Every other startup fails because it doesn’t get funding or runs out of money, and AI investments have gone up and down in recent years. With investors getting more picky, the front-end for AI takes the front seat. Clean design and intuitive navigation enhance customer experience in AI. But they can also boost your chances of getting funded.

Exoft has assisted several startups in developing front-end for AI solutions, and we’re happy to share our insights. For more info on the development outcomes, feel free to check our case study library.

The Importance of Customer Experience for AI Solutions

Four out of five business owners prioritized customer experience (CX) and support in 2023. CX trends provide a competitive advantage, remaining a driving force in achieving business goals in 2024 and the near future.

Discover User Needs

Non-user-friendly products cause 9% of startup failures. This rate is higher than the lack of demand and market competition, both 7%. Still, you need to understand that users strive for a perfect customer experience. CX management techniques like A/B testing work wonders for adjusting user interface, navigation, and customer support. Implementing these insights in front-end development for AI will herald other business benefits.

Promote User Adoption and Build Trust

Zendesk CX Trend Report claims that 60% of customers choose vendors based on the services they expect to receive—moreover, 73% switch to competition after several negative experiences. Although early adopters often disregard CX shortcomings, expanding the user base requires enhanced customer experience for AI solutions. That’s especially true considering the cutthroat competition in the booming market.

Drive Business Value

According to McKinsey, improving customer experience affects the bottom line. Sales revenue increases by 2% to 7%, while profitability sees a modest 1% to 2% rise. At the same time, shareholder return can increase by up to 10%. The latter is a convincing argument for potential investors interested in your AI software.

Successful CX Examples in AI Solutions

Many generative AI solutions look alike. However, small things can make or break the customer experience. Here, we’ll cover several excellent examples of leveraging the front-end for AI.

Canva

Magic Edit in Canva enables users to add to or alter existing images. The interface includes a toggle between the Brush and Click options. Moreover, it’s possible to navigate the feature with pop-up tips. Also, a disclaimer reminds users that Magic Edit doesn’t work for faces, legs, or hands. Choosing among four generated results further enhances customer experience in AI editing.

Gemini

Gemini is another prime example of successful front-end development for AI solutions. Thanks to its intuitive multimodal interface, users generate text, images, coding fragments, and more using simple prompts. Text-to-speech and speech recognition capabilities enhance accessibility. Meanwhile, instant feedback prompts user engagement and improves generative capabilities.

Grammarly

Grammarly has built generative AI functionality into the preexisting software. AI-suggested improvements are neatly relegated to a separate tab. The app relies on its tried-and-true approach of underlining problematic words and phrases and highlighting suggested changes.

Like Grammarly’s standard suggestions, users can accept or dismiss AI-powered recommendations. They can also report problems and turn off specific types of suggestions. Grammarly uses established navigation and control patterns to make users comfortable with the new functionality — and it works.

Creating an Intuitive and Attractive Design

The “form before function” principle only looks good in designer portfolios. On the other hand, the function can also suffer without putting much thought into form. Users who don’t understand how to use and navigate your AI project will eventually get frustrated and abandon it. In the worst-case scenario, they’ll also leave bad reviews and create a bad reputation for your app.

In contrast, users rarely value attractive and intuitive interfaces because their experiences are smooth and hassle-free.

An intuitive customer experience for AI solutions should focus on the following:

  • Simplicity. Nothing should overwhelm the layout unless it adds to the customer experience. Eliminate visual clutter and group similar items and features. It will make it easier for users to locate those elements. Minimize clicks, taps, and other actions for users to achieve their primary objectives.
  • Clarity. Using your app shouldn’t be as challenging as navigating a foreign country without knowing the local language. Use familiar navigation patterns, like a hamburger menu, and create clear labels to accompany icons. Finally, turn to front-end technologies for AI apps to collect feedback. Vibration or color changes are the best ways to confirm actions.
  • Consistency. Before working on the UI, choose the design system, including color scheme, font, etc. Use the same terminology and interactions throughout the app to ensure users understand your labels and receive predictable outcomes.

Three components of an attractive and intuitive UI design for AI solutions.

The Importance of Front End in AI Solutions

The front end is responsible for the user’s side of an AI solution. So, it’s the ultimate tool for improving customer experience. These are standard tasks front-end development for AI solutions can address:

  • Optimize the app’s performance. The response time of most generative AI solutions hinges on the backend. Still, an effective front-end for AI can make the wait time more bearable for users. Cleaning up HTML and optimizing CSS will make UI loading quicker, as will prefetching and caching technologies. Faster responses will reduce the bounce rate and encourage users to keep interacting with your solution.
  • Implement responsive design. Mobile traffic is around 63% globally, while desktop is only 37%. Therefore, mobile-first front end for AI applications should be a priority. New solutions must automatically scale up or down to any screen size to gain and keep the audience. That includes everything from the web app layout to typography, icons, and menus. Designing with the thumbs in mind is also critical to enable users to operate your app with one hand.
  • Ensure cross-platform functionality. Adjusting the UI isn’t the extent of responsive design. Cross-platform front-end for artificial intelligence should also maximize the built-in hardware to make things easier on mobile. For example, while voice recognition integration may be tricky on a desktop without a quality mic, it’s convenient on mobile. The same applies to uploading photos or direct camera input.

