Automated – Pavvy Designs

Automated User Testing – sometimes referred to as Automated UX Testing – is increasing in popularity as ever more complex ways to test UX become available.

But what is Automated User Testing? And should you be doing it in your business?

Automated UX testing: a definition

Automated User Testing is essentially the automation of manual test tasks. Usersnap defines it as “simply when you and your Quality Assurance team use scripted tests that have been prewritten and run automatically.”

Recent advances mean that there is now some incredible UX testing software available that has been specifically developed to automate the whole testing process, allowing designers and developers to work with remote participants, gather data and identify where improvements can be made at every step of the design process.

What are the benefits of automating user testing?

It has long been accepted that UX should form an essential part of the design process.

In fact, Creative.onl was writing nearly three years ago about the importance of using a UX specialist to design your website or mobile app.

So UX testing as a vital part of the design process is a given. But what about being able to automate this testing? And what are the benefits – to both your business, as well as the end user?

1. A more efficient use of resources

Automating any process is usually done to save time. And automating user testing is no exception.

Done properly, once it has been set up, automated UX testing should lessen the demands on both people and time, allowing you to reallocate resources to resolving any issues that automated testing throws up.

2. A more cost effective way to test UX response

It should follow that if automating a process saves time and human involvement, it ought to save money too. And by and large, that should be the case once the initial investment in the software and setting it up has been taken into account.

Don’t forget that the ability of this type of software to, for example, identify bugs very early on in the process can also save much needed expenditure that may have been incurred if it was otherwise overlooked in manual testing.

3. The ability to test a greater number of variables in a shorter amount of time

There is no denying that machines can be faster than man. And automating your user testing allows you to run more test case variations in a shorter period of time than you would using manual testing alone. These tests can, for example, cover areas such as multiple browsers, multiple operating systems, screen resolutions, mobile devices and connection speeds.

4. The chance to simulate thousands of virtual users and shorten the development cycle

Collaborative design platform, Marvel App, sees automated user testing as an invaluable opportunity to “can simulate hundreds, if not thousands, of virtual users, simultaneously, that is before you let the real ones in. Making sure that your application is durable and shortening your development cycles.”

5. Elimination of human error

Unlike people, computers never tire of repeating a task or analysing data, meaning that automating your user testing not only allows you to process high volumes of data, it also helps eliminates human error.

Are there any disadvantages to automated user testing?

Despite it benefits, automated UX Testing is not necessarily the best solution for everyone.

The initial investment in both time and money in setting up the testing software can be prohibitive for smaller companies or smaller projects.

And no matter how good the software, it is only as good as the way in which it has been programmed.

As Usersnap points out “An automated test does what you tell it to do. And it will stick to it no matter what. There is no way to find out errors or bugs that are not defined by your testing scenario.”

Usersnap goes on to add “Thankfully humans are not replaceable by computer programs (yet). Your automated tests will not be able to find UX flaws or Design issues that only can be seen by a human eye.”

So it’s worth giving careful consideration to the pros and cons of automating your UX testing before you commit to any hefty investment.

Deciding whether to automate your testing

Deciding whether to move from solely manual testing to incorporating automated testing may well depend on a number of factors, which have been helpfully summarised in the box designed by Usersnap below.

They suggest simply circling your answer to each question and then totalling up the number of answers for the automated column and the manual column. The advice is that the largest total will more than likely be the best testing method for you now.

How to start automating your user testing

1. Examine what you’re already doing

Take a look at what you do now, ideally with a fresh pair of eyes. What UX testing processes do you already have in place? How effective are they? And can they be automated? Objectivity is key here.

2. Ensure your UX testing is aligned with your business’ KPIs

It is only when your company has clearly defined business goals that you can know how automating your user testing might help achieve them.

Your user testing should therefore tie in to your strategic goals, giving you valuable data through which you can assess whether or not your organisational aims are being met.

3. Make sure you have the right tools for the job

This might be an obvious point but having the right tools for the job is essential. Not all software is created equal and finding the right one for your business may take time. But it will pay huge dividends going forward.

