Overcome the wrench of creating a Loyalty Program using Data Analysis

Data Science
January 18, 2023

Customer retention is the foundation of modern-day eCommerce. Once a customer has placed an order, there's a chance that he/she will come back for more products. Customer retention generates higher customer lifetime values, which in turn means more orders (frequency), more engaged users (reviews and social KPIs) and average order values.

A famous study done by Bain & Company showed that just a 5% increase in customer retention rates can boost company profit between 25% and 95%.

By offering a rewards program, a coffee shop can provide customers with up to 20% off the price of their cup when they accumulate four cups within a specified timeframe. Customers who usually purchase fewer cups, but often enough to reach the redemption hurdle, will get the discount on every cup of coffee. On the contrary, customers who buy more than four cups in one go don't benefit from this reward system and so may end up paying more for their beverage.

It may seem easier to just attract new customers, but in reality it's much cheaper to retain your current ones. This isn't just a cost, it's more efficient:

  • existing customers bring new ones
  • Share their happiness through social (UGC)
  • it helps businesses to expand in other markets
  • Customers appreciate your marketing strategy and are ready to try new things.
  • real feedbacks
  • increase the customer base for real: it's less decreasing in unsubscription and much more effect of marketing campaigns

As we know that customer retention is key for any business, we will do our best to identify the best ways your business can keep customers.

An interesting article of Harvard Business Review:The Value of Keeping the Right Customers
by Amy Gallo

There are many ways to achieve customer retention, but the most commonly used model is RFM Analysis.

The proof is in the numbers: according to studies done by Bain & Company, increasing customer retention by 5% can lead to an increase in profits of 25% – 95%, and the likelihood of converting an existing customer into a repeat customer is 60% – 70%, while the probability of converting a new lead is 5% – 20%, at best.

Customer Segments Analysis: a data-driven approach

Everything should be measured; how to measure customer retention increase? What are the best practices or practical examples of implementation? By looking at past clickstreams and your product catalog, we can predict the behaviour of your shoppers. Unstructured sources like social media help us understand consumer emotions and thoughts.

Social media data can lead to richer predictive models, and this is often accomplished by measuring social churn. We have a five-step process where we merge all the data from your major in-house systems to arrive at a score for potential churners.

One way that analysts are able to determine if customers are going to churn is by assessing a scoring model. The churn model helps you decide how to prioritize marketing strategy. You'll know whether to focus on retaining churners or on your loyal customers by deciding what group of customers is worth more to your business. The model can analyze net campaign gains for each group of churners by calculating the cost of reaching out to a segment of customers, and the discount rate offered to that customer. Predictive churn management models can help you anticipate turnover by offering insightful data, and that information is really useful for your BI strategy.

What is customer segmentation?

Customer segmentation is the practice of dividing customers into distinct groups that share common characteristics. With it, you can streamline support experiences and better target them to a particular audience. Using this technique, you can identify traits such as geographic location, career, or hobby and cluster customers accordingly. Alternatively, segmentation can be used to organize customers by behavior or demographics like age or gender. Ultimately, the goal is to create meaningful segments in order to meet the needs of customers and ultimately drive up retention.

Customer segmentation vs. market segmentation

Market segmentation is an effective marketing strategy that enables companies to tailor their products or services to the needs of targeted groups of consumers. By analyzing different categories such as geography, demographics, and behavior, companies can maximize profits by minimizing risk and investing resources in efforts most likely to yield a return. Additionally, they may be able to uncover new opportunities and expand their reach with untapped markets.

Customer Segmentation Benefits

  • helps to detect and exploit new market opportunities.
  • improves how to predict customer behaviour.
  • Increased customer retention and loyalty.
  • improves the perception of a brand through personalization.
  • streamlines and improves workflow.
  • helps to improve customer lifetime value.
  • Email marketers have witnessed a 760% increase in revenue by segmenting their email campaigns.

Loyalty and retention recommendations

We discovered redemption hurdles provide a solution to price segmenting customers in scenarios where listing different prices is impossible. Retailers can use past customer purchases, survey responses, or other market research data to judge how much their customers are willing to pay and how frequently they make purchases. By creating redemption hurdles that divide customers into groups based on frequency and spending, firms can charge different effective prices accordingly. This aids firms in tailoring their offerings to meet customer needs better.

If a coffee shop has a scheme where customers can receive a free cup of coffee after buying four within a certain date range, then those that make use of the reward will pay about 20% less for each cup. This way, customers with the lowest willingness to pay, who buy frequently, will still get a reduced price, while high-willingness-to-pay and infrequent purchasers will pay more.

If the shop avoids using an expiration date, it runs the risk of either charging too much for customers with lower willingness to pay, or not taking full advantage of those who would be willing to spend more.

McKinsey – Company performance that use data analytics

As you can see, the optimal expiration term varies according to your consumers' buying habits. Grocery stores, commonly frequented by shoppers, set much finer parameters than specialty stores such as GameStop and Dick's Sporting Goods. According to our data, the average expiration term for grocery store reward points is roughly 7 days — quite a contrast when compared with a maximum of 365 days for certain other retailers.

An investigation of purchase frequency revealed that when customers have varying frequencies, a shorter expiration period benefits companies. On the other hand, with less divergent rates, a longer expiration period is more effective in segregating customers into distinct clusters. This is due to the difficulty of creating subsets when purchase habits are analogous.

Useful market insights

  • 71% of consumers believe personalized experiences would influence their decision to interact with emails.
  • 80% of respondents indicating they are more likely to do business with a company if it offers personalized experiences.
  • 88% of U.S. marketers reported seeing measurable improvements due to personalization, with more than half reporting a boost greater than 10%.
  • A recent McKinsey survey found that companies that extensively use customer analytics are reporting 115% higher ROI and 93% higher profits.