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How to Measure Your Omni-Channel Loyalty Program Metrics?

An omni-channel reward program that works well can help you build strong, long-lasting ties with your users. But how do you know if your program really works? To find the answer, you need to know omni-channel loyalty program metrics.

In this blog post, we’ll show key metrics for omnichannel loyalty program performance that can help you gauge the success of your program. You can learn a lot about how customers act and find places where things could be better. Eventually, make your program work better.

Introduction to omni-channel loyalty in e-commerce

Traditional loyalty programs often limit rewards to one specific place, like a store or website. But omni-channel loyalty programs are different. They let customers earn and use rewards no matter where they shop – online, in-store, or on their phone. It makes shopping easier and more rewarding.

We have an article explaining Omnichannel Loyalty vs. Traditional Loyalty Programs

Key omni-channel loyalty program metrics you should track

To really know how well your omnichannel reward program is working, you need to keep an eye on the right measures. You can learn a lot about how customers act and how well your program is doing by keeping an eye on these key performance indicators (KPIs).

1. Customer Retention Rate (CRR)

Customer Retention Rate is one of omni-channel loyalty program metrics. In its simplest form, this metric means keeping your current customers happy and sticking with your brand, goods, or services over time. 

We will suggest some ways for you to keep track of your customer retention rates: 

1.1. Track membership longevity:

You can use loyalty program software to track the frequency of point accumulation and tier advancements. Also, tracking engagement metrics, such as redemption rates, purchases, and interactions with your brand.

Read more: 10+ Loyalty Programs Software For Small Business.

1.2. Tracking return visit frequency:

To track in-store visits, you can use loyalty card data or point-of-sale (POS) systems to track how often customers visit your physical stores.

To keep track of online views, you can use Google Analytics to see how often people go to your online store. 

Tracking store visits with Google Analytics feature.

By keeping a close eye on how many customers leave, you can make smart choices that will help your business grow.

2. Redemption Rate

Your redemption rate shows how many customers are actually using the rewards you offer. It’s like seeing how many people cash in their coupons at the grocery store.

Redemption rate = (Number of rewards redeemed / Total earned rewards) x 100
Redemption rate formula.

So, what’s a good redemption rate? Aim for a double-digit rate, somewhere between 10% and 30%. We think a 20% rate is often considered ideal. 

If your rate is too low:

  • Keep customers engaged by sending emails or notifications reminding them of their points and the cool rewards they can get.
  • Personalize your offers by using customer data to send tailored rewards and promotions.
  • Tiered rewards to encourage customers to reach the next level by offering exclusive rewards.

If your rate is too high, rethink your rewards. Are they too generous? Consider adjusting the point value or the rewards themselves.

When you make big changes, you should think about how your customers might feel about them. Know how to keep your return rate low so you can make a reward program that makes people happy and makes them want to come back for more. 

3. Repeat Purchase Rate (RPR)

Your Repeat Purchase Rate (RPR) shows how many of your customers make a second purchase. It’s a great way to measure customer loyalty and see if your strategies are working.

Here’s a formula you can use:

Repeat Purchase Rate = Number of Repeat Purchase Customers / Total Number of Customers
Repeat Purchase Rate (RPR) formula.

We recommend you figure this out to have all of your customer and order information in one place so you can divide the numbers by month and the amount you want to look at for your product, as shown in the picture below.

4. Average Order Value (AOV)

Average Order Value (AOV) is the average amount of money each customer spends when they come in. It’s not how much one customer spends over their lifetime but rather how much the average customer spends in a single visit.

AOV = Total Revenue / Number of Orders
Average Order Value (AOV) formula.

For example, if you made $1000 in sales from 100 orders, your AOV would be $10.

Here are some techniques you could consider:

  • Comparing AOV before and after the loyalty program. We think that business owners should look at AOV for at least one month before and after starting a reward program. This way, they can see how the program affects sales during different times of the year.
  • Divide customers into segments based on their loyalty tier or other relevant criteria. When you compare the AOV of different groups, you can see which ones respond best to the loyalty program’s rewards.
  • Tracking AOV over time to identify any significant changes that may be related to the loyalty program. For example, if AOV increases after a specific loyalty program promotion. It could be said that the promotion was effective in driving larger transactions.

