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In B2B SaaS, retention stands out as a crucial metric for sustainable growth, and customer churn can be a significant roadblock to success.
That's where predictive models come into play, and in this article, we're looking into how a tool like Forwrd.ai can supercharge your retention strategy with two customer churn models.
Before we get into the specifics, let's clarify the significance of customer churn models.
These predictive models leverage advanced algorithms to analyze customer behavior, identify product-usage patterns, and forecast potential churn.
By understanding when and why churn might occur, businesses gain a competitive edge in addressing issues proactively.
The first 90 days of a customer's journey are critical. It's a period of discovery, onboarding, and acclimatization with your product.
By building a predictive model that focuses on this initial phase, Forwrd.ai enables you to identify red flags that might indicate early churn.
These flags could be missed onboarding milestones, a lack of engagement with key features, or inadequate support interactions.
The number 90, which we used in this example is rather arbitrary. If your product has a 30-day trial, you’d want to investigate for early churn within the first 30 days.
Beyond the pivotal first 90 days, the customer relationship evolves. This is where the second churn prediction model steps in.
Forwrd.ai empowers you to create a model tailored to this later stage, predicting churn signals that might emerge as the customer's needs evolve.
It considers factors such as changing feature usage patterns, declining interaction with your platform, or changes in the customer's business environment, such as mass layoffs.
The insights provided by the model can be employed to enhance customer retention.
For example, if the model reveals that a specific engagement with a Customer Success Manager led to improved retention, you might consider duplicating this interaction with your remaining customers.
For your predictive models to be effective, you need data – and a lot of it.
Forwrd.ai integrates seamlessly with all of your data sources, pulling in data from customer interactions, usage patterns, support tickets, and more.
By incorporating a wide array of relevant data, the predictive models become more accurate, enabling you to take precise data-driven actions.
A fantastic example of the effectiveness of these two churn prediction models is the case of Jasper.ai.
Jasper integrated Forwrd into their Customer Success RevOps strategy and witnessed remarkable results.
By employing the early churn model, Jasper could proactively identify struggling customers and extend timely assistance.
Additionally, the later churn model allowed them to tailor interventions, ensuring their product stayed aligned with customer needs.
Forwrd's insights alone won't cut it. You need to get moving from predictions to actions.
To ensure your frontline employees, like CSMs, get the hottest insights at the right time, Forwrd syncs with Slack, automatically sharing the churn model insights with the go-to-market team for swift reaction.
Not only Forwrd tells your CSMs which customers are at risk, it will also tell them why each customer is at risk.
Forwrd surfaces specific issues that give your frontline team context and crystal clear directions, helping them retain and delight their best customers and accounts.
Customer churn is a challenge that demands innovative solutions.
Forwrd offers two predictive churn models that revitalize your retention efforts.
By identifying early and later churn signals, and leveraging diverse data sources, you're able to proactively engage customers and align your product with their evolving needs.
This transition from insights to action is where the real magic happens.
We invite you to take this opportunity and incorporate these predictive models to solidify your position in the competitive landscape.
