Why the Email Batch and Blast Practice Is an Addiction and How to End It
In email marketing, “Batch & Blast” is a common practice. But dare I say, it's the junk food of marketing. We all know that the email batch and blast practice really isn’t good for anyone, but many marketers just can’t seem to wean themselves off of the practice.
The addiction level in some cases is as bad as that of an opioid, not some casual black bubbly water loaded with sugar. I’ve seen marketers who are so addicted to it, they blast emails to “everyone” on the list multiple times a day. With the same creative and offer,.seven days a week. If that's not junk mail — yeah, I said that ultimate dirty word in 1:1 marketing — I don’t know what is.
It's a vicious cycle. With that many emails literally bombarding the targets, the list gets saturated. Open, clickthrough and conversion rates start to go down. To make up for lost sales, marketers send even more emails to cover the difference. And the downward spiral continues.
I’ve actually received requests from such clients to figure out how many “more” emails they can send out in situations like that. My answer? If everyone is getting 14 or more emails every week, there is no need for further study. Everyone in the database is over-promoted, so give them a break in the name of humanity, if not for best practice in marketing.
Nevertheless, many still see every email drop only as a sales opportunity, and they believe that more is always better. From the receiving end, however, it's a nuisance — or even torture. Had it not been for the “unsubscribe” button hidden at the bottom of the email with the font size of a few pixels, many would have just opted out from the brand. Most email recipients would just “highlight all, then delete.”
Many marketers believe that batch and blast works, because some revenue comes in with every email campaign drop. However, in my opinion, that is like believing that prolonged trawling in the fishing industry is beneficial in the long run. Yeah, you'll catch lots of fish that way. Initially, for a while. But if you and your fellow fishermen keep doing that, there won’t be many fish left in your area in the near future. Then what? Just eat more meat?
Sadly, many folks who are in charge of email marketing don't even care about the long-term effects of indiscriminate and incessant email bombardment. They may not even be in that position in a particular company for long, anyway. Even if they do care, many email marketers are compensated based on the number of successful email drops and attributed revenue numbers. When the bonus plan is tied to such things, who cares about the long-term effect of batch and blast? Well, CEOs and CMOs must care.
Not that I will convince every email marketer here, but let’s pose the question, nonetheless. Why is the batch and blast practice bad for the brand in the long run? Let’s go down the list one by one.
- Train the audience to ignore your brand: Sending non-personalized emails to everyone very frequently always ends up training valuable audiences to ignore the brand message. Yes, I do get multiple emails a day from certain reputable retailers, like Amazon. But I'm not always annoyed, because the email offers from Amazon are “somewhat” personalized for me, based on my past purchases and individual profile (or the profile of a segment to which I happen to belong). Sending irrelevant messages is bad enough. Do that every day, multiple times a day? You are literally asking them to ignore you. Tell me how that is good for anyone in your organization?
- Opportunity cost, if not real cost: Proper targeting had been at the center of 1:1 marketing strategy in the days of direct mail. Because it costs so much money to procure lists, process data, print marketing materials, put postage on them and mail them out, every marketer needed to target better. In fact, modeling techniques for target marketing were paid for by the savings from reduced mail volumes. With properly built targeting models, we could achieve revenue targets without mailing to everyone. Math worked because, in general, it would cost more than $1 to send out a piece. No one would send an expensive catalog to “everyone” in the database if the mailer could get the same revenue by sending copies to 10 to 20 percent of the target universe. On the contrary, in the world of email, such costs are irrelevant. Marketers would still have to pay for an ESP, anyway; so why bother with targeting? In fact, why mail less, at all? But, we must think about the opportunity cost. Danger of un-subscription is real, if you consider the acquisition cost (which is always high). Dwindling open and click rates are very much real, too, bringing in less and less revenue per campaign as time goes by. And the cost of training customers to ignore brand messages? It's hard to calculate a short-term monetary loss on that, but it's a real loss in the long-run, nonetheless. You’d always need a fresh set of new customers, only to abuse them until the point of non-response.
- No personalization: Batch and blast, by definition, is sending the same message to everyone, all of the time. In the days when we can't avoid the word “personalization” in any marketing conference, that's a real shame. There are plenty of studies and stats emphasizing that relevant messages lead to higher conversion rates. Claims vary — some are bolder than others, like eight times the conversion rate — but one thing is for sure. People respond better when the message is about them. I find it very difficult to convince batch and blast addicts to subscribe to the benefits of personalization. It is almost as difficult as converting a conservative person to a liberal, or vice versa. Now, why is that? Don’t they get tired of the same of messages from a brand as consumers themselves? I often hear about the difficulties of not having enough creatives. But that alone can be an excuse for not even trying. If it's difficult to go for a more elaborate kind of personalization, then start with just two creatives first and add more layers slowly (refer to “Road to Personalization”).
