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Retaining an existing customer costs five times less than acquiring a new one, and the time and human resources involved in customer acquisition are significantly higher.
Sure, reducing CAC (Customer Acquisition Cost) is a great way to boost revenue, but reducing customer churn (the event of a customer leaving) is an even better alternative.
However, it’s not particularly a good idea to measure churn through cancellations alone. Infact, churn occurs long before a customer decides to cancel their subscription, sometimes as early as the onboarding process and there are clear indicators if you know where to look.
This article is all about understanding why customers churn, what signals they give before they churn, and how a good customer onboarding experience can help prevent that.
But before we get into that, let’s understand what churn actually means.
Churn is a term commonly discussed in business circles because it quantifies a significant challenge: customers discontinuing a service or leaving. It's often synonymous with 'customer churn,' which measures the rate at which customers cease engaging with a brand.
While the prevailing perception is that customer churn is a distinct event marked by subscription cancellations or non-renewals, we offer an alternative perspective. We see customer churn as a process, not a one-time occurrence.
There are specific events that culminate in the customer no longer finding value in the product like difficulties accessing features, longer problem-solving times, or a sense of being undervalued. Let's call these events 'RFEs' - Red Flag Events.
A good question to ask here would be “Are RFEs even quantifiable and can they be identified?”.
The answer is a no and a yes.
REF’s aren’t quantifiable unless you use surveys of some sort that offer customers a scale to answer specific user experience questions. However, that doesn’t mean you can’t identify them without surveys.
As a business, you need to understand that every interaction with the customer is a chance to nudge them in the right direction. Depending on what user touch points you take your data from, you can easily identify RFEs and reduce customer churn.
Perhaps the most valuable touchpoint in this context is customer onboarding.
Let’s understand why.
The initial step in onboarding is a post-sale kickoff call between a customer success manager and the user. It helps identify user pain points, challenges, objectives and communicate the inherent utility of the tool.
The kick-off call is a critical touchpoint for two key reasons:
1) The decision makers are eager to prove to their bosses that they made the right decision by investing in the tool
2) Buyer’s remorse kicks in naturally, and the stakeholders are very sensitive towards any signs of incompatibility or friction.
One wrong move and you could be guiding your new customers towards the exit or at least towards the stairs that lead to the exit.
For instance, if the user feels that the vendor made false promises during the sales process, or if they’re simply confused and can’t figure out how the product works, they will likely churn.
Vendors often use rigid onboarding processes that save time and resources but lead to higher customer churn. Users have varying needs, awareness levels, and challenges. Recognizing that your product replaces an existing process is crucial, and a flexible custom onboarding eases the transition, while a rigid one overwhelms users.
There are multiple axioms of activity churn that stem from the intersection of the core user challenges and the product’s ability to address them. Depending on which interactions you choose as your data points, you can identify critical churn signals and prevent the impending churn.
The length and frequency of user login sessions during the first 30 days of free trial is an excellent metric to deduce activity churn.
Users who frequently log into the software and have longer sessions during the initial 30 days are more likely to become paying customers compared to those who log in occasionally and have shorter sessions.
This observation is further reinforced when we consider how Groove effectively reduced their churn rate by monitoring login sessions and adjusting their strategy to focus on users with infrequent logins and shorter sessions.
When Groove noticed that their churn rate was over 4.4%, they realised that something was wrong with the onboarding flow. So they went digging and uncovered an interesting statistic. Users who converted into premium customers after 30 days, spent more than 3 minutes on average in every login session, while those who didn’t convert had an average login session of 30 seconds.
Moreover, converting customers logged into the softwares more than 4 times a day while those who didn’t convert only logged in once or twice.
So Groove decided to target users whose first session was less than 2 minutes with a personalised email offering help during the set-up process and the e-mail garnered a response rate of over 26%.
The company also targeted users who logged into the platform less than 2 times within the first 10 days with the following e-mail and ended up having a response rate of 15%. Majority of users who responded to these emails converted into premium subscribers lowering the churn rate significantly.
Let’s be honest, despite being one of the most pivotal metrics for any business, it isn't the easiest thing to measure. It involved monitoring various metrics like how often does the user engage with the brand across engagement channels like blogs and social media, what percentage of customers give positive reviews or refer the product, the nature and frequency of customer queries.
Hubspot has a dedicated index that measures customer satisfaction called the CHI Score or the Customer Happiness Index. It uses the weighted analysis of data from thousands of customers to assign a CHI score to every customer and uses this score for specific targeting of users and lower their churn rate.
Hubspot enhances its customers' CHI scores by offering a mini-education course and a monthly account review as part of the initial onboarding process. This helps users make the most out of their subscription.
