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How to Sell UX Research to Your Clients?

By :
4 minutes read

Let’s begin with some words from the father of modern innovation, Steve Jobs, Design is not just what it looks like and feels like. Design is how it works”.

How the design works is essentially the crux of user experience design. The interaction and connection with any product is achieved by pure experience design. To make the user ‘fall in love’ with the product or experience is the core task of the designer. To achieve intuitive experience, what we need is a strong UX research in place to drive the design process and justify our decisions based on user analysis. This is where the gap exists with most products as the stakeholders don’t see how UX research translates into a business value for the long run. We as UX/UI designers need to convey the monetary impact of research on their product and how it will result in selling more. In the end all they (stakeholders) really care about is MONEY! So let’s show them how UX research will get them more of the BILLS.

How to Sell UX Research?

HOW TO SELL UX RESEARCH?

To sell UX research to your clients, the first approach is to talk about the importance (ROI) of UX research, the methods and tools used in the process. Taking all the UX jargon and dumping it on the stakeholders, in the hopes that they will believe in the process strongly. This can be a little too overwhelming and make it tough for them to comprehend as they don’t know the meaning or the importance of these UX terms like usability, mapping, personas etc. 

We need to first start with the people’s own experiences with products and then convey the UX concepts behind it. Try connecting with them on a common product we all experience, like Google and bond with them. Then we need to instigate a discussion where the stakeholders themselves try to identify the assumptions and hidden complexities of their product. We need to ask small relevant questions and listen carefully and slyly push them to pinpoint the user understanding gap which will further motivate them to get answers. We have to stay away from vague questions and focus more on questions that feel actionable.

You see, once you have posed the questions to them, UX research is not a hard sell and we have everyone’s attention on its relevance and need. In the final step we take all the user research questions we have compiled and discuss the risk levels associated with not answering them. We make them advocate for user research and lead them to believe it is their idea. We need to do this gently and with a positive emotion. Draw some inspiration and insights on how to lead this process from https://alistapart.com/article/how-to-sell-ux-research/ .

Now we know how to lead the pitch, what we need is the backdrop before the pitch. 

How to sell UX Research?

WHAT WE NEED TO PREPARE?

As important the sales pitch is, the time before that probably holds more importance. We need to get all the machinery working beforehand for it to go successfully. We are selling research to our stakeholders so here is where we prove how good we are at it. Research and have a good understanding of UX (obviously), the industry domain in which the product is in, and few successful products benefiting largely because of their focus on UX. A deep understanding of the product and how it is competing in the market is also needed along with their company’s vision and the structure of the management team (if possible would be helpful).

We need research plans and user gaps established from our end and then further break these down to structured questionnaires that we put across to the stakeholders. As researchers and designers it is part of our scope to figure out where the biggest opportunities for improvement lies with the product and how we can add more value to it with our designs. 

For strategizing into the finer details of the sales pitch, do go ahead and give this article a read –  https://www.uxmatters.com/mt/archives/2008/10/selling-ux.php

How to Sell UX Research?

THE TAKEAWAY 

In case you are the kind who don’t like to read and just want the details in under 30 secs, this is for you. 

Successfully selling UX is not talking about its importance but rather pitching the current gaps in the product. It is the soft skills that will help you achieve this goal. Communicating with a clear, positive and enthusiastic emotion towards the product and careful listening skills when people tell you about their business and issues, is what drives this pitch. Selling UX is more about your people’s skill, conversational skills and quick on the feet thinking.

Structuring the pitch and research questions is the main task in hand and this is where you employ your research skills. Research about your users and understand their needs from this project and start asking the questions which leads the stakeholders to believe the need for UX for their own product. Once you pose the questions and give them real life examples is when they start questioning how the screen design will proceed without the relevant answers and they will be proactive in finding the right answers alongside you. It’s not about selling UX, it’s about selling their future product to them.

About the Author: 

Diya is an architect turned UI/UX Designer, currently working at Mantra Labs. She values designing experiences for both physical and digital spaces.

Want to know more about designing?

Read our blog: Designing for Web 3.0

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Smart Machines & Smarter Humans: AI in the Manufacturing Industry

We have all witnessed Industrial Revolutions reshape manufacturing, not just once, but multiple times throughout history. Yet perhaps “revolution” isn’t quite the right word. These were transitions, careful orchestrations of human adaptation, and technological advancement. From hand production to machine tools, from steam power to assembly lines, each transition proved something remarkable: as machines evolved, human capabilities expanded rather than diminished.

Take the First Industrial Revolution, where the shift from manual production to machinery didn’t replace craftsmen, it transformed them into skilled machine operators. The steam engine didn’t eliminate jobs; it created entirely new categories of work. When chemical manufacturing processes emerged, they didn’t displace workers; they birthed manufacturing job roles. With each advancement, the workforce didn’t shrink—it evolved, adapted, and ultimately thrived.

