For retailers, the best defense against new and existing threats is a loyal customer base. Traditional methods to mitigate churn are no longer enough. How can retailers leverage digital intelligence to accurately predict churn and drive customer retention?
33% of customers are willing to switch brands after just one poor experience, and only 1 in 26 unhappy customers will complain before they leave, the rest will simply churn. Retailers are looking to the power of machine learning and digital intelligence to help them improve customer retention.
Retention: Art or Science?
Customer loyalty and retention can feel like more an art than a science, and people churn for a myriad of reasons. It’s estimated that 50% of customers naturally churn every five years. But increasing retention by even just 5% can increase profits by 25 to 95%. Brands that focus on using the power of digital intelligence to craft personalized experiences can put the power of science to work to reduce churn.
- Understand engagement effectiveness. How well are your campaigns really working? What’s resonating and what’s not? By getting real-time data from your website and apps, you can gain a clearer understanding of how your campaigns are landing with their target audiences. Once you have this insight, you can craft better campaign strategies.
- Use predictive analytics to spot churn before it happens. With tools like Localytics Predictions, you can identify the warning signs of churn and take action to re-engage customers. You’ll understand the behavioral differences among those who churn and those who don’t, and segment users into low, medium, and high risk churn groups.
- Intelligently personalize engagement. When you have deep insight on who your customers are and the behaviors that signal loyalty, you can craft personalized engagement that truly meets customers where they are—when, where, and how they interact with your brand.Your customers want a personalized experience, and it can’t be more helpful in the retail industry to know what your customers want. Brands must know the products they are looking for—if a customer spends most of their time in the basketball section of Nike’s app or the hiking boots section of Patagonia’s website, these brands would want to know to focus their advertising and communications on basketball apparel and hiking equipment.
- Deliver seamless omnichannel experiences. Pull all the insights from digital intelligence together to create a shopping experience and buyer’s journey that flows across mobile, web, social, SMS, email, and in-store.
In the above example, if a consumer places basketball shoes in their mobile app shopping cart, they would want that information to translate to Nike’s website. Not only the shopping cart, but the behavior information too. Nike’s web push notifications should still be personalized to basketball, even if they didn’t spend time on the website’s basketball page and only the mobile.
- Re-evaluate engagement effectiveness. Data feeds a continuous customer journey cycle. Digital intelligence gives you deeper insights and broader access to get closer to your customer, craft personalized experiences that resonate, and continue to hone and refine engagement to improve retention.
How are your efforts to reduce churn and improve retention working?
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