Weighted Email Attributes

I'll use my headphone hobby as an example.

Weighting (you'll develop your own weighting scheme based on a regression model).

• 0-12 Month Purchases = 100% Weight.
• 13-24 Month Purchases = 60% Weight.
• 25-36 Month Purchases = 35% Weight.
• 37-48 Month Purchases = 20% Weight.
• 49-60 Month Purchases = 12% Weight.
• 61+ Month Purchases = 7% Weight.

Let's say a customer purchased two times.

• October 10, 2024 = $200 on in-ear monitors, $140 on a dac/amp.
• May 1, 2021 = $800 on open-back headphones.

Weighted spend:

• In-Ear Monitors = $200 * 1.00 = $200.
• Dacs/Amps = $140 * 1.00 = $140.
• Open-Back Headphones = $800 * 0.20 = $160.

Weighted percentages:

• In-Ear Monitors = 200/500 = 40%.
• Dacs/Amps = 140/500 = 28%.
• Open-Back Headphones = 160/500 = 32%.

On the surface, the customer spent 800/1140 = 70% of historical spend on open-back headphones.

Because the open-backed headphone purchase happened a long time ago, the purchase isn't weighted as heavily ... so it's "relevance" is 32% of past purchase activity.

You'd market all three categories to the customer, given that weighted history is mostly equal. And yes, you'd correlate historical weighted percentages with future activity to "know" that the weights are relevant.

Regardless, use weighted email attributes to personalize your assortment to each individual email subscriber.

Two Clicks

There's a nice hierarchy in email marketing.

1. Segment buyers by the Elite / Loyal / Quality / Average / Struggling / Lapsed framework.
2. Segment email subscribers by Inactive / 1 Click-Through Past Year / 2+ Click-Throughs Past Year / 1+ Email Purchase Last Year.

Overlay (1) by (2) and you have something!

Regardless how many email campaigns you send per week (or per day) clicking through two campaigns in the past year is a meaningful metric ... those are the email subscribers you focus extra effort on.

You've Probably Done This Already ...

... but I sense some in the audience would appreciate a refresher course.

Test:

• Group "A" receives all emails in the next month (i.e. 25 contacts).
• Group "B" receives some emails in the next month (i.e. 10 contacts).
• Group "C" receives no emails in the next month (0), though I realize some of you find this unpalatable, so you could make it a small number (i.e. 4, one per week).

Results:

• Measure total spend after a month, at a customer level.
• Group "A" = $25.00.
• Group "B" = $23.00.
• Group "C" = $20.00.

Adjusted Results:

• We adjust for the fact that the customer would have spent $20.00 no matter what ... that's the organic amount.
• Compared to Group "A", your organic percentage is 20/25 = 80%.
• Group "A" = $25.00 - $20.00 = $5.00.
• Group "B" = $23.00 - $20.00 = $3.00.
• Group "C" = $20.00 - $20.00 = $0.00.

From here, we can fit the relationship with a power function.

And you now know the amount of incremental demand/sales you generate at each number of contacts in the month studied. Also, yes, I understand that your analytics guru thinks this is a poor way to design a test and then measure results. No worries. It's important to be in "do something mode" in 2025.

Lost

There are many ways to tell if a marketing team is lost.

One of the most important metrics is new customers acquired vs. new customers needed to maintain flat sales (or whatever your sales goal is). If you aren't measuring this, you are already lost.

Meanwhile, we have email marketers. 

Here's how one brand treated me from 1/1 - 1/5.

• January 1 = 3 Campaigns.
• January 2 = 3 Campaigns.
• January 3 = 5 Campaigns, Including 3 Within 9 Minutes of Each Other.
• January 4 = 3 Campaigns, Including 2 Sent Within 1 Minute of Each Other.
• January 5 = 3 Campaigns.

That's 17 Campaigns within 114 Hours. One every 6.7 hours. Throw out 8 hours of sleep per day and they sent me one every 4.8 hours.

Of the 17 Campaigns sent within 114 Hours ... a total of zero (0) featured any merchandise above-the-fold. Zero (0). Every single message featured a percentage off, with anything goes between 30% and 60%.

This is where the email marketer typically emails me (see what I did there), suggesting they are not lost, suggesting instead that the Management Team is lost because the Management Team demands they send this cadence with this style of messaging. That's fine. But somebody is lost.

Now, it is possible that somebody A/B tested these ideas and these ideas worked best.

But if the cadence was not A/B tested? Then the marketer is lost.

P.S.: Yes, my teams executed email marketing campaigns back in the day, and they executed campaigns where, at any time, a store manager could request that their campaign trumped the e-commerce message ... and yes, at any time, four store managers could request that their campaigns trumped the e-commerce message and we had to prioritize which of the four store managers got to communicate to the individual customer. And if no store managers requested access to the customer, the customer received one of ten (10) possible campaigns, all ten with the same core marketing message but personalized with a different merchandise assortment based on prior customer purchases.

