Successful eCommerce businesses that have been able to prosper in a cut-throat environment know what a treasure trove loyal customers can be. They toil hard to keep their existing customers coming back. There’s already enough proof that customer acquisition is way costlier and far more difficult than re-selling to an already existing customer base.
However, does that mean that 100% of existing customers demand equal undivided attention? Will all of those customer groups turn out to be the most valuable and profitable for a business? The simple and straightforward answer to this is ‘NO’.
Unfortunately, most new and naive eCommerce businesses crumble trying heedlessly to retain a large chunk of their customer base. In the process, they only end up getting crushed under the ever piling cost burden.
If you’ve just launched your eCommerce Shopify store or are planning to start up soon, hear this out loud – only 20% of customers can get you a whopping 80% of sales. Yes, the well-noted Pareto Principle applies to eCommerce sales too! The deal is that you must be able to correctly skim your creme de la creme customers from the rest.
Smart eCommerce merchants realize that there’s no sense in treating all customers alike.
That’s why they spend considerable time slicing and dicing data to get a clear picture of their most valuable customer segments. And, this is where they put 100% of their effort – on their best customers.
Instead of steering resources, time, effort, and money on trying to move random customers up the loyalty ladder, these businesses focus on retaining the right customers, right from the start.
Ok, but how do you do that? This is where a simple segmentation technique called RFM comes into the picture.
RFM segmentation – What is it?
Ready to delve deeper into RFM for eCommerce? Let’s start with defining what the abbreviation stands for. The term or the marketing methodology is an acronym for the three parameters that the model uses for calculating scores or ranks basis which you find out which are the best customers to get you good sales. As such, RFM stands for:
- R – Recency – How recently did a customer purchase from you?
- F – Frequency – How frequently does the customer purchase from you?
- M – Monetary value – How much on an average does the customer spend buying from you?
It’s important to note here that using only one of these parameters is insufficient for correctly identifying who your most valuable customers are.
Let’s say, you have a segment of people who’ve spent 3x more than all the other customers who’ve purchased from you in the previous month. Are they your best customers? Probably not! What if they don’t purchase anything from you next month, and for the next three months?
Scoring customers based on a single aspect can be absolutely misleading about their lifetime value. The power-packed RFM trio, instead, ranks customers based on three most important factors that determine the odds of them returning and repurchasing from you.
The upcoming section talks about how RFM for eCommerce can help you rank your ideal customers. Read on.
How RFM for eCommerce can help you identify your best customers?
So far so good. We know that in RFM three metrics or attributes are used for arriving at scores or ranks for different customers. However, are all these attributes of equal importance? How do you arrive at an accurate score to identify your best customers?
RFM for eCommerce sets pretty simple and straightforward ground rules for scoring customers. As per the model:
a) Customers who’ve recently made a purchase are more likely to revisit and repurchase from you than those who haven’t shown up for quite a while.
b) Those who buy from you more frequently are more likely to return and repurchase than those who buy from you once in a blue moon.
3) Customers whose order value exceeds the average, and those who spend more than the rest, are likely to buy again as compared to other segments.
Out of the three attributes – Recency, Frequency, and Monetary value, Recency is given the most weightage. What’s the logic behind this, you may ask. It’s simple – The longer the time-period that a customer stays dormant the lesser are the odds that he or she will return at all. However, recency alone won’t help you sift creme customers from the rest.
By definition, good customers are those who buy from you frequently. Think about the segment of shoppers who always like your products and offerings rating them four or five on five in reviews. Maybe these customers also really enjoy the kind of shopping experience you offer on your newly launched Facebook shop – say the ease of checkout, quick delivery, easy returns, etc. That’s what gets them coming back to you! As such, purchase frequency quite clearly reflects on the positive and motivating customer experience you are providing, and how well it is translating to customer loyalty.
The last connecting dot in the RFM models is how much a customer spends on an average when making a purchase. This metric or attribute helps you assign a certain weightage (basis light and heavy spenders) while calculating the total customer RFM score.
If a customer purchased very recently he gets a higher score (4- 5 on a scale of 0 to 5). If he/she is also a frequent buyer he gets a higher score on that metric too ( 4- 5 on a scale of 0 to 5). Average order value is higher than that of most other customers? ( That gets him/her another 4 or 5) on this metric. Combine the three and you have the final RFM score. This customer most definitely is the closest to what you’ll call an ‘ideal’ customer. Gryffindor for them, please!
Till now, we’ve detailed on how RFM helps you identify the best customers out of your existing pool. However, there’s a lot more to this technique. Not only can you identify your best customers using it but can even know which segments are the least valuable. Or, even figure out segments of fairly new customers who are contributing tremendously to your revenue base.
Once your segments are sorted you can run highly personalized and targeted campaigns for them. The underlying idea is to glean maximum ROI from each.
Different customer segments you can create using RFM
Here’s how you can go about categorizing your customers based on their calculated scores:
- Champions – Bought recently, high frequency of purchase, big spenders
- Loyals – Buy often, May or may not have bought recently, spend good amount of money
- Potential Loyals – Have purchased more than once but are fairly new customers. Spend a decent amount purchasing from you.
