Rough Economic Waters: Optimizing Customer Success Team Structures Image

Rough Economic Waters: Optimizing Customer Success Team Structures

It would be an understatement to say that the global economy is going to be unstable in 2023 and probably in 2024 as well. Navigating the storm isn’t going to be easy and B2B businesses are already trying to do more with less. But how does this fit in with your current customer success team structure? Is it built for scale? How can you keep growing despite the limitations? Let’s find out.

Structuring customer success teams well is crucial in the current business climate

Unless you have just returned from a round-trip to Mars recently, it’s pretty evident that we are now in a global recession. B2B businesses are already taking preventative measures that are directly impacting customer success team structures.

The modern customer success team structure includes the following personas:

  • VP of Customer Success – This persona essentially oversees all customer success activities within the organization, manages strategy implementation, and reports directly to the management on an ongoing basis.
  • Chief Customer Officer – As B2B companies start to scale up, this persona helps create training programs and aligns new workers with the latest policies. Needless to say, this position is now being seen as a luxury by many.
  • Customer Success Director – This is another position that is being seen as one that can be ignored. CS directors essentially monitor and nurture customer relations, while detecting new usage and sentiment trends.
  • CS Team Lead – The trend continues with the customer success team lead, who is supposed to implement and track new KPIs for ensuring sustainable growth. More and more SMBs are playing the waiting game with this hire.
  • CS Operations Manager – The customer success operations manager essentially enforces the team strategy and recognizes dips in KPIs. This is another position which is in danger of going extinct in 2023.
  • Digital Success Manager – The digital success managers manage tech stacks and are in charge of onboarding new CS solutions. This is more of an operational position that is also being passed upon by startups and SMBs.
  • CS Analyst – Just like marketing analysts, CS analysts work closely with all team members and constantly look for actionable insights. Their findings go directly to CS leaders and executives for better strategic planning.
  • Customer Success Manager – The CSM is basically the driving force in CS teams, with responsibilities ranging from customer support, all the way to responding to sentiment drops or relationship changes.

Due to the changes in the economic climate, many of these positions are being eliminated altogether. The impact on the customer success team structure is huge. More and more responsibilities are being transferred to CSMs. They are now being asked to do more by CS leaders, who are also feeling the heat from the management. This new reality is creating multiple challenges for post-sales teams.

Here are three main ones.

  • Book of business obesity

Simply put, CSMs are being asked to take on more accounts, even while working for B2B businesses that are scaling up fast. This means that they have less time to invest in each customer, nurture champions, and pinpoint growth avenues. Customer relationships need to be monitored and tracked constantly, something that is becoming extremely difficult today.

  • Automation means tightening corners, not cutting them

The growing lack of time and resources means that more and more B2B businesses are looking towards automated solutions. This can be emailing tools, chatbots, AI-driven responses, and more. But who is feeding the machine and what type of data are you feeding it? CSMs need accurate solutions. Another problem with “over-automation” is the rise of false alarms in high-touch situations.

  • Getting trapped in a reactive mindset

CSMs are looked upon as bonafide brand advocates and advisors, but are they really able to fulfill these responsibilities? Unfortunately, time-consuming chores and responsibilities force them into the reactive corner. They get trapped into acting as buffers between frustrated customers and stressed teams (product, engineering, etc.). CSMs are finding it hard(er) to shine in their true roles today.

Related: How to effectively build a modern CS tech stack

How your customer success team structure impacts your business

Relationships with customer accounts resemble marital ones in many ways. You need to keep an eye on your champions, track use cases, and attend to high-risk customers just like you do with your in-laws. Your team’s structure has to enable successfully all customers to the right experience they signed up for and are reaching aha moments sooner than later. Not an easy feat by any means.

For starters, old and reactive approaches simply won’t get the job done anymore. NPS and other surveys paint a partial picture, not to mention the data that can be outdated and irrelevant. Detecting friction and other risk factors are also crucial while scaling customer success.

When you look at it up close, every tier is going to require something different and these specific needs to be addressed in your scaling plans. Scaling it correctly with flexibility leads to stickier accounts, positive adoption, and increased NRR.

When is it time to revise your customer success team structure?

Timing is everything when it comes to scaling business functions and customer success isn’t different. Waiting for too long can lead to accelerated churn and brand damage that can’t even be fixed in the long run. If you are in a niche industry with a limited customer base, this can be a recipe for disaster. Many businesses get intoxicated with their early wins and fail to start scaling customer success on time.

