Customer Service

6 ways to scale customer service [Part 1]

6 ways to scale customer service [Part 1]
Customer Service Researcher
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6 ways to scale customer service [Part 1]

We're not the first to write about the challenges of fast-growing companies.

But, there's little out there written specifically for support teams.

For this article, we've listened to podcasts, downloaded eBooks, and even interviewed experts from companies like Gousto, Loom, Miro and Get Your Guide to understand the challenges faced by, and solutions for, the scaling support team.

We've found that the fundamental challenges are the same across industries verticals and product horizontals.

However, the experience of scaling up is never equal. There are too many variations of existing talent, expertise, culture, global events, and industry trends for the everything to be the same across the board.

For example, Loom, the video messaging company, saw an overnight 6x in ticket volume at the beginning of the pandemic. Miro, the web whiteboard company, saw 7x.

This overnight 'hypergrowth' is unusual. The pandemic was unpredictable and accelerated the need for both of their products globally.

The luckier support team has a little more time to prepare. Their growth trajectories being fast, but predictable.

Regardless of scenario, support volume will increase linearly or exponential in line with customer growth, leading to increase resource expenditure and long ticket queues.

We've found that three core questions arise for the support team in this situation.

Three challenges facing the scaling support team

1. How can we maintain customer experience and satisfaction?

As customers are left frustrated and waiting, your customer satisfaction scores are likely to dive. For example, Loom's CSAT score dropped 10% when they were unable to manage their 6x rise in ticket volume (credit to Susana and the Loom support team for regaining that 10% quickly).

As a brand, you make a promise (formal through SLAs and informal through brand) to new and existing customers. Part of that promise is that both responses and resolutions will be timely—or else you're likely to receive negative word of mouth and lose customer loyalty.

2. How can we remain cost-effective as we handle new high ticket volume?

Rising ticket volume will force you to implement changes and spend resources (we’ll take a look at how companies can respond later, but any response requires investment).

New employees (salaries + overheads) tend to be the most expensive method of tackling new demand, so it must be considered against alternative solutions.

Fast-growth companies will want to look for ways to reduce ticket volume by investing in systems like better self-serve, AI-based automated tagging, and productivity tools.

3. How can customer service continue to support the wider growth of the business?

As a company grows, it needs to continuously innovate and improve products and operations to capture market share and create customer loyalty.

In the early stages of any company, customer service plays an important role in this need to innovate.

However, as you scale, access to support insights can vanish. No longer can your agents pop their head around the door and explain why customers are complaining today.

Most companies we talked to turn to manual or keyword-based ticket tagging to categorise tickets at a generic level, then relying on manual analytics efforts to uncover insights that are a sharable standard.

These methods are inadequate for a scaling company. A fast-growth company intent on staying innovative needs granular, actionable support ticket insights at its fingertips, otherwise the support-product-operations feedback loop breaks down (we'll dig into this later in the article).

Support leaders must act fast to understand what's driving customer contact, friction and negative experiences, and help the rest of the business leverage that insight to drive loyalty, lifetime value, and conversion rates.

Six solution areas to help you scale customer service

So, how does a scaling support team maintain CSAT, stay cost-effective, and continue to contribute to company growth?

Let's take a closer look at how support leaders are solving those problems (before looking at where AI can underpin these strategies).

1. Hiring more employees

Depending on your growth rate, hiring may need to happen fast and frequently. You’ll need to forecast demand and calculate the number of agents needed to deliver a great customer service experience.

As a leader in a team that's scaling, you need to think proactively about what skill gaps you have in the team and whether there's time to train existing agents or you need to take on experienced hires.

Fresh talent, like graduates, is cheaper. But they don’t hit the ground running and will require active training and coaching. More experienced hires who have 'been there, done that' can make all the difference to your peace of mind as you scale.

Hiring is the most expensive choice available for 'queue crushing', so looking into automation and deflection solutions first a cost-effective approach.

