Singapore – Regional fashion and lifestyle e-commerce platform ZALORA has announced the launch of its AI-powered customer service chatbot, designed to provide seamless and personalised support to customers across Singapore, Malaysia, Philippines, Indonesia, as well as in Hong Kong and Taiwan.
ZALORA’s new customer service AI-powered chatbot is the result of a partnership between ZALORA’s technology team and Forethought, a provider of customer-first AI experiences.
The chatbot leverages AI that is programmed to learn and understand the intent behind customer inquiries, to provide relevant, accurate responses in a highly intuitive and visual format. For simple queries, it leverages generative AI and draws from an ever-growing comprehensive knowledge base of FAQs, while for more complex questions, it utilises natural language processing to grasp the customers’ intentions before providing useful answers.
Moreover, the chatbot can adapt and respond to any language communicated with it, for instance, an entire conversation can be started in English and ended in Mandarin or any of the local languages seamlessly.
In addition to delivering a seamless customer experience, the chatbot is envisioned to support and augment the capabilities of our human customer service representative. Across the e-commerce industry, millions of customer service inquiries have to be answered each year, which traditionally requires a human customer representative to address.
For ZALORA, what makes its AI-powered app to other ones in the industry is that it has a deep integration with our consumer core services. This means, once customers sign into their ZALORA shopping profiles, the chatbot can directly access and offer personalised information linked to their accounts, this includes information about the status of their orders, deliveries, and returns.
Liam Hutchinson, director of product at ZALORA Group, said, “As a fashion company at heart, we want to help our customers discover great products and brands that make them feel great and confident. ZALORA is known and loved for its industry-best customer service and we’re continuously exploring ways to improve that experience, especially in a more scalable and digital-first way.”
He added, “The innovation around generative AI and large language models (LLMs) has given us access to more capabilities and partnerships to deliver experiences to give our customers an elevated fashion shopping experience.”
Meanwhile, Sumit Jain, chief technology officer at ZALORA Group, commented, “The chatbot sits as part of our broader investments in automation & artificial intelligence under TITAN, our proprietary platform intended to lead fashion e-commerce innovation in maintaining a safe and seamless experience for customers and taking the online shopping experience to the next level.”
As Google prepares to phase out third-party cookies, marketers are exploring alternative strategies to directly gather valuable customer data. In their quest to drive customer engagement on social platforms, AI-powered chatbots have emerged as both a viable and effective tool for boosting conversions. These intelligent chatbots excel at facilitating meaningful conversations, offering real-time personalised assistance that aligns with a brand’s tone and identity.
Training language models typically involves three techniques: pre-training, fine-tuning, and in-context learning. While these approaches aim to improve model performance, they vary in methodologies and objectives. Therefore, when implementing an AI chatbot for your brand, it’s crucial to understand the key differences between these training approaches and, more importantly, recognise why in-context learning models provide the most compelling solution for businesses looking to optimise marketing efforts while minimising costs.
Understanding Training Language Models: Pre-training, Fine-tuning, and In-Context Learning
Having a basic understanding of training language models is advantageous for marketers as it allows them to establish realistic expectations for chatbot capabilities, tailor chatbot responses to align with marketing objectives, and foster effective collaboration with technical teams engaged in chatbot development. Here’s a concise overview of the three techniques:
1. Pre-training:
Purpose: Establish a foundation of knowledge and generate coherent and contextually relevant responses in a wide range of topics.
Benefits: Learns general linguistic patterns, grammar, and semantic relationships.
Limitations: May not be domain-specific or tailored to specific tasks.
Potential Marketing Use Cases: Text generation, language translation, news articles entity recognition, sentiment analysis for social media.
2. Fine-tuning:
Purpose: Adapt the model to a specific domain or task and improve task performance.
Benefits: Learns from task-specific examples and becomes more relevant to a particular application.
Limitations: Requires a labeled dataset specific to the target domain, which can be expensive and time-consuming to create.
Potential Marketing Use Cases: FAQs, text classification for document categorisation, sentiment analysis for market research.
3. In-context learning:
Purpose: Enable the model to understand conversational dynamics and generate contextually appropriate replies based on the given instructions.
Benefits: Learns from conversational exchanges, including user inputs and system responses.
