Leveraging analytics to drive and transform effective customer loyalty programs

Leveraging analytics to transform customer loyalty programs

 | 
Last Updated on June 20, 2019
 | 

“Customer satisfaction is worthless. Customer loyalty is priceless.” – Jeffrey Gitomer

Customer loyalty programs are counted as one of the foremost strategies used by brands to encourage loyalty among customers. However, in the current technology landscape, loyalty programs of yore are simply not enough. The customer of today looks to enroll in a loyalty program only and if it offers personalized benefits tailormade to enhance their individual customer experience.

According to a recent HBR study, it is 5-25 times more expensive to acquire a new customer than to retain an existing one. Existing customers are also known to spend more than a newly acquired customer.  Successful businesses dedicate their time to not only figuring out how to acquire new customers, but also to understand how and why it is vital to retain ones they already have. And that’s where customer loyalty programs come in.

So, what exactly is a customer loyalty program?

Customer loyalty is the relationship between a company and the customers. Customer loyalty programs are offered by companies to identify the customers making frequent purchases, and in-turn reward them with incentives. The goal of a loyalty program should be to attract the right customers and create a long-term relationship with them. According to an ITA report, “Existing customers spend 67% more than new customers. In short, customer loyalty really pays off – and customer loyalty programs end up paying for themselves.”

What are the customer loyalty program benefits?

  • Customer retention: The primary motive behind customer loyalty program ideas is to retain existing customers. A well implemented loyalty program will increase overall revenue through effective customer retention strategies
  • Access to customer data: The company will have access to customer data once the customers register themselves to the loyalty program. This will help in profiling their customers better and in better planning and pricing of products/services.
  • Reducing unprofitable customers: A loyalty program can help companies segment their customers better and identify their profitable and unprofitable customers. Through loyalty programs, businesses can reward better customers more and thereby minimize the payout to unprofitable customers.

Designing a customer loyalty program

The loyalty programs sound like the key to instant success, but it isn’t the case for most companies. The keys to most successful customer loyalty program ideas are:

  • Easy and simple:  This is the most common and important feature of a loyalty program. If the program is difficult to understand, it will not be successful.
    • For example, a customer gets 2 stars per $1 spent at Starbucks. These stars can be redeemed for free food and drinks at Starbucks. You need a minimum of 125 starts to redeem a free item. Additionally, there are perks like birthday rewards, pay by phone, skip the queue, etc.
  • Make earning and redeeming simple:  It’s always better to keep a simple point system for customer loyalty programs in retail. If the program is a points-based loyalty program, the conversions should be simple and intuitive.
    • For example, for every dollar spent on Sephora merchandise online or in retail stores, the customers get 1 beauty point. They have accelerated rewards for elite members.
  • Having the end goal in mind: The loyalty program should be designed in such a way, that it helps the company achieve its organizational goals.
  • Using a tier system: Implementing a tier system encourages customers to purchase more.  Giving away small rewards for initial purchases and increasing the value of the rewards as the customer moves up the loyalty ladder will help in keeping the customer active as they will keep an eye on the rewards that are of higher value!
    • For example, Uber Rewards that are available in limited cities has grabbed a lot of eyeballs with its simple 4-tier mechanism, i.e. Blue, Gold, Platinum, and Diamond. The rewards keep getting better as the customer climbs the loyalty ladder.
  • Gamification: Businesses can come up with contests and sweepstakes to include a fun and interesting element to the loyalty program.  
    • For example, Flipkart recently launched their loyalty program ‘Flipkart Plus’ which offers 1 coin upon spending Rs. 250 on their website. They have a separate game zone for their Plus members where they conduct daily quizzes and games. This is an excellent example of gamification in customer loyalty programs in retail
  • Refer and Earn: This is an effective strategy for businesses looking to acquire new customers and increase market share.
    • For example, Zomato Gold has its own refer and earn feature. The customer registering via an existing customer’s referral gets a 20% discount on their registration fee. The referrer in-turn gets free food or drinks at partner restaurants and an extra one month added to their existing membership.
  • Make it about the customer: Carrying out surveys to get suggestions and feedback from the customers will help design a customer centric program.
  • Charge an upfront joining fee: This is applicable to businesses which thrive on frequent purchases. The customers are then relieved of inconveniences they might face during future purchases. The upfront fee takes care of extra convenience charges in case of future purchases.
    • For example, Amazon Prime members are eligible for free same day and two-day deliveries with no minimum purchases. Additionally, they have complementary access to Prime Video, a movie/TV series streaming website, and Prime Music, a music streaming platform.
  • Tie-up with other businesses to provide all-inclusive offers: Businesses can tie up with other companies to provide a variety of offers to the customers and could also include offers from other industries.
    • For example, American Express Plenti has tie-ups with multiple companies from different industries such as Macy’s, AT&T, Enterprise Rent-A-Car, Hulu, Mobil, Exxon and more.
  • Charity/Donations: Customers want the flexibility to support causes that are close to their heart. Companies are partnering with charitable organizations to provide loyalty program members a chance to redeem their points for charitable donations.
    • For example, Microsoft Rewards has partnered with charitable trusts like Special Olympics, The Nature Conservancy, Girls Who Code, etc. Customers can redeem their points for non-profit donations to these Institutions.

