In order to target the right customers with the right campaigns RFM was developed in the 90s for catalog retailers. Today, we can use the RFM model in ecommerce to boost marketing ROI and retention.
The RFM Model was developed in the 90s by Jan Roelf Bult and Tom Wansbeek for catalog retail organizations. Catalog sales were the pre-cursor to the world of online retail we have now, and when we dive into the RFM model you will quickly see how relevant it is for retail entrepreneurs and even established retail organizations.
First of all, RFM is not a fad or gimmick. It's been around for decades, and has been proven to work. It was proven to work by Blattberg at al. in 2008 after an extensive study applying it to marketing databases. At the crux of the framework is Pareto's 80/20 principle. You've probably heard about the 80/20 rule. Where 80% of your results from from 20% of the inputs. Vilfredo Pareto was a pre-eminent Italian thinker, economist, engineer, sociologist and philosopher who first discovered this pattern. His 80/20 rule first came as a result of his studies which found that 80% of the land in Italy was owned by 20% of the population. He then did the same study in several other countries and found the same 80/20 rule. Long after Pareto, other companies have noticed other similar patterns, such as in software, Microsoft found 80% of the code can be written in 20% of the time; fixing the top 20% of the bugs can solve 80% of the errors. The same principle was also found to work in athletic training, where 20% of the exercises led to 80% of the improvements. It was also found that ~15% of professional baseball players produced ~85% of their team wins.
The RFM Model leverages this centuries long proven 80/20 pattern. It teaches us to focus on the 20% of the most engaged, highest paying, and more frequently buying customers in order to drive 80% of the results from targeted campaigns. This isn't to say we should ignore the bottom 80%, it's part of understanding the importance of focusing on certain segments over others. Let's get into it...
The RFM Model is a framework for determining customer segments for marketing and retention campaigns. It's a function of the following three factors:
Recency is a score between 1 and 5; 5 being the most recent and 1 being the least recent. Recency is significant because the more recent a customers interaction with your brand, the more likely they are at respond and engage. Additionally, depending on the product you sell, it's important to target and market to customers differently (i.e. product shelf-life, replacement cycle, available upgrades, etc).
Frequency is a score between 1 and 5; 5 being the highest frequency or orders and 1 being just 1 purchase. It's the number of orders that customer has placed. The more number of orders, the most we know this customer trusts our brand. The fewer, or just one (say over a lower Recency score), number of orders, paints a different trust or need profile for that customer segment.
Monetary is also a score between 1 and 5; 5 being the most amount spent, and 1 being the lowest spending (or $0 spender if it's an abandoned checkout or simply a newsletter subscriber). Monetary will likely be correlated somewhat with frequency, but it's still important to score it independently. For example, those customers with high R, low F, and high M, could be a potential "champion" customer and with the right campaigns could create extremely valuable retention.
Using the above three factors in scoring each customer helps us understand who is most likely to engage with a promotions. This is important because it helps us focus and maximize ROI from the most likely customers.
There are at least 11 segments we can identify through RFM. Although not all 11 are needed or worth actioning, for every business, some retailers may only need to know about 8, for example. The below diagram shows these 11 possible segments.
1. Champions - Reward them. Ask them for reviews. They can be early adopters for new products.
2. Loyal Customers - Up-sell higher value products. Ask for reviews. Ask for referrals, Engage with them; send them free gifts, pizzas, hand-written cards etc.
3. Promising - Offer subscription and loyalty programs. Provide recommendations. Ask for reviews. Send gifts, handwritten cards, etc. Make one-on-one personalized phone calls.
4. New Customers - Provide post-sale support. Give them early success, offer free gift cards. Start a one-on-one relationship.
5. Abandoned Checkouts - Provide pre-sale support. Start building a relationship. Learn their wants/needs.
6. Warm Leads - Reach out personally and provide proactive support. Learn about them and build a relationship.
7. Cold Leads - Reach out personally through email or SMS to revive interest. Learn about their passion/problem.
8. Need Attention - Make limited time offers. Recommend new products or services based on past purchases. Try to re-sell or cross-sell.
9. Shouldn't Lose - Win back through special offers. Talk to them, survey them, don't lose them to competitors.
10. Sleepers - Send personal emails and messages to reconnect. Provide helpful resources.
11. Lost - Try to revive interest with reach-out campaign, otherwise ignore.
Traditional marketing lends a lot of influence to email campaigns. The problem with the traditional way of doing this, for most small and medium sized retailers who don't have data scientists and statisticians advising them on customer segmentation, is the one-campaign fits all mentality. Most retailers will send the same email campaign to a customer who only made a $15 purchase 3 years ago, as the customer who just spent $200 last week. This strategy will only ever deliver the minimum possible results.