Today, we’re witnessing another manufacturing transformation on factory floors worldwide. But unlike the mechanical transformations of the past, this one is digital, driven by artificial intelligence(AI) working alongside human expertise. Just as our predecessors didn’t simply survive the mechanical revolution but mastered it, today’s workforce isn’t being replaced by AI in manufacturing,  they’re becoming AI conductors, orchestrating a symphony of smart machines, industrial IoT (IIoT), and intelligent automation that amplify human productivity in ways the steam engine’s inventors could never have imagined.

Let’s explore how this new breed of human-AI collaboration is reshaping manufacturing, making work not just smarter, but fundamentally more human. 

Tools and Techniques Enhancing Workforce Productivity

1. Augmented Reality: Bringing Instructions to Life

AI-powered augmented reality (AR) is revolutionizing assembly lines, equipment, and maintenance on factory floors. Imagine a technician troubleshooting complex machinery while wearing AR glasses that overlay real-time instructions. Microsoft HoloLens merges physical environments with AI-driven digital overlays, providing immersive step-by-step guidance. Meanwhile, PTC Vuforia’s AR solutions offer comprehensive real-time guidance and expert support by visualizing machine components and manufacturing processes. Ford’s AI-driven AR applications of HoloLens have cut design errors and improved assembly efficiency, making smart manufacturing more precise and faster.

2. Vision-Based Quality Control: Flawless Production Lines

Identifying minute defects on fast-moving production lines is nearly impossible for the human eye, but AI-driven computer vision systems are revolutionizing quality control in manufacturing. Landing AI customizes AI defect detection models to identify irregularities unique to a factory’s production environment, while Cognex’s high-speed image recognition solutions achieve up to 99.9% defect detection accuracy. With these AI-powered quality control tools, manufacturers have reduced inspection time by 70%, improving the overall product quality without halting production lines.

3. Digital Twins: Simulating the Factory in Real Time

Digital twins—virtual replicas of physical assets are transforming real-time monitoring and operational efficiency. Siemens MindSphere provides a cloud-based AI platform that connects factory equipment for real-time data analytics and actionable insights. GE Digital’s Predix enables predictive maintenance by simulating different scenarios to identify potential failures before they happen. By leveraging AI-driven digital twins, industries have reported a 20% reduction in downtime, with the global digital twin market projected to grow at a CAGR of 61.3% by 2028

4. Human-Machine Interfaces: Intuitive Control Panels

Traditional control panels are being replaced by intuitive AI-powered human-machine interfaces (HMIs) which simplify machine operations and predictive maintenance. Rockwell Automation’s FactoryTalk uses AI analytics to provide real-time performance analytics, allowing operators to anticipate machine malfunctions and optimize operations. Schneider Electric’s EcoStruxure incorporates predictive analytics to simplify maintenance schedules and improve decision-making.

5. Generative AI: Crafting Smarter Factory Layouts

Generative AI is transforming factory layout planning by turning it into a data-driven process. Autodesk Fusion 360 Generative Design evaluates thousands of layout configurations to determine the best possible arrangement based on production constraints. This allows manufacturers to visualize and select the most efficient setup, which has led to a 40% improvement in space utilization and a 25% reduction in material waste. By simulating layouts, manufacturers can boost productivity, efficiency and worker safety.

6. Wearable AI Devices: Hands-Free Assistance

Wearable AI devices are becoming essential tools for enhancing worker safety and efficiency on the factory floor. DAQRI smart helmets provide workers with real-time information and alerts, while RealWear HMT-1 offers voice-controlled access to data and maintenance instructions. These AI-integrated wearable devices are transforming the way workers interact with machinery, boosting productivity by 20% and reducing machine downtime by 25%.

7. Conversational AI: Simplifying Operations with Voice Commands

Conversational AI is simplifying factory operations with natural language processing (NLP), allowing workers to request updates, check machine status, and adjust schedules using voice commands. IBM Watson Assistant and AWS AI services make these interactions seamless by providing real-time insights. Factories have seen a reduction in response time for operational queries thanks to these tools, with IBM Watson helping streamline machine monitoring and decision-making processes.

Conclusion: The Future of Manufacturing Is Here

Every industrial revolution has sparked the same fear, machines will take over. But history tells a different story. With every technological leap, humans haven’t been replaced; they’ve adapted, evolved, and found new ways to work smarter. AI is no different. It’s not here to take over; it’s here to assist, making factories faster, safer, and more productive than ever.

From AR-powered guidance to AI-driven quality control, the factory floor is no longer just about machinery, it’s about collaboration between human expertise and intelligent systems. And at Mantra Labs, we’re diving deep into this transformation, helping businesses unlock the true potential of AI in manufacturing.

Want to see how AI-powered Augmented Reality is revolutionizing the manufacturing industry? Stay tuned for our next blog, where we’ll explore how AI in AR is reshaping assembly, troubleshooting, and worker training—one digital overlay at a time.

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