A higher AOV directly impacts your Customer Lifetime Value (CLV). If customers spend more per visit, their overall value to your business increases.

5. Customer Lifetime Value (CLTV)

CLTV is the total amount of money a customer spends with your company over the course of their connection with you. How much money do you think a loyal customer will bring you over time? 

While there are several ways to calculate this critical metric, let’s focus on a simple yet effective customer lifetime value formula:

CLTV = Customer Value × Average Customer Lifespan
CLTV formula.

So, what makes a good CLTV?

Ideally, your CLTV should be far more than your CAC (cost of acquisition). A 3:1 CLTV:CAC ratio is a decent general guideline. Accordingly, you will make $3 for every $1 you spend on acquiring a customer. 

You can refer to our article The Ultimate Guide to Improving LTV:CAC Ratio.

Now, we will recommend some strategies to improve loyalty and profitability:

For personalized customer experiences:

  • Customized offers exclusive deals and discounts to high-value customers.
  • Personalized communication with customers through personalized emails, SMS, and social media messages.

Loyalty programs:

  • Create a tiered loyalty program to reward customers based on their spending and engagement.
  • Offer exclusive access to products, events, and customer support.
  • Incorporate gamification elements into your loyalty program to make it more engaging.

Excellent customer service:

  • Responsive support through multiple channels.
  • Support and deal with problems before they happen.
  • Train customer service agents to be empathetic and helpful.

Every time you talk to a customer, you have a chance to earn their trust and confidence. Use these chances to show how committed your company is to doing its best.   

Advanced methods for assessing omni-channel loyalty program metrics success

You can check the reward program using common methods. Advanced statistics, on the other hand, can tell you more important things. Advanced methods let you find hidden trends and make decisions based on data that will help you make your program better. 

Let’s look at some more advanced ways to analyze your reward program even more deeply.

6. Customer Segmentation Analysis

One way to divide people into groups is to look at what they have in common and how they behave. Through this process, they can find out more about what their customers want and need. That can help them come up with better ways to sell. 

Demographic segmentation

Demographic segmentation is a powerful tool for understanding your customers. While traditional methods often focus on age and gender, just showing our image below, we recommend you gain deeper insights by combining multiple factors.

An example of demographic segmentation.

For instance, customers can be segmented by life stage. It can reveal specific needs and preferences, such as new parents or empty nesters.

Behavioral segmentation

Behavioral segmentation is all about understanding how your customers interact with your brand. If you know how your customers act, you can make better reward programs that keep customers coming back.

Here are some key behaviors to track:

  • How often do they shop?
  • How much do they typically spend?
  • What products do they prefer?
  • How do they respond to rewards and promotions?

A high-end store that found that customers who bought items were much more likely to come back is a great example of this. With this information, they came up with focused marketing that gave extra points for buying accessories. Because of this, return trips went through the roof.  

Implementing segmentation strategies

These segmentation techniques don’t need to be difficult to implement. It’s easy to look at customer data and find useful information with today’s reward program tracking tools. You can make more focused and effective reward programs by using these tips. 

7. Net Promoter Score (NPS)

Net Promoter Score (NPS) is a simple but powerful tool to gauge customer loyalty. It asks a straightforward question: “On a scale of 0 to 10, how likely are you to recommend our product or service to a friend or colleague?”. By asking this question, you can quickly assess how satisfied and loyal your customers are.

The formula is:

NPS = (% of Promoters) – (% of Detractors)
Net Promoter Score (NPS) formula.

So, how do you analyze your NPS feedback?

Your NPS score is now found on a scale from 0 to 10. You can get a better picture of your customers’ comments by color-coding the NPS scale and dividing your customers into the following groups:

  • Promoters (9-10) are highly satisfied, loyal, and likely to promote your brand to others.
  • Passives (7-8) show they may or may not actively promote your brand and are susceptible to competitive offers.
  • Detractors (0-6) are at risk of churning and may even share negative feedback about your brand.

Take the role of a coffee shop owner who has a reward program. Net Promoter Score (NPS) feedback is something you get from your customers.

