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Everybody has an opinion, but know what trumps opinions? Data. Here are 3 strong opinions I’ve held over the years in email marketing that have been changed by data.
Time to First Purchase from Awareness is Longer Than You Think
Recently, I’ve been going deep into post-purchase surveys for a slew of brands we onboarded in the past few months.
One of the most interesting questions I’ve been observing is “When did you first hear about us?” for first-time buyers.
Something that surprised me has come up again and again: people often take longer to make a decision than you think.
Take a look at this data below in response to this question:
Conventional knowledge (and something I’ve advocated for in the past) has been to scrub people off the list and stop communicating with them if they haven’t made a purchase within the first 30 days.
I’ve even gone as far to suggest creating a “rapid sunset flow” that utilises a webhook to suppress these profiles to keep costs down.
And while I still believe this strategy has credibility if the prospective customer hasn’t responded (opened/clicked) to any email within 30 days upon subscribing to the list, I’ve reigned in my views that these are useless leads that simply contribute to cost in your ESP.
The data shows that capturing and nurturing these leads to their first sale may take longer (a lot longer) than you initially thought.
It makes sense when you dig deeper. Consumers are bombarded with a massive amount of media and advertising far and wide on a daily basis, so capturing their information and convincing them to buy in a sea of noise will forever be a challenge in this digital world we live in.
This has amended my strategy two-fold:
- Your welcome flow may need to be a lot longer than the traditional 4-7 days, &
- Your segmentation strategy for prospects needs to take into account this consideration cycle
Simply put, we cannot look at prospects in a vacuum as redundant if they haven’t purchased the moment they first land on your site. Life is busy and people often need more convincing than a solitary Facebook ad and welcome flow discount.
ALSO READ: Creating the Perfect Email Automation Strategy with Data
Resends: Maybe not so bad after all?
Anybody that has followed me on social media for a while knows that I’ve been a hater on resends for as far back as I’ve posted.
My reasoning has always been relatively straightforward: if a customer didn’t respond the first time to something you sent to them, why annoy them a second time?
Yet in my opening discussion of this article, I think it’s evident that this logic is quite flawed.
This shift in perspective on resends happened during a recent intensive period of revenue targets for a selection of brands on our roster in Q4 last year (2022) which stretched a few of our teams to the limit.
While we had exhausted the number of deliverables the client had paid for and wanted to squeeze some more juice from their account over a key holiday season.
Reluctantly, I agreed to do resends:
Now, I am aware that this is just a single email and doesn’t statistically prove long-term that resends are a credible technique.
However, I have softened my stance on resends a lot, purely as I’m trying to think more like a business owner as opposed to a channel marketer. After all, what does the brand really care about the most? Profit. And in the example above, we saved money on the execution of another deliverable and generated additional revenue from the same creative.
Obviously, there are other things to consider here, such as the long-term impact resends have on deliverability and subscriber churn. There is also the fact that due to iOS updates, we can’t accurately even track opens anymore, making segmentation to non-openers practically impossible.
Limited to certain occasions, however, I see no harm in trying to get more mileage out of your sends.
After all, we get retargeted by the same ad on social media continuously, yet never bat an eyelid. Is it really that intrusive to occasionally send the same email twice?
While subscriber trust is paramount, we also need to balance that with the brand’s need to make money as well. And here, resends have credibility.
ALSO READ: Creative ways to collect Zero-party data
Email Frequency: Perhaps you need to send more emails?
Another issue I’ve been quite negative towards in the past is the sensitivity around email frequency, especially when it comes to campaigns.
My historical viewpoint was that most brands completely overdo it when it comes to email frequency and the incremental impact this has on returning customer revenue. However, the inverse is also true: brands that don’t send enough emails can also miss out on a ton of repeat revenue.
While the only way to measure the true uplift of an increased email frequency is with holdout testing, this technique can also be affected by elements such as seasonality, new product launches, etc. After all, do you really want to conduct a holdout test during BFCM or restrict customers to a massive new product launch? The potential for missed returning customer revenue opportunities often outweighs the risk a lot of the time, and although a statistician may argue otherwise, I’ve seen so many instances at this stage of my career where I’ve observed continuously how an increased frequency correlates to more revenue.
The caveat here, of course, is quality over quantity. As the size of the database grows, scale of the brand and product assortment increase, segmentation becomes more important and the capital of resource allocation in going after perceived “low-hanging fruit” needs to be measured.
The bottom line is: the only true way to validate an increased frequency and its impact on CLV/revenue is with holdout testing. Due to the dynamic pace of business and elements of maturity in the CRM setup, there are probably more cost-effective areas of the business that most marketers can spend time optimising in most businesses, especially when it comes to email, given its relatively low cost.
On a very high level, MoM, I like to pay attention to how the increased frequency is impacting negative intent signals (unsubscribes, spam rates, etc), as well as whether the total clicks are going up and website traffic is increasing proportionally with the increased cadence.
A final note here: start slow, and increase frequency gradually. It is very hard to perform these experiments in reverse as the brand becomes attached to the revenue-hits campaigns often generate at scale. It is very hard to reign this back in when they’ve been a fundamental part of business strategy for so many years.
Conclusion: Challenge everything and reinvent yourself
I am willing to continuously challenge my beliefs in a relentless quest for truth. I believe the best marketers are adaptable, governed by data and willing to experiment like crazy. If you can’t remove bias from the process, you can’t move closer to the source of truth, and this is what I want to pride myself on: for the best outcome, truly. I suggest we all do the same.
I cover this more extensively in Monster Email Marketing where I explain the exact strategies I've used to win deals with 8-9 figure DTC brands and continuously drive an additional 15% revenue from every email campaign you send.
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