, check out this article.

Step 4

👉 Select the right tools and/or update your implementations to ensure all questions are answered.

The consumer-centric questions will always be the hardest to answer as they require the most complex data capabilities to answer. Therefore, your requirements should be led by the consumer-centric analysis requirements and then work backward to ensure your tools can answer the easier three.

In conclusion

There are some key requirements that everyone must have in place to truly have a consumer-centric data set:

  1. Access to data that is summarized around users, not around visits or pages.
  2. A strategy to link user data across platforms, meaning an identity resolution system
  3. A plan and commitment to build cohorts of users and develop for customized marketing and product experiences based on those cohorts

Shayna is a Product Manager who is passionate about consumer-centric product strategy, design and an advocate for consumer-directed data strategies to match.

July 29, 2019

Stuck in the “Paradox of Choice”? Use Recommendations to Build Better CX

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:

  • Spotify has over 50 million tracks in its catalog (Source: Spotify Newsroom)
  • Etsy has over 60 million items listed on its site and (Source: Etsy’s SEC Filing)
  • Netflix has anywhere between 2000 to 6000 titles based on your region (Source: Quartz Atlas)

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.

Reduce decision-making complexity

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.

Source: Uber Eats

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:

  • The “popularity” widget lets the users make a quick decision by surfacing the most popular content and also shows awareness of context by taking the user’s current location into account
  • The “freshness” widget surfaces new and possibly little-known places for users who like to try new places — in a marketplace, this ensures that new restaurants get sufficient visibility and that the “rich don’t get richer”.
  • The “recommended dishes” widget uses the signals captured about the user to jump from restaurant-level recommendations to item-level recommendations and
  • The “offers” widget surfaces attractive offers for a value-conscious customer

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.

Create diversity and serendipity

It is easy to fall into the trap of using implicit and explicit signals to only recommend items with a high probability of purchase.

While an e-commerce site may actually be doing this for certain items to increase repeat purchases, customers allow very little leeway for inaccurate recommendations and find them redundant and un-intelligent. 
Source: Twitter

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 creates up to six “Daily Mixes” with personalized content
Source: Spotify

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)

Source: Twitter

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.

Think outside of the core product experience

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.

Source: Netflix Mobile
Source: Netflix Desktop

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.

Evaluate downsides and create feedback mechanisms 

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!

About the Author

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 2, 2019

“Omni-Channel” Is Over: Every Business Needs A Smart Consumer Experience

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:

  • Firstly, it does not make sense to be on all channels broadcasting disconnected information about yourself.
  • Secondly, the word “channel” doesn’t make sense to use anymore because that is not how your customers view the word.

What you really need is a Smart Consumer Experience (Smart CX for short).

Let's see why.

Smart CX: the Anti-Omni Strategy

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.

Smart CX: To understand your customers, think and talk like them

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:

  • If a user already has your app, then generally you should surface information through that property.
  • If a user has no knowledge of you, you should have a strategy to answer their specific question, likely through web property.
  • In addition, you should also have a good answer as to how your app and web properties work together.

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.

The Four Components of Smart CX

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.

1/Simplistic: Is this the simplest way to convey my content?

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:

  1. Language that is easy to understand / non-expert specific jargon (unless your audience is an expert audience);
  2. Design in which only the most important is shown.

Take Robinhood vs. eTrade for example.

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.

2/Contextual: Am I serving up the right content given the mindset of the user?

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:

  1. You have many marketing tactics that are not using complex exclusion logic;
  2. The industry has a long sales cycle or there are barriers to switching providers;
  3. Your company has many different products, thus different entry points to bundling product.

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:

  • Notifies of changing flight prices
  • Ticket confirmation email
  • Things to know about your travel to the upcoming city
  • Flight status
  • Baggage updates
  • Boarding updates
  • Call center reps who can complete the same tasks as the at-counter reps
  • Immediate social responses to complaints

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.

3/Automated Decisioning: Is this helping potential customers make a decision?

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.

