List Fatigue: Growing Concern For Email Marketers

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It’s become clear that many of the common business challenges marketers face remain the same as in the past.

Email marketers are still overworked. They remain focused on building more personalized and contextual messaging, but are hamstrung by the ability to get the necessary data.

However, from recent interactions, I’m sensing a newfound challenge: list fatigue, which I define as the reduction in engagement (opens, clicks) and conversion that comes from once-engaged subscribers, in addition to those who opt out from the list.

What is causing this increase in list fatigue? The sources vary by marketer, but the most common themes appear to be:

  • Email volume per subscriber is up across the board. This drives some subscribers to become long-term inactives faster (or unsubscribe more often) than in the past.
  • Changes in filtering at mailbox providers mean global engagement can impact inbox placement for addresses that are usually productive.
  • Changes at mailbox providers mean that unsubscribes are easier than ever, which is starting to be a larger drag on list growth.
  • In some cases, new subscribers aren’t as productive as they once were, as marketing teams experiment with new acquisition sources and approaches.

How should marketers address list fatigue? At a high level, I’ve observed that our clients are trying two different approaches.

First, they are changing what they send to subscribers. Specifically, many clients focus on building win-back campaigns to drive re-engagement for subscribers who have tuned out. Some of the best practices for win-back campaigns are:

Send multiple messages. Typically subscribers will not respond to the first win-back message. Sending multiple messages gives you more bites at the apple. We see a significant decrease in efficiency after the fourth message.

Subject lines that use emotion (including humor) don’t perform significantly better than subject lines that are more matter-of-fact. This means, as with everything else, you’ll need to test a wide variety of subject lines.

Absolute discounts ($ off a purchase) do better than percent discounts (% off a purchase). I’m sure there is some deep psychological reason for this. Or maybe it just takes more work to calculate the value of a discount with a “percent off” offer.

Get them early. Don’t wait until the subscriber has been inactive for a long time to attempt a win back.

Personalization. As with other messaging, personalizing the products shown, calls to action, etc., drive better performance.

Win-back campaigns are a solid tactic, but they are still inferior to preventing subscribers from tuning out in the first place. Building a program that relies more on contextual and personalized messaging will cause less list fatigue than a mass campaign-based mail with little personalization.

The second approach is to vary how much mail subscribers receive. I’ve written about this previously.

When marketers experiment with cadence/frequency optimization, they tend to change the frequency for all subscribers, which leads to suboptimal results. Like any other aspect of an email campaign, cadence must be personalized for each subscriber. In this case, customization is based on subscriber activity level.

Crude activity buckets (“subscribers who haven’t opened or clicked in more than X days”) are a common approach, but they tend to underperform. Instead, more subtle signals that can be captured by machine learning models do a much better job of optimizing cadence.

Of course, many marketers don’t have a data science team available to help with this more-sophisticated approach. In that case, the activity bucket approach is better than nothing.

This post originally appeared on Media Postg.