Scenario 1: High NPS

If your NPS scores stay high, it means that your customers are very happy with your business. Right now is a great time to:

  • Implement a tiered loyalty program with exclusive perks for top-tier members.
  • Using customer data to send tailored promotions and discounts.
  • Offer early access to new products or limited-edition items.
TANIT’s early access email example.

Scenario 2: Low NPS

If you receive low NPS scores, it’s a sign that there are areas where you need to improve. You can use this feedback to:

  • Analyze the feedback to pinpoint specific issues, such as long wait times or poor customer service.
  • Take steps to address the identified issues, like hiring more staff or improving training.
  • Provide discounts or free products to customers who have had negative experiences.

By letting NPS direct your rewards program and listening to what your customers have to say, you will strengthen your relationships, make them happy, and ensure that they will continue to return for a long period. 

8. Attribution analysis

Attribution is the process of giving credit to all the different connections that lead to a sale. In an omni-channel context, credit is very important for figuring out how each channel affects things.

Here are some examples of how attribution helps identify the most effective touchpoints:

  • Customer journey: A customer first sees an ad on Instagram. Then, they visit the website through a Google search and finally make a purchase.
  • Attribution analysis:
    • With last-click identification, the Google search button gets all the credit. As the last point of contact before the sale.
    • First-click attribution: Assigns 100% of the credit to the Instagram ad. As it was the first touchpoint in the customer journey.
    • Time decay attribution puts more weight on the Google search click as it occurs closer to the purchase.
    • Position-based attribution gives more weight to the Instagram ad (first touchpoint) and the Google search click (last touchpoint).
    • Multi-touch attribution gives credit to both the Instagram image and the Google search click based on how much they helped the sale.

The online store can find out which outlet (Google or Instagram) is best at bringing in customers by looking at these different credit models.

Common challenges in measuring omni-channel loyalty program metrics and solutions

Integrating data from multiple channels and touchpoints

The biggest challenge in measuring omni-channel loyalty program metrics is tracking customer behavior across multiple channels. This can include data from in-store purchases, online transactions, mobile app interactions, and social media engagement.

So, we recommend some solutions for you:

  • Install a unified customer data platform (CDP) to merge customer data from all channels. Google Data Studio is a good choice.
  • Use real-time analytics tools to gain immediate insights into customer behavior and program performance. You can do this through Google Data Studio using API technique.
Real-time analytics tools features.

Challenge 2: Ensuring data accuracy and relevance over time

Since customer habits and market trends change over time, it’s important to keep your information correct and up to date. Info that is wrong or out of date can make you think of the wrong things and make it hard to make smart choices. 

So, we recommend some solutions for you:

  • Regularly check data quality and identify any inconsistencies or errors.
  • Check your reward program on a regular basis to make sure it’s still in line with your business goals and customer wants.
  • To get rid of mistakes and other problems with the data, set up strong ways to clean and check it.

By dealing with these problems, you can get useful information from your omnichannel loyalty program metric. This insight can help you make decisions that will make customers happier and help your business grow.

Frequently Asked Questions (FAQs)

What’s the best way to measure omni-channel loyalty success in real time?

We recommend you leverage real-time analytics tools, such as Google Data Studio, to track key metrics across all channels. This is the best way to measure loyalty program performance.

How can small businesses affordably implement omni-channel loyalty tracking?

You should use reward programs that don’t cost too much and don’t break the bank. While still giving people fun benefits and making them more loyal to the brand without spending a lot of money.  

We have an article introducing 10 affordable loyalty programs for Shopify businesses.

If you run a Shopify store, BON Loyalty can be a solution for you. Starting at just $25/month, you can enjoy POS rewards, points end, email reminders, and analytics to measure customer satisfaction with omnichannel loyalty programs.

Conclusion

Although shopping is always changing, a well-run omni-channel reward program can help your business grow. By using ideas from data, you can give your customers more personalized experiences that connect with them.To stay ahead of the competition and improve your omni-channel loyalty program metrics. You use new methods like AI and machine learning as technology keeps getting better. Stay tuned for more tips on building a successful loyalty program right here on our blog.

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