Machine learning and AI are becoming more advanced every year. There is an increase in their capabilities, functionalities and applications across industries and domains. These technologies aim to empower testers, developers and programmers to work with higher efficiency and progress faster in product development and careers.
There are many ways a Machine Learning software development firm can revolutionise how users interact with software and businesses. Let’s take a look at the most notable areas of impact.
Impact of Machine Learning on Software Experiences:
Personalised Customer Service:Statistics show that 44% of customers in the US prefer chatbots for customer service interactions compared to humans. The human counterparts of customer service bots step in for exceptional cases. The Machine Learning algorithms in these cases learn how to handle a similar situation next time.
Higher Customer Loyalty and Retention:Businesses today can gain deeper insight into customer behaviour, social sentiments and transactions. This allows them to know which customers are more likely to leave and take corrective action. Machine Learning allows enterprises to combine these insights with profitability data and customise the customer experience to persuade the customer to stay.
Measurable Brand Exposure:Automated software enables businesses to recognise people, products, logos etc. Advanced technology can recognise images and track brand logo positions that appear in certain video footage. For example, sporting event sponsors would like to see the return on their investment to measure how much exposure their brand received during the game. This is done through detailed analyses, which includes duration, quantity and logo placements.
Fraud Detection:The average business organisation loses about 5% of its revenue to fraudulent activity every year. Machine Learning allows businesses to build models using pattern recognition and identify exceptions, odd behaviour and anomalies. This is done by using social media information, transaction history and external data sources. These security models help in preventing different types of fraud in real-time.
Predictive Maintenance:For years, enterprises and component manufacturers have struggled with ensuring product maintenance is done on time for a smoother customer experience. This includes aircraft or train component maintenance, for instance. This means instead of customers having to wait for maintenance after a component reaches the end of its lifecycle, predictive maintenance technology allows businesses to know when a product will give out. They can replace or fix it before the situation becomes critical.
Supply Chains Work Smoothly:Machine Learning allows data from logistics to go through contextual analysis, which helps predict risks to the supply chain and mitigate them. ML Algorithms can quickly go through social data and information in the public domain in many languages. This allows enterprises to detect any risks or disruptions and correct them before any damage is done.
AI and Machine Learning have automated and simplified large software development tasks to a great extent. However, this doesn’t mean testers and developers will be without jobs. A Machine Learning software development firm uses the experience and technical skills of programmers and developers to develop executable programs. Machine Learning relies on a collaborative relationship between humans and technology.
About the Author
Hi There, I am priyanshi bhatt. I am a content writer by profession. I love to write blog posts, guest posts, ebooks, press releases, Company Profile and Blog Posting. I mainly write on the topics related to Technology.
