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You might have heard of the $300 Million Button, in which UX designers discovered a simple flaw in their e-commerce form that was preventing hundreds of millions worth of purchases. Or the failed Snapchat redesign that led to the company’s slowest user growth rate ever.
At one point, bad user interface once cost Citi a half a billion dollars.
In this blog post, you’ll read about some of the underlying design practices that, at the very least, impact revenue and cost. At the most, they can lead to the kind of outcomes that make headlines. You’ll also learn how a practical design framework helps minimize UX mistakes significantly, if not eliminate them altogether.
UX relies heavily on a tacit value: trust. People use (and continue using) products because they trust that the product will create value in their lives—at the right time and as promised. That it will:
Trust building has significant business benefits. What McKinsey calls “digital trust leaders” are 1.6x more likely than the average business to see minimum 10% revenue growth rates. They’re more likely to enjoy higher customer loyalty rates, too.
Then again, it doesn’t take much to break this trust. According to Zendesk Benchmark Data, 50% of customers will switch to a competitor after a single bad experience; 73% will switch after multiple bad experiences. It’s happening, too, particularly for software firms: a recent Bain & Company survey showed net revenue retention rates down 75%.
If we understand trust as the “cumulative outcome of consistent, reliable experiences throughout the customer journey” (Journal of User Experience) then it’s easy to see how UX mistakes can erode this trust. UX and customer journey go hand in hand. When the customer journey degrades to the detriment of revenue, it might be worth verifying what role UX might be playing.
Here are some of the more common revenue-killing UX oversights that we see:
It’s not uncommon for designers to rely on assumptions. Sometimes, those assumptions are safe. For instance, it may be safe to assume that not all users share the same level of physical or cognitive ability.
Other assumptions require more thorough validation, especially as they relate to user needs/wants.A designer might assume the user wants less complexity, for example, when in fact the user needs the product to do more. They might assume the user needs speed, when in fact the user needs to slow down and focus.
Example: the mobile-first design paradox
Most design teams assume the need for mobile-first design. After all, 70% of the global population uses a mobile phone. Yet mobile-first design can degrade desktop experience. What if a significant portion of the user base still relies on desktop? And what if that portion is large enough for this negative impact to turn them away?
It might be a rarity, but it’s risky to assume your users aren’t the exception to the rule. By the time the design team sorts out why engagement, conversion rate, and renewal rate are down, the revenue damage may have already been done.
Sometimes UX teams release products or updates that overlook the ways their core user base has long interacted with their products. These usage habits might be the reasons those users fell in love with the product in the first place. Is it safe to assume that users will make the adjustment?
UX teams might also sunset a certain feature, or end support/compatibility for certain devices and operating systems, with a similar result. Think of the team tasked with replacing an embedded live-agent support option with an AI chatbot: what happens if users are so used to the old support method, that the new bot falls short?
The results can be costly: globally, organizations risk $3.7T annually due to bad experiences.
Example: Apple Patreon
Recently, Apple decided to force Patreon users to use its in-app purchasing system. Yet Patreon’s user base had grown accustomed to Patreon’s more flexible, “creator-first” system. What’s more, Apple decided to tack on a 30% App Store fee for these transactions. Perhaps Apple made peace with absorbing the blowback to that UX decision; still, they risk alienating a significant part of their user base.
A UX design choice may add considerable benefits—even justifiable revenue benefits—that do not outweigh the friction that they create for the user. If our goal is to keep a user engaged with a digital product, for instance, or to convert once we have their attention, why introduce a roadblock to that goal?
That roadblock could be as simple as a link that opens in a new window, or as disruptive as a required third-party process, which requires users to leave an app to complete an in-app task.
Example: pre-purchase upsells
On paper, inserting an upsell into your pre-purchase checkout experience makes sense. Yet another opportunity to boost average order value (AOV), right? So your app developers design an upsell that offers complimentary products right before checkout.
While the intention is to increase order value, the execution may inadvertently create friction in the checkout process. All of a sudden, cart abandonment is up, while conversion rates are dropping.
Why?
