Be Warned of the “Professional Plaintiff”

A client recently received the ultimate “shakedown” letter—claiming violation of the California CAN-SPAM law as a result of getting eight emails, demanding $80,000 in statute-mandated damages, yet willing to settle for $2400. Unfortunately, this has become a cottage industry. The California law has a private right of action that has been taken advantage of by a few noteworthy legal vigilantes. Their actions have created a template for the “shakedown.”

[Editor’s Note: Gary Hennerberg is traveling this week, but attorney Peter Hoppenfeld has stepped in to supply this week’s blog.]

A client recently received the ultimate “shakedown” letter—claiming violation of the California CAN-SPAM law as a result of getting eight emails, demanding $80,000 in statute-mandated damages, yet willing to settle for $2400.

Unfortunately, this has become a cottage industry. The California law has a private right of action that has been taken advantage of by a few noteworthy legal vigilantes. Their actions have created a template for the “shakedown.”

To add insult to injury, the “professional” victim opted-in herself for each of the lists that she claims issued a spam email. I’m fairly sure that she probably has a cyber-ambulance chasing attorney ready to pounce on a contingency basis.

What do you do?

The American Corporate Counsel Association has issued a white paper that is very helpful. Seems like the SPAM demand toolkit left out one key defense—if your ISP has reasonable processes in place to prevent spamming, the statutory damages in California are reduced from $1000 to $100 per occurrence.

Quoting my letter:

First, it is clear that you are following a textbook (albeit outdated) approach of a “professional plaintiff” under the California anti-spam law. Attached is a copy of a White Paper prepared by the Association of Corporate Counsel that clearly rebuts each and every point that you have raised in an attempt to coerce my client to pay you monies.

We are in possession of proof that you opted into a number of email lists as proof that these emails are not unsolicited. Even if unsolicited, all of my client’s emails contain compliant opt-out links and you have not elected to take advantage of that option.

The element of the California law that you conveniently ignored is Section 17529.8 which reduces the potential statutory damages to $100 per occurrence. Please note:

” … working with reputable email service providers (ESPs), advertisers can be more confident that recipients did opt-into receive commercial email. ESPs generally maintain or can produce evidence of each opt-in, in the form of IP address from which the consumer opted-in, date/time stamp of opt-in, and other information. {NOTE: ALL IN OUR POSSESSION.}

While plaintiffs may contest the veracity of such evidence in a proceeding, once the evidence is produced, the burden to show it is inaccurate generally shifts to the plaintiff [NOTE: WE ARE UNAWARE OF ATTORNEYS WHO WILL TAKE A MATTER ON CONTINGENCY WHEN THERE ARE BURDENS OF PROOF SUCH AT THIS.}

More importantly, statutory damages under the Code of $1,000 for each spam are reduced to $100 for each spam, when there is evidence that a defendant established and implemented practices and procedures reasonably designed to effectively prevent spamming. {NOTE: SUCH PRACTICES AND PROCEDURES ARE IN PLACE.}

Accordingly, we deem your demand a “shake down” and a nuisance, and to save time and expense offer you the sum of $800 in full and final settlement of this matter. No monies will be provided to you unless you agree in writing: that no Spam violation took place; to maintain the terms of this arrangement confidential; and to agree to a penalty of $10,000 if it is determined that in the future you are engaged in any attempt to assist others to assert this type of claim against my client.

The matter settled, but the complainer remained indignant. Unbelievable.

Key takeaways:

  • Have a complete understanding of the CAN-SPAM laws.
  • Use an identifiable “from” email, a non-deceptive subject line, include a physical address, provide for an opt-out link and remove people who opt-out within 10 days.
  • Even more importantly, if affiliates are mailing for you, make sure they “scrub” their lists against your Suppression list.

Good Luck All. It’s a jungle out there.

Peter Hoppenfeld is an attorney and adviser in the representation of direct marketers, speakers, authors, information marketers, “thought leaders,” entrepreneurs and domestic and international training companies and their founders. Reach him at peterhoppenfeld.com.

