The contact centre is customers’ main doorway to an organisation – and it is often presented as a giving a great customer experience, with the brand promise of caring and friendly staff, and an open and transparent philosophy. Sadly, for many, the customer experience doesn’t match the hype. This is where broken processes are letting businesses down badly.

It never ceases to surprise me how many businesses fail to recognise broken processes. While many are easy to spot, there are other broken processes that are much more subtle and more difficult to identify. It is no wonder that many contact centres are not aware that they even have them. I often speculate about how many revenue, customer and staff losses are attributed to hidden broken processes.

In this blog, I highlight five examples of broken processes in the contact centre.

1. Inconsistent data records

This is generally brought about by data and workflows not being integrated. Basically, the information gained is not being propagated to process management. This is a big danger area for many contact centres. Warning: this is one that will come back to bite you later.

Here is an example: a customer calls in to say that their parcel did not arrive, which gets dealt with by a member of staff in isolation. The problem gets resolved, but there is little or no understanding of why the problem occurred and no feedback loop to prevent it happening again. The solution is to have a well-documented and automated process for updating systems of record with newly obtained information, this will provide consistent levels of information throughout the business.

2. Long call-queue times

Long queue times are one of the biggest areas of concern in the contact centre and can be a huge contributor to customer frustration and churn. Identifying the root cause is almost certain to show that you have one or more broken processes. Are your staffing levels adequate? Are your staff properly trained? By analysing conversational data, combined with workforce and knowledge management, you will gain valuable insights into what is causing your long queue times.

3. Repeat callers

Your organisation may have spent time and effort to document processes and make that documentation available to your agents in a knowledge base. In theory, the knowledge base is intended to guide your agents through every customer call so that every issue is handled consistently. Unfortunately, this is often a manual process that can be slow. Every time an agent goes to the knowledge base, they must search for the information they need, read through the instructions and interpret how best to proceed, and usually while the customer waits on hold. Even the most comprehensive knowledge bases are inefficient and increase the likelihood for error. By automating your knowledge-base searches based on the conversation, you can deliver the relevant knowledge to steer your agents in real time, resulting in a more efficient, faster and more consistent delivery of information. Getting your customers the right information, first time, will significantly reduce the need for them to call back.

4. Manual processes

Businesses have a lot of manual processes, whether in customer service, fulfilment or logistics. We still use a pen and paper to take notes and write down instructions or even solutions to the problems that we have just resolved. However, what do we do with those pieces of paper? How do we get what we have just learnt, or maybe even fixed, back into the knowledge base? We can get all our pieces of paper together at the end of the day and manually update our systems of record, but we often do not. There is rarely time during the working day to do that and when the day is done so are we, resulting in everything we have learnt going nowhere. Automated conversational transcription or summary can be used to automatically document some or all the conversations and insert that summary or transcription into your CRM or system of record, meaning the information is available in the future. It can also be used to update your process management system, enabling processes to be automatically updated.

5. Survey results

Increasingly, businesses are turning to surveys to try to gauge how well they are doing, as well as highlighting areas for improvement. These may be collected traditionally or via social media sites. Information received could be gleaned from questions and answers or from frustrated comments. This can certainly indicate when something is not working. Being able to harness this information in real time or near real time will enable you to gain understanding and make fast changes before matters escalate, and will allow you to optimise your processes.

In summary, while I could continue with another 50 broken processes that businesses are missing, I hope that these will provide clues to where to target and probe a little deeper to uncover your broken processes.

Contexta360 is a broken-process expert. Our aim is to help businesses navigate and build better processes through conversational intelligence and AI-fuelled analytics.

Please get in touch if you would like to learn more.

 

Quality management has evolved over time: from the days of telephone operators and supervisors walking the floor, to random recorded calls being sent to team leaders and supervisors, to something of a more intelligent and automated offering.

Today, the contact centre is regarded as the centre of excellence for most businesses. Quality management (QM) is viewed as the main way to understand how your business is performing, what improvements can be made and if you are remaining compliant with the mass of processes and legislation.

