Áine McInerney - Synthetix

Conversational Chatbots: The Fundamentals For CX

Posted on 23 November 2020 | by Áine McInerney | Leave a Comment

Chatbots: Taking CX By Storm

Just decades ago, chatbots were considered futuristic or gadget-like, they were innovations with a huge untapped potential for CX. The chatbots we are familiar with today, however, are functional customer service tools that have taken CX by storm, particularly in recent years.

Today, approximately 1.4 billion people use chatbots worldwide – accounting for a significant chunk of the overall population that has digital access.

For many businesses, chatbot are now deemed essential – if they aren’t already part of the existing technology stack, they are quickly making their way onto CX roadmaps across industries. According to one study, 77% of executives have already implemented and 60% plan to implement chatbots for after-sales and customer service.

For customers, chatbots provide familiarity, convenience and instant access to relevant information on your company, products or services. This not only enhances CX but drives demand as the global chatbot market is expected to grow from $2.6 billion in 2019 to $9.4 billion by 2024 at a CAGR of 29.7%. For companies who wish to remain competitive but are yet to implement chatbots into their current offering, they are worth considering.

Simple Vs Conversational Chatbots

There are major differences between simple and conversational chatbots that can affect your customers considerably. Whilst simple chatbots often seem the more cost-effective option, when it comes to fulfilling your long-term CX strategy, this is where they fall short.

Types of Chatbot

There are 3 common chatbot types used in customer service, these include:

Menu-based chatbots
Keyword recognition chatbots
Conversational chatbots

Menu-based
chatbots

Keyword recognition
chatbots

Conversational
chatbots

Using menu buttons to help customers navigate to the answer required, this chatbot type has basic functionality. Menu-based chatbots are built on rule-based automation as opposed to AI, which means that they can only respond to queries that match their pre-loaded responses exactly. The limitation here is this chatbot will not recognise even the smallest query variation, this results in a dead-end response without the capability to further attempt to understand what a customer is asking.

Whilst this simple chatbot type might be adequate for very small or start-up businesses with extremely basic needs, for example serving a fixed set of FAQs, it is not sustainable for larger companies with more sophisticated CX goals.

This type of chatbot utilises basic AI to break down the query at hand, analysing each keyword to deliver the most relevant result. By focusing on different word classes, keyword recognition chatbots can determine the most suitable response. For instance, by isolating keywords “renew” and “subscription” or “setup” and “account”, the chatbot can assume the customer’s requirement and send a response based on this.

Although keyword-recognition chatbots harness AI to some extent, they are not effective at recognising and conversing with multiple query variations.

When it comes to delivering CX, conversational chatbots are by far the most effective type of chatbot. These advanced tools utilise AI, harnessing Natural Language Processing (NLP) to understand the context and intent of the question that is asked. This means that multiple variations of the same query can be asked and an identical answer is delivered seamlessly. Even if a question is not immediately obvious, conversational chatbots use decision tree technology to ask a series of questions until a resolution is found.

Conversational chatbots will never serve the response: “I’m sorry I don’t understand the question. Please try again.”

Unlike its basic alternatives, this chatbot type can be configured to naturally converse with customers, adding character to the experience whilst conveying brand personality. Through machine learning principles the CX is further enhanced as customer journeys are personalised; conversational chatbots can learn, store and use customer information for future sessions. By remembering certain details and preferences CX is of optimal efficacy.

Basic, rule-based chatbot

AI-powered chatbot

An image to demonstrate the differences between basic and advanced AI chatbot software.

Why Conversational Chatbots?

A report by Gartner reveals that 91% of organisations plan to deploy AI by 2022. Another report suggests that by 2025, 80% of large enterprises will need to have a “conversational-technology-focused-centre” implemented.

AI and the tools in which it powers are rightly viewed as game-changing technologies.

While AI has been around since the 1950s when Turing developed the Turing Test, followed by the debut ‘chatterbot’, ELIZA, that was developed in the 1960s, why is it that the conversational chatbots of today are experiencing such rapid adoption?

The answer is completely customer-centric; conversational chatbot adoption is customer-driven. As more and more businesses compete for customers, more and more new and innovative technologies are used to drive a high level of service. As they become accustomed to this, customers expect more from businesses in general. They want less effort and a better experience. They want the ease and convenience of using an online contact channel and the depth and personality associated with agent-assisted channels.

Chatbots do not only provide a familiar instant messaging interface for customers, contributing to an enjoyable experience, but they assist in guiding customers through their journey, from start to finish. When configured correctly, chatbots are your customer’s first port of call when looking for advice, they can be guided to their destination in a number of ways:

Most commonly, conversational chatbots solve customers’ routine questions instantly using AI-powered automation
For instances when customers don’t yet know the resolution they require, but know there is a problem, conversational chatbot utilise decision tree technology to take care of the problem-solving process until the correct resolution is found
Chatbots detect when a query is non-routine and therefore escalates the customer to an agent-assisted channel such as live chat where the adequate help can be provided – all of which takes place in the same window

Conversational chatbots are not only a hit with customers but with customer service and contact centre teams alike. Their capability to automatically handle significant contact volumes allows agents to focus on the queries that are complicated by nature, boosting CSAT and agent satisfaction. As a Result, Average Handling Times (AHT) are reduced by 25% and First Contact Resolution (FCR) is increased by 80% (Synthetix research).

Read: 8 Reasons Why You Need A Chatbot for Your Website

NLP, NLU, NLG & Machine Learning

How do these products of AI impact conversational chatbots and CX?

Natural Language Processing (NLP) is a branch of AI that deals with linguistics, its main purpose is to help machines understand the human language. NLP comprises Natural Language Understanding (NLU) and Natural Language Generation (NLG) to naturally interact with customers, simulating a real conversation.

Natural Language Understanding (NLU) uses algorithms to isolate and analyse the contents of a customer query. By identifying word classes and detecting sentiment, topics, entities and intent, NLU is essentially capable of comprehending context and what a customer is asking.

Natural Language Generation (NLG) is the process of taking the structured data that has been produced as a result of NLU and transforming it into consumable, natural language. Algorithms that understand the construct of a naturally phrased sentence build responses based on the understanding and processing of the interaction.

Machine Learning, a subset of AI surrounds the idea that computers can automatically learn and improve based on experience opposed to human intervention. Conversational chatbots adopt Machine Learning principles to personalise and enhance CX. By identifying trends in customer information, storing it and them remembering it for future interactions, chatbots create a positive and efficient experience for customers.

An image showing the relationship of NLP, NLU, NLP and ML

Implementing Conversational Chatbots

How do these products of AI impact conversational chatbots and CX?

At first glance, the implementation of conversational chatbots might seem daunting, but with the correct tools, processes and support, it’s straightforward.

Following the vendor selection process and agreed SRS, your first step depends on whether you have an existing knowledge base or not. You will either:

A. Integrate seamlessly with the chatbot so that knowledge can be shared back and forth between the knowledge database and chatbot interface

B. Collect all existing and extract any new company knowledge in order to populate your centralised knowledge base – you can find out more about the knowledge collection process here

Conversation Chatbots - Image of chatbot being sourced by knowledge

Next, configure any secondary search layers that are responsible for understanding grammar and synonyms. For example, Synthetix’s system, “Jabberwocky” unravels customer query sentence structure to understand the meaning of any synonyms or quirks that your knowledge base is not familiar with. This ensures a conversational response is always delivered and increases accuracy. You can also configure this system to match your brand’s tone of voice so that personality is effectively conveyed during conversations.

Following successful implementation, it is good practice to closely monitor analytics for usage and trigger management data that can determine how effectively the conversational chatbot is working. Settings can be adapted and crucial decisions can be made based on such analytics for future CX improvements.

If you enjoyed this article and would like to know more about chatbots, check out our guide here. If you’d like any advice on conversational chatbots or help with implementation, please

Get in Touch

Contact Centre Chatbots: Why Are They Critical to CSAT?

Posted on 5 November 2020 | by Áine McInerney | Leave a Comment

Why Chatbots?

Whilst they have been around since the 1960s, when the first chatbot, ELIZA was born, it wasn’t until recent years that the adoption of chatbots within business exploded. With the utilisation of AI and other intelligent functions, chatbots are no longer considered ‘futuristic’, rather a key component of the customer service ecosystem.

The global chatbot market is expected to exceed more than $10 billion by 2026 and will grow at a CAGR of more than 23% in the given forecast period.

It is also predicted that by 2022, chatbots will have saved businesses $8 billion per year, which is one of the key drivers for adoption and a fundamental reason why contact centre chatbots are fast becoming essential business tools.

So, how do they work?