Read more: How AI in customer service helps fast-growing companies scale.

2. Developing a strong culture to improve efficiency

Your team culture is a large part of your success. How motivated and independent each team member (critical to scaling quickly) is defined by how you pull together in busy periods, cooperate and share knowledge, and embed new employees into the team.

Onboarding is a great opportunity to maintain culture. In a recent interview with Charlotte Spain from Buzzbike, she told us about how they create a customer-obsessed culture thanks, in part, to onboarding.

When new hires are onboarded at Buzzbike, they spend time understanding the vision of the department and the principles and values by which customer service is done at Buzzbike.  

Not only does clarity from the beginning embed new hires into your culture, but with boundaries set you can trust every employee to make decisions by themselves. Trust is important as you grow fast because you as a leader can't be everywhere at once.

Sam Hurley said that in a scaling company, agents must have some freedom to make their own decisions “If our support staff have the freedom to make their own decisions, give away freebies and do whatever it takes to make the customer happy, that means less worry for them and increased productivity for the entire business.”

3. Investing in agent productivity

Fast-growing companies really 'crack the code' when they can grow without a substantial increase in costs.

Investing in agent productivity is the first part of that puzzle.

As ticket volume increases, you have to start asking, 'how can I give agents more time to handle more tickets?' or 'how can agents handle more tickets?'

By automating repeatable tasks and simplifying more complex tasks like analytics, you can save hours each month.

For example, by replacing manual tagging across 10,000 support tickets you could save 42 hours of total time each month. That’s a whole week of an agent’s time! (Check out our calculations here).

4. Ticket reduction via improvement projects and deflection (self-serve, knowledge-base, one-to-many)

Looking beyond productivity, ticket reduction can be achieved by other means like deflection and CX improvements.

Every customer interaction is an opportunity to learn, improve internal products and processes and build relationships with customers. So blindly reducing ticket volume isn’t a smart move.

Three techniques for reducing ticket volume as you scale are:

1/ Investing in your knowledge base

Often five or so high-level issues explain the majority of why customers contact customer service

For example, in eCommerce, delivery, payments and refund queries might make up 50% of ticket volume.

Whenever there's repetition, there's potential for automation.

As an example, lets say 5% of tickets are asking ‘how do I change my password?’

When the solution is the same every time (or most of the time) and the volume is significant, you know it’s time to write a mini ‘how-to’ article to answer that query.

Another option is to prepare a library of template responses to help agents reply faster, too.

We'll look into how AI can help with these later on.

2/ Add a user community where clients can answer each other's questions

User communities are a powerful asset for reducing support volume. As you scale and are feeling the stretch, a customer area to ask questions and learn from each other is vital.

For inspiration, check out Webflow’s helpful community.

3/ Develop a product-operations-support feedback loop

Scale customer support with product feedback loop

Frontline, customer-facing teams understand better than anyone the friction customers are experiencing.

Support conversations, in particular, hold high-quality insight: each conversation is fast, frequent, rich with information, and delivered at the moment the issue happened.

As quickly as possible, the scaling company will want to invest in methods to extract insight from support conversation and get them used company-wide.

When product and operations teams have clarity on which issues are driving customer contact, they'll start new projects and start fixing those issues at the root cause.

Over time, the support insight feedback loop will not only reduce support volume but it'll contribute to retention and loyalty.

We look into the 'how' in greater depth in our article in AI in customer service here.

5. Outsourcing customer service to help you scale

Outsourcing customer service isn't for everyone. But, it is one solution to flexibly managing new support demand.

We interviewed Roman Siepelmeyer, an outsourcing expert currently leading operational excellence at the rapidly growing (like really, they raised $484m from Softbank Vision Fund).

Roman says that outsourcing is an option everyone should consider, and it can be better for customer satisfaction.

To give you a brief preview, support outsourcing companies are flexible with your demand, have specialised expertise in-house, and manage all your training needs. If you're unsure of future demand, the well-chosen outsourcing partner can manage it all regardless of fluctuations.

