For years, retail banks have faced a consistent uphill battle: customer churn. The numbers haven’t changed much over time, with an annual churn rate of about 15 percent becoming the norm. It can almost feel like an unavoidable cost of doing business.
Why the Old Playbook Isn’t Working
Common churn mitigation strategies target improved onboarding, personalized product recommendations and loyalty programs. But when those methods don’t seem to be moving the needle, it can be largely because of a one-size-fits-all approach, or because the personalization that IS incorporated isn’t tied to specific behaviors that signal a potential break.
Customer “stickiness” is important but it’s not the same as a proactive churn prevention strategy that’s continuously watching for subtle signals that a customer might be on their way out, and then acting fast.
Customer churn signals span a customer’s entire relationship with the bank, well beyond transactions:
- Are there fewer logins?
- Is there a decline in card activity?
- Did a customer post a negative branch review on Yelp?
These signals tell a story for the banks that are listening. And banks don’t need more data to hear it, they need better data. Accurate, unified and contextual data unlocks insights that help to interpret customer behavior in context, rather than isolation.
Data Readiness Brings Game-Changing Results
Recognizing these nuanced customer signals through sophisticated analytics can help cut churn by more than a third, according to one study that also touted personalized engagement as a pillar of churn prevention. But that personalized engagement needs to address a specific indicator of churn, not just satisfy everyday expectations for a “Hello [First Name]” greeting.
The Right Data, the Right Churn Signals
Shifting the churn prevention mindset is more than a marketing tweak, it’s an enterprise-wide effort.
- Marketing teams design and execute triggered actions and journeys based on churn signals.
- Data teams build and train models that predict churn based on every relevant customer signal.
Customer experience teams ensure every interaction feels seamless and empathetic, turning insights into more meaningful engagements.
It’s about pulling in the right data – data that’s just as important as financial transactions in providing contextual understanding that reveals what’s important to each customer. When you understand more of the why behind the churn, it becomes easier to create campaigns that address the real root causes, rather than relying on intuition or gut feelings.
Churn Prevention is a Data Collaboration
The reason churn prevention should ideally be a collaboration between marketing and data teams is because churn indicators are revealed through two distinct groups of data that when combined yield an understanding of the larger data story:
- Contextual customer data, the page views, email opens, channel interactions and other signals familiar to marketers, and
- Contextual metadata, the data lineage (sources, recency, history), quality (accuracy and completeness), and meaning (definitions, semantics, relationships), which is typically under the purview of data teams.
Together, this collaboration is what creates data readiness – the organizational capability to unify, cleanse, and interpret all signals in context so that marketing and CX teams can act on them in real time. The combination of situational awareness and knowledge about the details of the data itself allow marketers – and systems – to understand, trust, and responsibly use the data.
Fight Churn with Data Readiness
When data is clean, unified and contextual, it unlocks the ability to orchestrate customer interactions that are not just personalized, but relevant to the moment.
It’s what gives teams the ability to not only spot all the churn signals, but to also make sense of them and then formulate and quickly respond.
Staying one step ahead of the game when it comes to identifying and mitigating churn requires data readiness, which means
- Cleaning, normalizing and standardizing data at ingestion
- Building a real-time, accurate unified profile through advanced identity resolution
- Understanding customers in the context of households or business accounts.
The reality is that fewer logins or a decline in card usage might mean churn for one customer, but not for another. Minimizing churn depends on being able to tell the difference, because a one-size-fits-all triggered action could backfire and end up creating more churn than it prevents. Preventing churn starts with knowing your customers in context, and that starts with data readiness.
Redpoint’s Data Readiness Hub helps retail banks unify, clean, and contextualize data across every channel, so you can spot churn signals early and act decisively. To see how Redpoint can help you develop a data-driven churn prevention strategy, using your own data, click here.