- Attribution: When you blast emails every day, multiple times a day, how would you ever know what really worked? What is the point of mixing up offers and creatives occasionally, if finding out how each drop performed is so difficult, or even impossible? Yes, one may rely on direct attribution (i.e., only counting direct clicks on email links leading to conversions), but we all know that is not the full picture. Consumers come back to the site not necessarily using the email links, and further, email isn’t the only promotion channel leading to the site. So, when “look-back” attribution is employed, how would you know what really worked when there are so many drops every day? Well, the answer often is that folks who just blast away emails don’t really care much about what elements of campaigns worked, for as long as they get decent — or usual — open, click and conversion rates (even if they are tainted figures). What a shame, in the age of 1:1 marketing via every conceivable channel.
How to End the Batch and Blast Addiction
Then, how do marketers wean off of the addiction?
Like any other type of addiction, it starts with the recognition. They have to realize that in the long run, the batch and blast practice is not good for the organization. I’ve been saying it for years, but let me say it again: 1:1 marketing (such as email campaigns) is about identifying “whom to contact,” and if you so decided to contact someone, knowing “what to offer, and when.” That’s it.
Even if you have a small customer base and you have no choice but to send emails to every available email address, can we at least agree that you must control the campaign frequency (i.e., “how often”), and try to send more relevant messages for each target or segment?
How do we control the frequency factor? To do that, marketers must be aware which target is over-promoted, under-promoted and adequately promoted. And such a calculation is not possible if you do not know both number of emails and number of responses on an individual level. One may say sending 20 emails to a person in a month is too much. Maybe. But what if the person purchased items more than two times in that period? Surely, that “20” looks quite different, doesn’t it?
If you keep track of response rates on a personal level, we can easily group them into Over-, Under- and Adequately-promoted groups based on response rates. Such rates often fit into a normal distribution curve, and dividing them into three groups would be simple (when in doubt, just use one standard deviation from each end, which will give about 16 percent from the top and the bottom). If anyone falls into the danger zone called “Over-promoted,” then put the red flag up for such a target, and suppress them before the campaign deployment until the flag is lifted.
Now, let me remind you that if you have been doing batch and blast for a prolonged period, do not bother with this type of data consolidation and calculation, as “everyone” in your base must be labeled as over-promoted. If fact, you may have to go the opposite way and decrease the frequency of emails for loyal customers first, to give them a break. “Loyal” doesn’t mean that you can abuse them or take them for granted. If you so must contact them frequently, at least treat loyal customers with special offers or invitations.
Of course, curbing the email frequency must come from the top. Without any elaborate calculation, CMOs may just mandate “maximum emails per person per week.” I’d say four to five times a week is a good start, but that depends on the product types and business model. The key is to give the target audience some breaks on a regular basis. If the benefits of such a practice is hard to prove to your fellow blasters, then create “hold-out” segments, and do not touch them for a set period of time. You may be able to see the before and after pictures after some hold out period (if the rules are honored by everyone in the marketing team).
As for personalization, I’ve written numerous articles about that for this fine publication. To summarize more than 10 articles in a few sentences (refer to "Key Elements of Complete Personalization," for one), I’d say start with basic “heuristic” segmentation and try to offer different discount and products to each segment. Then move onto more elaborate segmentation or clustering techniques for better results, and ultimately develop individual level personas using modeling techniques for best combination of target and offers (refer to "Segments vs. Personas"). That may sound daunting to many organizations, so that is why I emphasize using even heuristic segments (such as high-value customers, multi-buyers, recent buyers, tenured customers, inactive customers, etc.) is far better than keeping sending the same message to everyone, every day.
The batch and blast practice is an addiction that will lead to list saturation and an unresponsive audience. Unless you have cheap and unlimited acquisition sources hidden somewhere, please cherish your customer base and do not bombard them as if they will be there forever for you to meet your email goals. Now, to wean off addiction, an organization may have to go through a 10-step process for alcoholics. Starting with the “recognition.”
Stephen H. Yu is a world-class database marketer. He has a proven track record in comprehensive strategic planning and tactical execution, effectively bridging the gap between the marketing and technology world with a balanced view obtained from more than 30 years of experience in best practices of database marketing. Currently, Yu is president and chief consultant at Willow Data Strategy. Previously, he was the head of analytics and insights at eClerx, and VP, Data Strategy & Analytics at Infogroup. Prior to that, Yu was the founding CTO of I-Behavior Inc., which pioneered the use of SKU-level behavioral data. “As a long-time data player with plenty of battle experiences, I would like to share my thoughts and knowledge that I obtained from being a bridge person between the marketing world and the technology world. In the end, data and analytics are just tools for decision-makers; let’s think about what we should be (or shouldn’t be) doing with them first. And the tools must be wielded properly to meet the goals, so let me share some useful tricks in database design, data refinement process and analytics.” Reach him at firstname.lastname@example.org.