Posts Tagged ‘RFM Analysis’

The 4-Hour Customer Retention Workweek

August 17th, 2010

Timothy Ferriss, in his runaway bestseller The 4-Hour Workweek, describes how he transformed himself from being a miserable, unhealthy, workaholic, into a globetrotting, cage-fighting, tango-dancing, best-selling author. While most of us will never get to work 4 hours or less each week, we can learn a lot from some of the steps Ferriss took, specifically with regards to how we manage our customers.

Ferriss is the founder of BrainQuicken, who according to their website is the “leading developer and distributor of bioactive and pharmaceutical-grade neural acceleration products.” Before his short-week transformation, Ferriss worked around the clock, waking up at all hours to call on overseas customers, sacrificing his health and personal life in an effort to make his business succeed, until one day he realized he was miserable and depressed.

Being abused by your customers isn’t worth it

Begging bad customers to stay is a
bad strategy that many companies follow.

Once he reached rock bottom, he decided he had to change how he did business. Success simply wasn’t worth the price he was paying. He started by analyzing where his business was actually coming from, and realized that over 90% of his orders came from about 5% of his customers, and that the customers in the top 5% required very little maintenance. He was killing himself by trying to milk every last dime out of the bottom-feeders and complainers, customers that weren’t adding much to the bottom line. He quit calling on them, and most of them continued to order, but he didn’t care if they left. They weren’t contributing enough to count anyway.

Of the top 5%, a few of the customers were extremely squeaky wheels. Ferriss describes having “taken their browbeating, insults, time-consuming arguments, and tirades as a cost of doing business.” He let these customers know that if they wanted to fax in their orders, he would be happy to fill them, but that he would no longer tolerate any abuse. About half of these customers left, but the other half played by his new rules. He describes immediately feeling 10 times happier with minimal revenue loss.

Ferriss had about 120 wholesale distributors that he was dealing with, so he was able to analyze his data without sophisticated tools. The steps he followed:

  1. He organized his customers’ data
  2. He segmented his customers
  3. He decided how to treat each segment
  4. He acted on his decisions

Customer retention for customer files with millions of customers

If you have hundreds of thousands, or millions of customers, you can follow the same basic steps he took, but you will in fact need the help of data warehousing, analytical tools, and predictive models. Even so, the steps themselves are simple, and very similar to the steps Ferriss followed:

  1. Organize your customers’ data
  2. You will need to identify the different sources for customer data, including marketing, sales, and support databases (frequently several of each). If you have different divisions or have recently acquired another company, you’ll need to merge and deduplicate the records in these databases.

    Trying to run reports against your operational systems won’t work. You’ll bog down the systems that are needed to run your business, and you will be frustrated and confused by data that is designed for computers and not for humans.

  3. Segment your customers
  4. Once you have the data moved into an analytical application, you’ll need group them into meaningful segments. RFM Analysis is a great way to do this, and involves assigning a score to each customer for how recently (R) they have purchased, how frequently (F) they purchase, and how much they spend, or monetary value (M) of their transactions. Learn more about RFM Analysis for customer segmentation. Note that the segment a particular customer is in will change over time — this isn’t a one-time exercise.

  5. Decide how to treat each segment
  6. Most companies treat all of their customers the same, meaning they spend way too much time, energy, and money on bad customers, and not nearly enough on their good customers. If you have properly segmented your customers, you can do much better.

  7. Identify churn-ready plum customers
  8. Predictive analytics, when applied to your customer segments, can help you understand which of your best customers are going to leave before they leave. This is critical. If you reach out to these customers before they leave, you have a much better chance of addressing whatever issues they have. If you reach them after they have already gone, they will probably have a new supplier, and are probably too irritated with you to go back anyway.

  9. Act
  10. Execute the strategies you created in steps 3 and 4, communicating appropriately to each segment. Make sure that you A/B Test as you go, trying different approaches on subsets of each segment, identiying which of your actions has the greatest positive effect, and continuously refining your approach.

  11. Rinse and Repeat

The steps described here are not a one-shot fix. They are a process, and as each cycle of interactions takes place with your customer, if you continously measure what is happening, customer satisfaction, and consequently your profits and employee morale, will continously improve.