We saw this from Costco’s rationale for stocking only 4,000 items, compared to other grocery stores stocks over 50,000 items.

Fewer options, in this case, equates to Costco’s way of automating decisions, making grocery shopping more pleasant.

4/Coordination: Are all of the parts talking to each other?

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.

June 25, 2019

Don’t Overthink It: Design is a Tool For Making Businesses Better

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.

Funny right?

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.

June 11, 2019

6 KPIs That Will Convince the C-Suite to Obsess over Customer Satisfaction

By Marcela Lay | June 11th 2019

We are well into the experience economy: that's where customer experience has overtaken price and product as the key brand differentiator.

So it's hard to believe that brands today continue to create self-centric project briefs and request for proposals without any customer-centric KPIs.

Self-serving KPIs only allow for a myopic view of the desired results.  

So what's the recipe for success?

  1. Get alignment from the c-suite on the right mix of customer-centric KPIs to ensure organizational adoption.  
  2. Align expectations on long-term results instead of the unsustainable short-term results some companies chase.

Let’s break these two key concepts down - after that, you’ll be one step closer to being a customer-centric business.

1 / How do we get C-Suite alignment?

First, you need to understand the stage of customer obsession in your organization.

It's one thing to want your organization to enhance your customers' experience, but it's quite another to put it in practice.

This requires a shared Customer Experience Vision and Strategy to drive the decisions made by the leaders of each department when moving forward.

According to the 2017 eConsultancy guide around customer experience best practices,  is the silo mentality that brings a significant obstacle when getting buy-in on customer experience improvements.

The only path to break organizational silos is to get the C-Suite to buy-in into Customer Obsession, so alignment and adoption are instilled from the top-down.

And you can only get the C-Suite to listen when you speak their language:

You need to understand what matters to each executive, what they measure, and a set of CX metrics that can prove ROI.

Let's analyze the critical stakeholders and what matters to them.

Critical Stakeholder: CEO

What matters the most to this executive: Company vision, competitive position, and growth.

Supporting information:

A Forrester research confirmed how CX leaders lead over CX laggards on both stock price growth and total returns.

Critical Stakeholder: CMO

What matters the most to this executive: Brand awareness, engagement, loyalty, and advocacy.

Supporting information:

  • CX Leaders drive 4.5x willingness to pay a price premium from customers who have excellent experience versus very poor experience - Forrester.
  • Consumers with an emotional connection to a brand have a 306% higher lifetime value, and will recommend brands at a much higher rate (71% vs. 45%) -
  • 61% of loyal customers go out of their way to buy from specific brands, and 60% will make more frequent purchases - InMoment
  • Tempkin found a correlation between CX and trust, as well as consumers’ willingness to recommend a brand.

Critical Stakeholder: CIO

What matters the most to this executive: Technology innovation.

Supporting information:

  • According to a research by Deloitte, CIOs from High-Performing Companies (HPC) generally focus on CX as a competitive differentiator more than their peers.
  • According to a report released by Dimension Data, the virtual assistants (chatbots) were voted the top channel growth focus for 2017 while the deployment of the Internet of Things (IoT) was set to double.

Critical Stakeholder: CFO

What matters the most to this executive: Long-term growth and ROI.

Supporting information:

On Harley Manning’s Blog at Forrester, Manning discusses two studies, conducted one year apart, where five pairs of publicly traded companies were compared and where a company in each of the pairs had a remarkably higher score than the other based on Forrester’s Customer Experience Index during the period 2010 to 2015.

  • “In two industries, cable and retail, leaders outperformed laggards by 24 percentage and 26 percentage points, respectively. Even in the industry with the smallest spread, airlines, the CX leader enjoyed a healthy 5 percentage point advantage in global revenue.” — Harley Manning, Forrester
  • And according to Forrester’s Harley Manning, "a one-point score improvement in the CX Index can lead to an increase of $65 million in revenue in the upscale hotel industry."

2 / The 6 Customer-Centric metrics that demonstrate ROI

While business leaders default back to the most commonly used KPIs, there is a set of KPIs that can indisputably demonstrate the ROI in CX improvements.