Chatbots are a form of self-service that offer customer support through a familiar direct messaging interface. Built using AI and utilising Natural Language Processing, chatbots can facilitate a two-way conversation whereby the customer enters their query and the chatbot asks qualifying questions so that the most relevant answer can be delivered.

NLP utilises Natural Language Understanding (NLU) to dissect the query into keywords, search intent, grammar and popularity. Essentially understanding query context, an adequate and relevant answer can be generated through Natural Language Generation (NLG) using a conversational manner that matches your brand personality.

These mechanics help chatbots to understand multiple variations of the same question, meaning that they can successfully answer a query regardless of the language, grammar or idiosyncrasies that are entered. Chatbots that do not utilise NLP rely on customer queries matching their articles exactly in order to trigger a resolution, otherwise unhelpful responses such as, “I’m sorry, I don’t understand the question.” are delivered.

Basic, rule-based chatbot

AI-powered chatbot

Adopted by a multitude of businesses across many industries, chatbots can:

Reduce Average Handling Times (AHT)
Increase First Contact Resolution (FCR)
Cut operational costs
Boost CSAT
Enhance CX
Promote agent efficiency
Improve employee morale

Further, the role of the contact centre chatbot within the wider customer service ecosystem is an important one. Acting as an online concierge, it handles routine questions and tasks, whilst providing escalation to agent-assisted channels like live chat when human intervention is required.

If you’d like to know more on the fundamentals of chatbots, click here.

How Do Chatbots Benefit the Contact Centre?

No longer a perceived threat to contact centres, chatbots are now considered a vital tool for agents. Working in amalgamation with chatbots helps to combat the growing volume of routine contact queries associated with the explosion of digital transformation.

Contact centre chatbots have become increasingly popular in recent years, particularly in 2020 as a result of the pandemic. With a surge in support calls and emails and some organisations experiencing up to a 133% spike in contact , chatbots provide support to agents working remotely and in the contact centre.

Chatbots Help Your Contact Centre Boost CSAT

Through continuous AI improvements and NLP development, chatbots have evolved to better understand the context and intent of the customer queries they are asked. With advanced AI, chatbots can not only handle routine queries but many routine tasks, such as:

Taking a meter reading
Submitting a claim
Resetting a password
Booking and confirming a reservation
Checking a delivery’s location

Your chatbot can even be configured to match a certain tone of voice, providing the personal experience that so many customers require.

Whilst agents can only handle 1 call or email at a time, chatbots can automatically deal with large scale routine queries and tasks simultaneously. This, therefore, significantly frees up any channel congestion caused by large volumes of routine questions – the result of which means more customer queries are effectively dealt with and consequently, CSAT scores improve.

It also frees up agent resources, creating time and space for agents who can now provide their full attention and expertise to customers who require urgent attention due to their complex issues. If a customer is in a vulnerable position and needs urgent assistance, the last thing they need is to be waiting in a long queue to speak to an agent. This only reflects negatively on CX and CSAT but can be avoided by utilising contact centre chatbots.

Many customers prefer to self-serve if they can – around 73% in fact. By including a chatbot in your customer service offering you cater to your customers’ needs, improving CSAT.

Further, chatbots provide customers with 24/7/365 support, they can resolve queries and instruct customers outside of contact centre operating hours or during public holidays. AI chatbots can even assist customers through emergencies in real-time, successfully delivering relevant emergency contact details and instructions required.

Find out how a knowledge base can benefit the contact centre, here.

Chatbots Contribute to Agent Satisfaction

Contact centre chatbots, contrary to popular belief, don’t hinder agents, rather they have the capabilities to enhance their quality of work and job satisfaction.

When the vast majority of queries that come through the contact centre are the same mundane routine questions and monotonous tasks, this can take a toll on your agents – causing drive and morale to decline.

However, these routine questions can be dealt with at scale through AI, using chatbots, creating a greater bandwidth for your agents to which they can deal with more complicated, non-routine issues. When agents are able to dedicate their attention to helping customers with serious or complicated enquires it adds variety and purpose to their roles, which in turn contributes to job enrichment and motivation.

It’s no revelation that when employees are happy, this is reflected positively through their quality of work. So, when chatbots are introduced into the ecosystem, agents not only develop skills quicker but they are supported and happier at work, which has an impact on the service that customers receive, enhancing CSAT.

Chatbots Make Your Contact Centre More Efficient

Many company’s customer service and contact centre operations lack efficiency, particularly when it comes to the mechanics of the contact channels. Too often expensive agent-assisted channels are unnecessarily exhausted, or low-cost AI-powered channels are not utilised or difficult to find.

This is where chatbot solutions can assist the contact centre’s efficiency. Ultimately, when configured correctly, chatbots can sort queries into the correct channels, avoiding unnecessary costs. For example, if a chatbot is configured to be a customer’s first port of call for customer support it can either:

A. Deal with the customer’s routine query successfully

B. Or, detect that the customer’s query is non-routine and requires human assistance, automatically escalating the customer to an agent-assisted channel such as live chat

Through automation, chatbots can deal with routine questions significantly quicker than humans. There are many time variables when it comes to manually opening, replying, researching and resolving just one customer query compared to AI handling everything. This cuts your operational costs considerably, accounting for up to 30% support cost reductions.

Read: The 8 Biggest Chatbot Mistakes That Are Costing You Money

A chatbot not only escalates a query when it is non-routine, but it can also be configured to escalate to an agent-assisted channel based on the keywords the customer enters. Trigger management settings enable this escalation to take place based on certain keywords, for example, those that indicate urgency, such as “renew” or “cancellation”. By putting these customers in touch with a human that can efficiently deal with the matter, customer churn is reduced and revenue is increased.

Pair this with chatbots’ intelligent smart forms integration which collects targeted information from the customer throughout their journey and significant time is saved, slashing overall AHT.

Further, contact centres can become more efficient by utilising the data that chatbot technology produces. With detailed analytics revealing what customers are asking and article effectiveness, you can be in the know about current customer trends or issues. As a result, you can proactively better equip agents, building such intelligence into agent scripting and other learning tools.

If you enjoyed this article and would like to know more about chatbots, you can read our guide, here. or, If you would like any advice or assistance with contact centre chatbots

Get in Touch

Live Chat for Your Website: How Does It Work?

Posted on 30 October 2020 | by Áine McInerney | Leave a Comment

Why Consider Live Chat for Your Website?

Live chat is an important part of the customer service toolkit and is utilised by a multitude of businesses. With 67% of companies in the B2C sector and 66% in the B2B sector using live chat for customer support, the adoption of this key contact channel is expected to further skyrocket, as the market’s value is projected to reach $997 million by 2023, growing at a 7.5 CADGR.

Live chat facilitates two-way communications between your customers and agents, acting as a digital portal to which customers receive support, information and answers to their queries. Unlike self-service channels like chatbots or self-service FAQs that rely on AI, live chat utilises human intelligence to answer queries, making it the perfect solution for dealing with complicated non-routine questions.

Live chat is particularly popular within customer service because it’s versatile and low-cost to run in comparison to other agent-assisted channels such as telephony that doesn’t enable multiple queries to be solved simultaneously. Live chat for your website also offers the following benefits:

CSAT improvements
Enhanced CX
Agent satisfaction
Increased lead generation
Reduction in Average Handling Times (AHT)
Improved first Contact Resolution (FCR)

For more on how live chat can benefit your customer service operations, click here

How Does Live Chat Work?

Live Chat’s Key Role in Customer Service

Live chat earns its place as a key player in the online customer service offering by supporting other contact channels to ensure FCR whilst presenting itself at opportune moments to boost CSAT and revenue generation.

When the AI that powers your self-service channels such as an FAQ widget or chatbot cannot handle a non-routine question, the customer is automatically escalated to live chat where an agent can deal with the complicated issue. This is facilitated through seamless integration, all taking place in the same window for optimal CX and FCR.

Live chat on your website can also be presented to your visitors in specific forms and at specific times. Trigger management settings are configured to trigger live chat when certain conditions are met, these might be based on pages visited or duration spent on your website.

Selecting Your Live Chat Vendor

When it comes to live chat for your website, the selection process might seem monotonous, but choosing an effective vendor is arguably the most critical part of live chat implementation and should therefore be done with care. It’s good practice to conduct thorough research on multiple vendors to ensure you are delivered exactly what your company needs.

Whilst something might appear to be ‘good value’ at first glance, consider that in the long run, such solutions won’t serve companies and their requirements to scale.

