Self-Service Software for Customers: The Considerations
Rather than recommending something that should be subjective to each company’s needs, we have put together some considerations that will lead you to the best self-service software for your customers:
Does the self-service software utilise Natural Language Processing?
Is the self-service software fuelled by one centralised knowledge base?
Can the FAQ articles be found organically using search engines?
Can the self-service software be optimised for different customer journeys?
How easy is escalation between self-service and agent-assisted channels?
Can the self-service software’s content be improved over time?
Does The Self-Service Software Utilise Natural Language Processing?
Natural Language Processing (NLP), a branch of Artificial Intelligence (AI), is used to help analyse linguistics and by doing so, understand intent.
For customer service and particularly in self-service software, this means unpicking customers’ queries, analysing components such as grammar, keywords, intent and popularity to identify user intent. From here intent keywords are matched with knowledge articles, serving users the most relevant results.
Many companies consider NLP-powered self-service as essential. Not only does it provide customers with accurate resolutions 24/7/365, but it also helps to significantly reduce contact centre costs.
Because AI is capable of handling large volumes of routine queries – queries that would otherwise reach contact centre agents – the overheads associated with query handling are significantly reduced, bringing down support costs.
It can also remove the repetitive and mundane from agents’ day-to-day tasks. As AI is capable of dealing with routine queries and tasks, operators can help with more complex and ‘worthwhile’ issues, adding to job satisfaction, or ESAT (Employee Satisfaction).
Is The Self-Service Software Fuelled By One Centralised Knowledge Base?
A centralised knowledge base acts as your main source of information, powering all customer service channels including self-service software for your customers to use.
The benefit of utilising a knowledge base here – and particularly an intelligent, AI-powered knowledge base – is that it ensures consistency of information, encouraging CSAT but also helping to prevent any problematic situations that could occur as a result of inaccurate information.
The issue with having multiple channels and sources of information is that they have to be updated separately, increasing the risk of them displaying contradictory, inaccurate or misleading information on behalf of your company.
Not only may your brand’s reputation come under fire, but customer loyalty may also be affected or in some cases, the consequences of showing incorrect information could lead to legal action or worse.
Can The FAQ Articles Be Found Organically Using Search Engines?
There are a number of different ways in which a user might begin their journey. Whether it’s directly through your site or via a social media channel, it’s important to accommodate every user and their preference – including organic search engine results.
Having self-service FAQ results findable via search engine results not online streamlines the customer journey significantly, trimming time off their session and improving CX but can also help to enhance brand visibility.
So, how is this achieved?
For your FAQ result to be visible in search engine results, your self-service software provider translates each knowledge article into its own crawlable, searchable URL
Can The Self-Service Software Be Optimised For Different Customer Journeys?
Not every routine query or task has a cookie-cutter resolution or process, often there are variables and conditions that will affect the result.
Just as agents carry out the troubleshooting process by asking follow-up questions to a user’s initial query, the best self-service software does this too. Fuelled by AI and by harnessing intelligent decision tree technology, multifaceted routine queries can be automated.
By mapping out your users’ most common journeys, popular FAQs and additional questioning requirements, you can create smooth and effective routes to resolution – without having to involve human interception. All of which is achieved through an easy-to-use decision tree creation tool, knowledge articles can be dragged and dropped to fit common journeys.
Anticipating and catering to popular user journeys not only enhances CX significantly but it improves CSAT scores as users are served resolutions without having to wait on hold or repeat themselves.
How Easy Is Escalation Between Self-Service And Agent-Assisted Channels?
There will always be occasions where queries are too complex by nature to be handled using AI alone. This is where seamless escalation between self-service software and agent-assisted channels such as live chat is critical to CX.
Your users don’t want to be told: “Sorry no results found. Please contact support”, to then have to find a contact number, wait on hold and then repeat themselves. For your customers, it’s a huge waste of time.
Instead, Ensure your customer service tools are integrated, working together frictionlessly. When your self-service tools suspect that human intelligence is required, automatic escalation to live chat takes place, all within the same window to prevent repetition, improving CX.
Can The Self-Service Software’s Content Be Improved Over Time?
