natural language processing Archives - BotCore Enterprise Chatbot Fri, 15 Mar 2024 09:55:55 +0000 en-US hourly 1 https://wordpress.org/?v=6.6.1 https://botcore.ai/wp-content/uploads/2020/02/cropped-favicon-32x32-1-70x70.png natural language processing Archives - BotCore 32 32 Top 5 Ways Intelligent Virtual Assistants Augment Customer Contact Centers in Europe https://botcore.ai/blog/how-virtual-assitants-can-support-contact-centers-in-europe/ Mon, 12 Sep 2022 06:39:25 +0000 https://botcore.ai/?p=10707 Top 5 Ways Intelligent Virtual Assistants Augment Customer Contact Centers in Europe In today’s fast-paced, digital-first world, customer needs and expectations continue to rise, raising the demand for customer contact centers all over the globe.  In Europe, particularly, the change in customer demographics and the growing popularity of e-commerce has led to increasing pressure on […]

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Top 5 Ways Intelligent Virtual Assistants Augment Customer Contact Centers in Europe

In today’s fast-paced, digital-first world, customer needs and expectations continue to rise, raising the demand for customer contact centers all over the globe. 

In Europe, particularly, the change in customer demographics and the growing popularity of e-commerce has led to increasing pressure on contact centers for customer support. Here, companies, small, medium, and large, believe in focusing on their core operations; hence, Europe is one of the biggest markets that is outsourcing contact center operations.

The call center outsourcing market share in Europe is expected to increase by USD 3.73 billion from 2021 to 2026, and the market’s growth momentum will accelerate at a CAGR of 3.53%. The retail, IT, and telecom sectors will be the most significant drivers of contact center outsourcing in Europe from 2022-2024.

High agent volume and the need for diversity, scalability, and multilingual capabilities are the most significant reasons why most European enterprises are turning to automation and AI to scale their contact center operations.

That’s where intelligent virtual assistants, including chat and voice bots, come into the picture. Virtual assistants, also known as virtual agents, use intelligent conversational interfaces powered by AI, machine learning, and natural language processing technologies to understand and respond to customer inquiries in a human-like manner.

Let’s know the five ways  virtual assistants are well-placed to support European contact centers.

Five Ways Customer Support Chatbots Augment Contact Centers in Europe

1. Deliver exceptional customer support across geographies and time zones.

European companies prefer to focus on their core revenue-generating activities and prefer to outsource their contact center operations. However, they mostly outsource to nearby regions and time zones to account for language and cultural similarities.

This strategy suffers from a major drawback. Rapidly changing customer demographics have necessitated quick, 24X7 customer support. Thus, organizations may want to set up contact centers in distant countries to cover customer support beyond their usual business hours, demanding additional resources in terms of staffing and equipment.

AI-powered customer support chatbots transcend locational boundaries, especially in a continent like Europe that has multiple time zones, and provide instant answers to all customer queries at all times.

2. Make omnichannel chatbots the new gold standard in customer support in Europe.

Customers in different parts of Europe prefer different ways and channels of contacting contact center support. For example, the Netherlands has the highest number of non-telephone channel users, with email and web chat being the most popular.

On the flip side, people in Norway, Denmark, and Sweden prefer social media and web chat over email. The bottom line is that people prefer to communicate with brands on the channel of their choice and may even want to switch channels in the middle of an ongoing support case.

That’s where omnichannel chatbots play a crucial role. Virtual assistants can offer omnichannel experiences so customers can experience consistent and personalized brand engagement on their preferred channels. Moreover, customers can seamlessly transition from one channel to another without losing the context of the original conversation.

3. Address inquiries and grievances in customers’ native tongue in the land of many languages.

In a continent like Europe, where people speak multiple languages, it is challenging to personalize customer support for the entire customer base. After all, customers prefer being engaged in their native language. Moreover, it makes them feel comfortable, valued and heard.

Hiring contact center agents who speak multiple languages or training existing ones to speak in different tongues is costly in terms of time and money. That’s where virtual assistants play a crucial role.