How can businesses use analytics to improve their loyalty programs?

Data-driven decision making has become pivotal to the growth of a new-age business. Most businesses either have an in-house analytics team, or an external partner team helping them generate actionable insights through data, with a primary focus on improving customer retention strategies and loyalty. Below are a few key practices that loyalty programs can adopt to constantly improve and adapt to the new and highly competitive era of customer-focused marketing,

A) Measuring and monitoring data:

Businesses can now interact with the end-consumer via a plethora of platforms such as email, website, mobile applications, social media, surveys, etc. It is important that high quality data is collected across these platforms. Any data that is informative and the business believes is worth analyzing must be tracked and stored effectively. For ex., consumer demographic (age, sex, nationality, etc.) and other basic information can be inputted by a user on signup to the program.

User data tracked through different platforms can be merged into a unified framework to understand the value of each individual customer.  A user who is highly active on only a single platform is also valued, and it isn’t essential for a valuable consumer to be active on all platforms simultaneously. The Microsoft Rewards program enables users to earn loyalty points by actively searching on web (through Bing), purchasing Xbox games, participating in quizzes, etc. These earned points can then be redeemed to purchase Gift Cards, participate in Sweepstakes, make Donations, etc. A user who primarily searches on Bing can be as valuable to the business as a user who solely purchases Xbox games.  

A study by McKinsey found that, “Executive teams that make extensive use of customer data analytics across all business decisions see a 126% profit improvement over companies that don’t.”

B) Observational studies:

The initial stages of a data-driven loyalty program can be kick-started using observational research. This involves studying the measured data in a natural setting and drawing inferences based on the data collected.  

This type of study can help businesses identify the correlation between observed variables, but it does not help specify the direction of causality, nor does it account for the impact of other variables (confounding variables). For example, it is observed that the launch of a successful offer leads to higher sales for a sample loyalty program and a correlation between the two variables is identified. But the inverse can also be true, i.e., higher sales can lead to the success of a newly launched offer. Additionally, there could be other variables influencing this study, for example, the time-period considered happens to fall during a festive season, which will most probably have an impact on sales. Hence, we cannot incur with confidence that the launch of a successful offer leads to higher sales.

An observation study with matching variables is a more accurate way of evaluating the effect of a treatment. In this type of study, users with similar observable characteristics are matched and compared, which reduces bias due to confounding.

Observational studies are a cost-effective and quick method of analyzing data, and can be implemented for smaller businesses, or during the building stages of a budding loyalty program.

C) Experimentation:

Experimentation typically involves setting up randomly targeted treatment and control groups to measure the impact of a given treatment. There is no selection bias between the groups, which helps minimize the effect of observed and unobserved variables and a cause-to-effect relationship can be easily determined.

Most large loyalty programs typically involve launching campaigns/offers regularly and rely on A/A and A/B tests to quantify the impact of these campaigns, by exposing the campaign only to the treatment group and not the control group. The treatment and control groups are initially A/A tested to ensure the characteristics of users in both groups are similar before the launch of the campaign. After the launch of the campaign, the groups are A/B tested to ensure that the campaign has had a positive effect on relevant goals/KPIs in the treatment group when compared to the control.

Experiments can be conducted by setting up shallow as well as deep goals. Deep goals are relatively closer to business goals in comparison to shallow goals. For example, shallow goals could include clicks/opens on a mail, hours spent on app, etc., whereas deep goals could include net sales, profit, etc. Deeper goals are generally harder to track and measure. Hence, a tradeoff must be done while selecting shallow and deep goals to conduct a constructive experiment.

Experimentation is the most reliable technique of analyzing the impact of different treatments and understanding user behavior, although they generally cost more compared to an observational study and take longer to implement.

D) Personalization:

Once observational and/or experimental research is completed, the business will derive a greater understanding of the end user. The business can now cater to the needs of each individual user and personalize the features of the loyalty program based on his/her preferences/characteristics across different platforms.

Personalization can also be done by directly communicating with the customer through surveys, and regularly taking customer feedback. This will ensure customer satisfaction and increase the lifespan of regular customers.

Simple personalization techniques such as including the first name of the user in an email has generally had a high impact on the performance of the mail. Understanding the user demographic and tailoring the content of campaigns/offers addressing their needs is key to a successful loyalty program.

Conclusion

Customer loyalty in marketing can lead to retention, and successful programs help grasp the attention of the consumer by making the buying and selling process highly engaging. Companies looking to enhance their loyalty programs must leverage the power of data and analytics to drive personalization for customer loyalty programs as it will go a long way to enhance customer experience, thereby increasing profitability.

Using data to drive customer loyalty and retention

In the age of the digitally savvy consumer, it is imperative to understand the factors that drive engagement and retention to ensure customer loyalty. The rise of social media now provides a platform for customers share their experiences, both positive and negative. This gives marketers the opportunity to track online customer activity and develop strategies to keep the customers loyal to their brand. A data-driven design when it comes to a customer loyalty program can help brands go a long way. To find out how companies can tap into this data to improve their loyalty programs and offer an enhanced customer experience, please write into: sales@latentview.com

This site uses cookies to give our users the best experience on our website. By continuing on our website, you are agreeing to the use of cookies. To learn more, you can read our privacy policy.