Another great way of ensuring a high level of customer satisfactions is by assigning a Customer Account Management (CAM) team to every user post sign-up to customise the onboarding process based on their specific challenges and requirements.
A perfect example of this is Zendesk, a CRM software that assigns a CAM team to every user to customise their onboarding flow and help them navigate the tool in the most efficient manner.
HelpScout actively resolves user issues promptly and is always there for its users even across social media platforms.
HelpScout is never shy when it comes to celebrating the wins of their customers
In the realm of churn prevention through onboarding best practices, a 'trigger' signifies particular events that can lead to activity churn and might demand prompt intervention to avert future churn.
These triggers are intelligent metrics, and each business must identify them based on their industry, user goals, and product characteristics.
A prime example of this is Buffer's use of trigger-based emails to retain users and reduce their churn rate. As a Twitter analytics and scheduling platform, the company opted to focus on users who had no scheduled future posts by sending them custom emails.
Buffer’s internal research revealed that more than 33% of the users that churned were still active the day they cancelled their subscription. Which meant that users with less or no scheduled posts had a higher chance of churning, so they targeted these users with a friendly reminder to stack up their buffer account with posts.
Although not all businesses have the same triggers, there are intuitive triggers that every business can act on and reduce churn. For instance if a user signs up but doesn’t complete the setup process, act on it immediately with a follow up call or an email to help them complete the setup.
Another critical trigger is monitoring engagement flags. However, unlike what most companies do, you should monitor engagement across entire teams in an organisation instead of monitoring individual activity. It can be that certain individuals aren’t active because they’re on a vacation or they’re working on a different project.
Act only when engagement drops across entire teams.
Feature activation is the most important aspect of turning free trial users into paid users. A high feature activation shows that the user-team interaction is moving in the right direction and the user will likely convert into a paid customer.
However, if the feature activation and login frequency is low during the free trial, it can only mean one of two things:
While there isn’t much you can do about the latter, it is highly likely that you can prevent a confused user from churning by paying more attention to them.
Take Mention for instance, a platform that lets users monitor online conversations about themselves. The company was struggling with a high churn rate post 2,00,000 users, and realised the importance of free-trial users and the custom emails sent to them.
Mention segmented their users based on membership type and started handling support requests in batches that gave them more time to focus on free trial and paid users.
Moreover, they started sending pro tips to free trial users through automated emails to boost product activation and getting users familiar with the product.
The company also came up with a webinar called “Use-Case Masterclass” for free trial users to demonstrate Mention’s feature set through concrete examples from real users.
These efforts helped Mention lower their customer churn by 22% in less than 30 days.
Customer onboarding surveys help identify churn indicators long before the customer actually churns, given that you choose the right moment to send out these surveys. An optimal way to do this is to follow a two-fold approach.
Send out two surveys:
It's quite clear why we've chosen these touchpoints as survey milestones. We've previously highlighted how kick-off calls are crucial in the vendor-user interaction, and if the user remains confused even after being guided through the feature sets during user onboarding, the risk of churn is significant.
A post kick-off survey helps manage expectations and identify systemic blindspots. These surveys include questions such as the following:.
A post-user onboarding survey aids in locating any friction points during the user onboarding phase that might indicate a challenging path ahead. Identifying these areas of turbulence and addressing them paves the way for a smoother journey. These surveys typically contains similar questions:
A good onboarding flow consistently (and effortlessly) drives users to find value in the product and take positive actions.
What drives these actions are three essential ingredients:
A strong value proposition ensures that users are motivated and believe in the product. Therefore the message must be clear across all marketing channels to inspire action (in this case, a sign up).
Moreover, when a user looks at the product dashboard for the first time, it should naturally occur to them where to click next without someone guiding them through the whole thing.
That is not to say that you don’t need someone guiding them through their first session, it just means that the user should not feel at any point that they couldn’t have done it without the help. That’s what it means to make the user feel smart.
A great example of how to prompt users into signing up for the product without being too intrusive is Customer.io’s landing page, that lets users navigate the entire website without irritating them with free trial and live demo pop-ups.
The 'sign-up' and 'free demo' buttons are strategically placed in the top right corner of the landing page, ensuring an unobstructed view of the page. At no point does the user sense any pressure to sign up before exploring the product, and this serves two essential purposes:
1. It signals confidence in the product
2. Users feel in charge of decisions
Asking the right questions is the quickest way to identify activity churn indicators, but that doesn’t necessarily give you the answers. Answering these questions demands ongoing analysis of complex data from various user interactions throughout the onboarding process.
Even if you have a tool for gathering, sorting, and analysing multi-dimensional data, it can be challenging to predict which data points require examination to address your questions.
Moreover, all of this works on the assumption that the tool can decipher human semantics and make sense out of your questions.
This is exactly what Crunch’s proprietary machine learning algorithm does.
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