Limitations: Requires a dialogue dataset specific to the target application, but can be curated and augmented more easily compared to creating a fully labelled dataset from scratch.
Potential Marketing Use Cases: Chatbots and virtual assistants, dialogue systems, personalised recommendations.
Characteristics of In-Context Learning AI Chatbots for Marketers
In-context learning AI chatbots offer three useful characteristics that enhance organic customer interactions.
Firstly, contextual prompts can boost the effectiveness of personalised email marketing campaigns. Marketers can use in-context learning language models to ask subscribers about their fitness goals and preferences via email. Analysing the responses enables the generation of personalised product recommendations, leading to a more tailored and impactful email marketing experience.
Secondly, reinforcement learning or structured feedback can drive sales in e-commerce chatbots. Marketers can integrate a reinforcement learning mechanism by asking customers to rate the helpfulness of the chatbot’s responses after each interaction. This feedback allows the chatbot to prioritise and generate accurate, relevant responses, elevating the overall customer experience. Continuous reinforcement learning enables the chatbot to better understand customer queries and provide satisfactory solutions.
Thirdly, through multiple iterations of training, in-context learning AI chatbots can adapt to evolving marketing requirements and improve their responses. For instance, a travel agency’s chatbot can undergo iterative training to stay up-to-date with the latest travel destinations, flight schedules, and hotel availability. As new information becomes available, the chatbot learns and adjusts its responses, delivering customers accurate and timely travel recommendations. This iterative training process ensures that the chatbot remains well-informed and capable of meeting customers’ changing travel needs.
Cost-Effectiveness of In-Context Learning AI Chatbots
In-context learning AI chatbots offer a cost-effective solution for marketers compared to other training approaches. Here’s why:
Reduced Data Labeling Costs
In-context learning AI chatbots require a dialogue dataset specific to the target application. While effort is still needed to collect and curate this dataset, it is often less expensive and time-consuming than creating a fully labelled dataset from scratch, as required in fine-tuning approaches. This cost advantage makes in-context learning more accessible, particularly for businesses with limited resources.
Continuous Learning and Adaptation
In-context learning AI chatbots can continuously improve their performance through reinforcement learning or structured feedback mechanisms. This iterative process allows the chatbot to adapt to changing customer needs and refine its responses over time. Instead of investing in periodic retraining or fine-tuning, marketers can leverage the ongoing learning capabilities of in-context learning models, saving both time and resources.
Improved Operational Efficiency
By automating customer interactions and handling a wide range of queries, in-context learning AI chatbots reduce the need for human intervention. This streamlines operations, enabling marketing teams to allocate their resources more strategically. With AI chatbots taking care of routine queries and tasks, marketers can focus on higher-value initiatives, maximising their productivity and cost-effectiveness.
Enhanced Conversion Rates
In-context learning AI chatbots excel at delivering personalised and contextually relevant responses, which significantly impact conversion rates. By providing tailored recommendations, addressing specific customer needs, and fostering engagement, these chatbots create a more compelling user experience. Higher conversion rates translate to a better return on investment (ROI) for marketing efforts, making in-context learning AI chatbots a cost-effective choice.
Drive Customer Acquisition through AI-Enhanced Conversations
AI and predictive analytics are essential components of a comprehensive marketing strategy. In addition to its cost-effectiveness, in-context learning chatbots enable forward-thinking marketers to identify precise customer segmentations, optimise human resources, and drive conversions more effectively. Are you ready to take the lead and unlock the full potential of your customer interactions? The choice is yours.
This article is written by Henson Tsai, founder and CEO of SleekFlow
The insight is published as part of MARKETECH APAC’s thought leadership series under What’s NEXT 2023-2024. What’s NEXT 2023-2024 is a multi-platform industry initiative which features marketing and industry leaders in APAC sharing their marketing insights and predictions for the upcoming year.
Singapore – The Ascott Limited, the lodging business unit under CapitaLand Investment, is the latest brand to launch its own generative AI-powered travel chatbot. The service, named ‘Cubby’ after its own mascot, is equipped to provide travel insights including destination highlights, accommodation recommendations, must-visit attractions, suggestions for shopping and adventure activities, as well as the best ‘Instagram-worthy’ spots, amongst others.