These KPIs do a great job balancing out the self-centric business KPIs your company is tracking today.

Let’s take a look.

The fault-back KPIs:

  1. Net Promoter Score (NPS): NPS measures customer satisfaction and loyalty to a brand. It doesn't directly quantify the ROI of CX improvements, but only captures customer intent and visibility into issues.
  2. Customer Satisfaction (CSAT): It measures customer satisfaction to understand if the brand is meeting customer expectations, it can provide visibility into customer pain points.
  3. Conversion Rate: The percentage of total customers who transacted. How easily did the brand make it for the customer to convert?
  4. Customer Effort Score (CES): Determines the amount of effort a customer required to accomplish a task. The CES is a highly actionable piece of customer feedback.

Here are the KPIs that can balance out the self-centric business KPIs:

  1. Customer Lifetime Value (CLV): A long-term metric that supports sustainable results. The longer a brand retains a customer, the more revenue will be generated. Businesses with 40% repeat customers generate nearly 50% more revenue than similar companies.
  2. Customer Retention Rate & Customer Churn Rate: If the brand is not able to retain customers over time, a close look at the experience must be given.
  3. Up-Sell and Cross-Sell Rate: If the brand is providing an excellent experience to its customers, the customers will spend more in return. It is that simple.
  4. Average Order Value  (AOV) & Average Revenue per Customer (ARPC): The more effortless the experience, the more revenue the brand will generate per customer and order.

And then, of course, the Customer service KPIs:

  1. First Response Time (FRT): The longer the time, the more frustrating it is for the customer and the bigger the opportunity to improve the process to show the customer we value their time.
  2. First Contact Resolution (FCR) Rate: The percentage of customers whose question or request is resolved on the first attempt. How simple and friction-free are we making the process?
  3. Resolution Time (RT): it assesses how many interactions are necessary to resolve a customer issue; it brings visibility into the customer pain points and the potential areas for improvement.

In conclusion

Being a customer-centric business is a proven strategy for driving long-term success. To achieve that success, make sure to:

  1. Lean into the critical stakeholders at the c-suite for support as it is at the crux of CX transformation.
  2. Define and track the right KPIs that demonstrate CX improvements ROI.

Once you get the c-suite to listen and to align to Customer Obsession, move to identify the necessary technology, people, and process required to achieve those goals.

May 23, 2019

YML Partners With FinTech App, Earnin, on Customer Experience Development Work

YML announced Wednesday its partnership with Earnin, the Fintech payday advance app.

YML will work closely with Earnin to create a category defining digital experience in the coming months.

Earnin helps workers track and cash out wages in real time. The YML work will focus on the development of their mobile app, which is built to aid workers in getting paid as soon they leave work with no loans, fees or hidden costs.

YML is committed to advancing the cause of the gig economy, and working with Earnin exemplifies that effort.

May 15, 2019

YML Partners With on Customer Experience Design Work

YML is ecstatic to be partnering with Tom Siebel and the team to produce category defining customer experience design work. C3 is the leader in how to bring digital transformation across massive organizations, and we believe this work will be transformative for their brand.

Read more about the partnership here.

April 17, 2019

3 Reasons Why “Loyalty” Is an Outdated Strategy (Focus on People Instead)

By Shayna Stewart

BONUS MATERIAL: Who's winning at customer-centric strategies? Discover the strategies of leading brands.

Loyalty: the holy grail of all company metrics.

This makes sense -- the more people who continue to purchase, the more profitable a brand is.

However, loyalty as a strategy is a self-serving strategy that removes people’s needs and desires from the equation altogether.

What brands should focus on is creating people-centric strategies that provide long term intrinsic value in order to generate loyalty.

When brands use the word loyalty, they are typically referring to one of two things:

  1. A points system offered to repeat customer that results in discounted prices
  2. A business goal that refers to keeping people coming back to make a purchase

These constructs of loyalty are now outdated and the progression away from “loyalty” as a strategy has been happening for sometime.