When choosing a live chat vendor, consider these points:

Does the vendor meet your requirements and have they presented you with a business case? This helps you understand ROI, the payback period and whether they offer a flexible commercial model aligning to your needs.
Does the live chat software integrate seamlessly with other key customer service and 3rd party tools? Knowledge sharing and access to AI-powered functionality improves operational efficiency – ensure the vendor can facilitate this effortlessly.
Does it offer features that encourage agent productivity? Features such as live keypress feed, AI-predictive suggestions and chat routing promote agent efficiency and satisfaction.
Does it offer features that contribute to CX? Trigger management, integration with other online tools and escalation capabilities help visitors get to where they need to be, enhancing CX.
Does the live chat software include comprehensive analytics? Intelligence on agent activity, showing handling times, user feedback, login times, logoff times, active chat times and breaks is key to optimisation. Gamified user stats can also encourage healthy competition between agents.

Live Chat for Your Website: The Implementation Process

Once a vendor has been selected and the SRS has been agreed, live chat deployment – that’s being fully integrated, branded and up and running – should take a matter of days or weeks, depending on your business requirements and timeline.

The live chat implementation process will differ from company to company depending on its individual needs, but generally follows this structure:

Project kick-off meeting takes place: This is where key project expectations are discussed, including timelines, outcomes and functionality. It’s an opportunity for your vendor to thoroughly understand your requirements when it comes to execution.
Design guidelines are discussed: You want your customer-facing live chat channel to represent your brand, this is where brand and design guidelines are shared so that they can be built into your software.
First look designs are shared: Once they are built, the first look designs are shared with you and your team to ensure they have been properly executed. This is an opportunity to suggest any amendments if necessary.
Draft integration code is created and sandbox environment access is granted: Now that you’re happy with the design elements, your vendor will give you access to the sandbox environment where you can test the tool’s functionality. Again, if there are any apparent issues, this is where they can be discussed.
Design is signed off: Once you and your team are satisfied, the design is signed off.
Agent training: The account manager that has supported you throughout the implementation process will conduct the agent training. This is to ensure that your team get the most out of live chat and know how to use each feature adequately.
Testing: Next, thorough testing is carried out to eliminate any issues that could affect the tool’s effectiveness.
Final low-code integration is provided: The last step in the process is a simple one. It’s what gets live chat up and running on your website and involves one line of code. This is given to your developers by the vendor to install and you’re ready to go.

It’s good practice to discuss the implementation process with vendors in advance to manage expectations and make sure that these steps are included.

Measuring Live Chat Effectiveness

You can’t manage what you can’t measure. To continue reaping the benefits provided by live chat and ensure its constant optimisation, its effectiveness must continuously be measured. This is carried out by the frequent analysis and close monitoring of both performance and knowledge effectiveness metrics.

Performance Metrics

This group of metrics helps you to determine agent productivity, by providing you with data on each agent and their chat metrics, issues can easily be identified and resolved. These metrics include:

Operator’s Summary: This group of metrics gives a granular insight into agent activity, including, chat capacity, handling times, durations, user feedback, login times and more.
User Up-time: This demonstrates how your live chat teams’ time is spent throughout the day, showing data on login times, logoff times, active chat times and breaks.
Gamified Leaderboards: Visible to agents, these visuals encourage healthy competition by highlighting agents who complete the most chats or receive the most favourable customer feedback.

Knowledge Effectiveness Metrics

It’s important to study knowledge-related metrics in order to understand if the content and knowledge articles being delivered to your customers are serving them effectively. This set of metrics include:

Search Result: This collects data on every article, revealing how effective each is at answering customer queries. By pulling top-level effectiveness insights you can see how many queries were resolved and how many were optimisable.
Top Queries: This set of metrics including, top queries, how many results were generated and whether it could be resolved, help to gain insight into your customers’ behaviour and current needs, it can also help to reveal where any content gaps exist.
Triggers: Understand how well your configured triggers are performing with data that reveals where tools are being triggered on your website and which is most optimal.

If you enjoyed this article and would like to know more about live chat for your website, read our guide here. Or, if you’d like any advice on how to set up live chat, please

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A Screen showing an agent using Live Chat

Live Chat Knowledge Base Integration: The Key Benefits

Posted on 22 October 2020 | by Áine McInerney | Leave a Comment

Live Chat Knowledge Base Integration:
How Does It Work?

“The whole is greater than the sum of its part.”
– Aristotle

This phrase rings true when it comes to live chat knowledge base integrations; whilst each tool provides value to customer service individually, when combined, that value becomes significantly greater.

Before exploring the importance of this integration, let’s first unpack the impact that live chat and knowledge bases have individually on your wider customer service ecosystem.

Live Chat’s Role in Customer Service

In your customer service offering, live chat provides your customers with a platform whereby they can communicate with agents who will communicate back. Unlike self-service contact channels such as chatbots or self-service pages that utilise AI to solve with queries, live chat is operated and solves customer queries using human intelligence.

Live chat solutions are particularly popular due to their low-cost and versatility. Compared with other agent-assisted channels such as telephony, live chat, which allows agents to deal with multiple queries simultaneously, is significantly cheaper to run.

From a customer perspective, live chat combines the depth that is provided by agent-assisted channels with the accessibility and convenience of an online channel. According to one study , 79% of customers preferred to use live chat because it offers instant responses.

For more on the basics of live chat software, check out this article.

A Knowledge Base’s Role in Customer Service

A knowledge base’s role in your wider offering is an important one, it is the core knowledge repository and where all information is stored, collected, shared and updated. From company guidebooks to pension policies and product spec sheets to agent scripting, a knowledge base stores everything relating to your company, products and services.

The purpose of a centralised knowledge base is to provide quick, convenient access to information, to the right people at the right time. A knowledge base is versatile and can be utilised both internally and externally in the following ways:

By employees looking for company information
By agents searching for knowledge articles that will answer customer queries
By customers and prospects who require information on the company, products or services

You can set up various knowledge base views to include or restrict certain articles being accessed depending on who the audience is.

This nucleus of customer service feeds all your key business and customer service tools to ensure that any information that is distributed, internally or externally is always consistent and accurate. Without knowledge bases in place, companies must deal with disorganised databases and scattered information that leads to unreliable knowledge sharing.

Why Integrate and How?

Companies with efficient and functional customer service recognise the importance and make use of the integration between live chat and knowledge base software. By connecting the two a synergy is created, greater control over knowledge is gained and the overall cohesion makes for more efficient, lower-cost operations.

The live chat knowledge base integration is popular due to its abilities to:

Improve AHT
Enhance CX
Promote agent productivity
Produce valuable analytics
Boost ESAT and CSAT
Reduce costs

Implementing the integration is straightforward. Providing that your software utilises low-code development, the integration can be set up and ready to use following the simple installation of code.

Live Chat Knowledge Base Integration: What Are the Benefits?

Reduce Distraction and Enhance AHT

The integration between live chat and knowledge base software encourages agent efficiency. The agent interface offers an integrated knowledge feature, otherwise known as ‘mini knowledge’, it gives agents quick access to knowledge articles in the same window as the chat console. From there, they can simply copy and paste an article straight into the chat.

The advantage here is the reduction of distraction and noise, agents no longer must open new windows to search for answers in often multiple, disorganised places. Consider the sheer volume of routine questions that agents receive on a daily basis – this process becomes cumbersome when repeatedly carried out, eating up significant, valuable agent time.

Not only does the integration between the tools reduce AHT considerably, but by providing your customers with faster answers, CSAT is impacted.

Consistency Makes for Better CX

The circulation of inconsistent, inaccurate information not only damages brand credibility but could lead to anything from a surge in customer complaints to legal action being taken against the company.

Not only does this integration make the knowledge base available to live chat agents when dealing with customers, but it also powers all self-service tools that live on your website – whether its a self-service FAQ page, chatbot or widget. This means that the same information accessed by customers via your self-service channels is the same as the information that agents send your customers via live chat.

Providing such consistency is not only important for brand but it gives customers the right answers the first time, removing the need for customers to search around for adequate resolutions after they’re served inconsistent messages.

Optimal Agent Productivity Through Integration Features

By integrating live chat with your knowledge base, a series of features that contribute to productivity are unlocked. The live keypress feature that is made available in the agent interface allows agents to see what a customer is typing in real-time before they hit “send”. This lets agents resolve issues often before the query has been sent, saving considerable time.

AI predictive suggestions features are also made available through the live chat knowledge base integration. As customers type their query, in real-time, AI predictive suggestions will recommend a series of relevant articles in the ‘mini knowledge’ section. This is hugely useful for agents who can simply copy and paste an article and send to the customer without having to search for anything or leave the current window.

Both features help to save agents significant time so they can focus on other tasks, therefore promoting productivity.