The ChatGPT-fuelled chatbot is built on Microsoft OpenAI and Azure Services. Cubby also leverages real-time data, using Bing search, Azure Map (Nearby API), Azure Map (Weather API) and other Azure services, alongside data and insights accessed via Ascott’s global website DiscoverASR.com, to deliver on an improved, tech-enabled guest journey.
Currently in its test-bedding stage where learnings are still key, this transformative initiative is part of Ascott’s mindful adoption of AI-driven guest-centric innovations to support its rapid growth trajectory.
For a start, Cubby will be supporting Ascott’s live chat agents, so that the agents can focus on responding to more complex inquiries which require deeper and more thorough engagement with guests. For guests who enjoy having an AI travel buddy that is online on a regular schedule, Cubby has the ability to generate personalised itineraries according to user input.
The itineraries can be customised and amended according to the destination(s) selected, length of stay, travel preferences, and other criteria. Travel tips as well as health and safety information alongside advice on visa requirements, travel budgets and packing checklists are some of the added knowledge Cubby is able to share.
Tan Bee Leng, managing director for brand and marketing at Ascott, said, “An exciting quest of learning and discovery begins as Ascott takes its first step into the future of personalised travel exploration with the pilot launch of Cubby, where innovation meets warm and cuddly hospitality. Cubby, with its AI prowess, taps into a vast treasure trove of data, enabling fast analysis of travel preferences, trends, and recommendations; from suggesting hidden gems to tailoring itineraries that match specific areas of interests.”
She added, “As we journey alongside our valued guests in this shared adventure of experimentation, every interaction with Cubby is set to unlock a realm of limitless possibilities in AI-driven travel planning. Ascott is dedicated to nurturing Cubby’s growth, empowering it to deliver more personalised and engaging experiences with each interaction.”
In anticipation of evolving guest expectations, Cubby will become multichannel in its later phase, seamlessly integrating with different applications for greater convenience. Improved language capabilities will also be implemented to ensure that Cubby is optimised for local use. This integration will allow Cubby to respond instantly across channels, using the guest’s preferred language and platform while handling an immense volume of guest inquiries simultaneously and consistently.
“From computer vision to natural language processing, Ascott recognises the pivotal role of AI technology in shaping the future of travel experiences. The adoption of generative AI tools to create advertising campaigns has provided us a shorter time-to-market, and the development of a chatbot has deepened our level of engagement with guests,” Tan said.
She added, “Our commitment to equipping our associates with knowledge and expertise in AI is not merely an investment; it’s a pledge to futureproof Ascott and create a new paradigm of personalised engagement with our valued guests. Embracing AI humbles us in the face of technology’s vast possibilities, empowering Ascott to learn, adapt, and evolve with the times, so that heartfelt hospitality and cutting-edge innovation can harmoniously intertwine.”
Other brands that have previously released their own travel chatbots include Expedia and Trip.com.
Singapore – Singapore telcoM1 has tapped IT service management company Amazon Web Services to enhance its current customer experience by launching Maxine, a VoiceBot for its existing hotlines.
Said VoiceBot is built on Amazon Connect, AWS’s omnichannel cloud-based contact center service that helps improve contact center agent productivity and end-user customer experiences. ‘Maxine’ is able to engage in more lifelike conversations with customers, as well as help improve end-user customer experiences by engaging them in open-ended conversations instead of menu-driven interfaces.
The deployment of ‘Maxine’ is part of M1’s continuous transformation journey to be a digital platform. As a cloud native solution, M1 is able to regularly develop and deploy new and incremental features and capabilities that enhance Maxine’s services.
This solution enables M1 to scale up and down in a short period of time. It also provides call center agents the flexibility they need to work remotely, without compromising the customer experience.
According to Stamford Low, director of customer experience and retail at M1, customer experience has always been a top priority for them since embarking on their digital transformation journey two years ago. He added as well that they have doubled down on delivering exceptional experiences for their customers.
“We are committed to ensuring a seamless and engaging experience for our customers on all platforms, including our hotlines. With technology as our enabler, M1 will continue to train Maxine to improve its capabilities and add more value to our customers, through the development of a self-help service,” Low stated.