AI virtual assistants support contact centers by detecting the user’s language and switching the conversation flow to the native tongue. What’s more, the customer support chatbot can remember the customer’s language preferences and then reach out to them in the same language in case of a proactive outbound engagement.

4. Providing scalable self-service options and data-enriched proactive engagement.

In recent times, Europe has seen steady growth in using self-service solutions like websites, social networking channels (Facebook Messenger, Instagram, Telegram, whatsapp etc.), and IVR. These are easily accessible and take a considerable load off contact centers. To work productively and provide seamless, more meaningful customer engagement, organizations in Europe are embedding customer support bots on these channels.

70% of contact center agents say there are fewer calls when chatbots are available. Customer support bots and virtual assistants can shorten waiting times and collect relevant customer data before the call is passed on to the human agent. In cases where the requests are simple and repetitive, virtual assistants can solve them faster than the contact center agent.

Voice bot platforms have paved the way for conversational IVR in contact centers. Voice bots embedded within traditional IVR systems leverage natural language processing and speech recognition technologies to respond to users’ verbal commands using voice or text, enabling faster, more accessible, and more interactive user support. 

Moreover, predictive data analytics maps out the entire customer journey to personalize interactions, reduce mean time to resolve (MTTR), and increase overall customer satisfaction (CSAT).

5. Cost is always a significant factor!

Using virtual assistants — chat and voice bots, leads to major cost reductions for all enterprises.

For starters, outsourced customer service agents cost as much as €22,200 per agent annually in countries like Denmark, Sweden, and Norway. Even for employees hired in Central and Eastern Europe, where contact center jobs are amongst the better-paid ones, the cost of hiring a contact center agent can come out to be around €6,436 per year.

In short, hiring more contact center agents will always prove heavier on the organization’s pockets. On the other hand, intelligent virtual assistants can solve thousands of problems at a few pennies per transaction, making them highly viable, almost a mandate for countries in Europe where labor costs are very high.

How can Acuvate help?

Acuvate helps clients build and deploy virtual assistants – customer support & engagement chatbots and voice bots with its enterprise bot-building platform, BotCore.

As a Microsoft Gold Partner, we have the opportunity of leveraging the best of Microsoft’s AI, machine learning, and natural language processing (NLP) frameworks, including the Microsoft Bot Framework, Azure Cognitive Services, and LUIS.

Besides supporting languages like German, French, English, Latin, and many more (multilingual functionality), our bots work on popular enterprise channels (Teams, Slack, ProofHub, etc.) and social channels (Facebook Messenger, Instagram, Telegram, whatsapp etc.), thus helping organizations engage a geographically-dispersed workforce and customer base.

To know more about our bots and virtual assistants, please schedule a personalized consultation with our experts.

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]]> Conversational Commerce in various Social Channels https://botcore.ai/blog/conversational-commerce-in-social-channels/ Wed, 06 Jul 2022 12:17:59 +0000 https://botcore.ai/?p=10409 Conversational Commerce in various Social Channels We live in an era where artificial intelligence (AI) has taken over every aspect of our being. And customer experience (CX) is not alien to it. As the world embraces new-age customer experiences (CX) with open hands, warranting the delivery of hyper-personalized customer engagement to a more informed, connected, […]

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Conversational Commerce in various Social Channels

We live in an era where artificial intelligence (AI) has taken over every aspect of our being. And customer experience (CX) is not alien to it.

As the world embraces new-age customer experiences (CX) with open hands, warranting the delivery of hyper-personalized customer engagement to a more informed, connected, and empowered customer, organizations are left to deal with several questions and dilemmas.

After all, endless customer conversations are happening online on various social channels — Facebook, Instagram, WhatsApp, Twitter —  it’s challenging to cover every digital touchpoint and use the enormous amount of customer data it generates to fathom “what customers want.”

That’s where conversational commerce comes to the rescue. Powered by AI, conversational commerce solutions like chatbots, voice bots, and other digital assistants have enabled companies to render human-like customer interactions at scale. Conversational commerce apps on various social channels leverage the unending amount of customer data to analyze customer behavior, predict their needs to deliver proactive engagement, and provide more personalized support.

Let’s explore more.

Conversational commerce in various social channels - What can it do for your business?

