In Part 1 of this series, I covered some outdated design strategies that businesses still employ. Then in Part 2, I discussed how businesses could leverage big-data analytics to improve their UX design strategies and optimize them for the modern consumer.
Now, in Part 3, I’ll describe the role of data-driven UX design strategies in helping businesses to grow. What are the advantages of implementing such strategies? What is the impact of these strategies on businesses’ overall process and performance? How do they help augment growth for brands?
The Role of Data-Driven UX Design Strategies in Helping Businesses Grow
Big data is assisting businesses in creating robust, personalized surveys that help them gather accurate information. This information provides the basis of informed business decision-making that helps brands mold their design strategies to best fit their target audience.
Another advantage of leveraging big data is businesses’ ability to use predictive analytics to model valuable insights from what they learn about their customers. They achieve this through the Customer Lifetime Value Model and Customer Segmentation Model.
Big data also empowers businesses to make use of run-time analytics and analyze customer behavior based on predefined metrics such as the most frequently used features. This helps businesses optimize their platform based on the evolving needs of their target audience.
Eliminating Trial and Error Through Informed Decision-Making
Part 1 of this series highlighted the problems with trial-and-error–based UX design strategies. With the advent of big data, businesses can improve their brand’s performance, both in terms of financial improvement and their customer outlook.
Big Data Saves Time
According to a study by Bain & Company, organizations spend 15% of their collective time in meetings. While meetings are not necessarily bad, they can contribute to a lot of wasted time—especially if teams are not making data-driven decisions during meetings.
Big data supports much more straightforward, strategic decision-making in UX design. Thus, teams spend less time in decision-making meetings.
More importantly, big data saves time by reducing the number of UX design iterations that are necessary to finalize the design for a product. Conventionally, businesses design the user experience, test usability internally, then decide whether the design works. Teams iteratively make design changes when coming up with a new version of the UX design, then conduct more testing. This cycle repeats until everyone is satisfied.
Big data lets you map out the best UX design based on industry standards, optimize your UX design process, and bring efficiencies to your business.
Big Data Shortens the Product-Development Cycle
Avoiding trial and error shortens the product-development cycle. Whether you’re developing an application or any other product, you need the length of your development cycle to be as short as possible.
Relying on big data ensures that you have enough time to test products before releasing them, enabling you to adhere to project timelines. It also lets you provide additional value to your customers, who are often looking for quick solutions.
In my experience, product-development cycles often get extended because of a lack of certainty about or confidence in your knowledge of customer preferences. Big data lets you fill that information gap with the help of surveys and run-time analytics. This makes your operations more precise, giving your UX architects the information they need to design a top-notch user experience in a short timeframe.
Benefits of User-Centered Design and Personalization
In addition to big data’s organizational and operational benefits to a business, its role in UX design provides customer benefits. Run-time analytics is a key component of big data and plays an important role in achieving these benefits.
For example, through understanding customer-behavior and usage patterns, you can prioritize the development of certain functions over others—for example, the accessibility of your platform. Now, let’s look at the positive business impacts of big data regarding your customers.
Today, all companies should regularly update their platforms to improve the user experience. Companies can iteratively make small tweaks or bigger changes to cope with the evolving demands of customers
Customer demands are always in a state of flux, so making constant updates and changes is crucial to business success. What big data has made possible today is real-time understanding and analytics of customer demands. This lets businesses keep their platform in line with customer demands, making it more likely they’ll retain their customers. In the absence of this data, platforms risk becoming stale. Big data lets you keep your product fresh.
The broader principle I’m highlighting here: there is no such thing as an optimal UX strategy. User experience is demand-oriented so needs to change very quickly. A UX strategy that works in the modern world lets you make iterative changes based on accurate data. That’s the value big data provides to businesses today.
The digital world is competitive. There are many alternative products, providing maximal choice for customers. Therefore, businesses must go the extra mile to ensure they can outperform their competitors.
The benefit of leveraging big data is that it lets you evolve your platform in a way that reflects the needs of your target audience. The message that sends to your customers is that your brand listens to the voice of the customer. This perception is crucial in establishing a positive relationship with your customer base. It’s hard to do this without big data. How do you get this data? I discussed that in Part 2 when I covered different data models and their workflow.
Big data lets you establish positive customer relationships and ensures that your platform delivers an optimal user experience that is based on your users’ actual needs rather than on your perceptions and assumptions.
Defined Metrics for Prelaunch UX Analysis
I’ve already discussed how big data helps you make informed decisions during the planning and development phases. Now, let’s consider the business benefits of big data during the prelaunch phase.
Here, I’m referring to performance data. Predictive models can do more than just predict customer behavior. You can analyze data and predict time-based targets for performance indicators.
For example, if you’re doing something to improve your Web site, you need to know exactly how much difference it can make. You can do this through competitor data that lets you assess their growth. Data from other noncompeting businesses lets you use their Web site to generate more traffic and leads.
Similarly, you can track performance metrics for UX design updates—such as minutes per session. Once your UX design changes go live, these metrics play a vital role in identifying whether your prelaunch UX analysis was accurate. They give businesses an accurate understanding of the success rate of the UX changes, helping them improve their decision-making in the long run.
For businesses, there are numerous benefits of implementing data-driven UX design strategies—whether directly to the business or to the consumers of their products. Big data enables your platform to evolve along with evolving demand and, depending on your business model, make sure your business always caters to either the majority of your customers or your premium users.
Without data-driven UX design strategies, the kind of guesswork and trial and error that takes place at companies is often detrimental to their growth, time consuming, and inefficient. The likelihood that a business would miss crucial details is high. Big data has made it possible for businesses to tap into the minds of their customers and deliver user experiences that guarantee user retention and elevate business performance.
Asim is a tech entrepreneur with more than 14 years of experience leading development and design teams for all types of digital properties. His special technical expertise is on formulating frameworks for highly functional, service-oriented software and apps. As CTO at Tekrevol—an enterprise technology–development firm offering disruptive services in the app, Web site, game, and wearable domains—Asim is responsible for reviewing and mentoring all development teams. He is also an industry influencer and has offered his views on technology at multiple conferences, eseminars, and podcasts. He is currently focusing on how technology firms can leverage 4th-generation technologies such as the Internet of Things (IoT) and machine learning to unlock top-notch business advantages. Read More