It's sad because of all the time and effort marketers, copywriters, and business owners put into crafting the perfect email, creating the perfect funnels, and aligning their websites and offers to fit these campaigns. You may have an email list of 10,000 customers, but non-segmented email lists may only get a 1.5% click through rate. Worse yet, only 2 people from that 10,000 email list even made a purchase. Was all that effort worth it just for 2 sales?
The reason should be clear as to why these mass one-size fits all campaigns don't work. Because each of those customers is different and has a different need and expectation of your business. Customers who are big spenders expect more exclusive offers and personalized attention. Customers who barely spend with you probably need more information about your company and why they should trust you with their bigger needs. Treating your VIP customers the same as your worst customer, isn't doing you any favors in terms of keeping the VIP customers happy and appreciated. Imagine if a customer has been spending $150 per month on your business for the past few months, but they keep getting $5 off coupons for a new product that are sent everyone. You're doing more to annoy your best customers and potentially losing more future revenue, in the hopes of driving repeat purchases from the 80% of your customers who barely spend anything anyway. If you fall into the above "sad story" then reach out to us, and let's get smarter...
Here are some benefits of applying RFM to your marketing:
As explained earlier, RFM will make sure the right customers see the right campaigns. A core tenant of online marketing is the "Three Ps" - the right Product, for the right Person, with the right Promotion. RFM enables you to do this.
With the right usage of your emails and targeted campaigns (let's not over do it with hundreds of messages a year to each customer) you will reduce lost customers, increase up-sells, increase retention, cross-sells, and word of mouth referrals. Why? Because relevant and personalization is the key to not only maintaining, but also to growing a customer-business relationship. What does this mean? More sales from existing customers, which means higher LTV. Also, returning customers have been proven to spend more and buy more frequently than new customers.
If you promote new products to the loyal and champion customers first, you will get better feedback, and more likely to drive more pre-sales. If you contact these two customer segments even before you start developing a new product, you'll know what your highest spenders want, and so you know you'll be building the RIGHT product for the RIGHT customers.
RFM will help you find customers who are in the sweet-spot of "potential loyalists". These are customers who are just shy of being labeled "Loyal" or "Champion" and so by focusing on this subset of customers with the right campaigns, the right personalized attention, and gratitude and appreciation for their business the more likely they will decide to buy again next time they need something. It's also a great customer to promote your loyalty program to, encouraging them to make another purchase.
Data can tell you which customers are likely to forget you. You might find that customers who go one year without making a purchase are severely unlikely make another purchase again. In this example, as a retailer you need to reach out before the one year mark and give them an offer they can't refuse in the hopes of bringing them back into your fold. These "at risk" and "sleeper" customers need special attention, and must also be surveyed to understand why they aren't buying. By surveying them you will learn what NOT to do.
Marketing campaigns have a cost. We all know Facebook and Google advertising has a cost, but so do emails and SMS. By sending the right message (engagement request) to your customer, you may send the same number of total messages, but the engagement from each customer is more effective. Also, you may decide that "lost" or "sleeper" customers are not worth marketing to, which saves the cost of sending messages to them as well. Using Pareto's rule here again. If we spend $100 on Facebook re-targeting ads, only $20 will result in 80% of the ROI. So if we can identify which customers are more likely to be in that $20 bucket, why not either just spend that $20 on them, or spend all $100 on a special campaigns for them and further maximize the ROI?
Don't be like the majority of small and medium retailers who do not fully understand their customers. And it can be hard to do, but RFM is an easy way to do this. It will help you discover new customer segments you didn't even know existed. You may discover a new category of customers you didn't know about before that you could cross-sell a new product to. Talking to different customer will also give you better ideas on what new product might sell well, or what website optimizations you should prioritize. You business rests on the shoulders of customers, so learning as much about them should be every retailer's highest priority.
We've laid out the basics about RFM in this post, but if you would like to dive deeper in the math and the formulas to model your own customer segmentation it would be worthwhile to download our self-serve RFM guide. If you would like help doing it or need to outsource the service completely (we can send you a monthly spreadsheet of all the customers in each segment, as well as the changes in each segment) just reach out and request the service here.