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Striving toward Profitability: Best Practices for Sustainable CX Growth in a Downturn

Achkan Chavoushi

With unpredictable economic times ahead, it’s more important than ever for CX teams to demonstrate their value. As CFOs come under increasing pressure, CX teams — traditionally thought of as a cost center — face a real risk of budget freezes or cutbacks. 

With the right tools and strategies in place, CX has the potential to become a key growth enabler and revenue driver in any B2C business. Truly proactive CX teams have the capability to increase customer lifetime value, minimize churn, and inform mission-critical product or service improvements — all directly impacting the bottom line. 

But if you can’t demonstrate that ROI in black and white, you still have a problem. The issue that many CX teams face is that they don’t have access to tangible data that shows where they are adding value. 

So there are two important questions for CX teams. 

  • How can we clearly demonstrate the ROI we’re providing right now?
  • What can we do to improve that percentage moving forwards?

With those answered, you can make an informed decision on whether you need to restructure your team, rethink your processes, or rebalance investment in people versus technology. And you can put a dollar figure on everything you’re doing when reporting up the chain.

Here’s how — in 5 steps.

Precap: In this 10-minute read you’ll learn how to:

  • Turn customer conversations into actionable insights
  • Use those insights to map costs by activity
  • Identify where technology or new processes can help
  • Leverage insights to predict future needs
  • Make data-driven decisions on where to invest for the best ROI

01 - Turn customer conversations into actionable insights 

Unlocking the information in CX data is the first step for any organization looking to figure out where they’re spending the most. While CX teams are good at generating large amounts of qualitative data, they’re not always great at analyzing it in quantitative terms. 

Therefore, most of that data is unusable — you can’t draw any conclusions or plan actions with it. Essentially, unless you make a change, the more data you collect is just adding to the chaos. You need a better way of navigating your data to introduce some clarity.

Demographic tagging

Start by performing an in-depth analysis of your customer data. Tag records based on the demographic characteristics available to you — age range, gender, location, household income, preferred communications channels, and so on. 

Now you can segment your customer list in a range of ways, looking for common patterns or behaviors based on specific demographic information. The more detailed conclusions you can draw, the more you’ll be able to provide a personalized experience to each customer. This is crucial to reducing the volume and incidence — and therefore cost — of incoming support requests.

Lifecycle tagging

Next, categorize your customers according to where they are in the CX lifecycle — e.g., new, active, or lapsed. Support needs will vary at each stage of the customer journey — and if you can map where each of your customers currently is, you can make proactive interventions to reduce inbound tickets later. 

Ticket tagging

Having uncovered more details about who your customers are, and where they are in the life cycle, it’s time to look at how they interact with you. That means reviewing your historical support tickets to identify recurring patterns, themes, or issues and tagging or categorizing them so they can be analyzed and reported on. 

02 - Use those insights to map costs by activity

Now you have quantitative data on every customer interaction and you can see the picture more clearly — what types of requests take the most agent hours, which customer profiles require the most support, etc.  

This will help you to identify any underlying issues in the customer journey and be able to act on them. Having a clearer vision of customer interactions than ever before equips you to understand and prioritize issues at a macro level. 

You should also analyze any daily, weekly, monthly, or seasonal variations to find out where the bottlenecks are. You can then redirect agent resources to manage periods of peak demand — reducing waste — as well as introduce proactive strategies to minimize support requests at these times. 

Here are some examples of how this works.

For example, you may find that the highest number of tickets related to login issues come from new customers — suggesting that you need to proactively send out clearer instructions on how to log in following the sign-up process. If that works — you can prove a cost saving. 

Or, if you receive a high volume of WISMO inquiries every Monday morning, as customers come back online after the weekend, you could mitigate this by sending an automated order update summary to any customer with an outstanding delivery every Sunday evening — another potential saving. 

Now that you have a clear vision of what customers are actually saying, thinking, and doing — and you’ve mapped out your priorities for dealing with them, it’s time to see how you can make this process easier.

03 - Identify where technology or process changes can help reduce costs

You now have a lot more qualitative data, and you can break down the cost of supporting different customer segments. But tagging all your future inbound tickets and other data manually can present a significant resource challenge (and it’s going to push your costs back up). 

Automated tagging

Look at using automated tools to tag and categorize customer data — whether that’s the content of the tickets themselves, or associated service feedback. This can vastly reduce the cost of processing this data, and increase the speed and accuracy with which you can get your data triaged and separated into logical categories.

Automated replies

That’s just the first step. You can also use chatbots or AI solutions (like to proactively deal with a proportion of these issues — responding to common customer inquiries 24/7 and virtually instantly. Simple issues like order updates, basic queries, or requests for documentation no longer need to touch a human agent, which reduces support overheads significantly. 

