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Building a layered approach with AI

We have made significant strides in the evolution of design. It is crucial for us to recognize that disruptive technologies have always been the catalyst for change, shaping the way we design and communicate. In an era before the printing press, people painstakingly wrote books by hand. Similarly, the emergence of mobile phones, computers, and the internet has changed everything.

Embracing these changes and adapting to newer technologies is essential for staying relevant in the field of design. There are designers who use Adobe Dreamweaver and Photoshop to create website UI. It feels like a different era since the introduction of more recent software such as Figma, and Adobe XD. However, the core principle remains the same: staying pertinent requires adaptability as the times change.

While there’s an ongoing discussion about AI potentially replacing design jobs, my personal perspective is that we should not fear it but rather leverage it to our advantage since AI is an execution tool. AI is poised to simplify our lives. When you consider the broader picture, your value as a designer in the upcoming years will be determined by your ability to synthesize innovative ideas to solve problems. Let me elaborate on how, as designers, we must strengthen our problem-solving muscles.

How the layered approach works:

Tools like Midjourney are designed for image-specific tasks, enabling the creation of visually appealing images. Chat GPT on the other hand is a text-based AI model, although now with the incorporation of DALL-E inside Chat GPT, it gives image outputs too.

I want you to imagine for a second, what if you used Chat GPT to create nuanced prompts for Midjourney.

This is layering software on top of another software to receive your desired output. For this to work, you have to first train your Chat GPT agent on Midjourney’s functionality and then prompt using a basic framework.

The framework works like this:

First, you inform Chat GPT about your desired role or objective and define your approach or task. For example, ‘I am a skilled graphic designer who designs illustrations for top brands in India. You need to provide me with ideas for designing a coffee shop logo, along with some links for inspiration.’

Then, you specify your timeframe or any restrictions. For instance, ‘I can’t spend more than 30 minutes looking at inspiration, so please only provide the best ones you find that you believe would be most helpful.’

Finally, after training your agent, request Chat GPT to provide a prompt for Midjourney.

The key thing to remember while implementing this approach is to churn out a nuanced prompt that will serve as a base for your creative design process later. That’s it—two layers of software, and the pivotal layer comes into play once you’ve received the output: your creativity. You make AI as Robin to your Batman. Consider this as no longer needing to begin from a starting point. With AI tools such as these, people who have the potential to think clearly to formulate ideas would flourish. I encourage you to use these AI tools in your daily life to learn and become the best in your respective fields. 

There are many more tools that have come into the market such as for UI, a single line prompt can generate a whole app’s UI screens with tools like Uizard. Builder.io is a tool that uses AI to convert Figma design files into code. Recent developments also suggest that AI can help with user research for large organizations, potentially marking a paradigm shift in the UX industry, as these AI models have been trained on human behaviors, this has been put forth by fantasy.co. There is so much more to come, the least we can do is be prepared for it. 

I hope you had a good read and this article gave you a sense of what is waiting in our future.

About the Author: 

Shivani Shukla is a Senior UI & UX designer at Mantra Labs. Updating her knowledge and staying up to date with the current trends has always been her priority.

Further Readings:

Design and Technology Fusion Shaping the Future of Innovation

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10 Analytics Tools to Guide Data-Driven Design

Analytics are essential for informing website redesigns since they offer insightful data on user behavior, website performance, and areas that may be improved. Here is a list of frequently used analytics tools to guide data-driven design that can be applied at different stages of the website redesign process. 

Analytics Tools to Guide Data-Driven Design

1. Google Analytics:

Use case scenario: Website Audit, Research, Analysis, and Technical Assessment
Usage: Find popular sites, entry/exit points, and metrics related to user engagement by analyzing traffic sources, user demographics, and behavior flow. Recognize regions of friction or pain points by understanding user journeys. Evaluate the performance of your website, taking note of conversion rates, bounce rates, and page load times.

2. Hotjar:

Use case scenario: Research, Analysis, Heat Maps, User Experience Evaluation
Usage: Use session recordings, user surveys, and heatmaps to learn more about how people interact with the website. Determine the high and low engagement regions and any usability problems, including unclear navigation or form abandonment. Utilizing behavior analysis and feedback, ascertain the intentions and preferences of users.

3. Crazy Egg:
Use case scenario: Website Audit, Research, Analysis
Usage: Like Hotjar, with Crazy Egg, you can create heatmaps, scrollmaps, and clickmaps to show how users interact with the various website elements. Determine trends, patterns, and areas of interest in user behaviour. To evaluate various design aspects and gauge their effect on user engagement and conversions, utilize A/B testing functionalities.

4. SEMrush:

Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct keyword research to identify relevant search terms and phrases related to the website’s content and industry. Analyze competitor websites to understand their SEO strategies and identify opportunities for improvement. Monitor website rankings, backlinks, and organic traffic to track the effectiveness of SEO efforts.

5. Similarweb:
Use case
scenario: Research, Website Traffic, and Demography, Competitor Analysis
Usage: By offering insights into the traffic sources, audience demographics, and engagement metrics of competitors, Similarweb facilitates website redesigns. It influences marketing tactics, SEO optimization, content development, and decision-making processes by pointing out areas for growth and providing guidance. During the research and analysis stage, use Similarweb data to benchmark against competitors and guide design decisions.

6. Moz:
Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct website audits in order to find technical SEO problems like missing meta tags, duplicate content, and broken links. Keep an eye on a website’s indexability and crawlability to make sure search engines can access and comprehend its material. To find and reject backlinks that are spammy or of poor quality, use link analysis tools.

7. Ahrefs:
Use case scenario:
Research, Analysis, SEO Optimization

Usage: Examine the backlink profiles of your rivals to find any gaps in your own backlink portfolio and possible prospects for link-building. Examine the performance of your content to find the most popular pages and subjects that appeal to your target market. Track social media activity and brand mentions to gain insight into your online reputation and presence.

8. Google Search Console:

Use case scenario: Technical Assessment, SEO Optimization
Usage: Monitor website indexing status, crawl errors, and security issues reported by Google. Submit XML sitemaps and individual URLs for indexing. Identify and fix mobile usability issues, structured data errors, and manual actions that may affect search engine visibility.

9. Adobe Analytics:
Use case scenario:
Website Audit, Research, Analysis,
Usage: Track user interactions across multiple channels and touchpoints, including websites, mobile apps, and offline interactions. Segment users based on demographics, behavior, and lifecycle stage to personalize marketing efforts and improve user experience. Utilize advanced analytics features such as path analysis, cohort analysis, and predictive analytics to uncover actionable insights.

10. Google Trends:

Use case scenario: Content Strategy, Keyword Research, User Intent Analysis
Usage: For competitor analysis, user intent analysis, and keyword research, Google Trends is used in website redesigns. It helps in content strategy, seasonal planning, SEO optimization, and strategic decision-making. It directs the production of user-centric content, increasing traffic and engagement, by spotting trends and insights.

About the Author:

Vijendra is currently working as a Sr. UX Designer at Mantra Labs. He is passionate about UXR and Product Design.

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