Contact centres must implement a constructive process and workflow that focuses primarily on knowledge gained from customers and conversations, not just from internal performance criteria and metrics. The knowledge gained from customers must be the primary driver for your performance measurement, the employee development actions that take place, and to help you understand why your customers really contact you.

Traditional QM is based on manual evaluations. It relies on team leaders and supervisors to listen to calls and score them according to fixed criteria. It provides accurate, consistent and measurable analysis of agent performance over time, and it can be used to direct coaching and training efforts.

Add speech analytics, which is rapidly becoming a mainstream technology, and you open up a host of opportunities for contact centres, with technologies that can process 100 per cent of calls while identifying other key metrics such as sentiment, empathy, and insights into why your customers are calling.

Speech analytics enables users to systematically collect data from a large sample of interactions, but data is nothing unless it can be turned into information. Combining speech analytics with QM can help to turn that data into actionable information. Using the speech analytics tool to determine key issues that require a deeper understanding, and then combining that with targeted human listening to analyse the interactions for meaningful insights, root cause analysis and behavioural correlations, will create richer and more actionable outcomes.

Furthermore, the combined power of a speech analytics and a QM tool can identify calls that contain specific words or phrases, or even highlight areas of interest that you hadn’t considered. This is paramount when trying to pinpoint conversations that require escalation or immediate attention. The business can then leverage the outputs to focus on agent coaching opportunities – evaluating them for specific agent behavioural trends, identifying agent behaviours that need improvement, and providing actionable feedback to the supervisors for coaching and training purposes.

Add this value to other stakeholders, and suddenly you can link your conversational data right across your business. This includes correlating data right through to customer experience measures such as customer satisfaction, Net Promoter Scores and customer effort, as well as sales and operational KPIs, CRM data, complaint data and agent HR data. By integrating QM results with other key data points, business leaders can identify and address the true root causes of issues such as dissatisfaction, customer attrition and many other problems that can affect the health of the business.

By combining the power of QM and speech analytics as an integrated solution, you can fulfil the whole of your organisation’s needs in a compelling way. Speech analytics can collect data on both the conversational and transactional part of a customer interaction, and it can be used easily and effectively for compliance and automation to increase efficiency. However, without the integration of QM, the next-level insights that truly affect the whole customer experience are not identified or resolved.

To find out more why not what a short pre-recorded demonstration.

 

In the wonderful world of interaction analytics one of the key value propositions is the ability to identify broken processes. There is a wealth of technology available today, including speech analytics, interaction analytics, conversational intelligence, and more.

The issue is that businesses are stuck in their old processes and often don’t realise they have any that are broken until the complaints start rolling in. Then there is often a call for a quick fix, which isn’t always the best thing for long-term value.

Over the past five years, the role of the contact centre has been evolving fast and, thanks to the impact of the Covid pandemic on the workplace, this rate of evolution has accelerated exponentially. With the ever-growing popularity of the cloud, we are seeing the break-up of traditional bricks-and-mortar contact centres, with people opting to work at home rather than going to the office.

Businesses are busy trying to strengthen the front line with a combination of human capital and technology. This is great for routing and handling calls, however it is the process after the call that is often lacking. Rather than bolting on pieces of technology to solve a single problem, the future requires a more integrated and connected infrastructure. The notion “my bit is now done” is no longer an option. There is a need for automation that understands the context of conversations, whether human or machine, to drive end-to-end processes and then place that learning back into those processes.

We are heading down this digital transformation road, and a whole host of communications and intelligence solutions and methodologies are being created to revolutionise customer service and engagement. It is crucial that businesses do not fall into the trap of accepting or ignoring broken processes but instead focus their attention on ensuring all their contact centre processes are carefully planned, tightly integrated and well connected. Get it right and businesses should be able to identify, fix and eliminate broken processes, as well as delivering great customer service and real business transformation.