When it comes to self-service software for your customers, it’s important that knowledge article content is helpful and being optimised regularly.
One of the most effective ways to ensure your FAQ content is serving its audience effectively is by encouraging interactive customer feedback options. Asking users if a knowledge article helped resolve their issue can help uncover areas for improvement and ultimately other users’ journeys.
Self-service software that includes a prompt for query feedback is particularly effective when it comes to optimisation, by getting users’ take on why an FAQ did not help contributes to constant optimisation.
If you enjoyed this article and would like to find out more about self-service software for your customers, check out our guide here or for help selecting software
With the global chatbot market expected to reach $102.29 billion by 2026, registering a CAGR of 34.75% over the forecast period, 2021 – 2026, it’s critical that companies keep up with such CX trends and customer demands.
In this article we explore the advantages of chatbots in customer service:
Chatbots reduce support costs through automation
Chatbots enhance CX with seamless journeys
Chatbots boost CSAT through consistent, 24/7 support
Chatbots contribute to lead and revenue generation
Chatbots satisfy customers by offering smooth escalation
Chatbots channel your brand’s personality
1. Chatbots Reduce Support Costs Through Automation
Customer service chatbots are powered by AI and use sophisticated Natural Language Processing (NLP) in order to resolve users’ routine queries and tasks. Through harnessing NLP, chatbots understand user intent and can therefore serve accurate and relevant resolutions. In many ways, a chatbot takes on the role of a digital customer support agent – one that deals specifically with routine queries.
Chatbots can independently handle 20% of routine queries online.
Some chatbots enable Conversational Process Automation (CPA). By integrating with your core business tools, entire processes can be automated online. For instance, policy changes in the Insurance industry or meter readings in Utilities can take place completely online.
Now that these routine queries and tasks – that would otherwise reach the contact centre – can be handled through AI and totally online, support costs decrease. There is a myriad of contact centre costs associated with query handling that is reduced when a chatbot automates routine queries.
2. Chatbots Enhance CX With Seamless Journeys
Chatbots play an important role in the wider customer service journey. Acting as a digital CX concierge, chatbots can guide users through their entire journey if necessary, resolving queries along the way and ultimately helping them reach their end goal in the smoothest, most efficient way.
Not every user will have a query that warrants a simple, ‘one size fits all’ resolution. But not every problem must be escalated to the contact centre. This is where decision tree technology compliments customer service chatbots. They help with problem-solving common problems that often require follow-up questioning to resolve.
Managers simply map these common user journeys out using simple drag and drop systems and the entire journey is automated, providing excellent CX.
3. Chatbots Boost CSAT Through Consistent, 24/7 Support
Customer service chatbots are fuelled by one main source of information – an intelligent knowledge base. This is a library of knowledge articles that powers not only your chatbot and self-service platform but also powers the interface that agents consult when dealing with customers via live chat or directly over the phone. Because your flow of information to the public is derived from one source, it means accurate and consistent resolutions are served, avoiding problems that arise when misleading or inconsistent answers are given.
Issues for your customers will arise regardless of the time of day and for your CSAT ratings, it’s critical that support is available 24/7 for those out of hours queries. Chatbots do not need to be manned or take breaks, they are available 24/7 and rely on AI to answer queries as opposed to human intelligence.
Using sophisticated NLP, Chatbots take each user query and by analysing each keyword, user intent, grammar and popularity, produce the very best, most relevant answers. Pair this will 24/7 support and chatbots are catalysts to customer satisfaction.
4. Chatbots Contribute To Lead And Revenue Generation
Chatbots that specialise in customer service include a level of customisation that, when configured correctly can increase your lead and revenue generation.
Using custom triggers, you can determine where your chatbot proactively offers users help, whether it be once they have hit a certain high-value page or when they have spent a certain amount of time on a page.
Customer service chatbots utilise sentiment analysis that helps to determine user urgency based on the keywords they use, for example, ‘cancel’ or ‘order’. These signal that help is required, lead opportunity or even revenue generation. By proactively offering assistance at those critical user touchpoints, the chances of conversions taking place significantly increases.