Those that are leaders in loyalty are aware that loyalty as a strategy is dead, but the construct of loyalty that a person may have to your brand is very real.

In this article, we dive deep into why loyalty as a strategy can hurt your business and does not actually promote loyalty from real people, and how you can get started on a people-centric strategy to reconnect with your customers.

Table of contents

  1. Why loyalty points erode loyalty
  2. Loyalty as a strategy focuses on the past, not the future
  3. Loyalty as a strategy is not a people-centric strategy
  4. How to get started on a people-centric strategy

1 / Loyalty points erode loyalty

Brands are competing on consumer experience as opposed to pricing.

Historically the way brands captured market share, and what most of us learned in our economics books, is to reduce the price of your product in order to trigger demand for your product.

What this traditional framework does not account for is delivering upon a superior consumer experience.

In fact, we are seeing that people are willing to spend even more money for the exact same product with brands that have a superior consumer experience, which is an extreme deviation from our 101 economics books.

If you think that offering people discounts will sway them to buy from you compared to a competitor that has a superior experience, you will be sorely mistaken.

Intuitively, the price of a product is not the first thing you think of when thinking of superior brands - because pricing is table stakes these days. People just expect fair pricing for the value that is being provided previous to the purchase, and post-purchase.

The reasons the winners are winning is not because of a cheaper price, but because they provide superior connected digital and in-store experiences throughout their customers’ journey.

This concept is not new:

B. Joseph Pine II and James H. Gilmore published the first inkling of this concept back in 1997!

Below is how they framed up creating superior experiences as opposed to competing based on price for making goods or delivering services.

Source: Harward Business Review

There’s a new breed of companies that have changed the way consumers interact with their category altogether, all of which build their products with consumers' needs in mind first and the business second. This category is not represented in the framework above.

Think Uber, Etsy, Ebay, Amazon, any mobile banking app.

These brands and technologies have revolutionized their respective markets so much that they have shifted consumer expectations, which captured market demand without pricing playing a role. In these cases, the pricing strategy in terms of point systems or discounts came after they have proven the intrinsic value from their product.

Telling people that your product is cheaper is not a good long term strategy. Discounting your price via rewards points or continuous sales will erode the consumers perspective of your brand:

You become the “cheap” brand.

2 / Loyalty as a strategy focuses on the past, not the future

Loyalty as a strategy does not promote proactive optimizations to the product.

If return visitors are on the rise, then what is there to change?

People’s expectations are constantly changing. A simple UI improvement in an unrelated industry could become the standard for all industries (think the Like button from Facebook, which single-handedly changed review ratings forever).

The brands who are doing it right, know that they are never safe and therefore should always improve their digital presence.

They spend a significant amount of money doing so too.

Jeff Bezos recently said “Amazon is not too big to fail”. This is coming from the CEO of the brand that spends the most money on research and development in the tech industry.

If you feel you are in a safe climate where your return visitors are increasing, know that your success will not stay for long without the continuous optimization from your product teams.

In case you are experiencing a decrease in return visitors, loyalty tactics that typically will benefit your product will actually counteract increasing return visitors.

Counteractive Loyalty Tactic #1: Double down on core users

This tactic is great, particularly for new to market products, but in the case you have been available to the market for a while, this is counteractive to your long term growth.

Focusing solely on optimizing the product to core users will emphasize features that were already showcasing value to a small group of users instead of understanding what value to showcase to capture a more expansive return audience.

Counteractive Loyalty Tactic #2: Increase conversion for new users

At surface level this makes sense, you are trying to provide value to a new user by ensuring they have access to the product or service you are trying to sell.

This tactic does not improve loyalty long term if your product or service is not showcasing the value.

Think of Netflix:

they increase new user conversion rate by offering a free one-month subscription. Imagine that their product doesn’t showcase the value of paying for it in the first month, they would see a complete drop off in return visitors past that month.

If your product is not showcasing value to the users, then a conversion isn’t valuable to the business in the first place. In addition, this is a highly gameable metric as it’s possible to increase the conversion rate by offering steep discounts.