Performance and Article Metrics Are Activated

Connecting two powerful tools generates powerful results – and these should be measured. The integration provides you with detailed analytics on knowledge article insights, for example:

Search results: analytics that demonstrate the effectiveness of articles based on resolved queries, subsequently revealing the effectiveness of your knowledge base
Top queries: insights into not only customer behaviour and areas for improvement but also how well your team is resolving such queries and whether there is a gap that needs filling
Triggers: showing you where live chat and other tools have been triggered on your website and which trigger is most optimal

It can also help you measure agent performance with metrics such as:

Operator’s summary: In-depth data showing agent handling times, user feedback, login times and many more metrics
User up-time: a holistic view of how your teams’ time of spent, including data on login and logoff times, active chat times and breaks
Plus, gamified leaderboards to encourage healthy competition and agent progress awareness

With regular monitoring and analysis, such analytics can be the answer to continual content and operational optimisation.

Boost ESAT To Boost CSAT

The integration between live chat and knowledge base makes agents’ jobs much easier, providing them with features that simplify tasks, make knowledge articles more accessible and ultimately give them a head start on each chat they are assigned.

This relieves the pressure on agents who would otherwise be scrambling to find answers in messy, confusing databases and documents, all whilst hoping that the information they serve is up-to-date and accurate.

Instead, agents, equipped with the combined power of live chat and knowledge base features, learn how to quickly deal with routine questions and can therefore deal with larger volumes of complicated issues. This helps not only develop customer service skills but it provides agents with job satisfaction by resolving customers’ serious issues.

The integration allows routine tasks to be completed efficiently so that agents can focus on more complex issues that prove rewarding. This contributes to employee satisfaction (ESAT), which has a huge impact on the way queries are dealt with, thus CSAT.

Cost-Efficiency

As an agent-assisted contact channel, live chat is an excellent choice for your customer service offering in terms of cost-efficiency. It proves far cheaper to run in comparison with other agent-assisted channels such as telephony which unlike live chat cannot deal with customers concurrently.

But when live chat integrates with knowledge base technology there further, significant savings to be made. Features included in the integration such as integrated knowledge (‘mini knowledge base’), live keypress and AI predictive suggestions create small, incremental savings in agent time. When you consider how many agents are in a contact centre and how many customers they deal with in a day alone, this adds up to significant time savings, which of course brings your operational costs down.

Training costs are also reduced through the integration, the knowledge base itself is a training tool for new starters and gets them up to speed far quicker than costly training programmes.

If you enjoyed this article and would like to read more about live chat integrations, you can do so here. If you are interested in seeing the benefits of a live chat knowledge base integration, please

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18 Tips to Improve Live Chat for Customer Service

Posted on 21 October 2020 | by Áine McInerney | Leave a Comment

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These 18 tips offer recommendations and best practices to help improve live chat for customer service.

Ensure Live Chat Is Aligned with Your Business Goals
Configure Trigger Management for Maximum Lead Generation
Put Your Brand’s Stamp on It
Use Smart Web Forms for Pre-Qualification
Manage Customer Expectations When It Comes to Live Chat
Ensure Live Chat Supports File Transfer
Offer Live Chat Feedback Surveys
Integrate Live Chat with Centralised Knowledge for Consistency
Integrate Live Chat with Your CRM And Other 3rd Party Apps
Compliment Live Chat With AI-Powered Chatbots
Consider Live Chat’s Role in The Holistic Customer Journey
Make Use of Integrations That Handle Personal Data Securely
Use A Live Keypress Feed for Reduced AHT
Use AI Predictive Suggestions and Integrated Knowledge for Accuracy
Ensure Chat Transfer Is Seamless to Enhanced FCR
Study Live Chat Metrics for Continual Optimisation
Focus on ESAT If You Want to Improve CSAT
Utilise Agent Scripting

1. Ensure Live Chat Is Aligned with Your Business Goals

When implementing live chat into your wider offering it’s important to consider your wider business goals, which might surround:

Operational efficiency
Cost reduction
Customer Experience
Customer Satisfaction

Firstly, ensure all employees involved are clear on why live chat is being deployed and to which business goal it will help achieve. Having everyone on the same page, working towards a clear goal creates transparency and drive. This also ensures the utilisation of live chat for customer service teams.

It’s vital that live chat aligns to such business goals and their subsequent objectives as well as integrating well into your customer service ecosystem. This makes operations smoother, knowledge sharing easier, visibility greater which creates enhanced customer service.

2. Configure Trigger Management for Maximum Lead Generation

When configured correctly, live chat contributes to lead and revenue generation. Trigger management options let you determine when your live chat is displayed, made available or even pops up.

Live chat is configured to trigger when certain conditions are met, this might include when a visitor has spent a certain amount of time on the site, indicating they require help, or when a visitor lands on a particular product page signalling their interest. By simply letting them know someone is here to help, the chances of lead and revenue generation increases.

Similarly, a visitor might reach the website cart page, spending a few minutes here because they need a question answering – a trigger set up here can resolve this and lead to a sale that would otherwise have been lost without the presence of live chat.

3. Put Your Brand’s Stamp on It

Your live chat page, widget or pop-up is an opportunity to showcase your brand. Personify your brand attributes and personality through the many customisable features that live chat offers. This can be visually represented through colour schemes and logos to creates brand familiarity or to show your brand’s tone of voice, canned responses can be configured to include quirks that match your brand guidelines.

Further, it is good practice to include tone of voice and brand personality training in the onboarding process, agent scripts should also utilise this.

4. Use Smart Web Forms for Pre-Qualification

When it comes to live chat for customer service optimisation, agent time is precious. To get the most out of agent time, pre-qualify customers using smart web forms. Capturing all relevant data before the chat takes place can save significant agent time, especially when you consider just how many chats one agent might deal with over a day.

Smart web forms can be configured to capture the following data pre-chat:

Full name
Email address
Enquiry details
Custom fields if required

Companies might include just some or all of these fields depending on their needs.

5. Manage Customer Expectations When It Comes to Live Chat

There is nothing more frustrating for your customers than expecting to be put in touch with an agent via your live chat and instead waits in a ‘queue’ for hours before giving up. Your customers did not receive the service they expected and as a result, become angry and frustrated, leading to poor CSAT.

What is important in such instances, for example when agents are not available due operating hours, that expectations are managed. Ensure settings are configured to remove live chat as an available option as well as making operating hours clear.

You can also consult the analytics section of your live chat interface , where data will help you determine how many agents you require to fulfil chat volumes.

Check out our 2021 Live Chat Buyer’s Guide, here.

6. Ensure Live Chat Supports File Transfer

The queries that your agents handle through live chat cannot always be solved using text alone, often the more complex issues require file transfer capabilities. This might include:

Images
Videos
Screenshots
Documents such as Word or PDF files

7. Offer Live Chat Feedback Surveys

Offer your customers a feedback survey once their chat has ended. Asking questions about the chat itself, the agent and quality of resolution can reveal a lot about operations.

Collect and study such data to find out what you’re excelling at and what might need improving. This practice should be constantly carried out to encourage optimal CSAT and CX.

8. Integrate Live Chat with Centralised Knowledge for Consistency

Integrating your live chat solution with your centralised knowledge is key to providing accurate and consistent information both to customers but also internally.

By utilising knowledge base software , all relevant knowledge can be stored in one place to avoid errors and inaccuracies associated with multiple knowledge sources. By integrating live chat with a knowledge base, you can be assured that all information served to customers is regulated and fed from the same source as other customer service tools.

In addition, such integrations enable agents to look up results quickly and easily via the same UI as their live chat console, saving time and making their jobs easier.

9. Integrate Live Chat with Your CRM And Other 3rd Party Apps

Having your live chat, that collects valuable data on customers and your CRM platform, that stores this data, communicate with each other is fundamental. Not only does the integration enable automations that populate fields in your CRM based on the chat, but it creates a holistic view of the customer for your account managers – with data from entry to exit.

Choose live chat software that is built using open RESTful APIs to ensure quick and seamless integrations and two-way data sharing between live chat and your CRM.

10. Compliment Live Chat With AI-Powered Chatbots

Agent-assisted channels such as live chat often receive unnecessarily large volumes of routine questions. Chatbots can provide huge support to live chat by handling these routine questions through AI and subsequently freeing up the channel. The effect of which means that live chat agents can deal with the type of query they are trained to deal with – individual and complex.

By incorporating AI chatbots into your offering, automatic escalation to live chat channels take place. In instances where AI cannot find a solution to a non-routine query, the customer is seamlessly transferred to live chat, via the same window.

Further, such chatbots can be configured to automatically escalate to live chat when certain keywords are entered, for instance, “Renew” or “Emergency”. These keywords indicate urgency and therefore require human assistance.

11. Consider Live Chat’s Role in The Holistic Customer Journey

It’s important that the role of live chat as part of the wider customer journey has been considered. There is a multitude of potential customer journeys and its good practice to map the most common out.

Whilst live chat for customer service is necessary, not everyone that uses the channel needs to, a lot of queries and tasks can be dealt with using self-service tools and chatbots. Emphasise these self-service tools, so that they are your customers first port of call, not are they significantly cheaper to run, but according to one study , 73% of people said they preferred to use a website’s self-service instead of live chat and other channels.