Meanwhile, Dean Samuels, chief technologist for ASEAN at Amazon Web Services, commented that customers, such as those with M1, rely on actionable data to provide faster and more holistic customer experiences, optimize agents’ time based on what matters most, and enable customer service managers to take action in real time.
“With Amazon Connect, M1 can provide superior customer service at a lower cost with an easy-to-use omnichannel cloud contact center. Embedded artificial intelligence (AI) and machine learning (ML) with Amazon Connect makes it easy to automate interactions, understand customer sentiment, authenticate callers, and enable capabilities like interactive voice response (IVR) and chatbots,” Samuels explained.
To date, M1 has its 1627 (Bespoke), 1622 (Business) and 1800-843-8288 (Prepaid) hotlines operating on the Amazon Connect platform. This will be progressively rolled out to other hotlines.
Retail has been challenged on every front over the last year and a half, and as a result, there have been significant changes to customer experience (CX); from livestream shopping and social commerce to supply chain disruptions. All of which has pivoted towards digital transformation.
While customers have adapted to new digital models, it’s important to note that offline shopping isn’t going anywhere. The future of retail will embrace both online and offline shopping, creating a hybrid experience that will provide the customer with even more value. According to Statista, more than 57% of Asia Pacific (APAC) consumers will shop in physical stores post-COVID restrictions. Foot traffic will still be just as desirable as it is now but overall CX will take center stage.
Meet the metaverse
In late 2021, Facebook changed its name to Meta to reflect its growing focus on the metaverse. But what exactly is the metaverse? It is a shared, persistent, 3D virtual space where people can meet and interact. Augmented Reality (AR) and VR technologies are essential parts of the metaverse. These advances in digital imaging, display, and output devices are what make the metaverse possible. Bloomberg Intelligence forecasts that the market size for the metaverse could reach up to $800b by 2024. How will it impact retail in the next year?
Online shopping and deliveries quickly became the new standard throughout the COVID-19 pandemic, a trend that will be accelerated by the metaverse. With AR and VR experiences, consumers will be able to explore brands and products from the comfort of their own homes. Consumers will no longer need to frequent physical stores to try new products before purchasing.
The metaverse will also enable more interactive-in store experiences. For instance, in Malaysia and Singapore, property developer CapitaLand Investment launched ‘A Jolly Molly Christmas’ festive campaign in its malls, introducing shoppers to the AR world allowing them to interact with Singapore’s virtual influencer, Rae, in the physical world. Real-world stores are now becoming the gateway to the metaverse and will be the next evolution of omnichannel experience.
Surge in social commerce
In 2022, social commerce will continue to bring fun back into the digital shopping experience. Social commerce sales in the region are expected to surpass US$4t by 2024, expanding 25% year-on-year.
According to the Forrester Analytics Consumer Technographics Benchmark Survey, 2021, 85% of APAC consumers are using social media to discover, 83% to research, and ultimately, 76% are buying products. The number is projected to grow as features such as livestream shopping draw more engagement than other types of posts.
B2C social commerce investments are paying off: B2C companies in APAC have generated 10% of revenue from social media as cited in Forrester Global Marketing Survey, 2021 (B2C). Not only that, 55% of marketers increased their social media marketing budget in 2021.
Moving forward, brands investing in social commerce must provide more personalized customer interactions and care, such as virtual agents who can instantly answer questions, share the latest offers, or recommend additional products with the consumer. We’ll see more brands providing a connection throughout the customer social journey. They will begin employing one-to-one video shopping, implementing conversational commerce, and launching virtual video boutiques. Above all, brands must provide excellent care on social channels, using the right technology combined with the human touch.
Conversational chatbots
Advanced conversational technology will be key to providing such experiences at scale. Chatbots will play a key role in the next year, as more and more brands deploy advanced chatbots in their social shops that can handle sophisticated queries — and escalate to human agents when needed.
Most brands are employing bots that can provide routine answers to basic questions. While they don’t respond to more complex customer queries, this will change as more companies add AI-powered bots with advanced contextual and consultative abilities. In the next 12 to 24 months, Forrester reports that the vast majority of B2C brands plan to implement or are interested in developing advanced social bots that can provide a higher level of assistance.
