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Is RFM still valid in the online world?

Years ago in New York City I was introduced to the concept of RFM modeling (recency, frequency, monetary value). I briefly met Donald Libey and sat through a discussion / presentation with him while he mopped his head with a handkerchief. He was very enthusiastic about the topic and worked up a sweat - I supposed the room and lights might have also helped. :) Ever since, I have been a fan of this approach to business and have found it to be exceptionally useful.

In my career, I have used RFM in many industries, have combined it with frequency momentum and extended it by adding "depth" metrics drawn from web site traffic. And yet, I pose the question today, is it still valid in the online world?


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There are no secrets on the web...and everything is on the web.

Wouldn't it be wonderful to have an app that let's everyone in the family know where everyone is, at all times and in all places. Parents would love it. Kids would hate it - especially the teenagers. And some spouses would never stand for it. This little marvel of an app could not only identify location but send timely and relevant messages to members of the family using location based data. Example, Joe stops at the gas station to fill up his car on the way home from work and instantly he gets a text message from his wife asking him to pick up a gallon of milk and bring it home.


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Can email delivery analytics help you market smarter to your customers?

Recently I reviewed some material from my early days in catalog marketing and magazine publishing. The context of "deliverability" back then, as it still is today in the physical world, was all about understanding the postal system. Things like sectional center facilities (SCFs), zip code sort, zip+5, carrier route coding, bar codes, containerization, in-plant post office, merge/purge reports and site-penetration were just some of the things that were used to make decisions about getting your catalog or magazine delivered to the right people on time.

All of that seems to have been stripped away when deliverability was netted down to one item: the email address.

Or does it?

Some marketers would have you believe this answer. Especially those that work for small to mid-sized companies; or those that handle small to mid-sized volumes of messages.

I am not convinced. It seems too simple and fundamentally naive.

Getting your message delivered to your customers at the right time and in a place where they are receptive (device / location / time of day, etc) still takes work - and lots of it.

Consider for a moment the following scenario:

Your company markets through a marketing automation provider. It could be ExactTarget, Pardot, Marketo, Unica, Constant Contact, Act-On, Genius, Lyris, Eloqua, InfusionSoft, Responsys, Hatchbucket, Sailthru and a host of others.

Next assume that you do not use a dedicated IP for your marketing but instead used a shared IP hosted by your provider. What happens if one of their customers sends out large volumes of email with deliverability rates (delivered to a valid email inbox) of 90% and Open Rates of .25% and click-through rates of .0025%?

How do the spam houses respond to your email when it comes from this same IP address and your deliverability is 99%, Open rates of 63% and click-through rates of 25%? Well, if your volume represents just 2% of the total volume being sent from that IP address you'll be treated like big volume sender that is on the same IP.

Clearly the scenario above suggests that a dedicated IP gives you more control over the reputation of that IP. This is a good thing.

But what about high volume mailers? Those that use one or more dedicated IP addresses?

Here are a few questions to consider that may be useful in making better marketing decisions based on delivery analytics:

  • Number of hops per email sent. What are the typical number of hops required to get your message to each of your users? Why would anyone care about this? If you're sending a high volume of messages that are time sensitive (think financial services or emergency alerts sent by government agencies) how many hops and how much time transpires during the delivery process could make a difference. In the old days of "snail mail" number of days in the mail was a big factor when aligning inventory management, labor resources and customer expectations. Although the time measurement may have shrunk into the range of nano-seconds, the same issues exists and delivery analytics need to be visible to the the marketing manager.
  • Site penetration details. How much value can your company derive from delivery analytics (e.g. number of messages delivered to an IP address and the physical location associated with that IP address; or number of messages delivered to a specific domain.) In the olden days, site penetration details from a merge/purge house could be extremely valuable in making profit & loss decisions at the point of mailing. The same may be true today based on visibility of resources across your delivery infrastructure (number of hops, internet exchanges, physical location of destination IP addresses, time of day delivery, sensitivity of content, etc.)
  • Load balancing across the internet. Most of the time we think about load balancing internal networks. What I'm suggesting here is load balancing your delivery infrastructure (not sending infrastructure) but the routes across the global internet in order to align resources in a fashion similar to the old days of snail mail. Granted I am speaking of high volume, time sensitive messages, but the tools need to be available to pull it off in order for the marketer to make highly informed decisions. And if the tools are available, then they can be scaled down to the masses.
If it sounds like I'm stretching to find a solution for a problem that doesn't exist consider that we increasingly live in a highly connected world with projections of living in a world of "big data" and the "internet of things" with services offered by "cognitive computing services." It doesn't take much to consider how useful infrastructure delivery metrics could be during national elections, stock market trading, commodities purchasing, social media engagement for broadcast sporting events (e.g. the Super Bowl), storm warning systems and a host other circumstances where triggered messages are time sensitive and require high volume sending.

As a marketer that works with many companies, large and small, the delivery analytics and how that information is integrated into the sending and delivery processes, simply does not leave me with a warm fuzzy feeling. Too often it's a black box experience. One where the vendor says "trust me." That's just not working for me. What about you?
Customer Lifecycle Metrics, Part 4: Convert, and Create a Customer

This article talks about the "customer lifecycle" but in realty the author is talking about "prospects." and the use of "conversion" metrics from a Prospect to a Customer. The lifecycle being talked about is BEFORE the person or company even becomes a "customer." My definition of a customer being someone that buys something. Meaning if they haven't given you money for your product or service, then they're not a customer.