For enhanced CX and CSAT through quickfire answers to routine questions, put self-service at the forefront of your offering, but ensure that effective escalation points are set up for when agent assistance is required. Additionally, do not make live chat impossible to find – customers recognise when they require human-assisted support.

12. Make Use of Integrations That Handle Personal Data Securely

Integrate your live chat with Identification & Verification (ID&V) software that securely handles customer data to confirm identities. ID&V takes care of this whole process for you so that confidential account information does not need to be dealt with by agents. The secure questioning process simply tells your agent whether ID&V was successful and they can commence with the task at hand.

Your live chat can also facilitate secure payments through PCI partners, taking place in the same window for your customer’s convenience and your brand’s credibility.

13. Use A Live Keypress Feed for Reduced AHT

Live keypress feed is a feature utilised by agents for efficiency. It allows them to see what the customer is typing before they have pressed send. This lets the agent solve the customer query often before it has been sent, saving significant time in the long run.

Live chat that includes live keypress feed helps to slash AHT, which benefits both agent productivity and CSAT.

14. Use AI Predictive Suggestions and Integrated Knowledge for Accuracy

Another helpful feature that exists within the agent interface includes AI predictive suggestions. When live chat is integrated with centralised knowledge, your agents can view a mini knowledge base in the same window as the chat itself, which makes looking up a topic or article simple.

AI predictive suggestions work with the mini knowledge base by suggesting relevant knowledge articles as the customer types their query.

These features help to ensure that the knowledge that is shared with customers is accurate and in line with what the centralised knowledge base says.

15. Ensure Chat Transfer Is Seamless to Enhanced FCR

Your agents all specialise in different areas, whether its complaints, renewals, sales or insurance. Therefore, it’s best practice that the chats surrounding each area are transferred to the appropriate agents. This is not only important in ensuring that customers receive relevant expert help, but by offering smooth transitions, First Contact Resolution (FCR) is improved.

Before joining a chat, customers generally pre-select the area that they require help with and this puts them in touch with an agent who has the relevant skillset. However, in some instances, customers might require help in more than one area or an agent believes a different skillset would be more suitable. This is when a seamless transfer from agent to agent is critical – this should all take place timely and within the same window so that the customer is not inconvenienced.

16. Study Live Chat Metrics for Continual Optimisation

It’s vital that your live chat software includes comprehensive metrics that can be analysed to influence key decision-making and continual optimisation. Both agent performance and knowledge article metrics are particularly useful in improving operations over time.

Live chat software collects data and compiles it into visuals and graphs that reveal where improvements must be made, areas that need flagging or interesting behaviours and insights. All of these can contribute to crucial decision-making and change that ultimately enhance operations and output.

17. Focus on ESAT If You Want to Improve CSAT

It’s no revelation that when your employees are happy at work, it’s reflected through their productivity, attitude and quality of work. Satisfying agents’ hygiene factors is a given, but what is effective in contributing to employee satisfaction (ESAT) is equipping them with tools that empower them.

Live chat that integrates with other business tools, offers a live keypress feed, AI-predictive suggestions, integrated knowledge and other features helps agents to:

Hit targets quicker
Become experts in multiple areas
Help more customers with a wide range of issues

All of which can lead to job enrichment and a sense of purpose at work, which in turn improves ESAT.

18. Utilise Agent Scripting

Agent scripting that is built and customised using decision tree technology can have positive impacts on AHT and FCR. Contrary to outdated, print-based scripts, decision trees allow supervisors to customise scripts by configuring a series of connected questions that guide your agents through complicated interactions with customers.

This gives your agents not only the independence to answer complex issues without supervisor intervention, but by doing so, costs are kept down and the customer journey remains smooth.

If you enjoyed this article you can read more about live chat in our 101 guide, or if you would like to find out more about a live chat solution that includes the features discussed in this article, then please

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What Is Live Chat Software?

Posted on 16 October 2020 | by Áine McInerney | Leave a Comment

An Introduction to Live Chat Software

Whilst self-service channels are effective in solving customers’ routine queries, AI cannot always replicate the sensitivity and empathetic decision-making that comes with human understanding. Which is why live chat software is the perfect solution for queries that are more complex by nature, customers get the best of both worlds: the human touch and depth of answers that come with an agent-assisted channel, blended with the convenience and flexibility of using an online tool.

Customers are always going to have complex questions, the type that does not fit into the routine category and thus cannot be solved by self-service tools. This is why providing a live chat option online is paramount to CSAT and channel efficiency.

Beyond simple customer service, live chat can also facilitate lead generation and customer engagement, serving prospects, leads, new and existing customers.

How does it work?

On the customer’s end, a live chat conversation is initiated and their query is entered. This chat is received via the agent interface, otherwise known as the chat console, where it is assigned to an available agent, perhaps by skill if appropriate.

When integrated with a wider knowledge base, the interface recognises keywords that the customer has entered, prompting AI-powered predictive suggestions in real-time and shown in a ‘mini knowledge’ in the same window that recommends articles for sending. Agents can send pre-configured canned responses to save time or transfer chats to those with more appropriate skillsets. Certain live chat software includes live key-press features that allows agents to see what a customer is typing before they hit ‘send’, giving them extra time to resolve issues. All these functions are designed to promote incremental efficiencies.

Companies understand that there will always be non-routine queries to deal with and that agent-assisted channels prove costly. The reason why live chat software is so widely utilised is because it is a fraction of the cost of telephony and email. These features that enable incremental efficiencies along with the capability to handle multiple chats simultaneously, brings operational costs down significantly.

Want to improve your live chat software? Check out these 18 tips.

Live Chat Software Use Cases

Today, live chat software is diverse and can be used across multiple departments and for a range of functions.

Check out our 2021 Live Chat Buyer’s Guide, here.

Customer Service

Live chat is perhaps most commonly known for facilitating customer service online. It provides customers with quick, easy and convenient access to company representatives who can help them.One study revealed that 79% of customers preferred live chat over other channels due to its immediacy – a key contributor when it comes to CSAT.

Whether it’s a simple but non-routine query or a serious and time-sensitive issue, live chat software assists your customers when they most need it, building strong, positive associations with your brand.

Lead Generation

Live chat does not only serve customers post-purchase, but it can also assist in increasing lead generation. Live chat software can be configured to trigger under certain conditions, for instance, if a customer visits a certain product page more than once or spends a particular amount of time on the cart page. Such conditions suggest a lead is hot or is about to convert – this is where live chat can intervene via a proactive trigger, offering additional support and consequently secure the lead or sale.

According to one report, live chat leads to a 48% increase in revenue per chat hour and a 40% increase in conversion rate.

Customer Engagement

Live chat software can help companies build better relationships with their customers, enhance brand credibility and increase conversions – all through customer engagement. CX can be enhanced by personalising the customer journey. Agents have access to returning visitor’s preferences and transcripts and can therefore utilise this data to make the experience smoother, more efficient and more enjoyable.

Just by being present and available through live chat software, companies can reap the rewards of customer engagement. Kayako reported that 79% of businesses said that implementing live chat resulted in increased customer loyalty, sales and revenue.

Find out more about live chat deployment, here.

Benefits of Live Chat Software

For Your Company

The implementation of live chat software can reduce your company’s operational costs significantly. Agent-assisted channels such as telephony and email are particularly high cost to run, this is because there are an accumulation of staffing and operational overheads involved, not to mention the fact that only one customer can be dealt with at a time, increasing handling times by upwards of 40% for some products. So, when companies deploy live chat software, that enables agents to handle multiple chats simultaneously, your customer service operations become more efficient. Pair this with features such as AI-powered predictive suggestions, integrated mini knowledge, live key-press feed and canned responses, that are designed to incrementally boost efficiency and huge operational savings are made.

The software can also have a positive effect on agents, which in turn can promote productivity and improve quality of work. When you deploy live chat software in contact centres and customer service teams, you are empowering agents by equipping them with tools that make their jobs easier. Not only do the features allow them to work through queries quicker, helping more customers, but access to integrated knowledge lets them become experts in many relevant areas.

Further, by including live chat in your online offering and using trigger management to prompt the tool when certain conditions are met, both lead and revenue generation can increase significantly.

For Customers

For your customers that require help with issues that are not routine and fit into the complex category, live chat is the ideal contact channel. Not only do they get to speak to a human who is experienced in the area at hand, but live chat can handle their queries quickly and conveniently – allowing them to carry on with everyday tasks at the same time. This is a huge improvement from having to wait in line to speak to an agent via the phone. Not only does live chat software reduce Average Handling Time (AHT) significantly, but it makes for happier customers and this is reflected in your CSAT scores.

