Revenue growth powered by data, not your hunch.

Introducing the RFM Model: Eliminate segmentation guesswork and uncover clear pathways to maximize Email, SMS & Loyalty revenue Still relying on instincts to know which segments are driving the most revenue? Test your assumptions and reveal industry trends.
Want to understand your revenue opportunities?
Test your hunch and unlock benchmarks by industry.

Growth starts with knowing your customers.

Introducing the RFM Model: Automatically segment your customers and reveal clear pathways to grow Email, SMS, and Loyalty revenue. Test your knowledge of your customer segments. Get industry benchmarks.
Take revenue-driving actions.
Test your knowledge of your customer segments.
Get industry benchmarks. Take revenue-driving actions.
Introducing Yotpo’s Recency, Frequency, and Monetary Value Analysis
No-Lift Data Analysis
Yotpo's Recency, Frequency, Monetary model automatically calculates and populates directly from your order data.
Segmentation at Scale
Segmentation based on customer shopping behavior: Recency, Frequency, and Monetary spend.
Actionable Insights
Find your best customers or potential growth opportunities with new customers.
Build Better Campaigns
Get campaign recommendations or create your own to optimize revenue from each segment.
Enhance Flow Strategy
Automate engagement with timely flows or personalize existing flows with RFM data.
 
Introducing Yotpo’s Recency, Frequency, and Monetary Value Analysis
No-Lift Data Analysis
Yotpo RFM automatically calculates and populates directly from your order data.
Segmentation at Scale
Segmentation based on customer shopping behavior: Recency, Frequency, and Monetary spend.
Actionable Insights
Find your best customers or potential growth opportunities with new customers.
Build Better Campaigns
Get campaign recommendations or create your own to optimize revenue from each segment.
Enhance Flow Strategy
Automate engagement with timely flows or personalize existing flows with RFM data.

Yotpo’s RFM Model delivers understanding and action at scale

Data-driven segmentation
Analyzes shoppers based on their buying behavior, not assumptions. The RFM model analyzes transaction patterns to automatically place customers into actionable segments.
Proven value realized
Leverage trusted data methodology. Our Recency, Frequency, and Monetary value model consistently identifies your highest-value customer groups and opportunities for growth.
Personalize at scale
Move beyond insights to action. We provide ready-to-implement SMS, Email, and Loyalty touchpoints tailored to each customer segment optimizing revenue growth.

No more guessing which segments to target or what action to take next.

😴 Sleeping high spenders
🏆 Top customers
👀 Need attention

Sleeping high spenders

These customers have made infrequent, yet high value purchases in the past, but have not made any purchases recently. Stay top of mind for these valuable customers!

Goal
Recapture the attention of these high AOV shoppers.
Action
Create a high-touch campaign for this audience. Acknowledge past purchases by personalizing emails and offer values like free expedited shipping or bundled products for ease.
Result
Bring these shoppers back with a high AOV order and get further insight on their purchase behavior for future communication!

Top customers

These are your best customers! Customers in this segment have the highest spend, frequency, and recent purchases compared to other shoppers. Nurturing these loyal customers is crucial.

Goal
For your best customers, you want to maintain their loyalty and maximize retention. Treat them like the VIPs they are!
Action
Avoid generic messaging and service! For example, launch campaigns to nurture customer loyalty and exclusivity, by offering first access to new collections and sales.
Result
For most industries, this segment makes up 20%+ of revenue, just a 1% decrease in customer segment can drop store revenue by nearly 4%.

Need attention

These customers have previously made multiple purchases, but now they’re at risk of churn. Now’s the time to re-engage before it’s too late!

Goal
Prevent imminent churn by grabbing their attention and providing fresh value.
Action
Create a flow based on segment entry. Increase CVR potential by conditioning messages based on loyalty redemption eligibility and include personalized product recommendations.
Result
Success in bringing back just 20% of this segment for another purchase can result in revenue increase of a net new 2% revenue for the year.

Which customers are driving revenue for your brand?

First, put your assumptions to the test, then reveal RFM segment benchmarks for your industry.
Reveal Benchmarks

Power your strategy with data-backed insights

Unlock the potential of RFM data for your Email, SMS & Loyalty channels with actionable recommendations from industry experts.
Get the Strategies

Hear from the brands

How they level up with the RFM
Bullet
220%
more revenue
220%
more revenue
RFM lets us be strategic with discounts. With this knowledge, we achieved 220% more revenue per email and reactivated shoppers after 200+ days with our first RFM campagn.
Natasha Dabell
CRM Manager
Bullet
90x
ROI
90x
ROI
RFM identified a previously unknown audience we needed to re-engage; our targeted campaign achieved 90x ROI and double the typical CTR.
Katelinne Harner
Marketing Coordinator
Bullet
The RFM Model saves hours of manual work uncovering engagement insights. With the SMS, Email, & Loyalty data available, we can build smarter campaigns fast.
Anthony Geslot
CRM Manager

Your data is yours.
Why pay extra for it?

Leveraging your data shouldn’t come at an extra expense. With a direct connection to your Email & SMS channels, the RFM model and insights are free for all Email & SMS customers.
Do you know where your revenue is coming from? Which Segment Brings the Most Revenue?
Match the revenue % ball to the segment you think it belongs to Match the revenue % ball to the segment you think it belongs to
Top
Customers
7%
of Shoppers
Sleeping High Spenders
17%
of Shoppers
Regular High Spenders
12%
of Shoppers
Need
Attention
9%
of Shoppers
Your answers and industry benchmarks below
How'd your hunch perform?
Correct answers
Ball Segment
Ball Segment
Ball Segment
Ball Segment
Industry Insights
Revenue by segments breakdown
💄 Beauty
👗 Fashion
🍔 Food & Bev
🧴 Wellness
🏡 Home & Garden
Beauty
While Top Customers only make up 6% of customers, they contribute to 22% of revenue for most beauty brands, typically making an average of 5 orders a year. Loyal customers are the backbone of Beauty!
Top
Customers
Sleeping High Spenders
Regular High Spenders
Need
Attention
% of Customers
6%
18%
11%
10%
% of Revenue
22%
16%
19%
17%
Fashion
For fashion brands, Sleeping HIgh Spender segment makes up nearly 20% of their revenue, but customers typically only place one larger order in a year. The challenge: how do fashion brands bring these customers back?
Top
Customers
Sleeping High Spenders
Regular High Spenders
Need
Attention
% of Customers
5%
18%
8%
11%
% of Revenue
17%
18%
15%
20%
Food & Bev
Top Customers contribute to over a third of brand revenue, but this segment also represents the largest delta between customer share and revenue share. Top Food & Bev Customers are typically shopping every 20 days!
Top
Customers
Sleeping High Spenders
Regular High Spenders
Need
Attention
% of Customers
11%
14%
18%
6%
% of Revenue
37%
10%
25%
10%
Wellness
While it may seem like Regular High Spenders and Top Customers share similar purchasing behavior, Top Customers drive 30% of revenue in a year and place 7 orders on average. Hold on to these loyal shoppers!
Top
Customers
Sleeping High Spenders
Regular High Spenders
Need
Attention
% of Customers
9%
16%
14%
8%
% of Revenue
30%
14%
24%
14%
Home & Garden
Given the relatively low repeat purchase rate of Home & Garden overall, the two highest revenue-driving segments typically purchase 2x a year.
Top
Customers
Sleeping High Spenders
Regular High Spenders
Need
Attention
% of Customers
5%
17%
12%
11%
% of Revenue
14%
16%
21%
22%
Reveal your answers and industry benchmarks
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Drag the ball to the right customer segment
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