Catch the full interview here (added when available).

6. Invest in support operations early to help you scale

A final solution to the challenges of a scaling company is investing in support operations.

Support operations underpin everything you do as a team.

We interviewed Oleg Krasnov, Head of Support Excellence at Miro for insight into support operations as you scale.

Oleg led the customer support team at Miro as they scaled from 100 to 900 employees and at one point experienced more than 7x ticket volume growth in three weeks.

His advice for scaling companies was to invest in support operations earlier than you expect.

He suggests that as your team gets to around 10 employees, you need to start thinking about operations.

Support operations include:

• Developing onboarding programs.

• Developing an automation and efficiency technology stack.

• Hiring dedicated support operations employees to lead new improvement projects.

• Ensuring you understand why customers are contacting you.

• Investing in methods to extract support insights so they can feed the overall company/ product development process.

Bringing it all together

These six solutions cover the bases of scaling up a customer support function.

In part two, we take a look at how AI technology can help customer service teams scale.

Intelligent technology has the power to both improve customer satisfaction and reduce company costs as you scale up, it's win-win. Click the link above to learn what AI could do for you.

Join a community of 2139+ customer-focused professionals and receive bi-weekly articles, podcasts, webinars, and more!

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Customer Service

6 ways to scale customer service [Part 1]

Ben Goodey
Customer Service Researcher
In this article
Understand your customer’s problems and get actionable insights
See pricing

Is your AI accurate, or am I getting sold snake oil?

The accuracy of every NLP software depends on the context. Some industries and organisations have very complex issues, some are easier to understand.

Our technology surfaces more granular insights and is very accurate compared to (1) customer service agents, (2) built-in keyword tagging tools, (3) other providers who use more generic AI models or ask you to build a taxonomy yourself.

We build you a customised taxonomy and maintain it continuously with the help of our dedicated data scientists. That means the accuracy of your tags are not dependent on the work you put in.

Either way, we recommend you start a free trial. Included in the trial is historical analysis of your data—more than enough for you to prove it works.

We're not the first to write about the challenges of fast-growing companies.

But, there's little out there written specifically for support teams.

For this article, we've listened to podcasts, downloaded eBooks, and even interviewed experts from companies like Gousto, Loom, Miro and Get Your Guide to understand the challenges faced by, and solutions for, the scaling support team.

We've found that the fundamental challenges are the same across industries verticals and product horizontals.

However, the experience of scaling up is never equal. There are too many variations of existing talent, expertise, culture, global events, and industry trends for the everything to be the same across the board.

For example, Loom, the video messaging company, saw an overnight 6x in ticket volume at the beginning of the pandemic. Miro, the web whiteboard company, saw 7x.

This overnight 'hypergrowth' is unusual. The pandemic was unpredictable and accelerated the need for both of their products globally.

The luckier support team has a little more time to prepare. Their growth trajectories being fast, but predictable.

Regardless of scenario, support volume will increase linearly or exponential in line with customer growth, leading to increase resource expenditure and long ticket queues.

We've found that three core questions arise for the support team in this situation.

Three challenges facing the scaling support team

1. How can we maintain customer experience and satisfaction?

As customers are left frustrated and waiting, your customer satisfaction scores are likely to dive. For example, Loom's CSAT score dropped 10% when they were unable to manage their 6x rise in ticket volume (credit to Susana and the Loom support team for regaining that 10% quickly).

As a brand, you make a promise (formal through SLAs and informal through brand) to new and existing customers. Part of that promise is that both responses and resolutions will be timely—or else you're likely to receive negative word of mouth and lose customer loyalty.

2. How can we remain cost-effective as we handle new high ticket volume?

Rising ticket volume will force you to implement changes and spend resources (we’ll take a look at how companies can respond later, but any response requires investment).

New employees (salaries + overheads) tend to be the most expensive method of tackling new demand, so it must be considered against alternative solutions.

