The Relationship Between Customer Data and Loyalty Programs

As marketers creating better customer experiences stays at the core of all that we do. The idea is to make the customer's life easier and the key to that is data. Data helps companies understand their customers better and synchronize their products and services according to the needs of the customers. As customers, we don’t even realize how much data we are giving out to companies. All this data could be helpful for the company to customize its products and services to give you a better user experience, make better business decisions, understand its day-to-day operations, etc.

“With data collection, ‘the sooner the better’ is always the best answer.”

~ Marissa Mayer, IT executive and co-founder of Lumi Labs, former Yahoo! president and CEO

Types of Data 

A very common way of collecting data is through Loyalty programs but before we get into that let's understand the types of data companies collect.

First Party Data 

All the customer information that a company collects directly from the customer via multiple touchpoints comes under this category such as contact information, transaction information, web browsing data, loyalty data, etc.  

Second and Third-Party Data

Data that companies partner with or purchase to get come under this category such as audience data (likes, shares, etc), sociographic data, psychographic data, etc.

 Data Vs Loyalty

With the changing market dynamics, companies are moving in the direction of using customer data to gain customer loyalty. Loyalty programs are a great way to collect data and use the data to retain customer and their loyalty. It is a give-and-take relationship based on trust and understanding. But, collecting data could go in the wrong direction if not done systematically. According to Lia Grimberg,

 Let’s look at how ‘The Bay’ is successfully leveraging data to gain customer loyalty without losing trust through a presentation by Lia Grimberg. Lia is the Divisional VP, customer marketing at The Bay

‘The Bay’ Model

‘The Bay’ uses a 3-phase data analysis strategy where data is divided into 3 categories to analyze the impact of loyalty marketing on its customers and how it can be leveraged to gain loyalty.

• Descriptive Analysis- Understanding and interpreting historical data
• Predictive Analysis- Using descriptive data to predict future outcomes
• Prescriptive Analysis- Suggesting recommendations to achieve a certain objective

The company’s loyalty program is a great example of how data acquired and used correctly can lead to positive outcomes that impact the business at all stages of the customer funnel.

The Customer Funnel

Loyalty programs positively affect the customer funnel on all 4 touchpoints- 

Acquisition- Help lower acquisition costs by identifying the best channels and prospects 

Onboarding- Increase the reach which leads to higher engagement and lowers costs to reach customers 

Customer Affinity- Help in increasing spend, the share of wallet, margins, and returns on promotions 

Retention- Help in increasing customer lifetime value, reduces churn, and increases brand value  

4R’s of Loyalty Programs 

Recognition + Reward + Relevance + Relationship 

Recognizing the best customers and retaining them. Recognizing the next set of best customers and moving them to level 1. 

Using the tangible and intangible Reward systems as a medium to drive desired behavior.

Using the data acquired to customize products and services to stay Relevant 

Building Relationships to retain customers. 

Importance of Relevance  

According to statistics, 73% of customers prefer relevant brands. Customers expect brands to change with changing trends, incorporate trends, and personalize and customize their products and services based on previous purchase behavior and data. 

Imagine this if you buy a product online from a brand that you use often, would you expect that brand to ask for your email id, phone number, address, or card details every time? No Right? You would expect them to have these details already. The idea is to make the experience smoother and easier with every interaction. This is where relevancy comes in. Brands should use customer data to improve and incorporate changes for a smoother experience for their customers. 

The Case Study

Lia Grimerg offered a challenging case study as part of her presentation. As the loyalty manager of a department store that has a running loyalty and credit card program, our group was asked to use first-party data to determine 3 components. We had access to the loyalty data and e-commerce data to determine the target audience, products that can be offered, and promotions. The objective was to increase the frequency of one-and-done customers. 

Our group came up with the following recommendations- 

Target Audience- 1 and done Customers 

Products- Based on previous purchase patterns, seasonal products, most frequently browsed and searched products, products last purchased, cross-selling and upselling- Like salsa with nachos

Promotions- One single point card for customers that works both in stores and online, repeat purchase discounts, redeemable discounts, special student discounts, referral programs, cash back programs, click and collect discounts, and credit card discounts. 

It was great to see how all 6 members of the group came up with different recommendations using the same set of data. Every member had a different perspective on how to use the first-party data to retain customers. The same goes for brands as well. There are multiple ways to analyze data and incorporate changes but it depends on the brand's long-term strategy on how they do it. 

Loyalty marketing: Here for the long run

Well, it's safe to say that loyalty marketing isn't going anywhere soon. We live in a data-driven world and loyalty marketing is a strategy that helps acquire data and uses the same data to improve the brand's overall performance. A career in loyalty marketing seems to have a good scope in the long run. Not only is it interesting to play around with data but also interesting to see how that data can be used to move forward.  

I used to believe that brands like Netflix and Prime videos are not loyalty programs, but Lia, an expert on the subject proved otherwise. The fact that both these brands collect data and satisfy at least 1R of the 4 Rs of Loyalty programs makes them loyalty programs even though they charge their customers a fee.

With the interaction with Lia Grimberg, I got a better understanding of Loyalty programs and how data can be leveraged for the advantage of both the brand and the customers. As a digital marketer yet to make a mark in the industry it was inspiring to see Lia share her story and her journey as a marketer. I am even more encouraged to get into the field and use the knowledge I have acquired in a practical setting. 

Loyalty is what makes us trust, Trust is what makes us stay, Staying is what makes us love and Love is what gives us hope