While Shopify is the platform where you make sure everything works properly from an operational point of view, Reveal is the Shopify app that helps you optimize customer lifetime value with features that allow you to perform a deep analysis without wasting hours on manually aggregating data.

In a world where everybody seems to focus more on mastering ad spend than keeping valuable customers close in the long term, Reveal was developed as a solution for eCommerce businesses that want to generate growth by optimizing the customer lifetime value.

What is Reveal?

Reveal can be broadly defined as an app that uses automated RFM segmentation and transforms all of your first-party data into valuable insights to help you increase customer loyalty, improve Customer Lifetime Value and maximize Return on Investment.

In a sentence, Reveal is the first Customer Value Optimization software for Shopify Merchants.

What is Customer Value Optimization?

Customer Value Optimization (CVO) is a process that implies analyzing first-party data and using the generated insights to make adjustments across all touchpoints in the customer journey.

Using CVO helps you achieve multiple goals. The information you gather about your customers in this process contributes to:

  • Improvement of customer loyalty and increase in loyal customers;
  • Generating more frequent acquisition;
  • Increasing average order value and Customer Lifetime Value (CLV).

This process helps eCommerce organizations become customer-centric and provides teams with Key Performance Indicators that reveal the next steps for sustainable growth.

Accurate customer segmentation through automated RFM analysis

The power of Reveal lies in the clarity that RFM segmentation brings to your eCommerce businesses after an automated RFM analysis.

Before we explain how Reveal does this automatically, let’s make sure all the terms are clear.

  • What is RFM?

RFM is defined as a strategy that helps companies understand and analyze their customers by using three variables: Recency, Frequency, and Monetary Value.

  • What is RFM Segmentation?

RFM segmentation helps companies group customers into different segments depending on their purchase history: when they made the latest purchase, what is the average purchase frequency, and the average value of their order.

  • How does Reveal generate RFM analysis automatically?

Reveal uses historical data in your Shopify store to assign a score from 1 to 5 (1 being the lowest) for Recency, Frequency, and Monetary Value. 

Here’s how your first-party data from Shopify is processed by Reveal through automated RFM analysis:

  • First, it identifies the minimum and maximum values for RFM in your store. 
  • Then, each customer receives points for each RFM variable based on the buying patterns.
  • After the points are assigned, each customer receives a unique score, one that will constantly change based on the customer’s interaction with the store.
  • Once the initial RFM analysis of your customer base is done, Reveal automatically groups your customers into 11 distinct RFM segments.

Inspired by different stages of love life, the names of Reveal’s RFM segments reflect how good you are at keeping your existing customers loyal in the long term and how healthy is the relationship between your brand and each of your customers.

Customer count (aggregated view in Reveal)  

The default names that we gave to the 11 segments in Reveal are Soulmates, Lovers, New Passion, Flirting, Potential Lovers, Platonic Friends, About to Dump You, Don Juan, Ex-Lovers, Apprentice, Break-Up.

You can change the names of the RFM segments so they are intuitive for everybody in your company.

How can Reveal enhance your basic Shopify Reporting?

Now that your customer base is properly segmented, you’ll get an in-depth understanding of your business with data visualization that clearly emphasizes what you need to do next.

No more guessing, no more manual work to get important metrics and correlations between those metrics. Every report in Reveal includes actionable insights so you can achieve customer-centricity, an approach that generates sustainable growth.

Lifetime Value calculated automatically

Reveal makes you forget about complicated LTV formulas or LTV calculators, and wondering if you got this important prognostication right.  

Customer Lifetime Value is generated automatically once Reveal is integrated with your Shopify shop. Under Lifetime Value reports you will find:

  • Aggregated and timeline representations of predictive CLV and historical CLV
  • Predictive customer lifetime (expressed in years)
  • Aggregated and timeline representations of predictive CLV and historical CLV by RFM group

Here’s the difference between Predictive CLV and Historical CLV:

  • Predictive CLV is calculated based on several different equations, so it takes into account multiple factors, such as the Average Customer Lifespan, Customer Retention Rate, Profit Margin per Customer, the Rate of Discount, and the Average Customer Value per period. These metrics are computed based on the data spanning 1 year behind (relative to the month for which the CLV is being calculated). 
  • Historical CLV is calculated as the sum of all revenue produced by the average customer, since the first order of the shop and until the end date of each period from the graph.

You won’t need any other tool to calculate Customer Lifetime Value when you’ve got it as an integrated feature in Reveal.

Retention Analysis

The insights you can find in the Retention reports category help you identify how good your company is at creating long relationships with your new and existing customers. 

Reveal helps you see beyond the Returning Customers report in Shopify. As your business is analyzed based on the RFM model, you’ll find more than the value for the customer retention rate:

  • Revenue versus Margin by Customer Type (first-time customers versus repeat customers)
  • Revenue versus Margin by RFM group
  • Average Retention Rate
  • Chances to Place Next Order (the potential for a customer to place another order according to your historical data)
  • NPS Score
  • Customer Distribution 
  • Retention Curve
  • RFM Segmentation (Customer Count, Margin, Revenue)

You’ll need the metrics in this section to decide how exactly you should adjust your marketing strategies to generate healthy growth and more loyal customers.

Retention reports in Reveal

Customer Segmentation Analysis

The customer count report reveals the number of customers assigned to each of your RFM groups. Having an accurate image of how your customer base is distributed is the starting point of improving your retention strategy.

Customer count (aggregated)

The timeline view helps you see how each RFM segment evolved during a selected period. Is there a drastic increase in a problematic customer segment? You definitely have to dive deeper into analyzing what’s causing that trend.

