Ever feel like you’re throwing money at Meta and Google, but it feels like you’re just shouting into the void? We’ve all been there–staring at our ad dashboards, watching budgets disappear faster than free samples at Costco, while ROAS refuses to go beyond your break-even.

If this sounds like you, this one’s for you. There’s a way to make your ad spend work twice as hard and make your targeting precise with just a little bit of data magic. Well… not exactly magic; just math.

Enter RFM analysis.

RFM: A quick recap

If you want to know more about RFM Analysis, we’ve written a comprehensive article you can check out here. But don't worry. We'll cover the basics as we go. RFM stands for Recency, Frequency, and Monetary value. In other words:

• When was the last time someone bought from you?
• How often do they buy?
• How much do they spend?

Put together, these three factors tell you a lot about your customers. RFM assigns a score for each customer on a scale of 1-5. For example, an R score of 5 means the customer made a purchase recently, and a score of 1 means it’s been a long time since they made a purchase.

Do the same thing for frequency and monetary value, and you’ll end up with scores like (1,1,1) through (5,5,5). Something that looks like this:

You can create segments like:

• Champions: Recent buyers who buy often and spend big
• Loyal Customers: Consistent buyers over time
• Potential Loyalist: Customers showing promising signs of developing brand loyalty
• New Customers: First-time buyers within a recent time frame
• Promising: Recent first-time buyers with high spend
• Need Attention: Customers with declining engagement require immediate focus
• About to Sleep: Customers on the verge of becoming inactive
• Can't lose them: High-value customers showing early signs of disengagement
• At Risk: Previously regular customers who haven't bought recently
• Hibernating: Long-inactive customers with no recent purchases

Note: If you’re using a tool like Peel Insights, all of this is done automatically for you.

Each of these segments requires a different approach in your advertising strategy. And that's where the magic happens.

RFM and Paid Ads: A match made in marketing heaven

While Meta and Google Ads have solid targeting engines, they lack the insights that your business data is rich in. A blanket targeting strategy will only help you with reach, not conversions.

Bringing RFM data into the mix helps you divide customers into groups with their own traits. You’ll understand what makes them similar, what differentiates them, and most importantly, why they buy from you.

Suddenly, you're not just seeing a crowd; you're spotting individual customers, their habits, and their potential value and optimizing your ads based on hard data. Your ads will become laser-focused, budgets more optimized, and messages resonate better with your intended audience. Here’s what we’ll cover:

1. RFM for understanding your customers
2. RFM for customer acquisition
3. RFM for ad content optimization
4. RFM for budget optimization
5. RFM for seasonal and lifecycle campaigns

1. RFM for understanding your customers

Not all customers are created equal. Some are worth their weight in gold, while others... well, let's just say your resources are better spent elsewhere. RFM helps you figure out who's who. Having this understanding forms the foundational structure of your advertising engine.

The high-level analysis gives you a clear picture of what percentage of your customers are in good standing with your brand. When 55% of your customers are either lost or about to leave, there’s something that you need to improve on the product or business front. Maybe your customers aren’t buying/using your products as much as you’d like them to. Or maybe you haven’t built retention baked into your business.

If you’re using Peel Insights, you can get answers to some burning questions right from the RFM chart. Like:

• What’s the average number of days since the last order?
• What’s the average order count per customer?
• What’s the lifetime revenue per customer?

You can break these down based on individual segments depending on how deep you want to go into the analysis and your total audience size.

This initial analysis helps you fix these areas of concern and provides you with a set of baseline data that you might want to improve with your ads and other channels.
You can also dig deep into your champions and loyal customers, aka your best customers, and use filters like source, demographics, and first-purchase products to get a deeper understanding of them.

2. RFM for customer acquisition

If you’re using only demographics as opposed to interests, recency of visit, potential value, etc., that can severely impact your ad performance. When you combine the power of RFM with the targeting capabilities of Facebook and Google Ads, you're not just advertising – you're precision marketing.

Now that you know who your best customers are, it's time to find more like them. Here's how:

Lookalike audiences from high-value segments

Lookalike Audiences (or Similar Audiences in Google) are people who exhibit similar behavior to a list of people you can upload or create within the ad manager. Most brands do this by exporting a list of all their customers and creating audiences out of that. The problem with this approach is that you also bring a lot of your bad-fit or unprofitable customers into the mix.
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Instead, use your high-value segments like champions, loyals, and promising loyals to find more people like them. You can also combine this with the data from your Cohort Analysis to add more dimensions to your audience - like the most profitable ones, the ones with the highest repurchase rates, or the folks with the highest lifetime value.

Retargeting your customers

There’s a high likelihood that you’re only retargeting your site visitors with your Meta and Google Ads. However, you can also use RFM data to target customers who previously engaged with your brand. Let’s break it down.

Target your “About to Sleep” and “At-risk” segments with new products, limited-time discounts, and recommendations based on past purchases. You can also set up re-engagement campaigns for "Lost and Hibernating Customers" by reiterating your brand value, reminding them why they first made a purchase or offering them a discount or free shipping. Retargeting campaigns can also be set up for “One-time buyers” to incentivize a second purchase.