Which actually promotes a degradation in the brand perception.

Counteractive Loyalty Tactic #3: Spend more on marketing

Reaching new audiences is always a goal, but if your return visitors are declining, this tactic won’t fix anything; it will just decrease your marketing efficiency.

This doesn’t fix the problem because it does not address the product enhancements that need to happen in order to create the stop gap.

Andrew Chen summarizes this nicely, saying that you have to be customer-friendly, platform-friendly and product-friendly before you start on a marketing strategy.

Otherwise, this tactic is just throwing money at the problem without addressing the problem head on.

If you find yourself optimizing your product when the trends are not going your way, you are optimizing from a losing spot in terms of customer expectations. This is what a loyalty-centric strategy will produce.

To get ahead of this you need to adopt a people-centric strategy:

A people-centric strategy will allow for your product pivot as soon as the market changes and if you're lucky, create the pivot in customer expectations.

3 / Loyalty as a strategy is not a people-centric strategy

The key is to not focus on “loyalty” per se but to focus on the intrinsic motivations of why someone would want to come back; In other words, adopt a people-centric strategy.

Intrinsic motivations describe an innate reason for a person to perform some action: they are doing something because it feels good to do it.

Think about studying hard for an exam.

Some people may do it just for the A, which is an extrinsic reward. But some people may do it because they are generally interested in learning about the topic.

The latter would be an example of an intrinsic motivation, where someone does something because they just want to, no reward needed.

Designing around intrinsic motivations is where brands must spend all of their time because, ultimately, that will lead to a person's’ long-term engagement aka loyalty.

Can you remember the last time that you told yourself or your friends that you are going to be loyal to a brand?

No, you can’t because people don’t think like that.

The way you think to yourself about why purchasing or using a brand again is usually about:

  • Was that easy for me to use?
  • Did the product do what it said it did?
  • Was I able to contact service reps easily?

If the consumer answers yes to these questions, then the brand is successfully answering to intrinsic motivations (note: none of which have to do with price).

Unlocking a great people-centric strategy means you are leaning into the custom intrinsic motivations of why people would love your product.

4 / How to get started on a people-centric strategy

If you find yourself in this losing battle of loyalty as a strategy, there’s still hope.

Adopting and acting on a people-centric approach will enable you to pivot their digital product as quickly as consumer expectations change.

Here’s what you have to do:

First, get the team together to hypothesize more broadly around what is motivating someone to seek this product out.

Secondly, you must think through what are all of the questions that someone may have when understanding if this product is right for them.

This will help ensure that all of the content is succinctly and accurately answering the questions that someone needs answers to prior to purchase.

Lastly, the brand must make sure that as the consumer is qualifying, purchasing and engaging post-purchase that each step is delivering upon exactly what the person wants to achieve.

If you frame up your strategy with this framework you can quickly identify areas that consumers are most interested in and understand why.

This is the difference in being proactive vs. reactive where you understand what behaviors predict repeat visits as opposed to just monitoring if repeat visits are up or down.

Start thinking in terms of how people think.

If you do that your strategies will supersede market expectations, which will get you your desired outcome in the end, which is a growing group of long-term customers.

Want to see the people-centric approach in action? Check out how brands using people-centric approaches created wins and losses in their industries.

April 9, 2019

6 Ways Artificial Intelligence Can Deliver Superior Customer Experience in 2019

WHITE PAPER FREE DOWNLOAD: How are the most prolific companies using AI to deliver a better customer experience?

Last year, PWC named AI as one of the eight essential technologies in business and 38% of businesses employed AI in its systems.

That percentage is expected to grow to 62% this year.

IDC estimates that the AI market will grow to be more than $47 billion by 2020, and Gartner predicts “more than 40% of all data analytics projects will relate to an aspect of customer experience.”

Let's see how customer experience and Artificial Intelligence are blending together to deliver superior customer needs and increase customer satisfaction in the years to come.