“Human interaction matters now — 82% of U.S. and 74% of non-U.S. consumers want more of it in the future. Regardless, the technology supporting human interaction must be seamless and unobtrusive across channels,” stated PWC’s latest report, Experience is everything: Here’s how to get it right.

Conversational commerce solutions in the form of Facebook, Instagram, and WhatsApp chatbots are making this a reality. 

Conversational chat commerce, powered by advanced technologies like machine learning, artificial intelligence, and natural language processing, is the latest paradigm in the customer experience world that draws in huge investments from the C-suite leaders. Chat and voice bots available on various social channels are now being used to solve a host of simple and complex customer queries 24X7, understand customer emotions, store information about purchase history, discover patterns in their behavior, and act accordingly to achieve maximum customer satisfaction.

Modern customers live online. They may be awake at two at night, browsing for new products or even reaching out to customer support. And they may do so from their desired social channel, be it Messenger, WhatsApp, or Instagram. Moreover, they may want to switch channels amidst an ongoing support case, i.e., change from WhatsApp to Facebook. Here conversational commerce solutions take charge. Not only do they provide instant, round-the-clock customer support, but e-commerce bots can retain the original context of the conversation to allow seamless switching without the customer being asked to start over.

So, what are the use cases of conversational commerce? How can chat and voice bots present on various social channels delight customers and build value at each stage of the sales funnel?

Let’s find out.

Curating a personalized sales journey through conversational commerce

Below, we present to you the use cases of conversational commerce on various social channels that can help organizations tailor sales journeys and win the life-long loyalty of their customers.

  • Amplify reach to new customer segments by pushing alerts about new products, collecting customer preferences and behavior data, answering initial queries, and delivering personalized recommendations and tips.
  • Acquire customers by curating creative marketing campaigns on the most popular social channels, assisting customers with website navigation, payment, checkout, and product use, and tailoring product suggestions according to purchase history and past behavior.
  • Is this shirt available in a different color? When will I receive my package? Customers can get their queries addressed simply by approaching the brand’s chatbot on the social channel of their liking. In this way, not only customer support becomes more accessible, but brands also get hold of valuable information that can help personalize CX.
  • As and when the customer’s desired product becomes available, e-commerce bots can push notifications and alerts through various social channels and provide a CTA to “Buy Now.” It can also suggest alternative and supplementary products as the case may demand.
  • Collect customer feedback through Instagram and Facebook surveys on a test batch of a new product.
  • Curate loyalty programs and send personalized discount and reward coupons to encourage customers to share product ratings and feedback and develop long-lasting relationships.

Take a look at the type of conversations a bot can have with your customers.

Conversation Bot
Conversation
Conversations A Bot

A sneak peek into a few conversational commerce solutions on various social channels

At Acuvate, we help clients build and deploy bots on various social channels that consistently deliver exceptional CX with minimum friction or hassle with our enterprise bot-building platform called BotCore.

  • BotCore is a Microsoft Preferred Co-Sell-ready solution that leverages Microsoft’s best AI, machine learning (ML), and natural language processing (NLP) technologies.
  • Our conversational commerce solutions are deployable on popular social channels (WhatsApp, Facebook, Instagram, etc.) and support multiple languages, including German, French, Italian, English, etc.

Here are a few examples of how brands are using conversational commerce in various social channels to engage, inform, and support their customers.

1. POND’s SAL chatbot for Facebook Messenger

Chatbot For Facebook Messenger

An FB Messenger bot, also available on webchat in different countries, POND’s SAL can be accessed through Unilever’s flagship store on Shopee. Using technologies like AI and augmented reality (AR),  SAL interacts three-dimensionally with customers to deliver personalized and more immersive shopping experiences.

When a user uploads a selfie,  SAL works on identifying critical skincare concerns across four significant areas, namely, pimples, wrinkles, spots, and uneven skin tone.

The bot also sends relevant skincare articles and beauty tips to keep the users engaged.

Having completed the skin analysis, SAL then recommends suitable products from POND’s according to the customer’s skin condition.

2. pRANA’s chatbot for Facebook Messenger

Prana’s Chatbot For Facebook Messenger

Sustainable clothing company prAna’s chatbot for Facebook Messenger uses a casual, friendly tone to help customers shop online or get the information they need.

