For the last 30 years, businesses have viewed customer retention as a customer service problem – bad service creates customer churn. That’s an outdated concept. The reality in today’s customer-centric environment is customer satisfaction (…or dissatisfaction) is everyone’s problem – marketing, sales, and service. Organizations that are successfully retaining customers and reducing churn know it’s not just about agent-based service – it’s about understanding the needs of each customer on an individual level, and creating a relationship with them that is contextual, proactive, personalized, and seamless. Anything less is unacceptable.
To provide personalized engagement, you need to know each customer
Customers today are more plugged in, digitally connected, and well informed about both your company's and your competitors' offerings. They’re empowered and feel entitled to great customer engagement when they need it, on the channel they prefer, whether it’s via text, email, social, web self-service, phone, or direct mail. The problem is, most organizations aren’t well informed and plugged into their customers’ individual needs. This disconnect prevents you from providing the personalized level of 1-to-1 engagement your customers are seeking.
Static customer history data isn’t enough anymore. With the profusion of owned digital, paid digital, outbound, social media, or agent-assisted channels, you need to be able to gather and analyze customer interaction data from all sources, predict the triggers that may lead to customer dissatisfaction and churn, then build personalized offers geared toward reducing churn and retaining that customer. Plus, you need to be able to convey the best offer or message to your customer at the right time, even in real time.
Rethink your retention initiative and build customer value with these three important capabilities
As I mentioned at the beginning, customer satisfaction is a team effort. Organizations need to look holistically at how each customer engagement strategy incorporates marketing, sales, and service activities. Clearly, customer retention initiatives need to focus much further upstream, well before you drop customers and agents into a poisonous situation. An organization has to see every interaction as a tipping point, with only two possible outcomes: bringing the customer closer, or pushing them away.
To build personalized relationships that help retain customers and build value, you need to incorporate these three essential capabilities into your enterprise systems:
1. Predict your customers' needs using the data you’ve collected from them. Learn each customer’s product interests, channel preferences, pain points, communication cadence, etc. You need to know if people are ready to churn, versus when they’re ready to buy, so you can react in the moment and guide marketers and agents towards the right approach for each unique situation.
2. Understand each customer’s lifetime value. Know the potential of each individual you’re engaging with. Test sales and retention offers, bundle products that match their needs, and work within a personalized budget that will help agents contain discounts. Real-time predictive and adaptive analytics leverage big data to help you identify the personalized approach needed to capture new prospects or retain current customers with high customer lifetime value.
3. Adapt as your customer’s needs change. When a customer starts a new journey, finishes one, or simply gets stuck somewhere along the way, you need to identify the context of that customer’s situation, pivot your approach, and stay in tune with where they’re going – not just where they’ve been. This is a “next-best-action” approach. Sometimes the best action is to make an offer. Other times, the best action is to educate the customer on how use their service… or simply do nothing at all. How do you know which is best? Use AI to combine real-time context with data and analytics to suggest the next best actions for each customer and each engagement.
Personalized engagement works
In the well-documented case of Sprint, a U.S. tier one carrier serving almost 50 million customers, the company implemented a 1-to-1, personalized, next-best-action approach to customer engagement that reduced churn by more than 50% in a short period of time. By leveraging predictive and self-learning analytics, and prebuilt retention processes to identify customers at risk of churn, Sprint was able to create proactive, personalized retention offers. The result was a seismic shift across the U.S. wireless market.
Similarly, U.K.-based EE was looking to improve retention and increase revenue per customer for their more than 20 million subscribers through more personalized marketing. By using the Pega Customer Decision Hub™ to identify the best-fitting package for each customer from more than 100,000 potential combinations – and based on the real-time context of the engagement – EE realized a 40% reduction in churn, 300% increase in sales offer acceptance, 5% increase in Net Promotor Score, and a $40 million per year increase in total revenue.
It’s important to remember that results like these never happen by accident. They are made possible by thousands (sometimes millions) of individual interactions occurring on the front lines every day, each of them orchestrated in real time by a central decisioning tool that determines the best approaches in each individual situation. That may sound like a lot of complicated data to analyze, but by applying AI’s machine learning capabilities, organizations can determine the optimal way to engage with each customer on any channel – creating a seamless, simplified, personalized experience for both customers and agents.
- Read the 4-page brief, “Get relevant or get ignored,” to learn how personalization is helping communications service providers increase retention.
- Download the paper, “Crossing the chasm: From campaigns to always-on marketing,” to learn how personalized, continuous engagement can create amazing results.
- See how Brazil’s Oi is using AI-powered customer engagement to make complex marketing simpler and more effective.
- Discover why Ovum ranked Pega the #1 customer engagement platform in their 2018 Decision Matrix.
- Use our customer revenue calculator to quickly determine the value that real-time analytics could generate for your organization.