1.\u00a0What is RFM Analysis?<\/span><\/p>\n 2.\u00a0Analyzing RFM customer segments with RFM model<\/span><\/p>\n 3.\u00a0On the other side: recurring sad tale of email marketing<\/span><\/p>\n 4.\u00a0Advantages of RFM segmentation: Here\u2019s how RFM analysis becomes super useful\u2026<\/span><\/p>\n 5.\u00a0Proven effectiveness \u2013 Decades of academic and industrial research<\/span><\/p>\n 6.\u00a0Roots in direct marketing, database \/ catalog business<\/span><\/p>\n 7.\u00a0How to calculate RFM scores? \u2013 RFM score calculations simplified<\/span><\/p>\n 8.\u00a0Visualizing RFM data<\/span><\/p>\n 9.\u00a0Software\/ Tools for RFM Segmentation and RFM Analysis<\/span><\/p>\n 10.\u00a0Variations of RFM model<\/span><\/p>\n 11.\u00a0Applying RFM segmentation to your business<\/span><\/p>\n 12.\u00a0How to use RFM analysis \u2013 Practical strategies<\/span><\/p>\n 13.\u00a0FAQ\u2019s on RFM segmentation\/ RFM analysis<\/span><\/p>\n 14.\u00a0Summary of RFM segmentation \u2013 pros, cons, recommendations<\/span><\/p>\n 15.\u00a0Run RFM analysis and segment customers within seconds using Putler<\/span><\/p>\n What is RFM Analysis?<\/strong><\/p>\n RFM (Recency, Frequency, Monetary<\/strong>) analysis is a proven marketing model for behavior based customer segmentation. It groups customers based on their transaction history \u2013 how recently, how often and how much did they buy.<\/p>\n RFM helps divide customers into various categories or clusters to identify customers who are more likely to respond to promotions and also for future personalization services.<\/p>\n What is Recency, Frequency and Monetary analysis?<\/p>\n Valuing customers based on a single parameter is insufficient.<\/p>\n For example, you can say that people who spend the most are your best customers. Most of us agree and think the same.<\/p>\n But wait! What if they purchased only once? Or a very long time ago? What if they are no longer using your product?<\/p>\n So..can they still be considered your best customers? Probably not.<\/p>\n Judging customer value on just one aspect will give you an inaccurate report of your customer base and their lifetime value.<\/em><\/p>\n As you can gauge, RFM analysis is a handy method to find your best customers, understand their behavior and then run targeted email \/ marketing campaigns to increase sales, satisfaction and customer lifetime value.<\/p>\n That\u2019s why, RFM model combines three different customer attributes to rank customers.<\/p>\n If they bought in recent past, they get higher points. If they bought many times, they get higher score. And if they spent bigger, they get more points. Combine these three scores to create the RFM score.<\/p>\n Finally you can segment your customer database into different groups based on this\u00a0Recency \u2013 Frequency \u2013 Monetary\u00a0score.<\/p>\n Analyzing RFM customer segments with RFM model<\/strong><\/p>\n You can create different types of customer segments with RFM modeling, but here are 11 segments we recommend.<\/p>\n Think about what percentage of your existing customers would be in each of these segments. And evaluate how effective the recommended marketing action can be for your business.<\/p>\n On the other side: recurring sad tale of email marketing<\/strong><\/p>\n Consider this case\u2026<\/p>\n Carol has put up the perfect email newsletter \u2013 content, design, subject line, call to action, social media links\u2026 She sends out the newsletter expecting stellar conversion rates. Her mental math reasons that even if it converts at a \u201clow\u201d 10% rate on her 3500 customers, she\u2019d be richer by a few thousand dollars within hours.<\/p>\n Ten minutes.. half hour.. two hours..8 hours pass. But at the end of the day, it\u2019s only 1.5% people who clicked the link and a single sale.<\/p>\n Very disappointing, isn\u2019t it?<\/p>\n What did she miss out?<\/strong><\/p>\n Carol did everything perfectly,\u00a0except one \u2013 targeting.<\/p>\n She sent the same email to everyone.<\/p>\n I\u2019m sure you\u2019d agree:\u00a0different customers react to different messaging.<\/p>\n A price sensitive customer will grab a discount offer, but someone who regularly buys from you may get excited only about a new product launch.<\/p>\n That\u2019s the catch!<\/p>\n Instead of reaching out to 100% of your audience, you need to identify and target only specific customer groups that will turn out to be most profitable for your business.<\/p>\n We are leaving gold on the table\u2026<\/strong><\/p>\n Most of us are not even close to Carol.<\/p>\n Whether you are in online commerce, retail, direct marketing or B2B \u2013 most of us are so busy with daily chores that we don\u2019t spend enough time on marketing. Our marketing campaigns are hurried, fall short on copywriting, lack professional design, and we don\u2019t pay enough attention to tracking or improving conversions.<\/p>\n Of course, we wish to do all of that. But we don\u2019t.<\/p>\n What if we understood our customers a little better and sent them more relevant campaigns?<\/strong><\/p>\n I promise our success rate will be much higher.