Table of contents

  1. Are we delivering empathetic customer experiences?
  2. The shifting battleground: CX
  3. AI and the zettabytes of data
  4. Six types of AI engines helping brands create empathetic CX
  5. The next steps for brands

Are we delivering empathetic customer experiences?

Ever lost or misplaced your phone? Or how about the time when your computer or hard drive crashed and there were key files and data you hadn’t transferred yet to the cloud?

Remember how distraught and helpless you felt?

Now imagine if the customer service person you come in contact with was an imperious know-it-all? Imagine how that experience would add to the mental and emotional strain you already felt. Imagine how you would perceive that brand moving forward? In moments like these, it’s true that you want someone to fix your problem, but more importantly, you want someone to listen and acknowledge your distress.

Apple understands this all too well. The company includes an empathy guide in its training manual for frontline workers providing customers with device support in Apple retail locations.

Source: How To Be a Genius: This Is Apple's Secret Employee Training Manual

The training manual teaches Genius Bar employees how to assess what the customer needs based on their body language, and even suggests phrases to use depending on the customer’s specific needs at the time, like “I can appreciate how you feel…” which is a suggested phrase listed in the manual.

Today, nailing the consumer experience means going above and beyond, taking the time to understand customers, and applying insights to every aspect of the business, from new product development to call center training to designing a comprehensive user experience. The only way that businesses can do this effectively is by having actual empathy for the customer experience.

Here, we define empathy as a brand’s ability to experience their own product or service from the point of view of their customer.

There is no current shortage of brands claiming to deliver empathetic customer experiences.

But have we as an industry actually delivered?

According to Bain & Co., 80 percent of companies say they deliver 'superior' customer service — however, only eight percent of people think these same companies deliver 'superior' customer service.

The shifting battleground: CX

These harsh realities have made customer experience the new battleground at the top of business agendas today.

But while budgets and platitudes may continue to focus on CX inside boardrooms, the speed of technological change and the ephemeral wants and needs of consumers make this a quickly moving target.

And it’s easy to miss.

Consider how we got here: the modern manufacturing age — roughly between 1900 and 1960 — was marked by few pools of capital able to fund and maintain factories. As a result, the marketplace saw little legitimate competition, and an oligarchy of industrialists owned much of the global supply chain.

Source: Forrester

Starting in 1960 there were transformative changes to the industry, highlighted by globalization, deregulation and free trade deals that made it possible to manufacture goods more cheaply in other parts of the world. Even though customer experience were still important, it was price and distribution that were the real decision-makers for customers.

Then, in the 1990s, information and technology became readily available and accessible to the average consumer. This Information Age brought with it a shift in power dynamics, from sellers to buyers as customers now had information to easily compare brands.

The customer experience became a part of a business’s product and service — part of research & development, content marketing, public relations, social media, mobile presence and usability, and website design.

Today’s connected life — there are 4.3 billion mobile phone users worldwidewill see mobile experiences as the key touchpoint for businesses. Modern consumers want a seamless and integrated digital customer experience that ties into various devices and screens.

Source: Accenture

That means everything in the customer experience, from targeting to messaging needs an empathetic approach. Accenture found out that 44 percent of customers are “frustrated when companies fail to deliver relevant, personalized shopping experiences”.

Consumers today are increasingly less forgiving after a bad experience:

According to a study by WOW Local Marketing, 52 percent are less likely to engage with a company after a bad mobile experience — that includes everything from poor design, missing content, and even slow loading times. In Right Now Technologies’ 2011 Customer Experience Impact report, nine out of every 10 customers said they would walk away after a poor customer experience to conduct business with a competitor instead.

But it’s not all dire news. Studies have shown that customers will pay more for a better experience. After all, how many of us have paid for a more expensive airline ticket because we prefer the experience we have with a particular airline? Study after study show that good customer experience will boost even your stock value:

CX is an opportunity.

Source: The Customer Experience ROI Study

Businesses that truly understand the demand for empathetic design in the customer experience know that they can’t do it with human help alone. There’s just no way for humans to deliver against these expectations. Forward-thinking companies are turning to machine learning and massive data to make better decisions on their customers’ behalf.