As per a 2022 Saastr survey, 60% of respondents believe that a CSM is needed for every $0.5-1M of Annual Revenue Rate (ARR) as the business starts scaling up. This is contrary to popular belief that puts this number at $2M, a static and reactive estimate that doesn’t take many crucial factors into consideration – high touch accounts, market fluctuations, number of communication channels, and more.

The more you hire, the more proactive you become, assuming your ecosystem is built with the right solutions and the right amount of automation. Once you have high value accounts, you really don’t want to cut your post-sales budget. But as explained earlier, the ongoing economic turmoil is forcing companies to stay lean and avoid hiring CS professionals that are needed to scale up properly.

Related: A data-driven approach to balancing your CS team workload

To make matters worse, you have the traditional customer success approach.

The reactive customer success scaling approach

Customer success has evolved, but old habits die hard. Most CS teams are still implementing outdated and ineffective techniques, at least partially. These reactive approaches are simply not able to power CS teams to glory anymore.

Here are three old and reactive methods:

  • Checking in on accounts – Believe it or not, many CSMs are still reaching out to customers as a part of their strategy. Outreach KPIs can still be important with big accounts and top tier customers, but with stakeholders changing all the time, you may be wasting valuable time on these tasks. Also, more and more customers are becoming unresponsive due to busy schedules.
  • Playbooks – A good CSM playbook has a bunch of processes, best practices, guidelines, and action items for selected scenarios that help reduce response times. The biggest problem with playbooks today is their rigidity. They have to be updated constantly to stay relevant, not to mention the plethora of communication data that has to be analyzed and integrated into them.
    Also, many playbook tasks are irrelevant, which only adds to the noise and clogs the schedule. What happens when you are constantly flooded with a bunch of irrelevant and important tasks? You start ignoring them altogether.
  • Net Promoter Score (NPS) surveys – Net Promoter Score surveys have also been around for a long time. But unfortunately, these surveys are never taken by 100% of the customers. Also, the results never arrive in real-time, require CSMs to break down the results manually, and represent only a specific point in time. This becomes more and more frustrating as the business scales up.

So how can CS teams overcome these reactive approaches, especially with the streamlining of customer success team structures in 2023? The good news is that AI-powered technologies can help CSMs overcome the challenges of scaling customer success. These new capabilities help break down faster, generate insights that are unbiased, and automate many tasks. Too good to be true? Let’s find out.

AI-based customer success team structure scaling

Customer success scaling is best when done in a proactive and data-driven manner. Proper account health scoring is possible only with AI-powered solutions that are built especially for customer success purposes. Manual work won’t get you far. Smart, unbiased and standardized analysis of sentiment, engagement, and overall health is the name of the game in today’s tough economic climate.

Here are some key benefits of adopting AI-based CS solutions:

  • Unbiased and accurate analysis – Manual processing of information is time and resource consuming, but it is also very biased and inaccurate. AI-based solutions help CS leaders look at trends and even make accurate predictions.

CS leaders can now get unbiased customer sentiment scores on 100% of customers, without requiring biased feedback from CSMs or account managers. When scaling up, this removes the need to constantly listen to calls and read long threads. You simply get the low down, including pinpointing the negative responses received for quick damage control.

All of this helps CS leadership address negative sentiment drops faster.

  • Speed – Growing businesses have thousands of communications with customers on a daily basis. CSMs need this data to be analyzed in real-time to be truly effective in reducing churn and growing accounts. AI can crunch and digest loads of data in minutes, providing results that would take CS Ops months to generate.
  • Granular insights – The technology powering AI allows leaders to get next-level analytics on their customers. Imagine you can cross between topics it identifies to the sentiment customers have about it.
  • Zero dependence on CRM – Needless to mention, AI-based solutions reduce the need to sync perfectly with CRM tools that are mainly sales and marketing oriented. You no longer need indirectly-related personas to input data into CRMs and there are no broken links anymore. With AI, there is minimal friction with no dependencies that can affect customer success life cycles.

Flowchart showing "How AI Helps Scale Customer Success": Unbiased Analysis, Speed of Results, Granular Insights, Zero CRM Dependence. Each step highlights AI benefits like sentiment scores and advanced insights to navigate economic waters and optimize team structures efficiently.

Related content: Read our guide to scaling customer success

AI to the rescue with the brewing economic storm

Scaling your customer success operations? Remember that AI is not just about automation and customer success team structure optimization. It’s also about providing in-depth customer intelligence, sentiment scoring, relationship updates, and unbiased account analysis that leads to better business decisions. All of this needs to be achieved while maintaining maximal efficiency.

Only an AI-powered approach can help you reach 2024 in good shape. Try it out now.