When a customer isn’t happy, businesses tend to scramble and try to turn things around. However, reactive marketing is like a Band-Aid. It might stop the immediate hurt or frustration, but it doesn’t fix the underlying problem. Eventually, the wound could be reopened. The way around this is to build customer loyalty with an “always on” marketing strategy.
Poor customer service is the number one reason customers leave. It could come from the frustration of repeating a problem to each new representative, feeling like just another number, or struggling to get a simple return processed. Many customers also experience inconsistency in their interactions with companies.
In our State of Marketing report, we found that 53% of customers expect companies to anticipate their needs, but only 33% say most companies address service issues proactively. This gap between expectations and reality presents an opportunity for marketers to adjust their scope and zero in on customers’ needs.
How do you do it? By using data to build proactive marketing strategies that not only fix problems, but prevent them altogether.
What you’ll learn
Why Band-Aid marketing doesn’t work
Sure, your marketing team is busy. They’re constantly on the go addressing immediate issues with short term solutions — offering promotions to avoid plummeting satisfaction scores or responding to angry tweets after the damage has been done.
This reactive approach might seem efficient, but it can come at the cost of customer loyalty. Each short term solution is a missed opportunity to build customer loyalty, leading to churn, dissatisfaction, and lost revenue. Customers have come to expect proactive marketing that anticipates their needs and prevents problems before they happen, transforming your Band-Aid solutions to experiences that hit the bullseye.
Data as your targeting system to predict customer needs
You might be surprised to learn that you already hold the key to proactive marketing strategies — and it’s in your customer data. Unlocking this data allows companies to gain a better understanding of customer needs and wants, allowing them to consider the complete customer journey when defining a bullseye experience.
By analyzing this data with insights into purchase history, browsing behavior, or past support interactions, companies can identify patterns and trends that predict potential issues and inform proactive marketing strategies. For example, a surge in searches for a specific product on your website can trigger low stock alerts, allowing you to proactively inform customers and prevent stockouts.
This not only avoids frustration but also allows you to offer pre-order options or suggest similar products. Or, imagine a customer who frequently purchases large furniture that requires many assembly steps. Analyzing their browsing history might reveal they’re looking at a new bookshelf. This presents an opportunity to send a personalized email with a helpful assembly video or offer a discounted assembly service – all before they even encounter any difficulties.
By understanding past behavior and predicting future needs, proactive marketing, fueled by data, allows companies to deliver hyper-personalized experiences that not only address customer needs but anticipate them, leaving customers feeling valued and understood.
7 steps to build customer loyalty with proactive marketing
So, what are some tangible steps you can take to build customer loyalty ? Here’s seven ways to help you do it.
1. Uncover customer needs
Data is the key piece to understanding your customers. Analyze surveys, support interactions, and social media sentiment to understand common pain points. This helps you identify areas where proactive intervention can significantly improve the customer experience.
2. Map the customer journey
Visualize the typical interactions a customer has with your brand, from newbie to pro. Pinpoint potential hurdles and opportunities for proactive intervention through website traffic data and user feedback. This helps you anticipate where customers might need help before they even ask.
3. Predict needs, not problems
Go beyond analyzing past data. Use predictive AI to anticipate future customer needs and prevent issues. Imagine notifying customers of recalls and offering refunds before they ask, or identifying customers who might struggle with complex product setup based on browsing patterns.
4. Communicate proactively
Implement proactive communication strategies. Send personalized notifications for only those who should see them, such as subscription renewals, low account balances, or abandoned carts. Offer helpful reminders and educational resources relevant to their recent purchases or browsing behavior.
5. Leverage technology for support
Embrace AI-powered chatbots to handle routine inquiries and basic troubleshooting, freeing up human agents for more complex issues and personalized interactions.
6. Measure, analyze, and adapt
Proactive service isn’t a one-time fix. Track key performance indicators (KPIs) like customer satisfaction scores, customer lifetime value, and churn rate to gauge the effectiveness of your strategy. Use data and customer feedback to continuously improve and refine your approach to stay ahead of customer needs.
7. Create a lasting and consistent experience
Don’t keep customer data siloed. Share across different departments to provide a seamless and relevant customer experience. For example, if marketing has access to customer service data, they can use specific ads and promotions to target unhappy customers with an open support ticket. Or, a sales rep can access purchase data to send a follow-up email about a customer’s recent online purchase. Fixing these once time-consuming and frustrating handoffs can increase customer satisfaction and lifetime value.
Customer loyalty in action: Reducing hospital readmissions with proactive care
Let’s look at a fictional healthcare provider, Great Health, Inc., which faced a high rate of hospital readmissions following patient discharges. This not only burdened patients with additional medical expenses and stress, but also strained hospital resources and negatively impacted Great Health, Inc.’s reputation. Traditional reactive follow-up methods, such as generic discharge instructions, were proving insufficient.
To transform its post-discharge strategy to focus on proactive patient care and personalized communication, Great Health, Inc. used a data-driven approach with Salesforce’s Data Cloud. Let’s take a look at how:”
Step 1: Data ingestion and unification
Great Health, Inc. started by ingesting and connecting relevant clinical data from Electronic Health Records (EHRs) into Data Cloud. This included details about a patient’s diagnosis, treatment plan, and existing health conditions.
Additionally, Data Cloud integrated with external systems, capturing the social factors of health data (e.g., living situation, access to transportation) that could influence patient recovery.
Step 2: Risk-based segmentation
Great Health, Inc. then created risk-based patient segments. By analyzing clinical data and external AI models, it categorized patients into different risk tiers for readmission based on factors such as age, diagnosis, and post-treatment complications.
Step 3: Proactive patient engagement
Great Health, Inc. activated the risk-based segments with Salesforce’s Marketing Cloud Engagement, allowing for personalized communication tailored to each patient’s needs. For example, patients in a high-risk tier might receive targeted educational content on managing potential side effects like dehydration or monitoring for signs of infection. This personalized content could be delivered via email, SMS, or the patient portal, ensuring timely and relevant information reaches the patients who need it most.
This proactive approach not only translated to improved patient satisfaction, demonstrating genuine care and concern, but also enhanced healthcare efficiency. With fewer readmissions, hospital resources were freed up for new patients, creating a ripple effect of positive outcomes.
By embracing proactive marketing, you can ditch Band-Aid solutions and reactive scrambling and create relevant experiences that build lasting relationships. So, take aim at customer loyalty with these seven steps, and hit your bullseye every time. After all, happy customers are loyal customers.
Say hello to Data Cloud
Want to improve your personalization and break down silos that lead to a disjointed customer experience? Data Cloud brings it all under one platform, having all your teams working together.