Such advances in automation will enable more effective and satisfying care throughout the customer journey — before, during, and after the purchase. In many cases, social bots will respond to queries that used to require a human agent. More and more, shoppers on social channels will be able to access personalized answers, recommendations, and resolutions to their problems, whenever they need help.
Looking forward
Over the next year, brands will take what they learned during the pandemic and leverage technology-driven solutions that help build deeper connections and relationships with their customers. By creating immersive, personalized, and hybrid experiences, and always keeping CX at the heart of everything, retailers can excel in 2022.
This article is written by Shellie Vornhagen, CXO at CX platform Emplifi.
The article is published as part of MARKETECH APAC’s thought leadership series What’s NEXT.This features marketing leaders sharing their marketing insights and predictions for the upcoming year. The series aims to equip marketers with actionable insights to future-ready their marketing strategies.
If you are a marketing leader and have insights that you’d like to share with regards to the upcoming trends and practices in marketing, please reach out to [email protected]for an opportunity to have your thought-leadership published on the platform.
Customer experience is founded on customer expectations. Marketing leaders must understand the evolving expectations that consumers have of their interactions with brands – this includes customer experience and support that, hopefully, meets their needs but ideally delivers above and beyond these expectations.
As the pandemic turns endemic, delivering a consistently excellent customer experience is by no means an easy feat. Safety measures to protect our health and well-being have created a next normal for marketers. In fact, brand and marketing decision-makers need to constantly calibrate and innovate how they deliver on their brand’s promise and keep an engaged audience base.
The silver lining is that this scenario provides a real case for rolling out genuine omnichannel customer delivery and engagement models – something that has, for far too long, been relegated to the back burner for many brands. By setting new goals for customer service standards, relooking operational processes, and investing in technology solutions, strengthening consumer connections is possible even in a time when change abounds and reliability is imperative.
As such, we’ve seen customer experience agents take on multiple and increasingly important roles: from technicians and consultative sellers to today’s need for them to be empathetic community managers.
Not just a touch-feely bonus: The importance of empathy today
A recent McKinsey study reported that businesses that have empathy towards the customer will have a net positive benefit on their bottom line. Among 170 publicly traded companies examined, the top 10 with outstanding empathy ratings outperformed the bottom 10 by two times on the stock market.
Today’s environment has led to general expectations of a certain level of emotional empathy, no matter who we are interacting with. And brands are not spared – digital empathy and human empathy have taken on a new urgency.
Brands now have to understand audience emotions, their feelings, and thoughts, their pressures, their desired digital and real-world experiences, and even anticipate future reactions. Empathetic brands that are using this period to rethink, reinvent, and leapfrog will most certainly be developing evolved blueprints for the entire pre-, during, and post-transaction customer journey as a result. At the frontlines of the customer journey – the shape-shifting customer experience agent, who must now play multiple roles.
Technology as an ironic accelerator for empathy
Some may think empathy and technology don’t go together. In fact, technology can help customer experience agents manage their hybrid roles and fulfill the need to be empathetic community managers. By combining proactive support with increased automation, brands can provide personalized support engagement at scale, without sacrificing empathy.
By centralizing omnichannel communications with customers, organizations can upgrade and reinvent the role of customer experience agents. For example, with the ability to manage communication over Instagram and other social media channels through industry-leading contact-center-as-a-solution services available in the market today, customer experience agents have the ability to become community management extraordinaires. Empowering agents with 360-degree customer profiles and full conversation histories all in one place will allow them to unlock valuable insights and provide fast and personalized customer support.
Unlocking the power of social media messaging for customer support is more important than ever as we consider these stats from data from global cloud communications platform, Infobip: 70% of people globally expect to message businesses for customer service questions, and 64% would rather message than call a business.
As agents and representatives help transform customer interactions from being transactional to becoming more involved, these experiences are likely to be highly engaged, emotionally charged, and mission-critical for loyalty and retention. Consumers will also in turn anticipate that agents demonstrate they understand their problems and provide relevant reassurance.
This points to agents needing to be able to put themselves in the customer’s shoes and build quick rapport. This doesn’t just affect formats that provide visual and verbal cues – it also applies to digital channels such as chat, email, and social media, where agents cannot be certain of the tone of the conversation.