The bot helps shoppers navigate through the online store by asking them to choose between options like  “Shop Women’s, “Shop Men’s, or “Shop Best Sellers.” Moreover, the bot’s intuitive conversational AI interface gives the option to type a message or easily navigate to the previous menu.

3. BMW’s “Follow Now” chatbot on WhatsApp

Chatbot On Whatsapp

To combat the massive inflow of service requests when summers and winters are approaching, BMW launched its “Follow Now” chatbot on WhatsApp to help customers book an appointment from the convenience of their home from an app they use every day.

The bot offers real-time updates on the service status of their car and intimates them when their cars are ready for pickup. Moreover, service assistants can intervene and answer certain queries if the bot isn’t able to answer those.

4. Clear’s Cera chatbot for Facebook Messenger

Clear’s Cera Chatbot For Facebook Messenger

Clear is Unilever’s leading anti-dandruff shampoo brand. The company’s chatbot Cera, available for the Indonesian market on Facebook Messenger, acts as your go-to hair care assistant offering personalized hair diagnosis, advice, and product recommendations for dandruff, dry hair, oily hair, etc.

The bot proactively sends relevant articles to the users after analyzing their behavior, preferences, and needs and delivers answers to a range of frequently asked questions related to hair care.

5. Roma by Rochi’s chatbot for Instagram

Chatbot For Instagram

Roma by Rochi is a popular fashion brand in Argentina that revolves around encouraging women to embrace their sense of style.

Though quite popular on Instagram from likes, comments, and story mentions, recently, the brand launched a digital assistant on the social media platform to assist with a “tag and like” giveaway.

Post the deployment of the bot; the brand experienced an astounding 82% increase in reach in one week and a whopping 741% rise in engagement.

The brand also has a Facebook Messenger bot, which they use to answer queries, upsell products, and notify customers when sales begin.

We, at Acuvate, can help clients across industries build engaging conversational commerce experiences in various social channels using our enterprise bot-building platform called BotCore. To know more, please feel free to schedule a personalized consultation with our AI experts.

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]]> Understanding The Role Of Sentiment Analysis In Chatbots https://botcore.ai/blog/understanding-the-role-of-sentiment-analysis-in-chatbots/ Fri, 01 Mar 2019 10:00:00 +0000 https://botcore.ai/?p=4003 Understanding The Role Of Sentiment Analysis In Chatbots Chatbot technology has had an undeniable impact on digital transformation of organizations; customer experience management, in particular. When we talk about conversational AI solutions and other AI-based applications for augmenting customer  and employee experience, chatbots emerge as a front-runner. According to Gartner, 70% of white-collar workers will engage […]

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Understanding The Role Of Sentiment Analysis In Chatbots

Chatbot technology has had an undeniable impact on digital transformation of organizations; customer experience management, in particular. When we talk about conversational AI solutions and other AI-based applications for augmenting customer  and employee experience, chatbots emerge as a front-runner.

According to Gartner, 70% of white-collar workers will engage with conversational platforms on a regular basis in the next three years. The research firm’s 2019 CIO Survey revealed that chatbots are the main AI-based application used by the participating companies. Therefore, we can see increased investment in chatbot development and deployment.

“There has been a more than 160% increase in client interest around implementing chatbots and associated technologies in 2018 from previous years. This increase has been driven by customer service, knowledge management and user support,” shared Van Baker, VP Analyst at Gartner.

However, in the earlier stages, chatbots used to have limited capabilities and deliver standard responses. With the advancements in AI and machine learning, chatbots have become more powerful and incorporated new features that helped improve user experience. And one of these latest features that is taking user experience to the next level is sentiment analysis.

Sentiment analysis helps a chatbot to understand the emotions and state of mind of the users by analyzing their input text or voice. This analysis enables chatbots to better steer conversations and deliver the right responses. Sentiment analysis is also playing a key role in driving user adoption for enterprise chatbots.

