For every business across the globe, repeat customers are considered one of the most valuable assets to maintain profitability. Apart from spending more money, repeat customers are also easier to sell to, and let’s face it, retaining loyal customers costs companies way less than acquiring a new one. The hard truth is retailers are still struggling with a high percentage of one-time shoppers. They are investing more resources in advertising campaigns to garner new customers than retain the existing ones. That’s where customer loyalty reward programs come in. However, retailers are still slow to turn the tide of repeat customers in their favor. A rewards program can be a game-changer if created with care and precision.
Set against this challenging backdrop, California-based Zinrelo—a modern-day, data-driven loyalty rewards platform supporting omnichannel deployments—is empowering businesses to quickly launch customized rewards programs that unlock customer loyalty across multiple dimensions including transactional, social, advocacy, engagement, and behavioral loyalty. “Unlike traditional loyalty programs that only focus on points of purchase, we create 360-degree engagement with customers through different types of actions, not just transaction, helping retailers increase repeat sales and per customer revenue,” says Jai Rawat, VP of Product Strategy at Zinrelo. “For instance, if a customer writes a review, refers to a friend, or shares information about a brand on social channels, the brands can instantly track and reward them.”
Zinrelo is seamlessly integrated with the Magento (via Magento extension) and helps businesses to get started quickly with a highly customized rewards program. Zinrelo is backed by 5-star support and is the top-rated loyalty platform on Magento and leading review platforms.
As opposed to competitors that offer a generic template for loyalty programs to every retailer, Zinrelo believes in customization. The company initiates customer engagement by collecting their historical transaction data of two to five years to understand the state of the client’s business. Following this, the data sciences team at Zinrelo thoroughly analyzes the data to provide a variety of compelling insights while calculating their retention rate, ROI requirements, margin requirements, and more.
With this information, Zinrelo recommends a custom loyalty program structure for the client, which fits their business-specific needs. “With a generic template, the loyalty programs tend to be either too aggressive or too conservative, which can result in loss of revenue. Our goal is to strike a balance to maximize the ROI, and it is not possible without the collection and analysis of data,” comments Rawat.
With such robust capabilities, Zinrelo has acquired a legion of clients across diverse fields. In one instance, a large cosmetics brand, despite acquiring numerous new customers, failed to retain them. This was affecting their overall business revenue. Zinrelo launched a customized loyalty program for them, which increased its revenue by 48 percent. Additionally, the client did not want to launch a promotion-oriented campaign to attract customers. To that end, Zinrelo enabled them to create an attractive rewards program based on bonus loyalty points, which helped the brand to amp up sales and profitability by improving their loyal customer base.
Scripting similar success stories, Zinrelo has established a strong presence in the market. In addition, the company has introduced a receipt scanning solution to allow brands to recognize and reward loyal customers who purchase their products on different retail channels. The company also plans on leveraging machine learning capabilities to make loyalty programs self-learning. Once launched, a program will be able to monitor itself and adjust as needed to self-optimize. Zinrelo will also bolster its presence in other segments. “Beyond the retail vertical, we are witnessing significant growth and traction in the B2B sector, and we are constantly honing our capabilities to extend our solutions in this sector,” concludes Rawat.