An ABC Introduction to Data Mining for Dollars: Slicing and Dicing Your In-House List for Profit (Part 2 of 2)

In my last post, I introduced the RFM method, an effective direct response strategy to slice and dice your list for better conversion rates. The “R” represented recency—how long your customers have been with you. Today, I’m going to talk about the other components of frequency and monetary.

In my last post, I introduced the RFM method, an effective direct response strategy to slice and dice your list for better conversion rates.

The “R” represented recency—how long your customers have been with you.

Today, I’m going to talk about the other components of frequency and monetary:

Frequency
This segmentation tactic is another way to break down your house list: by how frequently customers have bought from you. So once you’ve divided your list based on recency, you look at it in terms of your customers’ purchase behavior. First, you identify your multi-buyers—customers who’ve purchased more than one product from you. You then split this list further, segmenting out two-time, three-time, four-time (and more) buyers. Those who have bought from you most often have proven their loyalty and obviously like the products and services they’ve been getting from you.

So if, for example, you’re considering launching a new product with a high price point, these would be your best prospects.

Monetary
Finally, you look at your list in terms of money. One way to do this is to divide your list by the amount of money each customer has spent with you. You might, for example, assign a benchmark dollar amount, such as $5,000, $10,000 or more. Customers at that level make up your “premium buyers.” This is the group that has the most favorable LTV for your company. These are your “VIPs.” Once you discover who your VIPs are, you can design products or offers specifically for them. Let’s say you have some kind of exclusive—and expensive—lifetime membership club. You would market this to multi-buyers who also fall into your “premium buyer” category.

If you offer payment options to your customers, another monetary way to divide your list is according to the payment options they have chosen: monthly, quarterly, yearly, etc. This will help you determine the initial purchase tolerance of each group of customers and which ones may respond best to future price points. As you can see, by looking at your customers’ purchasing habits—recency, frequency and monetary—you can identify the best customers for certain products. And by offering a product to customers who are likely to want it, you can improve your conversion rates.

By using the proven RFM method and other data-mining techniques, I’ve seen conversion rates double and triple. I’ve also seen inactive subscribers’ open rates surge from 0 percent to more than 30 percent.

However, many companies that send emails don’t have the capacity for data mining.
Unfortunately, some smaller businesses or start-up companies typically cut robust email features and analytics for cost savings. Oftentimes, these companies save money using online email service providers that can certainly get the job done, but don’t offer segmentation tools that allow for list analysis, where you can dissect your database into subgroups or “buckets.”

So when you’re searching for an email service provider, try to project what your segmentation needs may be going forward and if data mining is a strategy that you’ll want to deploy.

Hot Tip! When looking at email marketing companies, make sure you ask if there’s a list segmentation or data mining feature that can easily be done through their email platform. Find out the level of segmentation capacity (how far the segmentation of data can be drilled down to); if certain segmentation features are a standard feature or an upgrade; and what those costs may be on a monthly basis. Sometimes it may be an additional fee, but will certainly pay for itself over time.

Some Email Industry BS We Should All Be Wise to by Now

Quick! Which email service provider has the best delivery rate? Don’t know? Neither do I. Let’s try and find an answer. According to a list put out by ranking firm topseos, Pinpointe On-Demand has the best delivery rate of 10 email service providers it ranked for January. Let’s just cut to the real problem with Topseos’ rankings list—that it mentioned ESPs’ so-called “delivery rates” at all.

Quick! Which email service provider has the best delivery rate?

Don’t know? Neither do I. Let’s try and find an answer.

According to a list put out by ranking firm topseos, Pinpointe On-Demand—as topseos referred to it—has the best delivery rate of 10 email service providers it ranked for January.

The company name is actually just Pinpointe, but let’s not quibble.

No, let’s just cut to the real problem with Topseos’ rankings list—that it mentioned ESPs’ so-called “delivery rates” at all.

ESPs don’t have delivery rates. Or they shouldn’t anyway.

Why? Because every major lever that affects whether email gets delivered to people’s email boxes is under the list owner’s control.

Email inbox providers’ spam filters have traditionally relied on three major metrics to determine whether or not email coming from a specific sender is spam: the number of spam complaints, the number of bad addresses a mailer tries to reach and the number of spam traps they hit.