My team did this. In 2004 they did this. They were spectacular marketers/analysts. 

So do not tell me how "difficult" your email marketing job is, resulting in having to send three campaigns to me within minutes of each other communicating different messages. Your email service provider would LOVE the opportunity to execute something sophisticated on your behalf.

P.P.S.:  My best e-commerce clients generate about 30% of annual sales from email marketing, and their programs are not communicating sale messages with varying percentages off every 6-7 hours. You'll know when your email marketing program works well when you generate 20% to 40% of sales from email marketing. Generate less and your email marketing program isn't working well as it should. Generate more and the rest of your marketing program is not working as well as it should.

Not An Outpouring, But ...

I performed a Saturday test (click here).

Turns out that if I talk about Affiliate Marketers scamming you, you respond. En masse. Not an outpouring, but one of the larger post-COVID outbursts I can remember.

Your responses suggest that some vendors are out to mess with you, without regard for the health of your business.

The past year has been so darn fascinating. In catalog marketing, your paper/print partners messed with you. You didn't like that. Remember that feeling.

Yesterday, the e-commerce audience responded, loudly, with stories of being ripped off by digital vendors.

When you (unscrupulous vendors) scam my clients, how does that make you feel? When you buy a new Lexus because you siphoned off a portion of client profit for your own benefit ... by lying ... how do you sleep at night?

I worked in the vendor world for one (1) year, back in 2000, at a retargeting startup. My goodness. What a train wreck. While the company generally tried to do good for clients, the employees were all about stock options, and would do what the felt was "right" to boost the stock price so they could retire as a 28 year old. I have a patent for a product that I created in response to employees choosing to not serve clients, causing me to invent a competing product within my own company so that clients could benefit. I know a little something about vendor employees and self-interest, even if that knowledge is dated.

P.S.:  What's awful is that nasty vendors get all the attention. I had a video conference a few months ago with a catalog agency that keeps things quiet ... minimal publicity, working hard to do "what is right". Really good vendors are out there, folks. They just keep their good works quiet.

Greatest Twitter Marketing Thread Ever

Just read the entire thread ... every word (click here). Every word, please.

Don't have Twitter? I did you a solid ... here is the text. Everything that is wrong about digital marketing, corrupt vendors, and muttonheaded marketers at brands who can't be bothered to ask simple questions is on display here.

My team built the leader competitor to

@honey

This "scam" story is absolutely wild to me.

In his video today,

@MKBHD

makes two claims about Honey's foul play:

1. Honey effectively steals commissions from their affiliate partners by being the last to drop their cookie when a user checks out.

2. Honey's value prop to retailers is dubious since they are giving customers discounts on products they were already about to buy. So, why is this wild?

Because this is exactly how it has been since the beginning.

In 2016, I was at a startup that aspired to take on Amazon by consolidating every product on the internet via a Chrome Extension.

Turns out that's pretty hard to do, and after working at it for years, we were coming up short.

Our business team noticed another e-commerce Chrome Extension (guess who?) seemed to be making waves and growing fast. They dug in a bit, and while I wasn't in the room, I gather their reaction was something like this: They're getting paid HOW MUCH to do WHAT?! From the start, it sounded ridiculous. A user on the checkout page is at the bottom of the funnel. They are the highest-possible-intent customers. Right on the cusp of purchasing of their own free will. At full price. Of course consumers were loving it -- it was the closest thing to "free money" they could get.

But the retailers? Why the hell were they paying for this?

It all makes sense -- sort of -- when you understand how affiliate marketing works.

(Feel free to skip this part if you already know it)

The original purpose of affiliate marketing was to enable hardworking content publishers (like Marques) to get paid for referring customers to retailers (like Best Buy). (This is just an example, I don't know who he has affiliate agreements with, if anyone). It's a brilliant idea, and it makes quite a lot of the internet go round. It's largely done via "affiliate networks" -- companies like Rakuten, Impact Radius, CJ Affiliate -- who make it easy for retailers and publishers to pay and get paid.

It's quite obvious why Best Buy would want to pay someone like Marques (again, just an example) for referrals -- he *sends* customers who otherwise wouldn't be shopping right to Best Buy's door. That's value!