Make sure your user testing software has the kind of automation functionality that meets your needs. Whether that’s gathering both qualitative and quantitative data, filtering your results or enabling you to share your findings with your key stakeholders, it is worth ensuring taking the time to ensure your UX software works for you.

4. Share your findings with your teams

It may take a cultural shift within your team to appreciate the value of agile UX testing. But including key stakeholders along the way and sharing your progress as you go will help your team better connect with the end user at all stages of the development journey.

Looking for help with automating your user testing?

Automation is surely the next step for UX testing and understanding which software is right for you as well as how to incorporate it into your existing UX testing processes is a big consideration.

Whether you are a small local business or a large corporation, Creative.onl can help you decide how best to automate your UX testing in order to get more accurate feedback more quickly.

Creative.onl are a small and friendly team based in the East Midlands, with expertise in the following areas:

App development
Web development
UX design
Digital strategy
Responsive web design
Graphic design
Video animation
Content
Marketing support

And we would love to help you with any aspect of automating your user testing when it comes to UX design.

Whatever you are looking for, get in touch with us to talk through the creative processes of any of our services and products.

Across industries and in nearly every vertical, AI is driving digital transformation. In sales, for example, 70% of US-based professionals are now using some form of AI at work. In marketing, platforms like IBM’s Watson Marketing, Salesforce Commerce Cloud, and Pega’s Unified DMP are bringing brands closer than ever before to their customers. Project scheduling optimizers for engineering, telecommunications AI that recognize early signs of churn, and personalized gaming experiences based on in-game data are just a few of the ways AI is disrupting major industries today.

AI is no longer the exclusive domain of massive enterprise with equally outsized R&D budgets, either. Intelligent automation is now accessible to even the smallest of businesses; call it entry-level AI, if you will. From full-service marketing platforms like MailChimp for SMBs to individual standalone tools like EyeLevel.ai and LivePerson’s Maven, AI-powered martech opens the door to a world of cost savings, new revenue and enhanced customer experience.

For marketers of all skill levels and disciplines, the time to become AI-proficient is now.

How AI is changing the automation game

Martech evangelists are having an easier time getting buy-in lately; after all, inefficiencies cost money – as much as 20 to 30 percent of an organization’s revenue each year. While a Walker Sands report found 33% of marketers said they faced internal resistance to martech in 2016, just 27% experienced the same in 2018. CMOs have realized the benefits of using automation to reduce manual labor, execute repetitive tasks, and respond to opportunities in a more timely way. As of May 2019, for example, more than 70% of advertisers were using Google automated bidding strategies.

Obviously, efficiency and scale are great benefits in themselves, but it’s when you layer Artificial Intelligence on top that digital gets truly interesting. This is where the magic happens. Automation and AI are no longer the new kids on the block, but together they’re maturing and truly testing the limits of what’s possible. Machine learning has grown in leaps and bounds and, as C-level executives have bought into its potential, has been given more latitude in actually making decisions and executing operations based on data.

Take warehouse robots, for example. Perhaps one of the most recognizable early applications of intelligent automation, these machines zip around warehouses picking and packing orders. In 2012, Amazon started a retail arms race by acquiring Kiva Systems and cutting off the warehouse robot supply to competitors Walgreens, Staples, and more. Kiva became part of Amazon Robotics, a company that in its own words, “…automates fulfilment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands.”

But they aren’t the only player in the game. That earlier decision to strip competitors of their technology made way for innovators like 6 River Systems, a startup founded by former Kiva engineers. Their robot, “Chuck,” is designed to engage associates, keep them on task, and boost human productivity. They call it a “directed approach,” where humans are in control of and aided by their collaborative robot partner.

Vecna Technologies has been making medical robots and software for two decades, but just got into the warehouse robots game, as well. Their self-driving warehouse vehicles use machine learning to continually optimize workflow and improve human performance, as well.

Warehouse operations and order fulfillment are just one area in which humans and machines are learning to work together, but it’s big business. In fact, warehousing and logistics robotics is an industry expected to reach a market value of $22.4 billion by the end of 2021 (Tractica).