And these days, ISPs are reportedly increasingly looking at engagement metrics—clicks and opens, for example, or lack thereof—to weed out unwanted mail.

All of the above-mentioned metrics are directly attributable to the sender’s behavior, not the ESPs’.

Yet, some email service providers tout their so-called delivery rates in their sales pitches.

For example, Constant Contact claims its delivery rate is 97 percent. But when one reads why its delivery rate is so high, it becomes clear

“We hold our customers to high standards with good email marketing habits and practices,” says a headline on the page touting Constant Contact’s delivery rate.

There is nothing wrong with Constant Contact touting high standards.

And this isn’t to say an ESP has nothing at its disposal that can affect delivery rates. For example, an ESP can affect deliverability by throttling-or sending the messages at a slower rate—so ISPs are less likely to block them.

Also some ESPs have better support structures in place than others. As a result, delivery rates can reportedly vary from ESP to ESP. But it’s not the ESPs’ delivery rates we’re discussing here. It’s the senders’ delivery rates.

This may sound like a ridiculously minor quibble. But referring to email delivery rates as the ESPs’ shifts responsibility for behavior that helps ensure high delivery rates from where it belongs—the sender.

Senders of commercial email must continuously be made aware that the responsibility for ensuring high email delivery rates lies mostly with them and there’s not an ESP in the world that can magically overcome the deliverability consequences of sloppy email address acquisition practices and poor list hygiene.

Attribution is the Word of the Day

I’ve just returned from a few days in sunny Florida, attending the Direct Marketing Association’s Retail Marking Confernce 2010, and the main takeaway I received from it was that multichannel retailers today are struggling with attribution.

I’ve just returned from a few days in sunny Florida, attending the Direct Marketing Association’s Retail Marking Conference 2010 (RMC), and the main takeaway I have from the event is that today’s multichannel retailers are struggling with attribution.

Attribution is determining which of your marketing vehicles is reponsible for generating consumers’ purchases. And it doesn’t have to be all or nothing. For example, a catalog and search can share credit for a sale.

While attribution in the retail world is often viewed strictly as a way to figure out which online marketing programs — e.g., search, affiliate or display, social media — are responsible for the most sales, it also refers to figuring out which sales channel (online or off) are bringing in the most dough.

It’s a tricky thing: Old-line catalogers at the event claimed catalogs drive more online sales than websites or search efforts. E-commerce guys, on the other hand, said websites are where sales occur, so attribution should be credited to them. Email marketers were in the mix, too. They believe email messages received by opt-in consumers are the main driver of in-store and online sales.

Attribution is even more important these days, as corner offices are closely watching marketing teams, who are operating with tighter budgets, to see if spending is being accurately assigned.

The issue of attribution was discussed in several sessions at the RMC. A preconference intensive session led by Al Bessin, a partner at multichannel direct marketing firm LENSER, for example, discussed how customer and transactional information from multiple sources, such as website reports, email service providers and order management systems, can help marketers figure out which channels are working to ensure they’re spending their marketing budgets in the best ways possible.

Attribution was also discussed by Chad White, research director at Smith-Harmon, a Responsys company, in his his closing keynote.

White correctly identified attribution as the missing link, citing an Epsilon study that found 33 percent of permission-based email recipients said they usually visit a brand’s website directly after receiving an email about that brand, instead of clicking on an email link. So, he said, “online conversions attributed to email may be undercounted by as much as 50 percent.”

White also discussed an attribution experiment performed by REI, the outdoor gear merchant. In an effort to test email attribution, REI withheld emails from a certain group of customers while continuing to send them to another, and began monitoring sales. When the test was completed, REI discovered it was overstating the impact of email on online sales since a good portion of customers still bought even without receiving an email.

However, White said, “after determining email’s impact on store sales, which email previously got no credit for, REI discovered that email contribution to total sales was actually twice the level of cookied sales.”

So what’s the answer? Which channel drives the most sales? It’s really hard to tell, and it’s not an exact science. Whether you’re at a large company that has the resources to institute an attribution modeling system or a smaller company that performs witholding tests, it’s still a crapshoot, in my opinion. How can you really know why a customer decides to buy something?

How do you handle attribution? I’d love to hear from you.