<\/p>\n Not only will we make more money, but our customers will also be happier and loyal.<\/p>\n Still not convinced yet? You will be in a few minutes.<\/p>\n Advantages of RFM segmentation: Here\u2019s how RFM analysis becomes super useful\u2026<\/strong><\/p>\n Sending a message tailored to the customer group will generate much higher conversions.<\/p>\n Isn\u2019t it obvious?<\/p>\n All marketing campaigns should pick up a target segment first, then create promotional material that will resonate with that audience, and then put the pedal to the metal.<\/p>\n Unfortunately, most of us don\u2019t do that.<\/p>\n That is where RFM Analysis is super useful.<\/p>\n RFM makes identifying customer groups easy<\/strong>.<\/p>\n The lesson so far<\/strong><\/p>\n RFM considers recency, frequency and monetary values for each customer. Combines them, and then groups them into different customer segments for easy recall and campaign targeting.\u00a0RFM analysis is super useful in understanding responsiveness of your customers and for segmentation driven database marketing.<\/p>\n RFM segmentation readily answers these questions for your business\u2026<\/p>\n Proven effectiveness \u2013 Decades of academic and industrial research<\/strong><\/p>\n RFM has a track record of decades. It\u2019s not a fad or a marketing gimmick. It\u2019s a scientifically proven process.<\/p>\n First of all, it\u2019s based on the\u00a0Pareto principle<\/strong>\u00a0\u2013\u00a0commonly referred to as the 80-20 rule<\/strong>.<\/p>\n Pareto\u2019s rule says\u00a080% of the results come from 20% of the causes.<\/strong><\/p>\n Similarly,\u00a020% customers contribute to 80% of your total revenue.<\/strong><\/p>\n People who spent once are more likely to spend again. People who make big ticket purchases are more likely to repeat them.<\/p>\n Pareto Principle is at the core of RFM model. Focusing your efforts on critical segments of customers is likely to give you much higher return on investment!<\/p>\n Roots in direct marketing, database \/ catalog business<\/strong><\/p>\n The concept of RFM was originally introduced by Bult and Wansbeek in 1995. It was used effectively by catalog marketers to minimize their printing and shipping costs while maximizing returns.<\/p>\n Rising popularity of computerization made it even easier to perform RFM studies because customer and purchase records were digitized. An extensive study by Blattberg et al. in 2008 proved RFM\u2019s effectiveness when applied to marketing databases. Numerous other academic studies have also approved that RFM reduces marketing costs and increases returns.<\/p>\n\n
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\n Customer Segment<\/strong><\/th>\n Activity<\/strong><\/th>\n Actionable Tip<\/strong><\/th>\n<\/tr>\n<\/thead>\n\n \n Champions<\/strong><\/td>\n Bought recently, buy often and spend the most!<\/td>\n Reward them. Can be early adopters for new products. Will promote your brand.<\/td>\n<\/tr>\n \n Loyal Customers<\/strong><\/td>\n Spend good money with us often. Responsive to promotions.<\/td>\n Upsell higher value products. Ask for reviews. Engage them.<\/td>\n<\/tr>\n \n Potential Loyalist<\/strong><\/td>\n Recent customers, but spent a good amount and bought more than once.<\/td>\n Offer membership \/ loyalty program, recommend other products.<\/td>\n<\/tr>\n \n Recent Customers<\/strong><\/td>\n Bought most recently, but not often.<\/td>\n Provide on-boarding support, give them early success, start building relationship.<\/td>\n<\/tr>\n \n Promising<\/strong><\/td>\n Recent shoppers, but haven\u2019t spent much.<\/td>\n Create brand awareness, offer free trials<\/td>\n<\/tr>\n \n Customers Needing Attention<\/strong><\/td>\n Above average recency, frequency and monetary values. May not have bought very recently though.<\/td>\n Make limited time offers, Recommend based on past purchases. Reactivate them.<\/td>\n<\/tr>\n \n About To Sleep<\/strong><\/td>\n Below average recency, frequency and monetary values. Will lose them if not reactivated.<\/td>\n Share valuable resources, recommend popular products \/ renewals at discount, reconnect with them.<\/td>\n<\/tr>\n \n At Risk<\/strong><\/td>\n Spent big money and purchased often. But long time ago. Need to bring them back!<\/td>\n Send personalized emails to reconnect, offer renewals, provide helpful resources.<\/td>\n<\/tr>\n \n Can\u2019t Lose Them<\/strong><\/td>\n Made biggest purchases, and often. But haven\u2019t returned for a long time.<\/td>\n Win them back via renewals or newer products, don\u2019t lose them to competition, talk to them.<\/td>\n<\/tr>\n \n Hibernating<\/strong><\/td>\n Last purchase was long back, low spenders and low number of orders.<\/td>\n Offer other relevant products and special discounts. Recreate brand value.<\/td>\n<\/tr>\n \n Lost<\/strong><\/td>\n Lowest recency, frequency and monetary scores.<\/td>\n Revive interest with reach out campaign, ignore otherwise.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n
![\"Pareto](\"https:\/\/mintea.blog\/wp-content\/uploads\/2021\/12\/pareto-principle.png\")
Pareto principle(this is one of my biggest business lessons)<\/p>\n