According to IDC’s 2016 Worldwide Semiannual Cognitive/Artificial Intelligence Systems Spending Guide, the market for cognitive/AI solutions is expected to experience an annual growth rate of 55.1 percent between 2016 and 2020.

Using the powerful combination of AI and data means businesses have a better chance of giving customers exactly what they want — and even preemptively anticipate their needs before they’re even aware.

It’s this kind of empathy from brands that deepens trust and keeps customers coming back.

AI and the zettabytes of data

Think about how much data is produced everyday, from photos to videos to songs to text messages. The total amount of data in the world was 4.4 zettabytes in 2013 and that number is expected to rise to an astronomical 44 zettabytes by 2020.

To put this in perspective, one zettabyte is equivalent to 44 trillion gigabytes and to break that down even further, one gigabyte is enough data for the books needed to fill a

30-foot shelf. That’s a lot of collected data.

So how can companies make sense of all the information, especially considering most of it is unstructured?

They can’t. Not with human employees in real-time anyway.

In short, this means that brands that stand out during the customer journey have to turn to artificial intelligence to personalize experiences by identifying areas that are relevant to individual customers.

If empathy is all about understanding and being aware of and sensitive to the experience of another, then empathetic customer experiences should be focused on recognition and responsiveness.

Six types of AI engines helping brands create empathetic CX

Empathic thinking requires thinking the right systems in place so that you can proactively respond and resolve issues that come up at the speed of human expectation. While only a few brands employ empathic design well, the ones that do should serve as examples for the rest of the business world.

Below, we’ve listed six examples of AI engines that help brands transform the customer experience through empathetic designs.

WHITE PAPER FREE DOWNLOAD: How the most prolific companies in the world are using AI to deliver a better customer experience

1 / Recommendation engines

Recommendation engines are probably the most common form of machine learning and currently used largely in online retail and media industries and rely on algorithms based on the customer’s past behaviors and patterns. Like receiving a gift from a friend who really knows you. Brands implementing recommendation engines connect the massive data they collect to personalize every aspect of the customer experience.

Perhaps the most influential recommendation engine in the world today is YouTube’s Recommended Videos on their infamous right rail. Of the more than ONE BILLION hours of Youtube we consume, fully 70 percent of it comes from these algorithmic modules. That’s a lot of cat videos, man.

Source: YouTube's AI is the puppet master over most of what you watch

In the future, we could see recommendation engines more prevalent in industries with vast amount of data like healthcare, where AI can help personalize care by taking into account patient history, lifestyle information, medical records, and more. Algorithmically recommended treatment courses, or specific prescriptions are not out of the question.

2 / Predictive Searches

Predictive Searches allow web visitors to get results faster by automatically populating results while the user is still typing. Typically, there is a drop-down list that pops up during the search, which guides users to potential results. When thinking of predictive searches, most of us think of Google’ Autocomplete invented in 2004. Then, in 2010, Google’s search technology expanded to include Instant Search, which uses machine-learning to predict what it thinks you will type, simultaneously streaming results for those predictions in real-time.

Many brands have since adopted Google’s original technology, but there are some drawbacks. In 2017, Google announced that it would drop instant search as its default setting given most searches are now done on mobile, and loading results for predictive searches on a limited screen ends up being a poor user experience.

A Google spokesperson said at the time:

“We launched Google Instant back in 2010 with the goal to provide users with the information they need as quickly as possible, even as they typed their searches on desktop devices. Since then, many more of our searches happen on mobile, with very different input and interaction and screen constraints. With this in mind, we have decided to remove Google Instant, so we can focus on ways to make Search even faster and more fluid on all devices.”

Even after developing an empathetic design — Instant Search — Google continues to find ways to be even more empathetic by thinking about how the product can be fast and fluid on all devices, for all users!

3 / Virtual Assistants

Virtual Assistants, like Amazon’s Alexa, Microsoft’s Cortana, Apple’s Siri, and  Google Assistant, range from chatbots to more advanced systems that are changing what customer engagement looks like.

