Any seasoned marketer knows that their audience is a diverse patchwork of people with different behaviors and values, making it critical for marketers to understand those differences and segment their audiences accordingly.
However, there are almost always small groups of customers whose email behaviors are so extreme that they can skew your overall key performance indicators (KPIs). While a handful of outliers are not a major threat, groups of them can muddy overall performance data, hide trends, and skew testing results. By understanding common email marketing outliers, you can better predict and proactively address problems they may cause to your overall strategy.
Open rates can reveal outliers on opposite ends of the same spectrum — subscribers who never open emails and those who consistently open them. While subscribers that always open emails might sound like a good thing, they do not necessarily result in click-throughs or conversions 100% of the time and are rarely indicative of broader trends. On the other end of the spectrum, subscribers who never open emails could either be an outlier (depending on normal open rates) or they could be part of a larger pool that just needs to be re-engaged, or ultimately scrapped.
Another common outlier to monitor is big-spenders. A segment of your audience might consistently spend money, but do not reflect overall sales or donation trends, which is an important distinction to make. If you segment this list of outliers and send them targeted messaging, you stand to reap major benefits from better understanding these unique customers, rather than simply lumping them in with your broader audience.
One of the more difficult outliers to track are non-customers, such as employees or peers in your industry that are reviewing or assessing your emails. These subscribers tend to engage with your emails more frequently, which can totally skew metrics like open, click-through, and share rates.
So, what do you do if you are seeing these outliers cropping up in your email marketing performance? Like analyzing any set of metrics, it’s important to take a holistic view. If your outliers are few and far between, it might make sense to simply exclude them from behavioral analysis. If your outliers are clear and defined, you can segment these groups and personalize messages that will increase chances of a conversion. Finally, you can use outliers to determine if there are any critical technical problems that are plaguing a subset of specific users.
Be vigilant for patterns in your email metrics and treat outliers with care to help optimize every email you send.
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