I’ve got 2 bonus steps for you, that aren’t customer retention steps, but that are low-hanging fruit if you are following the 6 steps above:

  1. Acquire more customers that look like your best customers
  2. Once you have properly segmented your customer base, profile the kinds of customers that make up your best segments, and target similar prospects for your customer acquisition efforts.

  3. Migrate unprofitable customers into your top segments

By applying the scores you’ve assigned to your customers historically, you can see what your best customers looked like years or months before they became your best customers. Find customers that you have today that match what your best customers used to look like, and cultivate these into your better segments.

 

Talk to different customers differently

July 2nd, 2010

Don Peppers of Peppers & Rogers spoke during an awards session at the Gartner Customer 360 Conference last week, and one of the things he talked about was the concept of speaking to different customers differently.

Use RFM Analysis to talk to your customers intelligently

This man swears loudly in front of children and takes advantage of your free wi-fi

Doesn’t Everybody Do This?

At face value, it sounds like a pretty silly comment. If you owned an ice cream shop, you would be very friendly to the polite, well-behaved, ice-cream loving, 7-kid family, but you would probably be a little less pleasant to the loud, inconsiderate man that swears into his cell phone at full volume, regardless of who is in the shop, and then buys a 50-cent soft drink so that he can use your free Wi-Fi all afternoon.

The problem is that you don’t own an ice cream shop, or if you do, you own hundreds or thousands of them, and the only way you can tell your customers apart is by looking at how they behave towards you through their interactions. These interactions might include what you sell them, how you market to them, and how they interact with you when they call a support line to complain about something.

Your best bet at knowing the appropriate way to interact with your customers is by combining these interactions with any other information you can gather about them, including where they live, their age, their birthday, as well as any other factors that may influence what you should be saying to them.

This first step of getting all the data together is a big one, and if you have a data warehouse, you may be well on your way to having some or all of it.

Once you know all there is that you can know about your customers, you need to segment them, allowing you to talk to them in the right way at the right time. You probably won’t have a swearing, wifi hogging segment, but you will be able to identify undesirables and desirables if you go about things in the right way.

Behavioral Segmentation

RFM Analysis is a powerful tool that can help. RFM stands for Recency, Frequency, and Monetary value. It is sometimes referred to as RFI, where the “I” stands for intensity, which is the term Ralph Kimball prefers. (Ralph Kimball is responsible for designing and evangelizing a special database structure that allows fast, understandable access to vast amounts of data.)

Recency

You assign each of your customers a score, typically from 1 to 5, based on how recently they have purchased from you. A score of 1 indicates somebody who has never purchased, and a 5 indicates somebody who purchased very recently.

Frequency

You do the same thing here, assigning a score based on how often a given customer buys. If they buy every day, or week, or year, depending on your business, they will be a 5. If they purchase once or twice in an unpredictable way, they might be a 2.

Monetary Value

Finally, give each customer a score based on how much they spend.

This RFM segmentation, or customer behavioral segmentation, gives you 125 segments. Here are a few of the incredibly valuable things you can do with these scores:

  1. Customer Retention:
  2. Identify which of your “plum” customers are at-risk of leaving. You can feed the segments that contain your best customers into predictive models that can use patterns of good customers that have already left to identify others who are exhibiting similar behavior while there is still time to save them.

  3. Customer Acquisition:
  4. Look back in time at your good customers and identify what they used to look like. Go after prospects that fit the mold.

  5. Customer Migration:
  6. Using a similar approach to step 2, look back in time at what your best customers looked like when they weren’t all that great. Find customers who fit that mold and identify what works best to move them quickly into “plum” status.

  7. Customer Pruning:
  8. You don’t want that swearing, Wi-Fi hog. He’s taking advantage of your excellent service, damaging employee morale, while costing you money. If you know who he is, you can change the rules so that he either becomes a good customer or leaves.

All of these are examples of how you can talk differently to different customers. There are many other examples, but in all cases you have to know who they are and what makes them different before you can determine what you are going to say to each of them.