Let’s say your AOV is $100. With 50,000 monthly visitors and a 2% conversion rate, your store generates $100,000 in revenue. Implementing pre-purchase upsells may increase your AOV by 10% ($110 AOV). But what if it ends up reducing the conversion rate to 1.8%? That’s an annual revenue loss of $12,000.
Poor or shortsighted UX choices can have downstream repercussions that affect sales, support, success, and overall operations. It’s often these departments that must respond to how customers react to flawed design. Responding to that reaction may incur significant cost.
Product teams and their designers routinely work with customer support. At least they ought to. The support team can, for example, map categorized cases to specific products and features. This data can alert the product team to problematic releases or updates. The product team can also rely on to inform UX design decisions before releasing them.
Surprises are what teams try to avoid. When an update or release causes a spike in support cases, it does more than impact contact center costs: the problem compounds when the support team doesn’t have the resources/knowledge to provide timely, relevant help.
In the effort to transform support from a cost center to a value center, UX clearly has a role.
Example: in-app license verification process
Let’s say users who purchase or renew a consumer anti-malware product receive a license key. To activate the premium version of that product, they need to enter the license key within the F5 settings of the product. In all previous versions of that product, and as documented in the knowledge base, this setting was located in the same area of the settings tree.
Now, the UX team has moved license activation as part of a settings-tree overhaul. Customers expecting to find it in one place cannot. What’s more, new users referring to existing documentation (still documenting the old process) also cannot. This causes a costly spike in volume that the support team can trace back to this minor product UX change.
Cost overrun is a common problem in UX design. For example, the UX team builds in complexity that drives up product development costs, eating up more budget on a product than the product ends up generating. Or, UX design decisions lead to recalls, rework, product overhauls, support cases, and training needs that further inflate costs.
It already costs a lot to build a great product. Almost every unvalidated UX decision contributes to product development costs, however incremental the contribution.
The be-fast-not-perfect approach can have consequences. When quality design loses out to speed of delivery on the priority list, technical debt can accumulate. The tech world already has a $2T technical debt problem.
Today, technical debt accounts for about 40 percent of IT balance sheets.
UX-related causes of technical debt
When designing and building products for customers, our team relies on a practical framework to audit and optimize design for business impact. This framework is designed to minimize the UX mistakes that can end up affecting cost and revenue.
Begin with a comprehensive UX discovery and evaluation process. This approach ensures that design aligns with user needs and business goals. By thoroughly investigating the current state of your UX, you can pinpoint areas of friction, inefficiency, and user dissatisfaction, setting the stage for targeted improvements.
Your discovery, evaluation, and audit may include:
Collect and scrutinize user feedback through interviews, surveys, and usability testing to gain insights into real-world usage and user satisfaction. This qualitative data complements quantitative metrics, providing a well-rounded understanding of your UX performance. For example:
Unlock the insights in the data you already have. Leverage large datasets to make, test, monitor, and iterate on hypotheses for different UX decisions. Will that newly designed setup workflow increase engagement? Better to rely on the data than guesswork.
You can also apply a data-driven approach for organizational efficiency. Data science and engineering can reveal operational bottlenecks, opportunities for proactive support, and untapped growth strategies.
Facilitate early and frequent user feedback, allowing teams to make essential adjustments throughout the development process. By prioritizing user needs and preferences, iterative design ensures that the product remains aligned with actual user expectations and market demands.
Through small, incremental changes driven by user feedback and data analysis, businesses can steadily enhance their UX, leading to improved user satisfaction and business outcomes.
For example, rather than completely redesigning UX, some teams opt for refactoring. Refactoring means reworking existing design or code without changing how it fundamentally works. Read more about refactoring vs. redesigning.
Align design efforts with business objectives and back them with robust technical implementation. By involving diverse stakeholders—including design, engineering, product management, support, success, and sales—you take a more holistic approach to UX.
We find that collaboration between design and engineering is particularly important. It can help avoid some of the revenue killers associated with UX mistakes, such as product delays, cost overruns, and technical debt.
To maximize the impact of your UX framework, consider partnering with experts who specialize in delivering business-driven design solutions. Transcenda's team of experienced professionals can help you spot and fix hidden UX mistakes, ensuring that your digital products deliver measurable business results. Contact Transcenda to learn more.
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