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Creating a Culture of Self Evaluation and Improvement to Deliver Better Customer and Business Outcomes in the Call Centre

For example, companies with high levels of employee engagement improved by 19.2% in operating income while companies with low levels of employee engagement declined by 32.7% over the study period – a delta of almost 52%! Similarly, engaged employees take less than half the number of sick days, an average of 2.69 per year – compared to 6.12 for the disengaged. The impact on service levels of this difference alone could be transformational.

The impact on call centre performance of engagement becomes even more important when you consider that engaged employees are 87% less likely to leave the organisation than the disengaged – providing a more stable team. Furthermore, 78% of engaged employees would recommend their company’s products or services, against 13% of the disengaged – meaning you have advocates answering the phone and responding to other customer interactions. But, perhaps most importantly, 70% of engaged employees indicate they have a good understanding of how to meet customer needs; only 17% of non-engaged employees say the same.

This Paper looks at how a combination of the insight provided by Interaction Analytics and smart coaching (ie coaching that is informed by accurate agent performance data) can feed the psychology of competence and create a culture of self-evaluation and improvement to enhance agent, call centre and business performance.

Work carried out to identify the psychology behind learning and competence can be very helpful to call centres in understanding how to trigger the right agent behaviour.

The individual does not understand or know how to do something and does not necessarily recognize the deficit. The individual must recognize their own incompetence, and the value of the new skill, before moving on to the next stage.

Though the individual does not understand or know how to do something, he or she does recognise the deficit, as well as the value of a new skill in addressing the deficit.

The individual understands or knows how to do something. However, demonstrating the skill or knowledge requires concentration. It may be broken down into steps, and there is heavy conscious involvement in executing the new skill.

The individual has had so much practice with a skill that it has become “second nature” and can be performed easily. As a result, the skill can be performed while executing another task. The individual may be able to teach it to others, depending upon how and when it was learned.

1. Introduction

2. The Psychology of creating high performing agents

2.1 There are four stages of competence:

a. Unconscious incompetence

b. Conscious incompetence

c. Conscious competence

d. Unconscious competence

Because the behaviour of call centre agents is so pivotal to the customer experience, and therefore customer satisfaction, it is vital that they are engaged and that they understand the impact their behaviour has on the customer experience. A Report from KPMG, entitled ’The real value of engaged employees’ highlights the huge gulf between the value delivered by employees who are engaged and those who are not.

A 360-degree scorecard can dramatically improve agent performance by:

Interaction Analytics is incredibly helpful in triggering the desire to become more competent. It does this by providing the proof an agent needs to recognise an area of weakness. Agents can identify where they need to improve by reviewing their personal scorecard of their performance for the last shift. This scorecard shows how they performed against a number of key performance indicators (KPIs). Agents know that they can trust in this data because they know it is based on 100% of their interactions. As a result it reduces the opportunity for inaccurate or unfair evaluations by a supervisor. This has a very different psychological impact than when an agent is told by a supervisor that he/she is underperforming based on listening to a random selection of calls.

Allowing supervisors to self-select and self-score immediately

Limited opportunity for self-development

Providing alternative viewpoints

Removing the “bad cop” stigma for coaches

Lack of ability to target coaching where it is needed most

Increasing credibility

No incentives and limited opportunity for income growth. Even if incentives exist, an agent may not feel they are achievable if he/she doesn’t have the skills required to achieve them.

Highlighting blind spots

Encouraging self-improvement and change

Scorecards

Another CallMiner white paper entitled: Understanding How Interaction Analytics Can Reduce Agent Attrition identifies the main causes of agent attrition. At least four out of the top seven can be addressed by Interaction Analytics and smart coaching to create unconsciously competent agents who are motivated to stay loyal. These are:

2.2 How Interaction Analytics and smart coaching fosters ‘unconscious competence’

Inaccurate and unfair evaluations

Interaction Analytics help you to capture and analyse 100% of customer interactions such as calls, SMS, chat, Twitter etc. This gives the call centre manager, supervisor and agent a complete picture of the entire customer contact journey not just the latest episode.