Specialized agents

If the AI can’t deal with them it can escalate them directly to an agent who can. 

That in turn allows your agents to specialize. Instead of the whole team scrabbling to cope with an overflowing inbox, each picking one off the stack after another, many of the simple tickets have already been resolved automatically. 

The tickets that remain are intelligently routed to the agent best placed to deal with them — so each team member is dealing with 2 or 3 types of issue or process, instead of 15 or 20 — helping them work far more efficiently — and leading to faster response times and higher CSAT. 

04 - Leverage insights to predict future needs

Implementing advanced analytics tools also allows you to more accurately analyze customer data and identify patterns that can predict future behavior. For example — targeting high-spend customers with well-timed upselling opportunities, or intervening before a lapsed user becomes a lost customer. 

These types of intervention can actively generate revenue, or prevent major losses — which you can factor into your ROI calculations. Communicating these results up the chain is vital to demonstrate your value as a business unit and, importantly for some — your impact on the bottom line. 

You should regularly be reporting on key metrics such as the number of tickets deflected, agent hours saved, or churn rate reduced — each with a dollar value attached to underline the contribution CX is making to overall company finances.

And with these tools in place, you can also predict support needs at a granular level — forecasting the potential issues faced by each demographic, segment, or channel. This makes it easier for CX leadership to assign resources in advance, avoid bottlenecks or overload, and pinpoint specific groups that may require additional attention or tailored support solutions. 

The more relevant information you can equip customers with, the less they’ll need to reach out to you for support. Depending on your specific industry and your customer demographics, you can create FAQ pages, how-to articles, searchable knowledge bases, or video content to guide customers in solving common issues themselves. 

As part of your continual analysis of customer feedback and support usage data, you should review, adapt and update your support resources regularly, to ensure they are meeting current customer needs. 

These insights aren’t just a value-add for the CX team — they have a wider impact across the whole business. Predicting customer needs and behavior accurately is a holy grail for accounts, ops, product, and marketing teams. 

And providing those teams with that actionable information is how you transform your CX function to become a proactive insight generator and strategy builder for the whole organization. That gives you a solid platform when you’re seeking further investment — now let’s look at where that investment should go.

05 - Make data-driven decisions on where to invest for the best ROI

The insights you’ve gained from your data have revealed where further investment in technology can deliver greater ROI. They should also help you avoid the trap of pinballing from overstaffed to understaffed on a seasonal basis, now that you can predict support volumes accurately. 

But you can’t automate everything — you’re always going to need people. What you need to do is find the right balance. Invest in tech to solve problems that agents can’t handle quickly or efficiently enough, and then invest in developing your people to provide the human touch — acting as the face of the company, dealing with complex issues, and ensuring customers feel heard. 

Investment in technology

To make a convincing case for investment in CX technology, especially during tough economic times, it’s important to demonstrate the ROI uplift by considering factors such as reduced ticket volume, improved customer satisfaction, and potential revenue growth. Once you’ve followed the steps above, you should have the figures to make that argument.

But if you’d like to get a quick forecast of the potential savings that you could achieve based on your own headcount and overheads, we’ve designed a simple ROI calculator that you can use. 

Just head to the link below and grab a copy of the Google Sheet, then tweak the values in the yellow cells to fit the model to your individual circumstances — and see where you could make substantial savings. ROI Calculator

Investment in employee development and training

As you implement new technological solutions to improve the efficiency of your support function, it’s important to develop and train your human agents to take advantage of the new possibilities available. 

In a reactive support model where you’re unable to accurately predict incoming issues, every agent has to be a generalist, able to step in and firefight the full range of potential customer issues. Now that you’ve moved to a proactive, predictive model, you can afford to develop your agents as specialists, creating new roles and responsibilities in line with the process improvements you’ve put in place. 

For example, you can assign specific agents or teams to deal with lapsed or disengaged customers, onboard new customers, handle technical versus service issues, and so on. And, with the increasing use of automation and AI, you’ll need specialists in using those tools, interpreting the reports and visualizations they generate, and training the models to improve over time. 

Where to go next

Following the steps we’ve laid out in this guide will transform your CX team from a reactive, customer-led cost center, to a proactive, predictive revenue driver — and most importantly you’ll be able to demonstrate that you’re contributing to growth and profitability — whatever the prevailing economic climate may be. 

For a clearer idea of what stage your CX team is at right now, and where you can make impactful improvements, check out our CX Operations Maturity Model which outlines what reactive, proactive, and predictive teams look like in practice. 

And once you’ve done that — whether you’re just getting started, or you already have some of these initiatives in place — feel free to book a session with one of our CX consultants for practical advice on the tools and strategies you can use to develop towards a truly predictive model. No strings attached :) 

Book your slot here.   

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