Customer Service
Case Studies
30SecondsToFly struggles to scale the automation of SMB corporate travel management with the deployment of text chatbots
30SecondsToFly''s Claire, a travel assistant, uses natural language processing and machine-learning capabilities to assist travellers with their bookings. The technology can provide SMBs with a valuable customer service provider able to adhere to a company''s travel policies. The chatbot is available to process booking queries through SMS or the messaging platform Slack.
Linked use case: Automate customer service conversations through a text chatbot
Abbvie achieves 90% cumulative medication adherence among patients with schizophrenia using image recognition
Abbvie used AiCure’s artificial intelligence platform to visually confirm medication ingestion. This has facilitated continuous monitoring of patient treatment leading to better compliance and streamlining of clinical trials by reducing sample size.
Linked use case: Monitor patient prescription compliance
Acer America improves service by decreasing repeat caller rate by 15% with responses powered by natural language speech recognition.
Acer America drives service improvements with Nuance''s natural language speech recognition technology on hosted IVR platform. The solution, which is based on Natural Language Processing (NLP) to offer call steering, has helped reduce repeat caller rate by 15% and decreases average call time by 50 seconds, among other benefits.
Linked use case: Optimise call routing based on customer characteristics potentially including expressed intent
AeroMexico''s customer-service can handle as many inquiries as two full-time employees per day through its chatbot
Aeromexico has introduced aerobot, a chatbot that handles customer service queries. Based on natural language processing, it has been trained to recognise the same questions asked differently. If it is not able to assist with a query, the chatbot redirects the client to a human attendant. The company claims that it is currently assisting 1,000 Spanish-speaking clients per day, which is roughly as many queries as two full time employees would handle, while saving costs.
Linked use case: Automate customer service conversations through a text chatbot
Alibaba has reduced customer service staff needs for its marketplace vendors by introducing a chatbot
Alibaba has introduced a text-based chatbot, Dian Xiaomi, which vendors operating on its marketplace platforms vendors can implement. Alibaba claims that AI algorithms are helping to drive internal and customer service operations including smart product and search recommendations: Alibaba’s software tracks customer browsing and interactions with the website to offer product recommendations.
Linked use case: Automate customer service conversations through a text chatbot
Amazon is testing its Prime Air drone delivery service promising to fly parcels to customers within 30 minutes of ordering.
Amazon has been testing drone delivery to enhance its Amazon Prime offerings through Prime Air, which will be able to autonomously fly packages to customers in less than 30 minutes, given they fulfil requirements, such as weight, size and distance of route.
Linked use case: Automate delivery to customer eg via drone or self-driving vehicle
American Express Australia used machine learning to identify 24% of customer accounts that would close within four months allowing them to take preventative save actions
American Express has over 100 million credit card customers globally representing over $1 trillion in annual charge volume. The Australian company used advanced data analytics and machine learning to analyse historical transactions along with 115 variables to forecast customer churn. They were able to identify 24% of accounts that would close within four months allowing them to take preventative save actions.
Linked use case: Predict and drive customer retention and churn management
Atolla identifies skin health issues and recommends skin care products using machine learning
Atolla is a skin care startup offering products specific to each consumer. Their treatment starts by testing the skin, for oil, moisture and pH. Based on the results the appropriate products are recommended. The company uses a machine learning model to generate skin archetypes based on all the factors that may affect the skin and another one to make predictions about skin change over time. Atolla wants to identify concerns across demographics, geographies and lifestyles to be able to create a personalised profile for each client.
Linked use case: Personalise product recommendations to target prospective customers
Avianca Airlines improves customer experience and cuts check-in waiting times in half with natural language processing
Avianca Airlines in collaboration with Accenture built Carla, a chatbot to assist customers with domestic check-in, itinerary checking, flight status updates, weather conditions, simple translations, and other useful reminders. The chatbot, which is available on Facebook Messenger, has been able to assist more than 1,000 customers as well as cut waiting times for check in in half.
Linked use case: Automate customer service conversations through a text chatbot
Aylesbury Vale District Council''s services team now replies to residents’ questions almost two times faster using deep learning algorithms
The Aylesbury Vale District Council (AVDC) in the UK leverages AI to improve its customer service operation. As part of its Connected Knowledge programme it implemented DigitalGenius in Salesforce ServiceCloud with the aim of lowering queries response times and reducing costs. The deep learning algorithms are trained on historical logs and provide predictive case-intelligence and AI-enabled answers. The council has managed to cut the response time in almost half, offering its residents better customer service.
Linked use case: Enhance product and service offering
Baidu does underwriting for consumers with limited credit history using machine learning
Baidu partners Zest Finance to use their machine learning platform to underwrite credit risk for consumers with little credit history. The platform analyses data such as payment and purchase history, customer support data etc. They also analyse variables such as how customers fill out forms, how they navigate websites, whether they are being honest about reporting income etc.
Linked use case: Evaluate customer credit risk using application and other relevant data for faster and more efficient decisions
Baillie Gifford investigates the potential of AI to improve efficiencies through automating fund manager''s tasks
Billie Gifford investment management firms has begun to investigate the potential of AI algorithms to suggest wealth management strategies and provide investment advice.