Even if you don’t need to develop a solution from scratch, consider hiring an experienced front-end team. Skilled specialists will augment the user-facing element of your AI application and boost customer experience, providing the benefits discussed above.


The role of responsive mobile-optimized front-end in improving customer experience.

Strategies to Enhance CX-Centric AI Design

Can you do anything else to improve your AI solution and front-end design? In addition to a mobile-optimized and user-friendly interface, try these strategies to enhance customer experience.

If you let Exoft implement these effective tactics, you won’t need to manage a development team. Our front-end developers will deliver the outcomes you want.


7 strategies for improving the customer experience of your AI solutions.

Work out Onboarding and Education

Customer experience depends on how comfortable users are with your technology. Still, intuitive interfaces aren’t always as clear and easy to navigate for customers as they are for designers. For improvements in onboarding, include a clear tutorial. Cover basic features, potential issues, and other hands-on tips. The tutorial should be short and sweet, with an option to skip it and return to it whenever convenient.

Suggested prompts (i.e., Gemini, ChatGPT) and prompt builders can be onboarding and training elements. The same applies to tooltips and explainer pop-up windows, however annoying they may be for some users.

Plan for Error Handling

Aside from disclaimers reminding users that artificial intelligence can make mistakes, every AI developer should address handling errors. Instead of blanking out, your solution should either admit its error or replace it with alternatives. Built-in reporting and correction capabilities will also serve a double purpose. On the one hand, they will appease the users. On the other hand, they will help log errors and inappropriate algorithm output, which you can address on the backend.

You can also add response confidence indicators to foster trust. It’s particularly crucial for predictions. AI apps can include these indicators verbally or provide calculations to support their predictions.

Highlight Capability Transparency

Dashed expectations lead to an unsatisfactory customer experience. Users should understand what your AI solution can and can’t do. You can explain it during the onboarding process or throughout the first few user interactions. For example, include a disclaimer about potential mistakes. Besides, users should know about the database limitations. So, if your AI app can only access data within a certain period, inform users about it.

Use badges such as “New” or “Beta” to highlight the latest releases and their status. Users will realize mistakes are more likely in the early adoption days. Thus, you’ll receive feedback and improve individual features without losing customer trust.

Develop Personalized Interactions

Considering artificial intelligence is at the forefront of CX personalization efforts across various markets, personalized interactions should also be among your customer experience strategies for AI. Analyze past actions, experiences, and feedback to create custom prompt suggestions and personalize AI output. Even something as simple as the user’s name in the Gemini’s interface will make customers feel valued.

Build Feedback Loops

Unlike retail, education, or trucking app development, AI solutions immediately adopt customer feedback to improve outcomes. Therefore, encouraging feedback is equally critical for customer experience. Offer users the opportunity to rate the results and share additional feedback. Explaining how user feedback affects the model and output will encourage customers to be more active with their reviews.

Many generative AIs rely on thumbs-up and thumbs-down buttons to generate instant feedback. ChatGPT comes with a reload button that creates a new output. Gemini, in contrast, requests additional feedback and provides several standard options for negative feedback.

Creating feedback loops enhances customer experience with AI solutions.

Encourage Self-Service

If you provide enough data-driven materials for customers, they solve any arising issues independently. These include FAQ sections, blog articles, community forums, and email newsletters. Chatbots are also valuable for enhancing customer experience in AI.

To make these self-service options helpful, ensure the search engine works properly. Also, check whether the information provided is relevant. Outdated answers lead to a negative customer experience and a decision to look for another AI solution.

Create an Omnichannel Experience

Synchronizing customer experience across different devices is crucial. However, you should also ensure their support journey is seamless and frictionless. Avoid making users repeat their issues to various department managers. It will only aggravate them and encourage them to switch to your competitors. Omnichannel routing should be a part of the front end for AI solutions to direct tickets according to their priority and your support team’s availability.

Conclusion

Businesses prioritize customer experience and support as competitive advantages, and AI solutions are no exception. Developing an effective and intuitive front-end design for AI requires consistency, simplicity, and clarity. Some other strategies for improving CX for AI include self-service options, omnichannel experience, and transparency. Personalized interactions and feedback loops also improve customer retention and boost lifetime value.

Exoft has used these insights through front-end development for several AI solutions. You can learn more about our cooperation models and experience with front-end AI development. We’d be happy to provide a more thorough consultation on the topic. Contact our team, and we’ll schedule a call to discuss your CX needs and how we can help you meet them.