Let’s deep dive!

understanding sentiment analysis

Sentiment analysis is a sub field of machine learning and natural language processing that deals with extracting thoughts, opinions, or sentiments from voice or textual data. It is currently widely used in marketing and customer service functions to analyse customer data from surveys, social media and reviews. This not only enables businesses to understand the impact of their products/services but also  to tweak their strategies as per the end consumers’ opinions.

In the context of chatbots, sentiment analysis helps in developing the bot’s emotional intelligence.

While machine learning helps to personalize the chatbot’s performance by harnessing historical customer data, NLP helps to evaluate and interpret the information sent by the customer in real-time.

These two features collectively help chatbots to deliver relevant responses and conduct meaningful conversations. Sentiment analysis takes this a step further by enabling bots to understand human moods and emotions.

Let’s break down how sentiment analysis in chatbots works:

  • It first identifies sentiment types and gauges if the emotions displayed in the conversation are positive, negative, neutral or objective. The technology detects emotions like anger, happiness, disgust, fear, sadness, curiosity, positivity and other range of emotions.

  • NLP and AI work in tandem to measures the intensity of the emotions and assign a numerical score to each of the core emotions.

  • After detection and classification, sentiment analysis presents the final output that enables chatbot to steer the conversation in the right direction. For example, for a text with a high positive score (joy + happiness), the digital assistant can use that as an opportunity for product recommendation or sales conversion. And in the case of a high negative score (sad + anger), the chatbot can escalate the complaint and transfer the call to a live support agent.

how can it be beneficial for your business?

Be it banking, insurance, hospitality, healthcare, travel or eCommerce, all customer-facing industries can benefit from sophisticated new-age chatbots that are integrated with sentiment analysis.

Take, American cosmetics brand CoverGirl, for instance. The company developed an influencer chatbot enabled by sentiment analysis, which helped them to improve mobile commerce performance. 91%  of the conversations via the chatbot earned positive sentiment, and on an average 17 messages were exchanged per conversation that reflects high engagement rate. In addition, 48% of those conversations led to coupon delivery and the coupons’ click through-rate was an impressive 51%.

The above example illustrates the effectiveness of sentiment analysis-powered chatbots in stimulating conversations, identifying customers’ intentions, providing relevant answers and delivering a meaningful customer experience.

Listed below are a few of the benefits of using a sentiment analysis enabled chatbot to augment customer experience.

  • Learn how customers feel about your brand

Emotions heavily influence a person’s decision making process. How a customer is feeling determines the length and the nature of the relationship with the brand. Make use of this technology to understand how customers are feeling about your brand and communicate effectively at any stage of the customer lifecycle.

  • Seamless agent handover

It is important to understand the impact of timely escalation of issues to human agents when it comes to customer service chatbots. In the absence of sentiment analysis, chatbots would not be able to sense the tone of the aggrieved customer. But a digital assistant with emotional intelligence will help businesses to deal with displeased customers in an efficient manner. If the customer sounds frustrated or angry, the bot can easily hand off the conversation to a human agent.

Learn more: Human Hand-off in Service Desk Bots

  • Memorable customer experiences

The basic intent of sentiment analysis is to personalize and modify a chatbot’s responses to match the customer’s mood. This will enable businesses to build engaging conversations with customers at a very early stage and create a delightful customer experience.

  • Keep track of performance

The biggest benefit of using sentiment analysis is that it provides unique and powerful consumer insights. The conversations of an emotionally intelligent chatbot can act as a treasure trove of accurate data, which can be used to measure effectiveness of products/service, design future strategies, segment the customer base and devise strong brand positioning.

  • Upselling and new user on-boarding

As exemplified by CoverGirl’s influencer bot, chatbots can assist companies in product discovery, recommendation and upselling their products & services to existing customers. It can also improve new customer acquisition metrics by retaining the interest of a new visitor by analyzing his/her sentiments.

As stated above, emotions influence decision-making. Sentiment analysis help chatbots to adapt to the users’ mood and respond accurately, effectively and in the right way. By deploying and investing in this technology, companies can not only improve customer experience but also allow human agents to focus on productive issues.

If you’d like to learn more about the role of sentiment analysis in chatbots, please feel free to get in touch with one of our AI chatbot consultants for a personalized consultation.

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