In warehousing, AI and deep learning are successfully enhancing human productivity, optimizing workflows, and improving customer experience. In B2B, intelligent automation is creating entirely new revenue streams.

DIFM service is an excellent example of humans and tech working together

While intelligent machines are being empowered to make some decisions, marketers’ jobs are not in danger – at least, not those who are willing to learn to work with them. In fact, intelligent automation can act as a great complement to and even dramatically improve human performance, when used… well, intelligently. What’s more, humans can enhance the value of a software application by specializing in it and helping others reap the greatest benefit from using it. Some have referred to this opportunity as the “Do It For Me” economy.

Anthony P. Lee, Managing Director at Silicon Valley venture growth equity fund Altos Ventures, explained in a TechCrunch column: “DIFM combines technology automation with specialized labor to deliver a complete solution to a business problem. It’s as much about people-powered customer service as it is about code-powered efficiency.”

For some, DIFM is creating new revenue streams. Rather than software-as-a-service, each using automation complemented by a secondary level of human expertise – deliver software-with-a-service. In making experts available to power the machine, they help customers get the maximum value possible from the program.

DIFM is not an entirely new phenomenon, but the tech-powered evolution of business process outsourcing or managed services. Once reserved for the wealthiest and largest brands, the new managed services are a hybrid of intelligent automation and specialized human services that deliver both the scale and expertise it takes to meet consumers’ heightened expectations.

Intelligent automation is forever changing the way we work

Concerns over robots displacing human workers are not entirely unfounded. As workflows evolve and repetitive tasks are automated, those jobs will indeed disappear for humans. But as Yaro Tenzer, co-founder of the mechanical hand order picker RightHand, argued to the Boston Globe, “People cannot find enough labor to do these jobs,” said Tenzer. “They call us and say, ‘we cannot fulfill orders. Can you help us?’ ”

Those with the technological savvy to work alongside the machines – to ensure they’re given good input, and to decipher and maximize their output – will increase their own value as employees.

At the executive level, a tangible and active commitment to digital transformation is the only way forward. According to KPMG, just 20% of firms surveyed said they are beyond the pilot stage and ‘up and running’ with their AI efforts. Organizational uncertainty around how to get started, integration, and workflows abound. With transformation comes a great deal of disruption, and business leaders must be able to navigate and move past it.

The cost savings and improved efficiency of successfully implemented AI are a bonus, but should not be your primary goal. From a more holistic perspective, intelligent automation can fundamentally change how your organization operates – from improved customer engagement to driving growth and creating entirely new areas of business.

In martech, this means developing the technical skills to maximize the machine’s output, while still nurturing the creativity that underpins the best marketing campaigns. It means succeeding in an area where many currently fail: integration (KPMG also found that only 10% of respondents are integrating solutions across automation, AI, and smart analytics).

It means moving quickly to coordinate efforts and getting rid of piecemeal AI efforts that may achieve one objective but do so in a vacuum.

Most of all, the AI revolution requires of marketers that we find synergy between our talent and technology; that we embrace our place as hybrid marketers. Learn more about developing the skills required of an AI mindset here.

Opinions expressed in this article are those of the guest author and not necessarily Marketing Land. Staff authors are listed here.

About The Author

Andy has over 15 years experience in formulating marketing, digital and content strategies for many of the world’s leading brands, agencies and technology pioneers. Andy works closely with CEO and CMO thought leaders, executives and technology partners on strategic marketing, digital and content marketing strategies. He has also spends considerable time consulting, and travelling across the World, for many digital and content marketing technology startups — working on research, event and publication projects. Andy has worked at the C-level with leading brands such as HP, Google, Facebook, Twitter, Apple, Microsoft, HSBC, United Airlines, Adobe, Apple, American Express and Fidelity International. He has also consulted on digital marketing projects with many of the world’s leading agencies such as Publicis, Aegis, Starcom, Digitas, Zenith Optimedia, GroupM and WPP properties.

What is automated user testing, and should you be doing it?