5. Chatbots Satisfy Customers By Offering Smooth Escalation
There will always be occasions where customers have complex questions that cannot be solved using AI alone. This is where human intelligence and understanding is required. However, what happens all too often is users interact with a company’s self-service tools to find that their query cannot be solved there. This is when they have to source agent-assisted channels, repeat the process and their query and time is wasted.
With an AI-powered customer service chatbot, users are automatically escalated to agent-assisted channels such as live chat when the chatbot detects that the query is too complex by nature for AI to solve. The escalation takes place within the same window and transcripts are transferred to avoid any user repetition taking place.
By streamlining this often onerous process, CX is enhanced and this reflects positively in customer satisfaction feedback.
6. Chatbots Channel Your Brand’s Personality
Implementing a chatbot into your online offering is not only a means to improve CX and customer service but also a branding opportunity.
Some customer chatbots include additional search layers that can be customised to fit your brand personality. This is where any quirks or idiosyncrasies that match your culture and character can be configured.
It makes the customer journey more enjoyable, replacing the same boring responses whilst injecting a piece of your brand personality.
If you enjoyed this article and would like to find out how your company could benefit from customer service chatbots, you can read our guide or
Synthetix have the complete platform of customer service tools. Book a demo of any of our products below
An Introduction to Chatbots
A chatbot is a software application primarily used by businesses to facilitate customer service. Unlike agent-assisted contact channels such as live chat or telephone, chatbots rely on AI to resolve customer queries. The tool that enables human and machine interactions has become increasingly popular over the last decade, often acting as customers’ first online port of call, but how did the chatbot become so sought after?
The first chatbot, ELIZA was created in the 1960s before the term ‘chatbot’, or its predecessor, ‘chatterbot’ was invented. ELIZA was an advance in computer science but was not made with the intention to assist customer service.
Following ELIZA, there were several failed attempts at producing an effective chatbot including the likes of Cleverbot and Tay AI. What these bots had in common was unregulated training data; the way in which they ‘learnt’ was from the information fed to them by their users – the public – opposed to being configured by professionals using benchmarking and objectives. The result of which led to Tay AI’s termination following a spurt of offensive views it shared on Twitter.
Today we are familiar with a different type of bot – the customer service chatbot. Unlike other chatbots whose purpose was simply novelty – to be played with and to provide entertainment – the chatbots we are used to today are there to provide help, automating customer queries, providing good CX and subsequently helping customer service teams.
How Do Customer Service Chatbots Work
Customer service chatbots are built on AI and through Natural Language Processing (NLP) and Machine Learning (ML) principles effectively ‘understand’ customer queries to provide adequate responses. Chatbots integrate with companies’ centralised knowledge so that depending on what query is entered, they can utilise smart algorithms to identify and serve the most relevant knowledge articles to customers.
NLP is the combination of Natural Language Understanding (NLU) and Natural Language Generation (NLG) and is constantly learning from each customer interaction to be as optimal as possible over time. NLP is responsible for unpicking the customer query, dissecting the sentence into intent-based keywords, subjects, grammatical quirks and keywords popularity to analyse, interpret and present an appropriate result.
It’s important to note that not all chatbots offered today are powered by AI, some are built on rule-based automations. Such chatbots can only respond to queries that exactly match their pre-loaded responses, leaving no room for query variations or synonyms. The result of which is “I’m sorry, I don’t understand the question. Please try again” served to customers more often than a genuine result.
This is why AI-powered customer service chatbots are so valuable to business. They are programmed to understand that there are multiple ways that a question can be asked, an array of synonyms and even idiosyncrasies. NLP helps to eradicate unhelpful responses.
Some chatbot specialists include additional layers of search for chatbots to consult if query intent is unclear. Synthetix’s system, “Jabberwocky”, for instance, unpicks query sentence structure, analysing grammar and a range of word classes. Its utilisation of proprietary NLP enables brand personality to be portrayed, increases answer accuracy and ensures that the customer always receives a conversational response.
Find out about the advantages of chatbots in customer service, here.
Why Use Chatbots In Customer Service?