Live chat software also contributes to a smooth and successful CX. The role in which it plays in the holistic customer journey is key in ensuring the customer gets to where they need to be. Live chat compliments other customer service tools that specialise in self-service, if a visitor engages with a chatbot for example and the software detects it cannot answer the non-routine query, a seamless escalation to live chat takes place, within the same window for great CX. The visitor does not feel inconvenienced and having interacted with the familiar instant messaging medium that live chat provides, CSAT is enhanced.

It’s clear why so many businesses rely on live chat as an indispensable tool in the customer service kit. Acting as an intelligent portal that connects customers to agents, live chat software promotes operational efficiency whilst bringing costs down. It is also heavily relied upon by customers – as the quickest way to contact your company, live chat enhances CX and contributes positively to CSAT.

If you enjoyed this article and would like to learn more about live chat software, check out our guide if you would like help regarding your organisational needs, please

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What Is FAQ Software?

Posted on 22 September 2020 | by Áine McInerney | Leave a Comment

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An Introduction to FAQ Software

FAQs, frequently asked questions are simply that – the routine queries that are asked multiple times a day, every day by your customers. They involve your company, products and services and include queries such as:

Having access to FAQs is vital to CX, today 67% of customers want to resolve their own queries through the power of self-service. This is why including a form of FAQ tool on your website is paramount. It enhances the customer journey by providing quick, convenient, 24/7 access to answers – which reflects positively in CSAT.

FAQ software facilitates this self-service. It lets your customers help themselves by providing a library of answers and search function that when engaged with, delivers the most relevant results.

Depending on your business size and requirements, a simple FAQ page might suffice for the most basic of self-service needs. However, for most companies, an excellent level of customer service and CX is essential and therefore such a solution would not be adequate. Instead, they opt for a more sophisticated AI-powered FAQ tool that can effectively provide customers with the answers they require through Natural Language Processing (NLP).

In addition to serving customers, FAQ software proves particularly advantageous to customer service contact centre teams. FAQ tools that utilise NLP enable the mass automation of routine queries and tasks that would otherwise be handled by agents. Not only does redirecting this type of query to an FAQ tool prove effective in reducing operational costs and staffing overheads, but it allows agents to dedicate more time to queries that are complex by nature. This contributes positively to CSAT.

FAQ software can do far more than simply answering a question, it helps customers get to where they need to be through escalation and from an internal perspective, acting as one centralised source of knowledge, empowers entire companies with the data it produces.

To learn more about how self-service software works, click here.

Types of FAQ Software

Basic FAQ Page Solutions

This type of FAQ solution is presented as a static FAQ page whereby users can type a question into a search bar and if there is an exact match, an answer that has been configured will show.

Whilst this might appear to be the best-for-value option, in the long run, it is likely to end up costing you more.

The content that is included on an FAQ page is based off opinion opposed to fact as a lack of data surrounding knowledge article popularity results in simple guesswork. What this means is that your FAQs aren’t FAQs, rather what someone believes them to be – which of course is problematic, creating a gap between you and your customers.

FAQ pages include a simple interface that is usually built with basic code, this means that making even a small edit involves many developer hours and before this, a long chain of command. The management of an FAQ page is therefore cumbersome, and often an inefficient use of many employees’ time.

Further, its basic setup restricts knowledge sharing and can increase the likelihood of errors occurring. Because an FAQ page is not the centralised source of knowledge, nor can it integrate with one, edits and changes cannot occur automatically. This results in many little updates that increase the chances of information inconsistencies and inaccuracies across the company.

Basic FAQ Tools

Basic FAQ tools have a similar structure to the FAQ page discussed – the only difference is that they can be presented in a variety of ways. Unlike the basic FAQ page solution, which is restricted to a static HTML page, basic FAQ tool solutions can take the form of a widget or pop-up. This is usually configured to show on certain pages and pop-up after a given amount of time.

Whilst this solution offers some flexibility in terms of presentation, its setup is basic and search functionality is limited. Its lack of AI and NLP utilisation removes any human-like understanding from the tool, so unless an exact keyword match is entered, results will not be triggered or therefore displayed to the customer. The effect of which takes a toll on CX as customers cannot find answers to their simple questions, often being told: “No results found.”

Poor FAQ Tools

Effective FAQ Tool

For these customers, their journey is cut short with no follow-up questions asked or channel escalation offered.

Intelligent FAQ Software

The solution for companies who want to:

Provide optimal CX
Ensure excellent customer service
Enhance CSAT
Have greater control over knowledge sharing, data and integrations

Far more advanced than the basic FAQ solutions previously discussed, intelligent FAQ software is the core of all company knowledge. Its role is fundamental, playing a key part in the overall customer service ecosystem and enhancing operations beyond the capabilities of other solutions.

Intelligent FAQ software is built on AI and stores all company information – from internal documents suitable for employees only to FAQs and product information, fit for customer consumption.

Knowledge base FAQ systems fundamentally instruct your FAQs. They track what customers actually ask most frequently; not relying on what you assume to be your top FAQs as other tools or static HTML FAQs do. You can’t improve what you can’t measure, so knowledge base analytics unlock a completely new dimension of CX delivery.

It is your centralised hub of knowledge, feeding any tool that relies on company information. It means that the answers your chatbot or self-service widget deliver to your customers are using the same source as the agent who is operating live chat is also referring to. This ensures complete consistency across all channels and reduces the risk associated with serving inaccurate information.

Your intelligent FAQ knowledge base can seamlessly integrate with:

Internal tools such as agent knowledge that assists in answering customers’ questions
Customer-facing tools that facilitate online self-service
3rd party applications such as CRM or email management tools

An FAQ knowledge base utilises NLP to better ‘understand’ customer queries, taking into consideration the many ways in which a question can be asked. NLP breaks down each query into keywords, intent, grammar and popularity, analysing each component to produce the most relevant results, encouraging CSAT. If the query is non-routine and complex by nature, escalation to an agent-assisted channel is offered where a human can intervene.

Unlike the basic FAQ software options, an FAQ knowledge base turns knowledge into an asset for your company. By collecting and organising useful data, teams can learn from customer behaviour patterns, companies can optimise articles and operations can become more efficient.

Because knowledge bases utilise Machine Learning (ML) principles they can even recognise patterns in customer preferences, language and grammar, storing such intel and using it for improved future interactions.

T o find out more about knowledge base s oftware, click here.

Every business and its requirements for FAQ software is different, but before beginning your software selection process, ensure you have outlined exactly what you need from it. For small start-ups with very basic needs, a simple FAQ page may suffice. But for companies that are focused on maximising customer service, they should consider intelligent FAQ software that supports customers and empowers employees.

If you enjoyed this article and would like to know more about knowledge management, you can read our guide here or if you’d like help with any organisational needs, please

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Why an FAQ Page Is Not A Substitute for A Knowledge Base

Posted on 20 September 2020 | by Áine McInerney | Leave a Comment

There are two key approaches that companies take to facilitate this. They include an FAQ page or a knowledge base.

But how do they differ?

FAQ Pages

Insufficient Data Leads to Insufficient FAQs

Generally presented on a static web page, FAQs are simply a list of frequently asked questions and answers. They aim to cover and address customers’ routine questions online and effortlessly, but unfortunately often miss the mark. Due to the lack of knowledge analytics, the frequently asked questions and answers that are included on such a page are usually based off gut or opinion rather than data itself. Because there is no data stored regarding popularity of routine questions, many companies don’t truly know their FAQs and rely on guesswork. Consequently, the FAQ content is often lacking, limited or general, resulting in customers feeling frustrated – which in customer service is exactly what you want to avoid.

An image that shows the lack of information available on an FAQ page.

Lack of Ownership Results in Inefficiencies

When it comes to the management of an FAQ page, editing, adding and updating can prove cumbersome. Built using basic code, even making one simple update to the content can involve a long chain of command. For instance, someone at head office notifies their team who must tell the web team or agency, who must then notify the developers to make a change. This inefficient way of information sharing means that mistakes are easily made or customers miss out on vital information due to FAQ page mechanics. This is only exacerbated in larger companies where small changes are not made ad-hoc, but instead they are collected and sent in bulk, denying customers of even more important information.

Information Architecture: The Lack Thereof

FAQs page do not utilise information architecture: the structural design of shared information for efficient user experience. Without the organisation, labelling, categorisation and lack of effective search systems, FAQs cannot deliver a positive customer experience. Instead, customers often find themselves going around in circles with no adequate results found and a limited access to content.