But which data do you need to take informed decisions about when to coach, and what to coach, so you can delight your customers? The answer is all the data from all the systems that impact on the customer experience, that measure the customer experience and, that provide customer and agent insight. Having access to ALL the data enables you to identify both the sources of churn and best practice contact behaviour – and thus drive both agent and process improvement. No more guesswork, just informed and targeted action.

The data sources include:

Rich contact metadata (agent, group, line of business, customer identifier, IVR path, etc.) provides you greater ability to analyse conversation data. Metadata is used to filter your searches and data visualisations, target categories and scores to certain conversation sets, compare and correlate various metrics, and identify root causes of various issues.

For example, metadata allows you to identify if the way calls are routed is creating customer dissatisfaction. Without this data an agent may be scored incorrectly because the customer arrives angry rather than because the agent has performed badly. It also means that a supervisor may think there is a training need for an under-performing agent when the root cause is a weakness in the call routing.

If the root cause is related to agent behaviour it is possible to highlight this in a personalised agent scorecard. This will help the agent to know where and what to improve. It will help the coach know how to support the agent with targeted personal coaching and development.

3. The data required to give agents the tools they need to become more competent and to drive customer delight

Metadata from related systems

Once an agent knows where they need to improve, he/she will need help to understand what they need to do to improve. This is where smart coaching is invaluable. It provides the knowledge and guidance the agent needs to fill the gap in their skills. This can be reinforced on a daily basis through the insight provided by the personal scorecard and daily discussions with the supervisor or coach to reinforce the improvements that have been made.

The personal scorecard also makes it possible for an agent to be reminded of the need to improve in certain areas. For example, before a shift starts, an agent may decide to focus on improving empathy and then measure their own improvement by reviewing their scorecard at the end of the shift. This is a good example for self-evaluation and improvement in action.

If an agent starts to revert to previous behaviour, automated alerts during an interaction with a customer, triggered by the Interaction Analytics platform, can be invaluable in reminding the agent about the correct method to be followed. Because the supervisor/coach can see the alerts too, it is possible to interject in a helpful way or to have a brief discussion after the call to reinforce the right approach. This kind of targeted coaching helps to build confidence and belief and to reinforce the right behaviour until it becomes a habit.

Unconscious competence – where a skill has become second nature - is the outcome of using Interaction Analytics and smart coaching. It produces agents that are high performers who can be used as best practice examples to help the rest of the team develop. The insight provided by the personal scorecard will help to identify these high performers. It will also help to improve overall call centre performance. For example, by identifying which agents are best at problem resolution or collections, calls can be automatically routed to them to meet very specific customer needs. Ultimately, the combination of Interaction Analytics and smart coaching produces agents that focus on delivering positive customer outcomes from every interaction. The impact on customer satisfaction, loyalty and advocacy can be transformational.

In the customer example mentioned above, automatic tagging for behaviour, reasons, products and competitors would have surfaced the emerging trend from the competitor’s campaign. Armed with this insight, and coached how to use it, the agents were able to ensure the first interactions delivered the right result for the customer and the company.

Tagging can be based on previous root cause analysis. It enables you to tag both positive and negative words and phrases at each step on the interaction Journey. The diagram below brings this to life. As you can see you can tag for everything from a proper greeting to churn or payment language, dissatisfaction, empathy and the end of the call. The call represented in the diagram opens well and finishes badly with ‘You people are useless’

Tagging data from the transcripts.

Reasons - the reason for the contact, in voice often referred to as the call driver. For example, you may call your bank for a balance inquiry, and as a follow up you may conduct a transfer – each of these would be reasons for the call.

Sentiments - what sentiments are contained in the interactions for both the agent and the customer? Does the agent respond appropriately to different customer sentiments?

Outcomes - measuring the response to specific actions. For example, how did a customer respond to an upsell offer?

Competitors - are certain competitors mentioned?

Procedures - are agents complying with procedures and adhering to scripts? Commonly used in collections to ensure agents are staying compliant with regulations.

Products - are certain products mentioned?

Behaviours - how are agents or customer behaving? For example, are they expressing dissatisfaction, and is there an empathetic response to that dissatisfaction?