You can also use the same strategy to connect with your best customers. Like an upselling campaign for "Loyal Customers" and “Promising Loyals.” Since these people already love your brand, the chance of conversion is higher than other campaigns, leading to higher ROAS and a better bang for your marketing buck.

Pro tip: You can also use the same tactic by bringing your email audience (or any other channel, basically) into Meta or Google and connecting with your 60-day unengaged segment, for example.

3. RFM for ad content optimization

Diving deep into your high-value segments reveals where they came from and what message(s)  made them buy. It tells you which products are hits among your best customers.

If you’re only spotlighting your hero product in most of your ads, you may be missing out on a lot of revenue. Build campaigns that are geared toward recommending relevant, data-driven bundles and cross-sells.

You can also retrospectively look at past ads and landing pages that led to higher repurchase rates, profitability, and LTR (instead of just conversions) and reuse the same messages to target newer customers. Finding demographic and interest-based zero-party data commonalities helps you refine your messaging.

Let’s take a kitchenware brand for example. Say, your best customers are mostly home chefs who appreciate the quality and durability of your knives, double down on that messaging.

If you’re using Peel Insights, you can create an audience slice to map RFM segments and ad campaigns with LTR and AOV. Just make sure all your ad campaigns have proper UTMs.

You can also boost retention rates and lifetime customer value by optimizing ad content to address the needs and concerns of at-risk customers. This segment is a treasure trove of insights. Analyze their feedback, reviews, and customer support tickets and you’ll understand why they stopped buying from you and the primary reason for their disengagement.

With these insights, you can create ad copy that directly addresses their concerns and showcase curated offers that resonate with this segment.

4. RFM for budget optimization

When you start using RFM for audience creation and content optimization, your ads convert more effectively driving your ROAS up.

Knowing which customers are worth investing in and how to communicate with them will ensure your marketing spend is directed towards the highest return segments. But, that’s not it. RFM analysis can do more: it can help you optimize budgets more effectively.‍

Budget allocation

Brands are rarely profitable on the first purchase. If you place your CPC or CAC bids based on those calculations, your ads might not give you the best returns. Even if it costs a bit more to acquire future champions and loyalists, the potential LTR more than makes up for it. You can also allocate your budgets for segment-specific campaigns based on the LTR of those particular RFM segments.

If your RFM analysis shows that a typical Champion customer has an LTV of $1000, you can afford a higher CAC for campaigns targeting similar folks. You might set a target ROAS of 3 instead of 5 for these campaigns, knowing the long-term value will make up for it.‍

Budget saving

Use your Recency data to avoid showing ads to customers who've just bought from you. It saves money and prevents annoying your customers. You can also do the same for your lost customers (or add them to a separate campaign with limited budget).

Pro tip: You can export these customers and add it to a campaign exclusion list.

5. RFM for seasonal and lifecycle campaigns

By segmenting customers based on their recent purchases, buying frequency, and spending levels, you can tailor your seasonal offers for maximum impact.

• Offer early access to holiday sales for your most recent and frequent buyers while using attractive discounts to re-engage less active customers.
• Send exclusive seasonal products to your high-value customers, while lower-value customers could be incentivized to purchase with bundled deals to boost their purchases.
• A high frequency - low monetary (5,2 or 5,3 or 4,3) shows that they buy impulsively and more often but are sensitive to price. Use time-sensitive offers like a flash sale for these segments.
• Target your champions and loyals with premium, limited-edition holiday items. They’re likely to splurge on unique seasonal offerings.
• Use the holiday season to introduce a "second purchase" discount for your new customers, aiming to increase their purchase frequency.

RFM analysis can be a powerful tool in your seasonal marketing efforts. The additional data helps you create a more nuanced, personalized shopping experience. This not only boosts short-term sales during the holiday season but also fosters longer-term customer relationships and loyalty, setting the stage for success throughout the year.‍

Measuring success

The real success of your RFM-based targeting will reflect in all areas of your business. There will be a few telltale signs like your ROAS and conversion rates going up. Your CAC will be lowered. People from at-risk, hibernating, and need-attention segments will transition to more positive segments. Apart from this, your customer quality will be way better.

Here are some of the metrics you might want to keep an eye on:

• Average order value
• Repurchase rate
• Repeat purchase rate
• Average number of orders
• Re-engagement rate
• Re-activation rate

It’s best to break these down by segments to see where your ads are the most effective and which areas need optimization.

Creating RFM audiences in Meta

You can export all your customers and orders from your Shopify account, put it across multiple sheets, and analyze data. Once you segment your customers, export those individual lists into your Meta Ad managers to create audiences. Oh, and you’d be doing this every time your data gets updated. That sounds exhausting, doesn’t it?

That’s because it is.

If you’re using a tool like Peel Insights, all of this is ready and out of the box for you. Your RFM data is updated in real-time and your audiences are never obsolete. You can directly create these audiences in your ad manager directly from Peel’s dashboard–at the click of a button.

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‍Put your data to work

By understanding who your customers are, what they buy, when, and how much they spend, you can create ads that speak directly to their needs and behaviors. You can allocate your budget more efficiently, target your best prospects, and re-engage customers at risk of churning.

Ready to turn your customer data into a superpower? Give RFM analysis a try. Your ad performance (and your budget) will thank you.

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