Existing Customers’ Needs Are Not Catered To

Furthermore, the content on FAQ pages generally address the basic queries of new customers, for example opening hours, delivery information, returns policies and so on. What they fail to cater to are the needs of your regular customers who will have more detailed routine queries. Questions that are product related, how-tos and purchase follow ups. Whilst customer acquisition is important, neglecting existing customers can prove detrimental to business. Consider the importance of customer value and loyalty and choose a knowledge tool that suits both new and existing customers’ needs.

Knowledge Bases

A knowledge base on the other hand acts as your company’s centralised library of knowledge, connecting to all outlets to provide customers with a wide range of accurate, consistent answers.

Ownership Allows for Efficient, Real-time Knowledge Updates

A knowledge base is a fundamental knowledge management tool that is overseen by a Knowledge Manager to ensure the right information can be found by the right people at the right time. It can store thousands of knowledge articles containing key questions and answers, multimedia and downloads. The content residing in a knowledge base can be developed, updated and edited in real-time, these changes are instantly reflected on your website and any internal users are notified to promote transparency. Such knowledge is intricately organised using multi-layered algorithms, Natural Language Processing (NLP), categories and advanced search systems to ensure customers are served adequate results regardless of how a query is phrased.

Knowledge Analytics Reveal Your Most Popular Questions and More

Because knowledge bases are built on AI, every customer interaction is stored as data and can be interpreted using its analytics. This is how knowledge becomes a true asset, providing valuable intel on customer behaviour, product and services, errors, bugs and of course, what a company’s most frequently asked questions are.

One Centralised Source Promotes Company-wide Consistency

Companies that implement knowledge base software benefit from operational efficiency. Because all knowledge belongs to one single source, the risk of error is significantly reduced. There is no long chain of command as a Knowledge Manager who is committed to optimising knowledge will amend content whenever is necessary. A knowledge base’s agility allows it to integrate with every customer facing and internal portal your company has, whether its live chat, web self-service , chatbot or internal knowledge , the results generated come from the same source every time for consistency and quality.

All Customer Types Are Served Through A Range of Tools

Unlike the static web page that FAQs are hosted on, a knowledge base gives companies choices as to how to present knowledge to their customers, including:

A self-service pop-up

A self-service widget

A self-service page

A chatbot

Live Chat

A combination or all of the above

Find out more about knowledge base integrations here.

This allows a greater volume of customers with different needs, at different stages of the buying cycle and with different query types to be catered to, enhancing CX, the likelihood that the query is resolved and therefore positive CSAT scores.

The key differences between a KB and FAQ page

	Knowledge Base	FAQ page
Artificial intelligence: AI and NLP are utilised to enable First Contact Resolution and therefore reduce overall costs.	✓	✗
Knowledge analytics: Knowledge analytics are available to provide intel on knowledge content, customer behaviour, errors and more.	✓	✗
Ownership: A dedicated Knowledge Manager has full ownership to ensure smooth and efficient operations.	✓	✗
Consistent knowledge: One centralised source of information is used, allowing for consistent company-wide knowledge sharing.	✓	✗
Information Architecture: Information is organised using search systems, categorisation and labelling to help users find the information they require.	✓	✗
Focus on new and existing customers: Knowledge can be presented in a variety of ways to serve customers at different buyer stages.	✓	✗

Impact on Consistency of Information

A key difference between FAQs and a knowledge base involves the consistency of information that is delivered to customers. The processes behind an FAQ page are inefficient and different sources of information are updated at different times leading to discrepancies which can prove detrimental for companies.

A small information divergence is annoying for customers, proving time wasting as they must take care of problem solving and discrepancies by themselves, this in turn can affect customer satisfaction resulting in poor CSAT scores.

However, what is more damaging for a brand is when a major update is not cohesive across channels and therefore the FAQ page is not changed in a timely manner. Inconsistencies in major delivery updates or critical allergy announcements can not only result in influxes of complaints that lead to a bad reputation, but more seriously, PR nightmares, legal complications and at worst, someone is hurt.

It is crucial for business that the information served to customers if always consistent, up-to-date and accurate. All of this can be guaranteed using knowledge base software. Because all information outlets, such as self-service pages, chatbots and live chat tools get their information from one centralised source – the knowledge base – the risk of inconsistencies are significantly reduced encouraging smoother operations and happier customers.

Impact on Operational Efficiency

Another fundamental difference between FAQs and a knowledge base includes operational efficiency, in particular operational costs and overheads.

Knowledge bases are significantly more cost efficient to run than FAQ pages, this is because the updating of an FAQ page requires a long chain of command, multiple people and teams, plus several layers of signoffs. This equates to an accumulation of high staffing costs. A knowledge base on the other hand, is managed, maintained and updated by one Knowledge Manager, removing all operational costs that would otherwise be associated with an FAQ page’s operations.

When it comes to running an FAQ page VS running a knowledge base, an FAQ page is considerably more expensive. The larger your company is, the larger the cost gap will grow.

Due to a knowledge base’s depth of answers available and the agile AI-powered search system that customers use to retrieve results, contact levels are significantly reduced, which subsequently cuts overall customer service and contact centre costs. In fact, a study by Gartner revealed that an 18% reduction in support costs occurred by encouraging knowledge management tools such as a knowledge base. Because a knowledge base has the capability to automate routine queries – giving customers the tools they need to answer their own questions online – agent assisted channels are given more capacity. These expensive contact channels like email or telephone now have a greater bandwidth to deal with customer issues that are more complex and require human assistance.

FAQ pages, in comparison, seldom provide customers with the answers they need, due to their simple setup, that unlike knowledge bases, are not built on AI or utilise NLP, they can never truly be a self-service tool. Instead they often send customers round in loops whereby customers’ frustrations only grow before inevitably having to call customer service to solve their problem. Their customer query has not been automated, high costs still occur and the customer is now annoyed.

To learn more about essential knowledge management tools, including knowledge bases, click here.

While it’s easy to get FAQs and a knowledge bases mixed up, the two are intricately different from one another. One includes a simple overview of basic information, whilst the other is an effective means to streamlined self-service. Most importantly, an FAQ page cannot be a substitute for a knowledge base.

Implementing a knowledge base into your customer service ecosystem helps to promote efficiency, reduce overheads, boost CX and of course improve CSAT scores. If you would like to learn more about knowledge management tools such as knowledge bases, you can do so here.

If you enjoyed this article and would like any advice regarding knowledge base solutions, please

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AI Chatbots in Customer Service: A History

Posted on 16 September 2020 | by Áine McInerney | Leave a Comment

An Introduction to AI Chatbots

In recent years chatbots have become an integral part of companies’ customer service offering, providing benefits such as:

Operational efficiency – the capacity to resolve mass queries at scale
Improved CSAT scores – utilising Natural Language Processing (NLP) for the best customer experience
Instant, 24/7 support – providing customers with around the clock assurance
Seamless customer journeys – guiding customers to the intended result
Brand personification – chatbots can be customised to represent company character
Lead generation – automating the qualification process for efficiency
Enhanced CX – Machine Learning principles enable improved experiences
Improved employee morale – automating routine queries allows agents to focus on complexities
Smooth escalation – identifying when a customer should be transferred to a human

So how does it work?

AI-powered chatbots utilise intelligent algorithms, Machine Learning (ML) principles and Natural Language Processing (NLP) to ‘learn’ from user behaviours and patterns to become more effective over time. Usually integrated with a centralised knowledge base, an AI chatbot can interpret query variations to identify the adequate result and deliver it using a conversational manner. The more interactions the chatbot has, the ‘smarter’ it becomes.

It is important to note that there is a key difference between an AI chatbot and a chatbot, one relies on artificial intelligence and the other relies on rule-based automations:

Basic, rule-based chatbots: built on simple FAQ automations, this type of chatbot can only respond to queries that exactly match its pre-loaded responses. These will only trigger when specific keywords are entered by the user, any variations will not register. The most common answer these chatbots serve is “I don’t understand the question”.
AI-powered chatbots: using multi-layered algorithmic Natural Language Understanding (NLU), these chatbots understand customer intent and respond conversationally using Natural Language Generation (NLG). This approach will deliver the right response, regardless of how a query is phrased.

Basic, rule-based chatbot

AI-powered chatbot

The global chatbot market is expected to grow by $1.11 billion during 2020-2024 – and CAGR of 29%. But how did we get here?

Early AI Chatbots

Artificial intelligence and bots can be traced back to as early as the 1950s when Turing famously designed the Turing Test which would determine whether a machine could pass as a human based on the answers it gave.

But let’s focus on 1990s when the then, “chatterbot” was born. Unlike the chatbots of today, the initial wave of chatterbots weren’t created to facilitate customer service. Instead they were essentially a toy that was played with to test the bot’s intelligence. The way these chatbots learnt was from people talking to them – the more intel their community fed them, the greater their database of ‘knowledge’ became.