Fast-growth companies will want to look for ways to reduce ticket volume by investing in systems like better self-serve, AI-based automated tagging, and productivity tools.

3. How can customer service continue to support the wider growth of the business?

As a company grows, it needs to continuously innovate and improve products and operations to capture market share and create customer loyalty.

In the early stages of any company, customer service plays an important role in this need to innovate.

However, as you scale, access to support insights can vanish. No longer can your agents pop their head around the door and explain why customers are complaining today.

Most companies we talked to turn to manual or keyword-based ticket tagging to categorise tickets at a generic level, then relying on manual analytics efforts to uncover insights that are a sharable standard.

These methods are inadequate for a scaling company. A fast-growth company intent on staying innovative needs granular, actionable support ticket insights at its fingertips, otherwise the support-product-operations feedback loop breaks down (we'll dig into this later in the article).

Support leaders must act fast to understand what's driving customer contact, friction and negative experiences, and help the rest of the business leverage that insight to drive loyalty, lifetime value, and conversion rates.

Six solution areas to help you scale customer service

So, how does a scaling support team maintain CSAT, stay cost-effective, and continue to contribute to company growth?

Let's take a closer look at how support leaders are solving those problems (before looking at where AI can underpin these strategies).

1. Hiring more employees

Depending on your growth rate, hiring may need to happen fast and frequently. You’ll need to forecast demand and calculate the number of agents needed to deliver a great customer service experience.

As a leader in a team that's scaling, you need to think proactively about what skill gaps you have in the team and whether there's time to train existing agents or you need to take on experienced hires.

Fresh talent, like graduates, is cheaper. But they don’t hit the ground running and will require active training and coaching. More experienced hires who have 'been there, done that' can make all the difference to your peace of mind as you scale.

Hiring is the most expensive choice available for 'queue crushing', so looking into automation and deflection solutions first a cost-effective approach.

Read more: How AI in customer service helps fast-growing companies scale.

2. Developing a strong culture to improve efficiency

Your team culture is a large part of your success. How motivated and independent each team member (critical to scaling quickly) is defined by how you pull together in busy periods, cooperate and share knowledge, and embed new employees into the team.

Onboarding is a great opportunity to maintain culture. In a recent interview with Charlotte Spain from Buzzbike, she told us about how they create a customer-obsessed culture thanks, in part, to onboarding.

When new hires are onboarded at Buzzbike, they spend time understanding the vision of the department and the principles and values by which customer service is done at Buzzbike.  

Not only does clarity from the beginning embed new hires into your culture, but with boundaries set you can trust every employee to make decisions by themselves. Trust is important as you grow fast because you as a leader can't be everywhere at once.

Sam Hurley said that in a scaling company, agents must have some freedom to make their own decisions “If our support staff have the freedom to make their own decisions, give away freebies and do whatever it takes to make the customer happy, that means less worry for them and increased productivity for the entire business.”

3. Investing in agent productivity

Fast-growing companies really 'crack the code' when they can grow without a substantial increase in costs.

Investing in agent productivity is the first part of that puzzle.

As ticket volume increases, you have to start asking, 'how can I give agents more time to handle more tickets?' or 'how can agents handle more tickets?'

By automating repeatable tasks and simplifying more complex tasks like analytics, you can save hours each month.

For example, by replacing manual tagging across 10,000 support tickets you could save 42 hours of total time each month. That’s a whole week of an agent’s time! (Check out our calculations here).

4. Ticket reduction via improvement projects and deflection (self-serve, knowledge-base, one-to-many)

Looking beyond productivity, ticket reduction can be achieved by other means like deflection and CX improvements.

Every customer interaction is an opportunity to learn, improve internal products and processes and build relationships with customers. So blindly reducing ticket volume isn’t a smart move.