- Explorers – Recency score is high, however, frequency of purchase and purchase values are on lower end. They are still trying to figure you out!
- High spenders needing attention – As the name suggests – they might not purchase often, may or may not have recently purchased, but have spent the kind of money that calls for attention.
- About to go dormant – Recency score is 1 or 2, frequency score is 1, monetary score is below average.
- Lost – No more yours! This segment will show the lowest scores on Recency, Frequency, and Monetary Value attributes.
We’ve touched upon only eight segments that can be created using. You can, however, try out different permutations and combinations and can come up with more customer segments for your business.
These segments that you’ve just defined, using three very critical attributes for eCommerce, are pure gold on the table right before your eyes! It’s everything that you need to run smart, highly targeted campaigns, to retain your best customers. Given that the odds of selling to your existing customers are between 60% to 70%, focusing on customer retention using the RFM segmentation can make all the difference!
With this let’s get to discussing how you can actually put RFM segmentation into action, for your eCommerce business.
Your plan of action post RFM segmentation
You can do a lot with the RFM segments to optimize your ROI. All you need is a strong plan of action. Let’s help you kickstart with one, right now, using the following steps:
- Define your goal
Do you wish to promote your new product? Your best customer segment to get you the initial traction would be the ‘champions’ and the ‘loyals’. Not only will they help you with unbiased feedback on your new launch but will also happily recommend it to others if they really like it.
Here’s another example. Suppose you identify that the segment ‘high spenders’ do not buy frequently. Your goal for the next six months could be to get them to buy from more.
- Run targeted messaging for the required segment
This is the next step after having defined your goal. Create personalized messages to target the relevant segment, through one or more channels of communication.
For example, you could run targeted repurchase emails for ‘high spenders’, to make sure they don’t go dormant after their first few purchases. Keep working on this goal to see how it turns out for you in the next six months.
- Analyze and track results on your campaign
Continuously, keep an eye on the results your campaign or campaigns are fetching. It may be the case that despite being shown the best-personalized offers with highly targeted messaging, your high spenders are failing to reach the kind of recency and frequency levels that you want. Would you want to continue running campaigns for this segment? Maybe. Maybe not.
On the other hand, you may find out that a subset of your fairly new customers shows a high recency and frequency rate. You could use that to your advantage for sure.
What more can you do using RFM?
eCommerce marketer can run different campaigns for different RFM segments and experiment with them to see what brings in maximum ROI. You could, for example, use these segments and:
- Run loyalty programs
Combine the NPS score, Klout score, and RFM score of customers to identify ‘advocates’ who are also ‘loyals or champions’. Segment them as your ‘ideal customer base’ and run loyalty campaigns for them. VIP treatment offers like ‘super speedy delivery’ or ‘loyalty discounts on your fresh arrivals’ should be used without fail for this segment to get them feeling like royalty. Offer additional perks on winning referrals from them.
- Improve and optimize customer lifetime value
Have a segment with a 555 or 455 or 454 RFM score? The lifetime value of these groups of customers is very important to your eCommerce business. To improve customer lifetime value of these segments you can leverage up-sell campaigns, cross-selling, or by showing them personalized on-site recommendations of high ticket items, etc.
- Increase customer engagement with highly targeted messaging
We’ve pointed out before that having defined your segments neatly, you can run super-targeted campaigns with personalized offers, in no time. Want to make sure that those new customers who’ve been spending good money on buying from you come back? Follow them up with timely promotions based on their likes and purchase history, and they are highly likely to buy again. Most importantly, keep a watch if your campaigns are successfully raising the frequency and recency scores of customers in this segment. If not, rethink and optimize your strategy.
Software to your aid – Getting the most out of RFM for eCommerce
Impressed by how much RFM can do to get your customer engagement and retention strategy going? But, feeling overwhelmed thinking who’s going to do all the deep historical analysis and number crunching? Moreover, RFM analysis isn’t a one time deal. You need to keep updating and upgrading customers from one segment to another. Too much heavy lifting work, isn’t it?
Thankfully, intelligent RFM software tools are easily available to share the load. These tools help you make sense out of complicated transactional data so that you can instead focus on creating relevant marketing campaigns to up your ROI from each segment.
Your time, money, and effort are too valuable to be wasted on customers that aren’t going to get you any sales. Chase the right segments and you will see your business flourish even in the worst of times (doesn’t matter even when a pandemic is raging right outside your door).
There’s a lot you can do when you clearly know who your ideal customers are. Think about this – using RFM you can determine the incentive value threshold that will help you offer high spenders who have in the recent past abandoned their shopping carts vs. others shopping cart abandoners. This segment, which has order totals above the set average could be given comparatively bigger discounts to complete their purchase.
Intelligently put to use, RFM can help you build your eCommerce empire leveraging segments you create using customer purchase history. Ready to grow your eCommerce revenue by 3x to 5x? Don your RFM sorting hat!