According to IBM , chatbots in customer service can solve 80% of all routine queries – including questions such as:
What is your returns policy?
Where is my delivery?
Can I apply for a refund?
Such routine questions make up a large percentage of overall contact volume, so when they are automated through AI and solved at scale, operational costs are significantly reduced. Without chatbot solutions in place, customer service teams would otherwise deal with routine queries, creating a backlog of tickets and an accumulation of overheads and staffing costs.
Did you know? Chatbots can save businesses up to 30% in customer service costs.
It isn’t just the bottom line that benefits from chatbots’ capabilities to automate routine queries, agents are given a greater bandwidth in which they can deal with customer issues that are complex or sensitive by nature, rather than the same queries time and time again. A study revealed that 64% of agents with AI chatbots are able to spend most of their time solving complex problems, compared to 50% of agents without AI chatbots. This in turn contributes to positive employee morale – their perceived quality of work is richer when the repetitive, mundane element is removed, promoting job satisfaction and therefore productivity.
Find out how chatbots are supporting agent morale and productivity, click here.
Customer service chatbots have a key role to play in customer satisfaction. Not only does NLP ensure that customers are served the very best results, encouraging improvements in First Contact Resolution (FCR) rates, but the channel itself is easy to use and convenient. Offering 24/7, real-time results, it’s a channel that customers can depend on, if for example, a chatbot provides customers critical information in an out of hours emergency, this of course is reflected in CSAT scores.
The adoption of chatbots also helps to optimise CX through Machine Learning (ML) principles and decision tree technology. ML principles enable chatbots capabilities to learn, store and utilise trends in customer behaviour, for example popular queries, colloquialisms or preferences are collected and then used for future interactions making the overall CX more enjoyable.
Effective customer service chatbots provide a smooth and enhanced customer journey through decision tree technology. To reach a successful result, an agent will usually ask customers a series of questions, but when there is no agent involved, how is this facilitated? Decision trees are configured so that chatbots can intervene at the problem-solving stage and ask such questions. This helps customers reach their destination result quickly and effectively, seamlessly transferring them to agent-assisted channels like live chat if necessary.
Types of Customer Service Chatbots
There are 3 types of chatbots that are commonly used in customer service, these are:
Keyword recognition-based chatbots
Menu-based chatbots use clickable menu buttons to help customers reach the result they require. Similar to the rule-based chatbot discussed previously in this article, this type of chatbot relies on one specific set of data and therefore cannot offer results based on anything outside of this. Although menu-based chatbots might be suitable for small businesses with super basic requirements, for instance providing answers to FAQs, they are simply not capable of answering queries more advance than this. As a result, the precision and efficiency of answers served suffer.
Keyword recognition-based chatbots utilise AI, isolating and analysing each keyword to determine the best results. With each query that is entered, this type of chatbot will concentrate on the keywords that warrant action, for example “order”, “account”, “payment” and verb word classes such as “setup”, “cancel”, “refund” to piece together the most suitable response for the question at hand. Keyword recognition-based chatbots, however, are not effective at recognising multiple variations of questions.
Contextual chatbots utilise both AI and ML principles, proving particularly valuable to customer service amongst a multitude of companies. This chatbot type learns and stores useful information to utilise in future conversations. By remembering certain customer preferences and behaviours, conversations with the same customer during different sessions are of optimal efficiency and CX. A large portion of time can be saved if the bot simply asks the customer if their preferences are the same this time around, opposed to carrying out the same question process time and time again.
In customer service, chatbots are not only an expectation but they can assist teams quite significantly whilst complimenting companies’ overall customer service toolkits. As chatbots are more widely accepted and businesses understand the importance of AI-powered tools, we can only expect bigger, more impressive things for the bots of customer service.
If you’d like to know more about the benefits of conversational chatbots, click here.
If you enjoyed this article and would like to find out more about chatbots, you can do so here . Or, if you’d like any chatbot advice or help with your organisational needs, please
A report conducted by the Institute of Customer Service that surveyed 10,000 people revealed that the number of complaints regarding poor customer service in the last six months was at its highest level since 2009.
It was also revealed that customers believe that companies too often use COVID as an excuse for the poor service they received.