AI is maturing and here to help
While human empathy is natural, artificial empathy must be learned based on the data collected within the rules or framework set up by a human. This is where technology like artificial intelligence (AI) can come into play. AI that analyzes incoming messages and highlights factors like sentiment, helps prepare agents to respond accordingly.
Thanks to natural language processing (NLP), we can communicate with chatbots using human speech. NLP is an area of AI that helps chatbots understand the way your customers communicate.In other words, it means enabling machines, like chatbots, to communicate the way humans would.
An NLP chatbot is an AI chatbot that uses natural language processing, based on deep learning, to better identify a customer’s intent and therefore provide more valuable support.
From the customer’s point of view, NLP helps them feel understood. From a brand’s point of view, these chatbots elevate customer support, create helpful dialogue, and capture insights into your customers’ goals and challenges. This lets you build a brand voice while simultaneously providing a customer-centric approach.
Chatbots provide instant answers. And when boosted by NLP, they’ll quickly understand customer questions to respond faster than humans can. In addition to text, these chatbots can enhance the natural conversation experience by sharing helpful images (product images), videos (how-to videos, product explainers), map locations (store or service center finders), and more. These lightning-quick responses help build customer trust and positively impact customer satisfaction as well as retention rates.
Malaysian Insurance company Gibraltar BSN launched GINA in 2019
Take for example Gibraltar BSN, a Malaysian life insurance company offering life and medical insurance along with saving and investment plans. The insurer had concerns that too many customers in Malaysia had not received important and sensitive documents sent through the post, especially during the pandemic. The company also wanted to optimize its contact center in a way that would allow them to engage customers using modern digital channels but still provide a critical level of empathy during a sensitive time.
By deploying AI-powered NLP chatbots, Gibraltar BSN facilitated the creation of its automated chatbot – GINA. With GINA handling simple customer service inquiries, human agents can help clients with more complex inquiries and offer a more personalized approach. Gibraltar BSN saw a 40% reduction in cost for delivering e-policies after rolling out this transformation.
Harnessing the full potential of the customer experience function
With the right level of support given to customer experience agents, the potential for businesses to exceed consumer expectations in a digital world is limitless. Today, customer experience, service, and support – an oft-neglected function – have the aid of readily available technology to bring another dimension of brand success.
For marketing leaders, working with CX is about quickly adapting to and adopting emerging technologies for their benefit. Be one of the first businesses to leapfrog and handle messaging at scale on social media, connect to new customers, and strengthen relationships with existing ones.
This article is written by Viven Ang, regional manager for APAC at Infobip.
Singapore – yellow.ai, a global conversation customer experience (CX) automation platform, has announced that is rolling out its newest AI-powered voice virtual assistant features across markets in Southeast Asia, a direct response to adding more channels to their existing text automation channels such as those in-site and in third-party messaging apps.
The human-like voice AI bots can understand sentiments, intent and past behavior, and also modify pitch, tone, excitement, and more, to suit customer sentiment and intent on channels like Telephony, Google Assistant and Alexa. The company’s bots can natively converse naturally in more than 100 languages across text and voice, such as Bahasa Malay, Bahasa Indonesia, Tagalog, Mandarin, English, Tamil, and more.
According to the company, with the growing demand for hyper-automation and on-demand resolution by customers in Singapore, adding voice AI capabilities to yellow.ai’s rich customer experience automation platform is a natural evolution to realizing a vision of total CX automation.
This is supported by a statement from Raghu Ravinutala, CEO and co-founder at yellow.ai, who explained that conversational interfaces are changing how we relate to brands and voice is playing a key role in enabling smarter brand-to-consumer interactions.
“Today, growth and success in every business are highly indexed to creating personalized and differentiated customer experiences. At yellow.ai, we are dedicated to enabling human-like, engaging conversations with our conversational CX platform, which is the ultimate balance between human + AI capabilities,” Ravintula stated.
Yellow.ai’s launch of these features follows after recent findings by Gartner, in which they predict that by 2025, 40% of all inbound voice communications to call centers will use voice bots. As a company who has worked with over 109 brands in the region, yellow.ai offers enterprise-grade chat and voice bots, weaving in the best of AI and human intelligence to deliver highly differentiated elevated customer experience at a fraction of the current operational cost.