Customer count (timeline)

The aggregated view of orders count helps you see which of the groups make the most orders and which make the least orders. Compare this metric with the customer count and you’ll notice that Soulmates (the most valuable customers in your RFM distribution model) represent a small percentage of your total customers, but generate a significant amount of orders. You’ll want to focus your customer acquisition efforts on targeting an audience with similar characteristics to your Soulmates segment.

Order count (aggregated) 

The timeline view of order count helps you see how purchase behavior changes over time. You might identify significant fluctuations or seasonality as a general trend for your eCommerce store and you can be more prepared for the next season.

Order count (timeline)

Now that you know how customers are distributed across RFM segments and how many orders each group generates, you also want to know the revenue and margin for each group. This calculation helps you identify which customer segments are more valuable to your business.

Revenue vs. Margin by RFM Group (aggregated)

In the Segments section, you can also analyze Revenue and Margin separately, with aggregated and timeline visualization for each RFM group. 

Revenue by RFM group (aggregated and timeline) and Margin by RFM group (aggregated and timeline)

Revenue Analysis

When it comes to revenue analysis, what Reveal adds to the basic Shopify Reporting is showing you how revenue is distributed across customer segments. 

Stick to the Revenue section in Reveal and you’ll find all the data you need to identify the most valuable customers and items to your business:

  • Revenue versus Margin by Customer Type
  • Revenue versus Margin by RFM Group
  • Top Customers
  • Top Brands
  • Top Products
  • Top Categories
  • RFM Segmentation (Customer Count, Margin, Revenue)
RFM Segmentation (Customer Count, Margin, Revenue)

These metrics help you focus on the RFM segments and products that have the highest chance to generate better profits. 

Customer Satisfaction and Customer Experience

Reveal uses Net Promoter Score (NPS) to analyze customer satisfaction and customer experience. In the Customer Voice section, you can see the pre and post order results for various metrics (aggregated and timeline):

  • General NPS
  • NPS per Brand
  • NPS per Category
  • NPS per RFM Group
  • NPS per Customer Attribute
  • NPS per Order Attribute
Net Promoter Score

The aggregated view of the NPS per RFM Group shows you the NPS score given by your customers based on the RFM group they belong to.

NPS per RFM Group (aggregated)

In the timeline view, you can analyze how the NPS evolved over time and it gives a hint about where you should look for problems in your customer satisfaction/ experience efforts.

NPS per RFM Group (timeline)

New customer information in your CRM

Synchronizing Reveal with your Shopify store will add new customer tags to your customer profiles:

  • RFM Group Name
  • RFM Score
  • Margin
  • Average Days Between Transactions

This new data that is added to your Shopify CRM is extremely valuable for your marketing team and will allow you to make more personalized offers and get prepared for their next move. You can use customer tags to customize their experiences on your site, the offers that you’re showing them, emails that you are sending and the ads that you are creating as a Shopify merchant. 

Connecting Reveal with EXPLORE allows you to automatically match your RFM groups and trigger a survey using the dedicated builder. 

Reveal’s integrations with Klaviyo or Sendgrid allows you to automatically send NPS surveys to your customers.

CRM section in Reveal

Buying Habits

Reveal allows you to perform a custom analysis of your customer’s buying habits depending on what you want to find about their behavior. 

You can perform searches using multiple variables:

  • Product ID/ SKU
  • Brand name
  • RFM Group name
  • Order count
  • Customer count
  • Revenue
  • Margin
  • Pieces

You can use this feature to better understand the correlation between these variables. The generated insights are vital to the accuracy of your customer behavior research. 

Product Performance

In Reveal, Shopify merchants find three sections dedicated exclusively to the product assortment performance:

  • Product Returns
  • Brands
  • Catalog

The Product Returns section helps you discover what generates dissatisfaction in your RFM segments and what brands and categories are problematic. The metrics in this section are Order return rate, Order return count, and Order return split. You can see each of them as aggregated and timeline values. Each metric is analyzed by customer type, by RFM group, by brand, and by category.

Order Return Count by RFM Group (timeline)

In the Brands section, you can see the NPS obtained by each brand in your assortment, the order return split by brand, and the top brands by order count, customer count, revenue, and margin.

NPS by brand (timeline)

The Catalog section helps you identify what products and categories are generating the best performances, the most returns, or the most satisfied customers. Analyze your catalog using reports in this section: top products, top categories, NPS by Category (aggregated and timeline), and order return split by category.

NPS by Category (aggregated)

Cohort Analysis

The cohort analysis report in Reveal shows you how good you are at retaining new customers over a selected period and helps you identify which strategies are more efficient in retaining customers, not only in customer acquisition.

This customer analytics feature in Reveal allows you to analyze repeated orders by year, by month, or by week. So, if you know that you’ve been running different promotions and campaigns to retain customers in the last 3 months, you can find how well they performed in terms of revenue, margin, order count, and customer count.

Cohorts by First Purchase Moment (customer count)

How to install Reveal on your Shopify Store?

Reveal platform is available in the Shopify app store and if you want to install it right now, just click here.

The integration is very simple and you need a minimum configuration of your store details (such as your average margin or managing guest accounts) before you can start using the platform.

Until all your data is generated in your Reveal reports, it can take from 5 minutes to several hours due to high volume of data.

This Customer Value Optimization tool makes the most out of your first-party data without affecting your dev team’s workload or your store’s speed performance.

Getting started with Customer Value Optimization

If you want to book a demo customized around your eCommerce business, our colleagues are happy to set a walkthrough so you can get an in-depth understanding of our CVO tool.

If you’re ready to try it for free, go to our Shopify app page and integrate REVEAL into your store!

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