Segmentation

Dueling data

One of the things I miss about being in science is the regular discussions (sometimes heated) about data and experimental results. To be fair, I get some of that when talking about email stuff with Steve. We each have some strong view points and aren’t afraid to share them with each other and with other people. In fact, one of the things we hear most when meeting folks for the first time is, “I love it when you two disagree with each other on that mailing list!” Both of us have engineering and science backgrounds, so we can argue in that vein.

One of the challenges of seemingly contradictory data is figuring out why it seems to disagree. Of course, in science the first step is always to look at your experimental design and data collection. Did I do the experiment right? (Do it again. Always do it again.) Did I record the data correctly? Is the design right? So what did I do differently from what you did? For instance, at one of my labs we discovered that mixing a reagent in plastic tubes created a different outcome from mixing the reagent in glass vials. So many variables that you don’t even think of being variables that affect the outcome of an experiment.

On Father's Day

always be batman
I’m on quite a few mailing lists for companies whose main product is sending gifts: food hampers, jewelry, flowers, overpriced desk toys and so on. They tend to ramp up their volume before appropriate holidays such as Christmas, Mother’s Day, Thanksgiving, Valentine’s Day or Father’s Day and target their promotions to those particular holidays.
One recipient may have a toxic relationship with their Mother and not want to be reminded of Mother’s Day, another may have recently lost their Father and not want to revisit that distress every time they open their mail client in June, yet another may be recently divorced and really not want to see diamonds and roses in their inbox right now.
You should try and avoid sending mail that will distress your recipients. You should do that because you’re a compassionate human and you want to treat your recipients as humans. But if you need an ROI argument to justify the effort needed to do so… those recipients will associate your brand with that distress and then they’ll buy less or they’ll unsubscribe and you’ll lose their business entirely – even if they are interested in and responsive to your offers for the rest of the year.
How do you identify those recipients? Maybe just ask them. Or add an “Unsubscribe from Father’s Day promotions” link next to the “Unsubscribe” link – it’s not hard to do. Help your customers segment your list for you.

Unsubscribe preference centers

I unsubscribe from a lot of opt-in lists around this time of year. I’m generally unbothered by a couple emails a week from companies I’ve purchased from in the past. But, a lot of these companies drastically increase their volume mid-November. I may not be averse to 3 emails a week, but that absolutely does not mean I want 2 emails a day.

Targeting and Segmentation

MarketingSherpa has a great case study of a retailer that got a 208% higher conversion (purchase) rate for a targeted email sent to a small segment (10%) of their list.

Relevant and timely marketing

What better time to advertise pizza specials than at 2:30 pm on a Friday afternoon?
Either my local pizza joint is doing sophisticated tracking (hrmmm… these people often order pizza on the weekend, email on Friday) or I’m just smack dab in the middle of their average demographic.
In either case, advertising pizza on a Friday afternoon strikes me as the epitome of timely, relevant marketing.
Pizza for dinner, anyone?

Now you know…

The key to email marketing, at least if you read blogs and talk to experts who blog about such things, is to segment your lists. But what does segmenting your lists really mean? Ken touches on it in a recent article about engagement and segmenting.
Segmenting your list means, quite simply, knowing your audience. It means tailoring your message to them, in order to extract as much money from them as possible. It means knowing which subscribers you can push with volume and which you will lose if you increase things too far.
In short, it means not treating all your subscribers the same, instead treating them slightly differently based on how they interact with your message.
To some people, this is too difficult. Ken even quoted someone in the industry as saying

Don't always believe the statistics

Mark Brownlow has a great roundup of how statistics and data can mislead marketers if they’re not really paying attention.