Zinrelo
Multidimensional, Data-driven, Personalized Loyalty Programs

Customer loyalty programs date back to the 18th century when a U.S. merchant issued copper tokens to his customers that could be exchanged for items in the store itself. Since then, businesses have been issuing generalized tokens, such as reward points, to encourage repeat purchasing behavior and ensure customer loyalty. It is a well-known fact that it is cheaper to retain an existing customer than acquire a new one. This is why loyalty programs have survived the test of time. However, with the entry of COVID-19 last year, organizations saw a big changein customer loyalty, especially in the e-commerce sector. The pandemic brought in tremendous growth (according to a McKinsey report, a change that would have otherwise taken ten years was achieved in 3 months!) but created more challenges for customer retention. Retailers are now making strides to sustain the growth momentum and stimulate customers for repeat purchases. And while customer loyalty programs seem to be the apparent road, the cost accrued is usually high. In this regard, Palo Alto-based Zinrelo has a unique offering.

Zinrelo platform follows a multidimensional, data-driven, and personalized approach to loyalty programs that aims to increase revenue. Zinrelo was the first to introduce the concept of a multidimensional loyalty program.Itgoes beyond the traditional transactional based programs and rewardscustomers for all forms of engagements. Retailers can track and reward customers for all forms of loyalty such as transactional, advocacy, behavioral, social, emotional to name a few.

Over time, the company enhanced the platform and added machine learning and data-driven personalization that significantly improved the performance of the loyalty programs. “Retailers can reward their customers for referring other customers, social sharing, reviews, photo uploads and other types of endorsement,” says Jai Rawat, Founder, Zinrelo. “It is four times cheaper to acquire customers via word of mouth recommendations, and these customers have three times higher lifetime value on average.”

Detailed analysis of retailers’ data helps Zinrelo create precise models of a customized loyalty program instead of providing a generic template. Zinrelo’s program keeps track of a client’s profit margins, the cost of rewards, breakage rate, and costs of managing the program to help maintain a high ROI.

We have been able to increase Jelly Belly’s customer retention by 77 percent and the number of reviews is more than 2x above the industry average

Once the program is launched, the machine learning module monitors the performance and suggests program enhancements to optimize it. Using the aggregated behavioral and declarative data, the platform can provide highly personalized loyalty programs for individual customers. Behavioral data refers to the customer shopping habits, buying frequency, average order value et al., while declarative data includes the details that the customer has declared, such as brand preferences, demographics, or data through the surveys. In addition, the platform is pre-integrated with all major e-commerce platforms, email service providers, review providers and other technologies used by retailers which makes it very easy to implement and manage.

With such tailor-made loyalty programs and the resulting revenue growth, the platform has found adoption far and wide. A case in point is Jelly Belly. When Jelly Belly wanted to increase their customer retention rate, repeat purchase revenue, customer engagement and reviews, Zinrelocreated a customized program to reward loyalty points for purchases, reviews and other forms of engagement. These points can be exchanged for free shipping, gift boxes, and discounts. The results are a testament to the market outreach and ecommerce potential of Zinrelo’s platform. “We have been able to increase Jelly Belly’s customer retention by 77 percent and the number of reviews is more than 2x above the industry average,” says Rawat.

Delivering massive growth to its clients, Zinrelo has been growing organically. And the company is not stopping here. Zinrelo will double down its data expertise, enhance machine learning and AI-based algorithms to cater to the demand of other verticals outside of retail.