Converting all interactions (including calls, chat, SMS etc.) to text, also allows you to carry out thorough root cause analysis and identify agent behaviour that drives delight or dissatisfaction. It also enables you to score or rank agent performance against key call and satisfaction criteria.

Because you are analysing all the data, all the time, it’s simple to set up the system to be sensitive to, and highlight, any new trends in the data that might represent the start of a new issue.

For example, one of our customers identified - within one shift - that a competitor had launched a campaign to encourage people to switch. This allowed them to come up with a counter offer and coach their agents to use that offer when their customers called in to cancel their contract. The net result was not only did their customers not switch but many extended their contract. Furthermore, our customer decided to launch a very similar switching offer and acquired many new customers because their competitors did not have the same analytics in place and reacted too late to stop customers switching.

Interaction Analytics makes it possible to spot these emerging trends by setting up contact categorisation. This is the automatic tagging of contacts that contain certain language patterns, keywords, phrases, or other characteristics. Any given customer contact is likely to be tagged as belonging to several categories. Categories allow you to find, count, and trend contacts that contain these characteristics. Common types of categories include:

Transcripts from 100% of customer interactions

By capturing and analysing every interaction, it is possible to identify, words, phrases or acoustics that are indicative of a call going well or badly. It is also possible to identify if adherence to a script bypasses common sense and causes anything but customer delight.

Interaction Analytics can also help to surface some of these areas for improvement by measuring the relative emotion of phone calls with automated sentiment analysis. Sentiment analysis combines both the acoustic characteristics of a speaker’s voice and the context of the conversation into a single score, which can be used to measure relative sentiment across various cross sections of calls, agent groups, and timeframes. Sentiment analysis measures:

Automated Interaction Analytics - Explained

This is very important because it enables you to identify if key words or phrases are related to changes in the way the customer or agent are feeling or communicating – such as an increase in stress or the call becoming confrontational. It is then possible to coach the agent to identify these phrases and respond accordingly.

Acoustic from the calls

The amount of physical stress in the voice

The changes in the stress

The rate of speech

“I quite often come across call centres that force agents to adhere to scripts. This often means

a customer who has called in and not had their problem resolved is asked: ‘Is there anything

else I can help you with today?’ Unsurprisingly this lack of common sense doesn’t deliver a

successful call outcome as the customer hasn’t been helped yet!

“

“

Carolyn BluntManaging Director | Ember Real Results

Interaction Analytics can seamlessly mesh these acoustic measures with the overall context of the conversation to determine the true meaning behind the spoken words – for example, when “amazon” means the rainforest and when it means the retailer. As a result, sentiment analysis provides critical insight into rapidly growing customer product and service issues.

As delighting customers is probably the driving outcome for call centres, it is vital to provide agents and supervisors with CSAT data too. Interaction Analytics can show the impact of agent behaviour on customer satisfaction and advocacy. Matching agent behaviour to CSAT can close the loop with the customer view. Linking these together in a single scorecard can be transformational in getting agents to think about customer outcomes. It can also enable them to adapt their behaviour and receive appropriate coaching to deliver higher customer feedback scores.

Customer satisfaction or net promoter score

Providing scores for individuals and teams is essential to driving improvement. By providing scores for a range of elements that are essential to achieving the right outcome, it is possible to create an environment of continuous improvement. The chart below shows an example of how scoring can focus on key outcomes. In this case it is looking at compliance and customer satisfaction and scoring against politeness, emotion and silence.

Scoring and tracking

Automated call scoring helps you track performance trends over time and compare relative performance across different groups of contacts (such as agent groups or teams). This enables you to define performance thresholds or acceptable and unacceptable ranges for scores for key moments on the customer journey. Labelling and colouring target ranges simplifies the analysis of scores in heat maps, scorecards, or the myEureka performance portal.

Sometimes a grade, descriptive label, or colour is more telling than the underlying number value and can trigger the right action to deliver customer delight. The personalised scorecard makes it possible to measure agent performance against key qualities linked to customer delight, such as showing empathy. This enables the agent to make a personal commitment to improving empathy skills – and to delivering a successful call outcome.