I'm not an expert on the history of Affiliate Marketing, but I gather it went roughly something like this:

1. Some time in the early/mid '90s: Affiliate Marketing invented.

2. Affiliate Marketing catches on like wildfire since it drives tons of new customers to online retailers and is much easier to measure ROI than, say, television ads. (Somewhere in here, Affiliate Networks are invented) 3. Online retailers begin hiring Affiliate Marketing Managers -- and even entire departments -- thanks to its overwhelming success. 4. Affiliate Marketing Managers are granted increasingly large budgets to spend on Affiliate Marketing initiatives. 5. ... < next section >

6. Honey is accused of massive scam

1. User lands on retailer (Macys, Foot Locker, etc) checkout page.

2. Chrome extension pops up, saying "We found N coupons. Want us to try them?"

3. User clicks "Yes."

4. -This one is critical- Chrome extension marks its territory by:

a) redirecting the browser with a retailer-specific affiliate link, or b) dropping a cookie, or c) running some custom javascript in the page.

Importantly, only one publisher can get attribution for a sale. And it's always the last one.

5. Chrome extension tries coupons, and applies the best one if any. 6. Customer finishes checking out (with their coupon discount, if applicable).

7. Retailer forwards sales data back to Affiliate Networks, who pay out commissions to publishers like Honey (and influencers like Marques).

So, why were retailers like Best Buy, Macys, Home Depot, etc paying Honey (and us) to give discounts to customers who were already about to buy a product at full price?

For us, the pitch was straightforward: "You're already paying Honey for it; why not pay us too?" (Thanks, Honey!)

But for Honey? The trailblazers?

In short: bad incentives, and incompetence.

Note: This is a bit of speculation on my part. I'm not referring to any one person or organization here -- this is broad strokes.

Here's how (I think) it went down:

Retailers set Affiliate Marketing budgets for the quarter or year. Their Affiliate Marketing teams are encouraged to spend -- if not rewarded for spending -- their entire budget.

Bonus points for discovering trendy new channels that customers love! Honey had a great brand, great user growth, and (I can only assume) a killer sales team. Some affiliate manager probably got promoted for bringing Honey on early! Honey's pitch? Something like: "Customers are more likely to convert (buy the product in their cart) when they've tried coupons first. It gives them confidence that they're getting the best deal!"

Note: This is a completely testable hypothesis...

I am 99% certain that Honey was *never* challenged on that claim by any of their retailers.

Why am I so certain?

In the throes of building our Honey competitor, I once asked our (absolutely killer) BD guy:

"How many retailers have asked you for hard data showing that trying coupons on the checkout page actually increases conversion rates?"

Those were data that we could easily collect. It's the obvious litmus test of whether we're adding real value, or if we're just parasites exploiting a (what we believed to be short-lived) loophole. His response? "One."

Thousands of e-commerce retailers paying us to try coupons on their checkout pages, and only one ever asked us to back up our central (dubious) claim.

It was site #537 or so in terms of priority. Boutique farm equipment reseller or something. The guy who asked was the CEO, if I remember correctly -- the kind of person who would actually care, or even think, to ask about ROI. Our BD guy's response to this CEO's more-than-reasonable request for evidence?

"Go pound sand!" (in so many words).

The crazy part about this Honey story coming out now is that we all saw it coming back in 2016.

Quite frankly, we thought this moment was so right-around-the-corner that we nearly didn't bother building the thing ourselves.

8 frickin' years ago. But we did, and we got acquired for it.

So did Honey, to the tune of $4 billion.

Innovation Responses

I asked readers to offer examples of e-commerce brands executing tactics that are "innovative". Based on my metrics, several thousand of you read the requests on LinkedIn and on this blog. Five responded. Here are the responses.

From LinkedIn: I don’t know how “innovative” this is — but the best ecom brands seem to proactively cultivate talent from within, rather than recruit from the outside as a first option. I’m surprised more DTC brands don’t pay more attention to player development (like sports teams).

From LinkedIn: See traq.ai for sales conversions and flow.space for growing CPG brands.

From LinkedIn (this one doesn't seem authentic): As a fellow e-commerce professional, I would like to acknowledge the innovative tactic of using AI-powered chatbots to improve customer service and increase sales. Companies like XYZ are leading the way in this area.

From Our Blog: Here we go: https://www.lavialla.com/. Product: overpriced, exchangeable Italian organic food sold by everyone else. Half jokingly. I have seen them telling their story and growing year over year while the products they sold were available for a fraction of the costs in any urban area. Or on Amazon, which they don't use. 

From Our Blog: I was shown the 'Your Style Assistant' (bottom left of home page) icon on michaelkors.com a couple of months ago. Its conversational Ai, allowing customers to input what they're shopping for, with results instantly served. It's provided by Dynamic Yield.  The use case I was shown: 

• I'm going to a wedding need a dress - statement dresses shown
• It's in Bali, do you have light weight dresses - relevant product shown
• Do you have any in brighter colours - relevant product shown
• Do you have any for under $200 - relevant product shown
• Do you have shoes to go with that - relevant product shown

A much more tailored, relevant, enjoyable shopping experience. I understand voice activation will be phase 2.