In 1980, Hazel O’Connor released a song called Eighth Day. This was, in essence, a song about technology advancement and how it was going to affect the human race.

Four decades later, much of what this song predicted has come to pass.

In a world where once humans did everything, slowly but surely machines and technology have become the driving force behind our evolution.

In business we are looking at how we can use technology to automate and optimise processes and redirect the expensive human element towards tasks that add value.

Since 2016, the interest in chatbots has grown exponentially. These intelligent robots have led us to believe that we can decrease the number of repetitive tasks performed by our teams, freeing them to work on other areas of focus in the business.

So, in case you weren’t a fan of 1980s’ punk music, what is a robot or, more relevantly, a chatbot? The latter is simply an application that automates tasks or simulates conversations. The software is programmed to read messages (emails, text messages, chat conversations, etc) and answer them in a short period of time thanks to a combination of pre-templated responses. Now, this is not to be confused with artificial intelligence, which refers to devices that imitate or replace human cognitive features. Most chatbots do not possess artificial intelligence, although this would make things a lot more interesting. Watch this space!

So, all-in-all, this sounds great. These chatbots are available 24/7 in real time, they can handle all communication channels and they can automate business processes. Hazel was right, there is no need for humans.

Well, no…

Chatbots, at least today, cannot replace human expertise and core business knowledge. The reality is that they are being used as call queue control can only interact at a very basic level. The current chatbot offering is falling short. It isn’t smart enough, it doesn’t have enough programmed templates to replace human core business knowledge, and it isn’t conversational, so may have a negative impact on customer experience. This leads to the human agent, in most cases, being re-engaged to deal with the customer frustration that the bot has created. This, in turn, leads to longer call-handling times, poor customer experience and demotivated agents.

Users are still attached to human interactions and there is always positive sentiment when users realise they are being supported by humans rather that robots.

Recent research has found that 86 per cent of consumers prefer humans to chatbots (CGS survey)
Forbes Synopsis.

When it comes to analysing human agent performance, there are myriad different solutions, some manual and some automated. This analysis helps us to understand how we interact with our customers, how knowledgeable and helpful our agents are, and whether we deliver a great customer experience.

So what metrics are applicable when we analyse bot performance?

Well, these seem to be more complicated than human performance analysis and very few of the companies that have embraced chatbots are doing any performance analysis against their bots. But there are a number of different metrics that apply to chatbots. The user metrics include:

• Total users: This captures the number of people using the chatbot.
• Engaged users: This captures the number of users that actively communicate with the chatbot.
• User sentiment: Like human metrics, this is captured by performing sentiment analysis so that you can categorise messages as positive, neutral or negative, enabling you to gain insights into the user experience and where and when the conversation potentially went wrong.

There are also message metrics. These metrics enable understanding of how individuals interact with your chatbots. These include:

• Conversation start messages: This is the number of messages sent by a user before the bot starts the interaction.
• Bot messages: This is the total number of messages sent by the chatbot in each interaction. This measures the length of a conversation between a customer and the chatbot.
• Missed messages: This is the number of messages a bot doesn’t understand.

Then there are bot metrics. It could be said that these are the most important in understanding the real performance of a chatbot. These measure retention rates, where your customers remain engaged with the bot, completion rates, confusion rates, where the bot doesn’t understand the conversation, and the human takeover rate, where the bot needs to pass the contact to a human agent.

So, while the world is going through some significant changes, businesses are struggling with the balancing act of optimising and automating their processes, maintaining great customer experience, and motivating their staff and making them feel valued.

Given time, chatbots will become smarter and more conversational, and will use AI and deep learning. They will set about replacing human agents on some interactions and will become far more useful. They will also replace assets such as FAQ pages and knowledge-base solutions and, as a result, they will lead a lot of users towards messaging solutions, whether chat or speech based. But, for now, chatbots remain queue management solutions, where they simply greet a caller before the call is passed to a human agent, who has greater ability and understanding, to deal with the task.