Cleverbot (1997) and other chatterbots constructed their replies by drawing on their database of previous conversations rather than consulting a regulated set of knowledge articles through NLP. This quickly became problematic when it was made available to the public.

Why?

Because people were intentionally ‘teaching’ the chatbots offensive ‘knowledge’, it would serve users just that.
Due to the nature of the learning process, there was no control over the content that was being delivered, this meant no way to prevent profanity or inappropriate ‘views’ being shared by the bots.
These chatbots were viewed simply as toys, they learnt nothing of true value and didn’t serve a purpose other than to entertain.

A screenshot of the disclaimer featured on Cleverbot’s homepage.

Following this, there were several developments to try and introduce Machine Learning (ML) chatbots, including Microsoft’s Tay AI (2016). This wasn’t specifically focused on customer service like the chatbots of today but was Microsoft’s attempt to find out if a chatbot could learn like a human.

Tay AI was launched on twitter as a novelty bot, using the tweets she was sent as her training data, Microsoft explained: “The more you chat with Tay the smarter she gets.” The fundamental issue here was the uncontrolled training data – Tay was learning from users who were tweeting their offensive, inflammatory views and once she has drawn similarities and identified patterns, she began to repeat such statements. Her sentence structures were sound, but their content was nonsensical and often controversial.

This is an example of how unregulated training data doesn’t work for customer service chatbots, whilst she managed to learn punctuation and how to form a sentence, she could not identify that what she was saying was offensive. Tay AI backfired for Microsoft and was removed from Twitter after just 16 hours.

Modern Day AI Chatbots

Today, AI chatbots don’t use unregulated or generalised training data, instead they utilise carefully curated data based on customer needs. Such data is usually stored in a centralised knowledge base which is configured to contain ML within set parameters so that companies can reap the benefits of using a chatbot, whilst avoiding fiascos such as Tay AI’s.

Modern day AI chatbots are most commonly used in customer service and use NLP to deliver results in a conversational way. Once a user enters their query, intelligent algorithms and NLP analyse the query, dissecting the sentence into search terms, grammar, and keyword popularity to serve relevant articles to the user.

If there is not an obvious match available then some AI-powered chatbots use additional search layers such as Synthetix’s “Jabberwocky”, which utilises NLP to understand sentence structure. It carefully unpicks the sentence into word classes and identifies conversational responses based on the proprietary Natural Language Generation (NLG) which can also be manually edited and configured by the Knowledge Manager.

The purpose of such additional search layers is to inject brand personality into the conversation whilst improving the accuracy of answers provided. It also ensures that customers will always receive a conversational response, not “I’m sorry, I don’t understand that question” – which proves frustrating for customers, thus poor CX.

The AI-driven chatbots of today are significantly more controlled than those of recent decades with greater efficiency of customer service but with the same, engaging human-like interactions.

AI Chatbots In Customer Service

AI chatbots are considered a crucial part of a company’s online customer service offering and can prove invaluable to both customers and teams across a multitude of industries.

AI Chatbots For Customers

When executed well, chatbots are considered a valuable tool for customers, providing them with quick answers 24/7 through a convenient platform. This is especially useful for those in emergency, out of hours situations who require real-time access to contact details for assistance, or those who simply don’t have time to engage with agent-assisted channels.

AI chatbots can significantly improve customer experience through customer journey technology and ML principles. Certain chatbot solutions utilise decision tree technology to effectively guide the customer to their intended destination. Whether that be a knowledge article, product page or social channel, decision trees, that are carefully configured by a Knowledge Manager, ask a set of questions that will ultimately determine the customer journey and end goal. Without such measures in place, the chatbot assumes that the customer has carried out all necessary problem solving themselves – which is rarely true. The same technology can identify when it is best for an agent to intervene and can seamlessly escalate a customer to an agent assisted channel such as live chat.

An image to show Synthetix Decisions interface

Moreover, chatbots can learn from every customer interaction, storing popular keywords, grammar and colloquialisms for future conversations – constantly improving CX.

AI Chatbots For Teams

Customer service and contact centre teams can benefit significantly from introducing chatbots into their offering. Because they are powered by AI and configured to utilse NLP, the accuracy, efficiency and quality of answers delivered is of a high standard, this improves over time as bots learn from their interactions, having a positive effect on CSAT scores.

Chatbots allow routine questions to be automated, this results in mass queries being resolved at scale promoting not only operational efficiency but reducing overheads. Accumulated operational and staffing costs are cut because a large portion of queries are dealt with digitally and via a bot. Additionally, because routine queries are automated, contact centre employees are given greater bandwidth to deal with more complex, sensitive and subjective issues. This encourages job satisfaction, empowers employees and impacts positively on staff attrition rates.

Chatbots can also directly attribute to revenue streams. Acting as a lead generation tool, some chatbots are configured to qualify leads before they are passed on to sales teams. Equipped with data including the questions they have asked, the preferences they have chosen and using data capture functions, their contact details, leads can be instantly escalated to an agent to nurture. This is particularly useful for teams who previously would have no intelligence on potential ‘hot leads’, but through NLP, can be identified and moved into the sales funnel.

If you enjoyed this article and would like to know more about AI chatbots, you can read more here or

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Chatbots: Taking CX By Storm

Simple Vs Conversational Chatbots

Types of Chatbot

Menu-Based Chatbots

Keyword Recognition Chatbots

Conversational Chatbots

Why Conversational Chatbots?

NLP, NLU, NLG & Machine Learning

Natural Language Processing

Natural Language Understanding

Natural Language Generation

Machine Learning

Implementing Conversational Chatbots

Why Chatbots?

How Do Chatbots Benefit the Contact Centre?

Chatbots Help Your Contact Centre Boost CSAT

Chatbots Contribute to Agent Satisfaction

Chatbots Make Your Contact Centre More Efficient

A. Deal with the customer’s routine query successfully

B. Or, detect that the customer’s query is non-routine and requires human assistance, automatically escalating the customer to an agent-assisted channel such as live chat

Why Consider Live Chat for Your Website?

How Does Live Chat Work?

Live Chat’s Key Role in Customer Service

Selecting Your Live Chat Vendor

Live Chat for Your Website: The Implementation Process

Measuring Live Chat Effectiveness

Performance Metrics

Knowledge Effectiveness Metrics

Live Chat Knowledge Base Integration:How Does It Work?

Live Chat’s Role in Customer Service

A Knowledge Base’s Role in Customer Service

Why Integrate and How?

Live Chat Knowledge Base Integration: What Are the Benefits?

Reduce Distraction and Enhance AHT

Consistency Makes for Better CX

Optimal Agent Productivity Through Integration Features

Performance and Article Metrics Are Activated

Boost ESAT To Boost CSAT

Cost-Efficiency

Synthetix have the complete platform of customer service tools.Book a demo of any of our products below

1. Ensure Live Chat Is Aligned with Your Business Goals

2. Configure Trigger Management for Maximum Lead Generation

3. Put Your Brand’s Stamp on It

4. Use Smart Web Forms for Pre-Qualification

5. Manage Customer Expectations When It Comes to Live Chat

6. Ensure Live Chat Supports File Transfer

7. Offer Live Chat Feedback Surveys

8. Integrate Live Chat with Centralised Knowledge for Consistency

9. Integrate Live Chat with Your CRM And Other 3rd Party Apps

10. Compliment Live Chat With AI-Powered Chatbots

11. Consider Live Chat’s Role in The Holistic Customer Journey

12. Make Use of Integrations That Handle Personal Data Securely

13. Use A Live Keypress Feed for Reduced AHT

14. Use AI Predictive Suggestions and Integrated Knowledge for Accuracy

15. Ensure Chat Transfer Is Seamless to Enhanced FCR

16. Study Live Chat Metrics for Continual Optimisation

17. Focus on ESAT If You Want to Improve CSAT

18. Utilise Agent Scripting

An Introduction to Live Chat Software

Live Chat Software Use Cases

Customer Service

Lead Generation

Customer Engagement

Benefits of Live Chat Software

For Your Company

For Customers

Synthetix have the complete platform of customer service tools.Book a demo of any of our products below

An Introduction to FAQ Software

Types of FAQ Software

Basic FAQ Page Solutions

Basic FAQ Tools

Intelligent FAQ Software

FAQ Pages

Insufficient Data Leads to Insufficient FAQs

Lack of Ownership Results in Inefficiencies

Information Architecture: The Lack Thereof

Existing Customers’ Needs Are Not Catered To

Knowledge Bases

Ownership Allows for Efficient, Real-time Knowledge Updates

Knowledge Analytics Reveal Your Most Popular Questions and More

Live Chat Knowledge Base Integration:
How Does It Work?

Synthetix have the complete platform of customer service tools.
Book a demo of any of our products below

Synthetix have the complete platform of customer service tools.
Book a demo of any of our products below