Three techniques for reducing ticket volume as you scale are:

1/ Investing in your knowledge base

Often five or so high-level issues explain the majority of why customers contact customer service

For example, in eCommerce, delivery, payments and refund queries might make up 50% of ticket volume.

Whenever there's repetition, there's potential for automation.

As an example, lets say 5% of tickets are asking ‘how do I change my password?’

When the solution is the same every time (or most of the time) and the volume is significant, you know it’s time to write a mini ‘how-to’ article to answer that query.

Another option is to prepare a library of template responses to help agents reply faster, too.

We'll look into how AI can help with these later on.

2/ Add a user community where clients can answer each other's questions

User communities are a powerful asset for reducing support volume. As you scale and are feeling the stretch, a customer area to ask questions and learn from each other is vital.

For inspiration, check out Webflow’s helpful community.

3/ Develop a product-operations-support feedback loop

Scale customer support with product feedback loop

Frontline, customer-facing teams understand better than anyone the friction customers are experiencing.

Support conversations, in particular, hold high-quality insight: each conversation is fast, frequent, rich with information, and delivered at the moment the issue happened.

As quickly as possible, the scaling company will want to invest in methods to extract insight from support conversation and get them used company-wide.

When product and operations teams have clarity on which issues are driving customer contact, they'll start new projects and start fixing those issues at the root cause.

Over time, the support insight feedback loop will not only reduce support volume but it'll contribute to retention and loyalty.

We look into the 'how' in greater depth in our article in AI in customer service here.

5. Outsourcing customer service to help you scale

Outsourcing customer service isn't for everyone. But, it is one solution to flexibly managing new support demand.

We interviewed Roman Siepelmeyer, an outsourcing expert currently leading operational excellence at the rapidly growing (like really, they raised $484m from Softbank Vision Fund).

Roman says that outsourcing is an option everyone should consider, and it can be better for customer satisfaction.

To give you a brief preview, support outsourcing companies are flexible with your demand, have specialised expertise in-house, and manage all your training needs. If you're unsure of future demand, the well-chosen outsourcing partner can manage it all regardless of fluctuations.

Catch the full interview here (added when available).

6. Invest in support operations early to help you scale

A final solution to the challenges of a scaling company is investing in support operations.

Support operations underpin everything you do as a team.

We interviewed Oleg Krasnov, Head of Support Excellence at Miro for insight into support operations as you scale.

Oleg led the customer support team at Miro as they scaled from 100 to 900 employees and at one point experienced more than 7x ticket volume growth in three weeks.

His advice for scaling companies was to invest in support operations earlier than you expect.

He suggests that as your team gets to around 10 employees, you need to start thinking about operations.

Support operations include:

• Developing onboarding programs.

• Developing an automation and efficiency technology stack.

• Hiring dedicated support operations employees to lead new improvement projects.

• Ensuring you understand why customers are contacting you.

• Investing in methods to extract support insights so they can feed the overall company/ product development process.

Bringing it all together

These six solutions cover the bases of scaling up a customer support function.

In part two, we take a look at how AI technology can help customer service teams scale.

Intelligent technology has the power to both improve customer satisfaction and reduce company costs as you scale up, it's win-win. Click the link above to learn what AI could do for you.

Frequently asked questions

Is your AI accurate, or am I getting sold snake oil?

The accuracy of every NLP software depends on the context. Some industries and organisations have very complex issues, some are easier to understand.

Our technology surfaces more granular insights and is very accurate compared to (1) customer service agents, (2) built-in keyword tagging tools, (3) other providers who use more generic AI models or ask you to build a taxonomy yourself.

We build you a customised taxonomy and maintain it continuously with the help of our dedicated data scientists. That means the accuracy of your tags are not dependent on the work you put in.

Either way, we recommend you start a free trial. Included in the trial is historical analysis of your data—more than enough for you to prove it works.

Do you integrate with my systems? How long is that going to take?

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What size company do you usually work with? Is this valuable for me?

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What is your term of the contract?

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How do you keep my data private?

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