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The growing impact of Artificial Intelligence in mobile apps

By :
2 minutes, 41 seconds read

Change is the need of time and advancement in technology is instrumental to drive innovation. Mediums of interaction with machine changes and calls for developers to be on edge to facilitate digital transformation. By the end of 2020, there’ll be over 6.1 billion smartphone users in the world, which will support almost every cutting-edge technology. In this article, we’ll discuss the growing impact of Artificial Intelligence on mobile apps.

Businesses around the world need a dynamic approach to ensure the best customer experience and AI is helping facilitate this strategy. Whether it is the health or manufacturing industry or logistic processes, Artificial intelligence is making operations and personalization a lot more convenient.

The impact of Artificial Intelligence in mobile apps

Extensive use of AI in mobile applications is becoming a new trend. Artificial intelligence is enabling mobile apps with precise, convertible, accessible, and customized options; thus, enhancing the functionalities and performance.

To avail the maximum benefit of AI in mobile technology, one needs a deeper understanding and right approach to improve mobile app user experience. The following are ways to leverage AI in mobile applications.

1. Accurate results

Artificial intelligence works on large data sets, considering every possibility and mapping. Industries like healthcare, which requires a high degree of precision, can harness AI to deliver accurate results. AI promises greater accuracy in medical diagnosis than traditional manual processes. Thus, while building mobile apps where accuracy is prime, AI can bring many positive solutions.

Also read: The Next Big Thing for Big Tech: AI as a Service 

2. Real-time forecasting

The integration of AI in mobile apps can help in real-time predictions. There can be multiple activities in a day, which are difficult to keep track of. By keeping track of the schedule, finding a correlation with external environments like traffic, weather, etc. a lot of time and energy can be preserved.

This attribute can be used in education applications to predict current affairs. Not only this, but AI can also help in correcting and formulating emails.

3. Customer experience

Most of the mobile apps are exclusively targeting customers and are designed according to the respective business modules. But, when it comes to customer behavior, every single individual is different from the other. AI can add the advantage of personalization in customer-facing mobile applications. Moreover, this is achievable at scale; i.e. the technology accommodates itself to individual user preferences.

More: AI in Mobile Development 

4. Personalized experiences

Search engines are becoming smarter and they’re incorporating AI and NLP to understand user intent and behavior on their platforms. Similarly, mobile apps can also leverage AI to understand their user and optimize search results based on their objectives. Users need not remember what they searched for a week ago because their app will do it for them. 

AI coupled with augmented reality is the next revolution in mobile apps. Users can get visual causes about the objects in a real-life situation. Apparel, cosmetics, and home decor industries are already deploying this technology to enhance customer experiences.

Final Words

The integration of AI in mobile apps is the need of the hour. The system will take time to evolve, but when it will, we’ll be dwelling into a whole new world of digital experiences. 

This article is contributed to Mantra Labs by Tayla Scurry. 

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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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