Eggplant Blog

Software Testing in a Voice-Driven World

10/1/19 / by Antony Edwards posted in User Experience, software testing, User experience testing, voice recognition software

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Over the next four years, Gartner predicts that 25 percent of employees will use voice to interact with applications in the workplace—up from less than 2 percent in 2019.   

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Shift-Up to the Edge

4/3/19 / by Michael Giacometti posted in DevOps, QA testing, User Experience, User experience testing, testing best practices, artificial intelligence, digital automation intelligence, QA, shift up, AI-assisted testing, user acceptance testing, usability testing

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"The quality of your company’s software has a direct impact on the quality of your company’s financial results. You know it. Management knows it. And the importance of quality will only continue to grow with the need for 24x7 operations, high availability requirements, aggressive service-level agreements, and the need to roll out innovative new web-based services."

This was the first paragraph of a paper I wrote in 2005 about how to build your organization around a Testing Center of Excellence.

15 years on, we are still struggling with these concepts. The focus has turned towards project outcomes rather than business outcomes. Reasons include faster release cycles, more complex technology, and more technically astute end-users, with the result that QA lost sight of who was really using their applications.

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Testing for Emotional Outcomes: another Shift-Up Blog

2/13/19 / by Michael Giacometti posted in DevOps, QA testing, User Experience, Performance testing, User experience testing, testing best practices, artificial intelligence, digital automation intelligence, QA, shift up, AI-assisted testing, user acceptance testing, usability testing

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With the Shift-Up series thus far, we have explored the importance of testing and thinking as a customer. The basic premise is that we need to add another dimension to Quality Assurance other than Shift-Left and Shift-Right. This new dimension focuses on how your customer is actually using your application and if the intersection of your application, customer behavior, and your company’s business objectives all align. 

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Link Real User Journeys and AI-Assisted Techniques to Improve Quality

8/22/18 / by Michael Giacometti posted in DevOps, QA testing, User Experience, User experience testing, testing best practices, artificial intelligence, digital automation intelligence, QA, AI-assisted testing, Customer Experience Insights, user acceptance testing

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To keep up with DevOps, testing and QA teams typically adopt a shift-up approach to move quality further up the software development lifecycle. The goal is to complete system testing, integration testing, and user acceptance testing (UAT) to ensure a bug-free release. While product quality has a direct correlation to increased revenue and positive business outcomes, this isn’t enough in the 21st-century marketplace. QA’s job isn’t just to de-risk applications by finding defects earlier but to help de-risk business strategy and potential problems with your user base by reporting customer experience defects. 

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Optimize Online Bookings in the Travel Sector to Delight Customers and Drive Revenue

8/20/18 / by Alex Painter posted in User Experience, Performance testing, User experience testing, Web Performance, user journey, Eggplant solutions, KPIs, customer experience optimization, Real Customer Insights, Customer Experience Insights, release quality, business outcomes, Eggplant Release Insights, business KPIs

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Providing an amazing customer experience is critical in the travel and hospitality sector. Competition is fierce and consumers are fickle. If one website fails to deliver a slick, easy-to-use online interface, an alternative is only a couple of clicks away.

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Transforming Customer Experiences With Eggplant

8/14/18 / by Michael Giacometti posted in User Experience, Performance testing, User experience testing, artificial intelligence, user journey, Selenium, shift up, Eggplant Digital Automation Intelligence Suite, customer experience optimization, Real Customer Insights, Customer Experience Insights, business outcomes, business KPIs

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Customer experience transformation is a key initiative for any business that wants to position itself for the 21st century. Two important concepts involve updating and digitizing technology, and creating persistent customer relationships. According to Bain & Company, customer experience transformation starts with “… simplifying your core business and digitizing it where it matters.” McKinsey & Company writes that in any customer experience transformation, “… the voice of the customer can be used to identify upstream and cross-functional issues and address the root causes of problems.” In short, to see positive results, you need well-tested, high-quality digital assets that reflect ever-evolving customer needs and desires.

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An All New Performance Trends Report

7/10/18 / by Drew Post posted in User Experience, UX, User experience testing, analytics, Eggplant solutions, real user monitoring, Digital Performance Management, website performance, performance trends, real user insights, KPIs, key performance indicators

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The weather, the tennis, the football — with all the distractions, you’d think those of us on the Real User Monitoring team would be kicking our feet up, right? Not a chance! I'm super excited to tell you about our latest release: a brand-new version of our Performance Trends Report. 

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A Design Pattern for Automation Repeatability

6/20/18 / by Randy Hesse posted in Software test automation, software testing, User experience testing, UX testing, testing best practices, testing strategy, QA, workflow automation, automated testing project

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Some of my customers are trying to design an automated script to perform specific workflows with a predicted outcome. Unfortunately, the automated workflow they want to execute has many variations in their environment, and they’re having trouble creating a dynamic, automated script that handles environment deviation.

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Shift Up: Out of One Tool, Many

5/31/18 / by Michael Giacometti posted in DevOps, User Experience, test management, User experience testing, artificial intelligence, shift left, shift right, shift up, voice recognition software, Eggplant AI

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This is Michael's third blog in his Shift Up series. You can read the first blog here and second blog here.

On May 21, 2018, Bank of America announced that it was rolling out its chatbot, Erica, to all its mobile customers. On the surface, the premise makes sense. It’s making the bank more relatable. It’s providing real-time customer support to people where artificial intelligence (AI) assistants like Siri and Alexa are becoming the norm. It doesn’t have the limitations that some phone-based IVRs have, and it aims to provide immediate assistance instead of making us wait for a human (we’ve all shouted “representative” or pressed zero dozens of times to get a real person). Erica is a great way for Bank of America to optimize the customer experience.

But let’s pull back the covers and ask some basic questions. How does Erica know the customer so well?  How does Erica pull from different sources of information? How does Erica know what products and services to offer? What systems, both homegrown and third party, does Erica need to be effective? 

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Don’t Test the Code, Test the Business

5/24/18 / by John Bates posted in Digital Experience, Test automation, User Experience, UX, User experience testing, UX testing, testing best practices, testing strategy, user journey, intelligent monitoring, continuous integration, continuous delivery, QA, Eggplant Digital Automation Intelligence Suite, intelligent testing

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Quality assurance (QA) used to be a compliance activity. You were releasing a product and needed to test it and stamp it “approved.” QA was about testing that the code worked. You might manually test the code. You might have even tried some automation — coding a set of test scripts that would try to capture regressions or errors that you had eradicated in the past, but which somehow crept back in. All in all, you were reasonably satisfied that you achieved a level of test coverage that met your goals. Then, you put your code into production and crossed your fingers that nothing went wrong. And if it did, you tried to fix it as quickly as humanly possible.

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