Linked use case: Forecast asset pricing based on market patterns
Bank of America improved call centre completion time by 23% by tracking and analysing behavioural data with machine learning that identified employee performance increases when they network and share ideas
Bank of America used smart badges to track call centre employee activity with smart badges. They recorded details such as employee office movement, who they interacted with, their tone of voice and whether they leaned into listen or leaned back. The data was analysed with machine learning and they identified that "network cohesiveness" could drive performance as employees were more likely to share ideas and help each other. This resulted in improved call centre completion time by 23%.
Linked use case: Map physical behaviour and interaction across the organisation to Improve team productivity
Bank of NY Mellon reduces processing and trade entry turn around time by 88% and 66% respectively using robotic process automation.
BNY Mellon has deployed more than 20 bots since the start of 2017. Using robotic process automation, the bank uses the bots to complete repetitive tasks, from back office tasks to customer service, enabling its employees to focus on value-adding services. Using software from Blue Prism, the company has improved its processing and trade entry turn around times and estimates that it will achieve an annual saving of $300,000 through its funds transfer bots.
Linked use case: Improve administrative productivity with Robotic Process Automation
Bank of the West announced implementation of Pindrop''s machine learning fraud detection software in its call centres
Bank of the West has turned to Pindrop to improve security and fraud detection for its call centre customer service by analysing customer voices and other call data during the phone call to determine caller authenticity.
Linked use case: Detect potentially fraudulent or nefarious users
Banner Health saves $29m in three years by helping avoid hospitalisation for patients with multiple chronic conditions by remote monitoring of vitals and analysis with machine learning
Banner Health has implemented Philip''s tele-health platform and predictive analytics to manage patients with multiple chronic conditions. Patients are monitored using wearables in real-time and changes in vitals that lead to hospitalisation are identified automatically using machine learning and preventive measures are suggested. Communication with patients to encourage medication adherence and self-care are done using chatbots.
Linked use case: Predict personalised health outcomes to recommend individual treatment approach
Barclays reduces telephone banking user authentication time to under 10 seconds using voice identification
Barclays introduced voice identification for its telephone banking customers in 2016. The system works by identifying over 100 characteristics of a user''s voice to confirm their identity and has reduced the time it takes to authenticate to under 10 seconds.
Linked use case: Authenticate individual identification through voice recognition
Blue Cross Blue Shield reduced post hospitalisation costs by over 20% by driving patient engagement with digital post care programs using smart devices, sensors and machine learning
Blue Cross and Blue Shield of Nebraska (BCBSNE) started using Wellframe''s solution to help customers manage health conditions. Using analytics and mobile app, they were able to implement health coaching and behavioral health programs. The app uses machine learning to map how to connect to customers better. It reduced telephone care manager support costs by 17% and mobile care management costs by 41%.
Linked use case: Detect potential medical events from wearable sensor data and signal emergency response
Booking.com resolves half of customer queries to its text chatbot in five minutes and without human intervention using semi-supervised learning
Booking.com has implemented a Booking Assistant chatbot to answer customer questions via text. The chatbot uses semi-supervised learning to successfully handle more interactions on its own, now resolving 50% without human intervention.
Linked use case: Automate customer service conversations through a text chatbot
Bradesco bank increases customer satisfaction and service efficiency by implementing a virtual agent to aid employees and automate responses
Bradesco bank in Brazil has implemented a conversational agent to interact with customers and employees in Brazilian Portuguese, called Bradesco Inteligência Artificial (BIA). It can answer both speech and text questions, and is presently capable of handling 94% of all questions asked.
Linked use case: Automate customer service conversations through a text chatbot
CARFIT is offering real time issue detection on tires, wheels, shocks and brakes with machine learning
CARFIT, an AI startup providing vibration-based predictive maintenance for cars, has joined the NVIDIA Inception program and will be preparing a monitoring solution for wearing parts based on machine learning. This collaboration will enable the startup to enhance its technical knowledge and accelerate their development of Noise Vibration Harshness (NVH) products.
Linked use case: Predict failure and recommend proactive maintenance on vehicle components
Cleo offers personalised support system for expecting parents which maps user preferences and helps them find matching providers and other services using machine learning
Cleo uses machine learning to personalise support offered to expecting parents. They match user preference with their network of health care providers and as the user interacts more with the app it finds better matching services. Cleo is used by several companies like Pinterest, Reddit, Slack etc to improve employee retention rates.
Linked use case: Monitor and advise on key health indicators during pregnancy
Copa Airlines enhances online customer experience through a chatbot travel agent
Copa Airlines is offering a virtual travel agent, Ana, which is able to respond to customers'' queries, such as destinations or baggage allowances. The chatbot responds within a customer''s browser using natural language processing and supports English and Spanish.
Linked use case: Enable enhanced retail customer experience and service through chatbots
DBS automates responses to 82% of their Digibank customer questions using the KAI chatbot
DBS Bank has introduced an online-only banking platform called Digibank in India, Indonesia and Singapore. Customers access the bank through mobile SMS, online or Facebook Messenger using a chatbot developed by Kasisto, KAI. This has automated 82% of responses to customer questions and reduced the bank''s infrastructure requirements.
Linked use case: Automate customer service conversations through a text chatbot
DGI improves customer service by providing portfolio commentary generated using natural language processing
DGI uses Quill, a natural language generation platform developed by Narrative Science, to generate reports from portfolio attribution analysis. Quill generates natural language reports that detail each fund’s performance, drivers of performance, and comparisons to to indexes and benchmarks, just as a human analyst would.
Linked use case: Create text based content optimised for customers and consumers