  • Google Duplex is a new capability of Google Assistant that can make calls on your behalf and book your next hair salon appointment or table at your favorite restaurant for you. And the person on the other side of the phone won’t even notice she’s talking with a bot.

Source: Google Duplex: An AI System for Accomplishing Real-World Tasks Over the Phone

Virtual assistants are definitely a growing niche, so why have only 10 percent of enterprises in the U.S. employed a virtual agent? Mainly because there are still a lot of challenges that can interfere with the digital customer experience. For instance, while virtual assistants are improving greatly with natural language, most of them are still far behind humans when it comes to understanding slang, typos, misspellings, or complex grammar.

4 / Natural language processing

Natural language processing is AI that can process massive amounts of natural language data and can therefore, understand human speech the way it is spoken. When thinking of NLP, an Amazon Echo often comes to mind with its voice recognition, but NLP’s technology holds promise in a lot of industries, including healthcare where it can help with faster diagnosis by finding patterns in a physician’s unstructured notes. Think of how many lives can be saved with AI mining our health records!

Think about Skype Translator, that can understand several languages at the same time, in real-time, which can encourage conversations between people who speak different languages.

5 / Sentiment Analysis

Sentiment Analysis evaluates voice inflections to determine the emotions, attitudes, and opinion in normal human conversation to determine what’s actually being said.

Vibe is a product created by Tokyo-based software company AIR that can scan conversations on workplace communication tool Slack to determine team morale. The product analyzes keywords and emojis used during conversations and places the team’s mood into five emotions

At YML, we used sentiment analysis to understand which company is loved the most: Uber or Lyft?

Source: Uber vs Lyft – Who is loved more? A deep dive analysis using Google’s Sentiment Analysis API

6 / Computer vision

Computer vision uses machine learning models to teach computers to see things the way humans see them.

A company doing a great job is Uru, that uses computer-vision to find spaces in videos where native advertisements can appear to create a non-obtrusive, uninterrupted, more organic experience for users.

For instance, the company’s algorithm identifies spaces, like a blank wall or the board of a snowboarder, where ads or brands graphics can appear. The startup has caught the attention of the industry’s top accelerators and investors.

The next steps for brands

The rise of the internet has provided us with various ways to communicate and interact. Even brands now communicate with their consumers through multiple platforms and channels, so it makes sense that customers expect you to “get” them.

After all, customers know brands are tracking, personalizing, and optimizing every step along the customer journey, so why shouldn’t they be more empathetic to CX? With so much competition out there, the only way a brand can have a competitive advantage is by maintaining an obsession with customer experience.

Once a brand has determined that they want to create empathetic experiences, they need to then do two things: (1) focus on results, and (2) focus on small wins.

When focusing on results, brands should identify the tasks they want to tackle first, then determine the optimal technology to help them accomplish those tasks.

This can get a little tricky with various AI technologies competing in the market, from machine learning, chatbots, virtual assistants, robotics, natural language processing (NLP), and much more: in order to achieve business goals, businesses need to think about the big picture, then work backward.

For instance, if your customers want 24/7 support, then it might be worth it to invest in a chatbot experience so customers aren’t waiting to get through to a human employee. Or if customer satisfaction seems to be an issue, consider a technology that can take the data you already have and connect them with what customers may need, based on their individual preferences. Customer satisfaction will surely improve if businesses present relevant recommendations rather than spewing out random offers.

Finally, brands need to focus on small wins if they want a chance at any of the big wins.

How do you know which small win you’d like to tackle first? Identify the low-hanging fruit. What complaints are you getting the most from customers? Tackle that area first.

As soon as you’ve identified the problem, it might be tempting to use AI to solve dozens of issues right away. This is not the best way to start improving customer retention quickly. Instead, if you want to make the most impact, you’ll want to tackle what’s easy to measure and achievable first.

In other words, think big, start small. What small wins can you achieve in the next few weeks or months?

AND NOW LEARN MORE: How are the most prolific companies using AI to deliver a better customer experience?


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