“With us, enterprises can successfully automate customer experience while elevating the quality of customer interactions. Now we are actively expanding our strategic partnerships and offices around the world, with Singapore as a key market, in Southeast Asia. We are delighted to extend our repertoire in the region with ‘conversational voice AI’, the future of CX,” Ravintula concluded.
Hong Kong – HGC Global Communications (HGC) has launched its retail ICT (information, communications, and technology) solution to cater to the needs of SME retailers in making their digital transformation strategy easier, especially as enterprise activity has been greatly affected by the pandemic.
An initial offering by the network company is making retailers stay connected to their customers, including Whatsapp+ service and automated chatbots for the retailer’s online chat system.
Furthermore, the new offering also aids SMEs in creating their online shop from scratch, including marketplace tools such as inventory management, trade reports, and analysis, as well as support for multiple payment methods.
Lastly, the digital offering allows retailers, more specifically in the catering industry, to practice electronic point of sale (ePOS) systems. The system supports digital menus, enabling customers to use their smartphones to order and pay for meals. This can reduce the necessary manpower and limit mistaken orders, so restaurants can deploy staff more flexibly and efficiently.
“SMEs are facing various challenges running their business in the midst of the pandemic. Even so, this presents retailers with an important opportunity to optimize their business operations. HGC strives to stand by SMEs at this critical time. Our Retail ICT solution can efficiently address the difficulties they encounter,” said Joe Cheong, COO for corporate business & enterprise market at HGC.
He added, “With the professional follow-up and support provided by HGC’s consultant teams, as well as our competitive pricing, we can guide them on a journey of rapid digital transformation to achieve significant improvements in operational efficiency. We hope to ease the pressure on SMEs, empowering them to continue running their business and identifying new business opportunities even during the pandemic.”
In addition to the digital marketplace package, HGC also offers retailers a unified communication solution (HGC UC) that combines business voice and mobile communication, plus other value-added services like mobile video conferencing to fulfill the needs of enterprises operating during the pandemic through a one-stop ICT solution.
India – India-based software development company XcelTec recently announced Ample, the company’s answer to sales automation in businesses using personalized bots.
Ample, which can be personalized by every user, is powered by artificial intelligence. This feature ensures the removal of any complexity that may arise in showing product demonstrations online. With the latest video bot release, XcelTec expects that business users will move towards online media for their business’ sales team, ensuring them to engage with customers online, with aid of the sales automation bots.
The recent software release is part of the company’s goal to simplify website chatbots, which has seen a 50% increase in sales activities online.
Singapore – Over the past 12 months, more than half of businesses in Singapore or 67% of them have used fintech in running their operations, and within this percentage, the top three forms of fintech used emerged to be mobile payments or digital wallets, robo-advisory or chatbots, and open banking APIs, according to a report by CPA Australia.
Mobile payments recorded the most adoption with 47% of businesses, followed by chatbots with 34%, while 30% said they have used open banking APIs.
Singapore has been widely known for being a top technology hub, and as the coronavirus started threatening safety, the government has further encouraged the use of fintech. In April, the Monetary Authority of Singapore (MAS) urged individuals and businesses to use digital finance services and e-payments to help contain physical contact.
Amid social distancing directives, more businesses have expressed desires to adopt fintech, with 73% expecting to use at least one fintech product or service in the next 12 months, with a third of them citing COVID-19 as a reason for further usage, to operate anew amid disruptions in operations.
The most boost in adoption is seen to come from the need to increase efficiency in doing business, with nearly 6 in 10 respondents, or 59.1%, identifying it as an important factor. Meanwhile, more than 4 in 10, or 43.6%, of businesses expect to use fintech to help them better understand and improve customer experience.
The top three most used fintech are still the same ones seen to drive the adoption for the coming months. About 42.7% of businesses believe that they will use mobile payments the most, followed by robo-advisory and chatbots with 23.6% , and open banking APIs with 19.1%.
While the report revealed that a positive adoption of fintech is on the horizon, it also found certain factors that hinder businesses to jump in.
The top concern showed to be cybersecurity with 34% identifying it as a barrier, while a lack of fintech understanding and knowledge within the board and senior management was also a concern with 30%. Meanwhile, 26% simply did not consider fintech to be necessary for business.
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