It also makes it possible for the supervisor to support that commitment with helpful coaching. Real-time Interaction Analytics solutions can also provide alerts, to the agent and supervisor, during a call, if it looks like a call is going ‘off the rails’. These alerts could be triggered by a change in acoustics, or word tags that might indicate increased tension. As a result the agent can adjust behaviour to bring the call back on track.

Data - Getting the right information to coach from

Missing contacts on the complete customer journey - It is vital to have visibility of contacts at all stages of the customer journey. Without this end-to-end view it will not be possible to identify where agent improvement is required and coach accordingly. Not only will this lead to a waste of time and effort by a supervisor or coach but it will also engender a negative response by the agent who will think the coaching is not only unnecessary but unfair.

Lack of fairness - Agents who feel coaching is not based on 100% of the data will feel like they are being treated unfairly. Research into the way the brain works proves that being treated unfairly can feel like physical pain. Not only will it not get the best from your agents but it also runs the risk of creating a reputation for your call centre of acting unfairly which will damage your capability to attract the best talent.

Subjectivity - Random call sampling won’t give you the full picture. It is therefore all too easy to be subjective rather than objective and allow unconscious bias to influence your assessment of an agent’s performance. This could mean that agents who are performing well become demotivated and less engaged.

Guesswork - Guessing what to do will never be as safe as taking informed decisions based on quality data – provided the data is current and delivered in a timely fashion. Interaction Analytics removes the need for guesswork because it not only provides insight based on 100% of interactions and other related data sources but also does so in real-time or near real-time i.e. at the end of a shift.

Failing to recognise emerging trends and the opportunity for improvement - It obviously makes sense to be able to identify emerging weaknesses in agent behaviour before they become a real problem. Contact categorisation and automated scoring, will highlight areas where an agent needs help and coaching to deliver a better customer outcome.

The business risk identified in the KPMG report The Report identified a number of negative impacts of disengagement for a call centre. These include: increased agent churn; increased sick days; a negative impact on the customer experience.

Demotivation/lack of engagement - If agents feel like supervisor assessments do not reflect their real performance they will soon become demotivated and disengaged. The business and operational cost of disengagement is clearly identified by the KPMG Report discussed earlier in the paper.

“When we are asked to develop effective coaching techniques to enhance agent performance,

the first thing I ask for is sight of all the data from multiple data sources. Without data,

coaching will be based on guesswork and opinion. Neither are solid foundations for

improving performance.

“

“

Carolyn BluntManaging Director | Ember Real Results

Coaching without data, from all the relevant data sources mentioned above, brings with it a number of significant risks if you are trying to delight customers and deliver other key outcomes like compliance. Just listening to calls without cross-referencing to CSAT or NPS scores won’t tell you if the customer was happy when the call ended.

The most common risks of coaching without having access to all the data, include:

4. How the absence of the right data makes it hard for agents to take responsibility for improving their performance

Interaction Analytics and smart coaching can really enable call centre agents to ‘excel early.’ By linking excellent performance to rewards you can create a positive reinforcement loop that further increases agent engagement.

Access to shift by shift analytics provides the data a coach needs to use the praise, analyse, praise technique to reinforce agent confidence and improve performance. The in-call alerts provided by real-time Interaction Analytics also enable the coach to provide in-call support – thus ensuring a positive outcome to the call and eliminating the negative sentiments that may come from post-call correction.

Manufacturing businesses have transformed their performance, and that of the supply chain, by moving to just-in-time manufacturing. The use of Interaction Analytics and daily discussion creates a just-in-time coaching environment that will transform agent and call centre performance. The chart below shows how to get the timing right.

Compliance is a good example of how Interaction Analytics, smart coaching and gamification can work together to deliver the desired outcome – ie 100% compliance. Delivering compliance, including essential components like treating customers fairly, can be broken down into a number of critical elements, such as script adherence and empathy.

Each of these elements can be measured and a ranking produced. As a result an agent may be #1 for empathy but back in the pack for something equally important such as using compliant words or phrases. Seeing this ranking will encourage the agent to improve all elements. This commitment to improve can be reinforced by in-call alerts when it looks like the call or interaction may not be fully compliant.