Customers were empathetic and patient towards the disrupted level of service in which they received during the first 6 months of COVID. But fast forward a year – that’s a year to adapt, plan, fail, try again and improve – and the blanket excuse, “because of COVID…” no longer cuts it.
It exacerbates the frustration that customers are already feeling. With the lockdown restrictions easing this week, they’re (quite understandably) fed up of hearing that excuse, leading CSAT scores to suffer.
The Companies Whose Customer Service Has Thrived Since COVID
Since the beginning of the pandemic, many companies have had time to adapt and even thrive when it comes to a new era of CX. Whether it’s remote working, new technologies or improved processes, a multitude of businesses has successfully adapted and through digital transformation, are more efficient than pre-COVID times.
So where have these companies found their online customer service wins?
Wider channel choice
A blend of self-service and agent-assisted contact options
The human touch via conversational AI
Wider Channel Choice
Customers want to be able to access your help articles and agent assistance from a range of channels. When they’re on the go or working from a specific device, sometimes navigating to a company’s support page, entering a query and browsing articles isn’t convenient.
Companies that offer multichannel customer support online are thriving when it comes to CX and satisfaction. Giving customers the choice as to how and where they access help is critical.
For instance, a majority of customers’ online journeys begin with the search engine. By fuelling your FAQs with an SEO Knowledge Base, you not only help provide the best answers quickly but by streamlining the user journey, save costs and boost CSAT.
Similarly, by offering live chat options via popular social and instant messaging channels, a customer’s journey is significantly more efficient and successful.
A Blend Of Self-Service And Agent-Assisted Contact Options
Companies that are thriving when it comes to customer service, offer their users a blend of self-service and agent-assisted contact options that are fuelled by the same knowledge base and frictionlessly escalate when necessary.
Offering self-service tools such as an FAQ page, FAQ widget or a chatbot reduces contact levels to the contact centre not because routine queries have been aggressively deflected, but because users have learnt how easy and convenient it is to self-serve.
For optimal CX, ensure your customer service platform includes seamless escalation between channels. If a self-service tool cannot deal with a query due to its complexity, it’s important to the user journey that an escalation to an agent-assisted channel such as live chat or the contact centre is available. This negates the need for customer repetition and streamlines their journey.
The increased demand for conversational AI technology such as chatbots is fuelled not only by its capability to automate routine queries and processes, significantly reducing contact and therefore support costs but also customer preference.
Whilst most customers understand they are not speaking with an actual human, the human touch that is provided by conversational AI and chatbots enhances CX as they are guided through their journey.
Powerful Natural Language Processing (NLP) unravels each of your users’ questions, analysing keywords, intent, grammar and popularity to ensure the best, most relevant results are provided. Sophisticated search layers can then be configured to add elements of your brand personality.
Since the height of the pandemic in 2020, companies have had time to plan, recoup and improve their customer service operations. It is therefore no wonder that customers are frustrated to hear COVID still being used as an excuse for poor service today.
However, for the many companies that are thriving, adaptability and new technologies are key. Utilising CX software that offers customers a range of channels, has a blend of self-service and agent-assisted tools and adopts conversational AI has proven fundamental for customer service success.
If you would like to find out more about customer service software that has helped companies thrive
The pandemic has impacted the way in which every business operates. As the only line of communication between companies and their customers, online CX in particular has never been more vital. Here, we discuss what CX will look like post-pandemic, and if it will ever be the same.
The Impact of Covid-19 Had On CX
When COVID-19 became a pandemic during 2020, the nation was told to stay at home, which involved working from home, ordering groceries online and communicating with companies digitally.
Nipping to the shops for a ‘non-essential’ item or popping into the building society were no longer options. This led to drastic and accelerated changes in customer behaviour fuelled by uncertainty. Companies experienced huge influxes of contact, on average a 20% increase, although some businesses, including supermarkets and on-demand groceries saw up to 130% increase in contact volumes.
Unprepared for the sudden crisis, companies, who now had far fewer opportunities for face-to-face, in-store experiences with customers had to adapt fast.
