In recent years, digital platform companies have faced increasing challenges in managing customer complaints, driven by widespread consumer adoption. This paper introduces an end-to-end pipeline, named RE-GrievanceAssist, designed specifically for real estate customer complaint management. The pipeline consists of three key components: i) response/no-response ML model using TF-IDF vectorization and XG-Boost classifier; ii) user type classifier using fasttext classifier; iii) issue/sub-issue classifier using TF-IDF vectorization and XGBoost classifier. Finally, it has been deployed as a batch job in Databricks, resulting in a remarkable 40% reduction in overall manual effort with monthly cost reduction of Rs 1,50,000 since August 2023.

We are at a true cusp of innovation within all aspects of our life. From shopping to communication, we all rely on technology to make our life easier. There has never been a more critical time to place customers' needs first. With current events, banking has never been more vital, and with a substantial shift in user behavior, the technology that supports customers must also transform and adapt. Those that fail to stay up to speed means losing customers to the competition.

Tahera Zamanzada, director of digital strategy for the global public sector at Salesforce (NYSE: CRM), said the COVID-19 pandemic has prompted government agencies to advance digital transformation and deliver better customer service through the adoption of cloud platforms. "The digital customer experience in government benefits tremendously from cloud technology because it supports mobile solutions in ways that otherwise would not exist and leads to much higher adoption rates plus happier customers," Zamanzada wrote. "Cloud can also handle the fluctuating bandwidth of demands so that agencies can scale up or scale down as needed." She noted that agencies should work to provide citizens with an omnichannel experience to facilitate communications and interaction with the government and use artificial intelligence platforms to gain deeper understanding of their customers in order to better meet their needs. "They can use those insights to create human-centered design frameworks as part of their digital transformation plans while they continue to fine-tune their business processes and home in on mission effectiveness," Zamanzada added.

About 10 years ago, all business communications were done through email. Then, with the emergence of social channels such as Facebook and Twitter, it became progressively essential for customer experience strategy to involve support teams to monitor these channels. In the last two years, businesses have seen an increasing preference for live chat messaging like Whatsapp and Facebook Messenger. It can be asserted from this timeline that the first and foremost necessity when assessing customer experience is to identify the channel the customer prefers to interact on. Nowadays customers interact on a multichannel level; to provide a seamless customer service across all channels, businesses should be prepared to maintain the context when interacting with a particular customer across various channels.

Wikifriend offers a platform which uses artificial intelligence-driven conversational technology to facilitate access to digital content that would otherwise require articulated steps for enjoyment. The platform allows businesses to offer a continuous support service guaranteeing a personalized conversational level improving the customer experience. Wikifriend is a human-to-machine conversational interface that facilitates the use of complex computer applications for any person, simply by using voice commands. From brand reputation management in digital media and fake news recognition to Health Care, Financial Services, Home Automation, and Computer Vision, Wikifriend brings disruptive innovation to the industry. Merge German semantic engine and high-security level sounds good to customers?

As products are getting more and more similar, technical differentiation becomes harder and puts excessive and unjustified pressure on the final retail price. In these conditions, another differentiation strategy could be to focus on customer experience. Long gone is the era of mass products, even if mass production is still on the rise. Personalization can mean that the same mass-produced item is sold in different markets and serving different needs, and this is just the tip of the iceberg. AI brings the opportunity to offer personalized customer care 24/7 for a fraction of the cost and with constant joy--the chatbot never has a bad day.

AI-powered chatbots come with many benefits for the businesses that adopt them, but in some instances, they can have greater impact for the everyday user. In this blog, we list four recent articles giving examples of where AI-powered applications and chatbots have been put into practice to help customers and the common man. The developer of the'world's first robot lawyer' application, which helped overturn more than one-hundred parking fines, is now adapting the functionality of the integrated chatbot to provide legal aid to refugees seeking asylum in the US and Canada, as well as asylum support in the UK. The original DoNotPay AI-powered application gives legal aid through a simple chat interface, where a chatbot asks a series of questions to help determine which application a refugee needs to fill out and whether they are eligible for asylum protection under international law. After this, the chatbot takes note of the relevant details required for asylum applications in the US or Canada, auto-fills the application form and sends.

About 10 years ago, all business communications were done through email. Then, with the emergence of social channels such as Facebook and Twitter, it became progressively essential for customer experience strategy to involve support teams to monitor these channels. In the last two years, businesses have seen an increasing preference for live chat messaging like Whatsapp and Facebook Messenger. It can be asserted from this timeline that the first and foremost necessity when assessing customer experience is to identify the channel the customer prefers to interact on. Nowadays customers interact on a multichannel level; to provide a seamless customer service across all channels, businesses should be prepared to maintain the context when interacting with a particular customer across various channels.

See first-hand how you can bring an NLP application to life. Last week I introduced No Jitter readers to Natural Language Processing (NLP) and Facebook's free NLP service, wit.ai. I wrote about intents and entities, and how they work together to convert human language into actionable components. If you are like me, though, you only learn so much from reading. You need to see it in action before the concepts fully seep into your brain.

If you talk to a man in a language he understands, that goes to his head. If you talk to him in his language, that goes to his heart. I would venture to guess that most people had their first encounter with natural language processing (NLP) when Apple added Siri to the iPhone. Starting with the iPhone 4S, you could ask "her" simple questions such as "Who was the 12th president of the United States?" (Zachary Taylor) and "Will you marry me?" (We hardly know one another). Personally, I use Siri on a near daily basis for getting me to where I need to go and finding the best Indian, Thai, or Mediterranean restaurant once I arrive there.