Capturing and recording 100% of interactions not only means agents can trust the scores they receive (ie they are not produced subjectively by a supervisor listening to random calls) but your company can also prove compliance by having the analysis available for audit purposes.

Furthermore, desired outcomes can be reinforced by analysing metadata ingested after the customer contact has taken place. For example, CRM data showing if a sale occurred, and for what value, can be attached to the call record within Interaction Analytics to prove that the call delivered a positive outcome.

6. Just-in-time coaching

The need to focus on successful call outcomes to drive agent behaviour has been mentioned already in this paper.

From a data perspective, agent scorecards and in-call alerts can have a very positive impact on behaviour, especially if they are supported by incentivisation and gamification. Incentives can be used to hit short term goals, but if you want sustainable achievement of outcomes, you need to create an environment of self-evaluation and improvement.

Gamification is very helpful in this regard because it works by showing agents where they ranked against their colleagues (anonymously) on their last shift. This ranking can be by team, division or global. The ranking – particulalry if supported by helpful coaching – can create a personal desire to move up the rankings.

5. Using valuable outcomes supported by incentives and gamification to drive contact centre agent behaviour

Carolyn Blunt, Managing Director of Ember Real Results is a recognised expert in creating a culture of intelligent coaching and self-evaluation and improvement in call centres. By working with call centre clients around the globe, Carolyn has identified Five Golden Rules of Contact Centre Coaching. These are:

To these five rules, we add three more:

7. The Golden Rules of Contact Centre Coaching

Build agents up – don’t knock them down

Always coach based on 100% of an agent’s interactions. This removes the likelihood that an agent will find suggestions for improvement unfair

Provide agents with a personal scorecard that measures their performance and compares their performance with that of their peers. This provides the insight an agent needs to create a culture of self-awareness, evaluation and improvement and deliver better customer and business outcomes.

Use root cause analysis to identify the reasons for improvement

Regularly calibrate coaching amongst coaches to ensure consistency

If you can’t find any room for improvement say so! Make that rewarding!

Ensure coaching results in action plans that are supported and linked to performance reviews

Bring in both customer feedback and agent self-evaluation. Create a culture where the agent wants to self-select their worst calls because they know you will help them not punish them

Integrating Interaction Analytics into your coaching program

Carolyn Blunt is Managing Director of Ember Real Results, a consultancy that works with contact centres to improve performance. For the past decade Carolyn has become especially renowned for identifying opportunities to improve customer experience and sales whilst creating efficiencies. Carolyn is co-author (with Martin Hill-Wilson) of the book ‘Delivering Effective Social Customer Service’ published by Wiley. As an industry writer and speaker Carolyn was voted Most Respected Person in the UK Contact Centre Industry 2012-2014 by readers of Call Centre Helper Magazine. Carolyn is an engaging and trusted speaker for ‘Customer Contact Expo’, ‘The Forum’ and ‘Call Centre Helper’.

About Carolyn Blunt

At Ember Real Results we are in the business of delivering lasting improvement through bespoke training and coaching in a cost-effective and results focused way. We create a plan that is unique to your needs and budget that achieves measurable results and culture change in customer service. All Ember Real Results trainers are CIPD or equivalent qualified with at least five years of business experience in their subject. As experienced training professionals, we aim to inspire others to do well and achieve personal and team success. www.emberrealresults.com.

About Ember Real Results

CallMiner believes that resolution is the fundamental driver of positive customer experiences. When contact center agents and others responsible for customer engagement are empowered by insight and feedback in real-time, they can dramatically improve the rate of positive outcomes. With the tagline “Listen to Your Customers, Improve Your Business” our goal is to help companies automate the overwhelming process of extracting insight from phone calls, chats, emails and social media to dramatically improve customer service and sales, reduce the cost of service delivery, mitigate risk, and identify areas for process and product improvement. Highlighted by multiple customer achievement awards, including six Speech Technology implementation awards in the past four years, CallMiner has consistently ranked number one in customer satisfaction, including surveys conducted by DMG Consulting and Ovum. www.callminer.com.

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