Not only were agents, like the rest of the world, adjusting to working from home conditions, but a surge in contact meant that companies had to employ many more agents to keep up with the volumes. Training and upskilling were major obstacles that companies faced as a result of the pandemic.
Companies that did not offer digital contact channels adopted them quickly in order to satisfy the surge in contact volume reaching contact centres, deflecting queries that could be automated, but also to cater to generation groups that were not accustomed to online experiences. Many companies had to reconsider their entire CX offering during 2020 as a direct result of COVID-19.
Forecasting the State of Post-Pandemic CX
We can’t predict the future, however, if 2020 has taught us anything it is that being prepared, agile and adaptable is fundamental in terms of survival and growth.
This of course relies on knowing whether things will stick or revert to pre-pandemic CX. We have drawn a number of conclusions as to how CX will look for both your team and customers post-pandemic.
What Does It Mean for Your Team?
A significant change driven by the pandemic that has affected most of the population includes the way in which we work, with millions of us advised to work from home when possible. Whether we like it or lump it, these changes – to a certain degree – are likely permanent.
The same survey found that 50 of the biggest UK employers had no plans to return all staff to the office full-time in the near future.
As the backbone of CX, it is important that your customer service teams and agents are fully supported in their working environment, whether that be working from home, flexi-working or in the contact centre – when this is possible. This includes their WFH conditions, wellbeing and tools you provide.
Whether your agents and highly experienced or in training, they need cloud-based, reliable and intuitive tools that make fulfilling their jobs simple.
What Does It Mean for Your Customers?
Customer behaviour has rapidly evolved throughout the pandemic, with CX stakes high and companies responding to new customer demands, a faultless, smooth and successful online customer experience is a minimum expectation.
Many have become accustomed to online grocery shopping, digital appointments and virtual meetings. For many sectors digital is the now new norm; with the likes of pioneer retailers such as Topshop being purchased by online retail giant ASOS – will the convenience of buying online stick?
According to one study half of customers say that customer experience is more important to them now compared to a year ago.
With a rapidly accelerated digital timeline and expectations for far greater online experiences, companies must be able to keep up with demand, providing customers with smooth, efficient and successful journeys on every session.
How to Meet Post-Pandemic CX Demands
Equip Agents with Agile, Intuitive CX Software
Agility is key in times of uncertainly. We can never be sure when a crisis will hit, so being able to adapt fast is fundamental.
Ensure that the software you choose to support your agents includes:
An integrated knowledge base – built on AI, this helps agents find answers to queries fast, without having to switch windows and worry about handling times.
AI-predictive suggestions – the integrated knowledge base suggests relevant articles based on what is being entered, on each keypress. Agents simply click to copy.
Live Chat with efficiency-boosting features – live keypress feed gives agents a preview of what the user is typing before they’ve hit send.
User-friendly interface – ideal for remote or flexi-working, the agent interface must be customisable and intuitive.
Natural Language Processing – AI interprets users’ search intent, providing agents with the most relevant answers. This provides experienced agents with confidence whilst reducing training times for starters.
Agent scripting – decision trees help new employees become seasoned experts with easy-to-follow processes.
Offers a range of AI-powered self-service options – harnessing Natural Language Processing makes finding that critical piece of information easy for customers.
Include a customer service chatbot – not only is this great for engagement, guiding customers to their destination, but a chatbot can contribute to lead and revenue generation.
Maps key customer journeys – decision tree technology lets you determine customer journeys based on the options they choose.
Facilitates smooth experiences – self-service channels that seamlessly escalate to live chat or other agent-assisted channels when complex queries need dealing with.
Whilst we cannot be sure what post-pandemic CX will look like exactly, we know that it is likely that remote working is here to stay. We know that CX is more important than ever and that companies are responding to this. In order to satisfy your employees, operations and customers, it is paramount that the software you choose is capable of supporting flexi-working and excellent CX.
To find out more about CX software that includes what we have discussed in this article, please get in touch with Synthetix.
Are you a social sharer or like to be kept in the loop? Fear not, Synthetix will keep you up to date. Sign up to our monthly newsletter by entering your email for insights into the world of conversational AI, customer service software and support.