We may be splitting hairs on this one, but Lisa still has some valid points and it's worth the read.

58 Emails and Counting...

A little more than 60 days ago I started tracking a $100M retailer to see how they manage their customer interactions. So far I have been disappointed. Especially since they are using the Eloqua platform and I have some familiarity with what it can do.

To make the point, here are a few actions I've taken and capabilities I have failed to experience:


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Does your customer journey start like this?

Recently I signed on to receive emails from a specialty clothing retailer - just to see how they do their marketing. What you see above is the result of my first 20 days of emails received. Notice that the Welcome Email came on day one, then a pause until day 7, then every day a new email. A few other things I'd like to point out:

  • No personalization exists in any of these emails
  • No dynamic content has been delivered
  • No gender specific offers

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London School of Marketing discusses the importance of conducting email marketing throughout the consumer lifecycle

It's refreshing to see the university crowd getting on-board with the idea of customer lifecycle marketing. Not that schools haven't previously been on-board, but the industry can use more marketing students coming out of school that have some concept of lifecycle marketing.

This is the 2nd article I have seen in recent weeks highlighting the usefulness of email marketing when applied to a defined customer lifecycle. Clearly this is not new to the marketing technology industry, but whenever 3rd party sources make the observation and emphasize the value of this typie of marketing, it is satisfying to those of us that have been practicing it for decades.


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Brands Set Rules to Manage Email Frequency

In the old days of direct marketing we called this recency, frequency and monetary value (RFM).  It is a highly useful technique and it's great that cars.com and others are applying it to frequency of email touch.  

The other method that is referenced we called, frequency momentum and again this is a highly useful technique but one that is rarely used.  It's too bad, because when frequency momentum is applied to "big data" it is exceptionally powerful.  Consider that mass x velocity = momentum and you begin to get the picture on what this one metric call tell us when dealing with "big data" customer files, transactional files, site traffic, etc.

"Who cares what they need-it's what they want that sells."

Many years ago, in the formative years of my career, this was one of the sage pieces of advice given to me. In truth, this goes against all the idealism that was poured into me in my tender youth. :)

However, there is some truth to this and it's important to reconcile with it in your efforts to constantly increase the economic exchange that happens as you work through the lifecycle of your customers. Let me illustrate with a few examples:


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Traditional campaign marketers fail when it comes to lifecycle marketing...

Unless they change their thinking and their behaviors.

Take a look at the ugly / simple chart above. Notice that a 5 day gap exists between each email in the campaign. Now consider that this drip campaign has 8 steps in the series. Simple math tells us that 40 days will pass before the prospect or customer passes through the entire series...

Years ago when I first started in direct marketing, one of the companies I studied was Reader's Digest. As I recall they used a 37 step renewal series. That's right, 37 steps! And they weren't mailing every 5 days. It took years to complete the series.

Why did they do this? Simple. They knew that it cost less to obtain an order by mailing their house file 37 times than it did to find a new customer that would buy that first time...

Sometimes marketers act as if the only answer they know is "more is better" and "faster" must be best of all.

This is foolishness...


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How Bank of Montreal has achieved one-to-one customer engagement - CMO Australia

Excellent view on transitioning an organization to become focused on the customer.  If you get only one thing - get this point:  The customer-centric approach also triggered a reorganisation of marketing in the last six months from a focus on product, to customer acquisition and lifecycle management.  Great products are wonderful, but they needed to be delivered to serve the needs of customers.  Focusing on the customer is the answer.

Customer Lifecycle Metrics: Nurture, Score, Repeat

Nicely written, Lisa Canon captures many of the reasons why marketing automation platforms are so popular. However, please recognize as you read through this, the metrics and reasons expressed can apply anywhere in the customer lifecycle. Remember, the customer lifecycle is all about the customer and metrics like those identified here, can apply to any stage of the customer's life experience with your company. Thy can occur as a Prospect, during Acquisition, Conversation, Penetration, Retention and ReAcquisition.


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Data-driven marketers are computer scientists? Or riverboat gamblers?

Way back when, in the early stages of my career I was told that my job was to be half computer scientist and half riverboat gambler. The trick was to figure which half, at what point in time and in what situation.

Teradata recently ran an ad in Forbes magazine with the headline, "Data-driven businesses outperform" and the sub-head of, "Becoming a data-driven organization is now a matter of survival in the market, because such organizations tend to outperform."

Oh really?


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Householding - is it a thing of the past?

Twenty-plus years ago when I started in direct marketing "householding" was a condition that every marketer with a database of any size had to deal with. For those that are too young to know what this is, let me explain:

Let's say you work for Sony and you want to market to Johnny Smith who lives at 123 Main Street, Toledo, Ohio. Johnny comes to a landing page, enters his name, address and email address into your nifty form and submits. He tells you he wants to receive email promotions and a catalog. Seems simple enough to interact with Johnny based on the information he provided.


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