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Open rates? Click throughs? Why classic marketing metrics don't work

Most marketers have it all wrong when it comes to measuring the success of their digital campaigns. Focusing solely on click-through or open rates doesn't tell marketers much, if anything, about their actual customers.

Here's why: a marketer may not think that an opt-out rate of 0.3 percent is alarming. But what if the marketer discovered that 50 percent of those opt-outs were its most valued customers? That's when a seemingly innocuous number becomes a gigantic problem.

Similarly, click-through rates may be skyrocketing, but that doesn't necessarily translate to an uptick in revenues if the ones clicking are low-value customers.

For these reasons and more, the classic metrics for measuring ROI on digital marketing don't work. They never really did, actually. There are smarter, more effective ways to quantify whether or not your email program is working.

Measuring quality over quantity

Marketers today are focused on data suggesting that email messaging is losing its effectiveness. That may be good or bad news, depending on who, exactly, is no longer opening or clicking on a message. What if the decline is attributable to inactive subscribers, or consumers who never buy a company's product anyway? What if one customer who is no longer clicking on emails is instead engaging with a favored brand via social media or display ads?

At many companies, a minority of high-value customers bring in the majority of revenue. High-value customers are the key to driving revenue, so understanding their behaviors through customer-centric metrics is essential. For example, one retailer drove 71 percent of its revenue from the top 20 percent of its email subscribers. The first place to start: stop putting low-value and high-value customers in the same ROI bucket.

Here's where customer-centric metrics come in. For example, if marketers pay attention to when customers are disengaging during their journeys and start tracking it as a metric, then marketers can proactively reach out to the fleeing customers to mitigate the churn behavior. This not only encourages a customer to reengage, but also gives marketers the opportunity to adjust their messaging so others don't flee for similar reasons.

On the flip side, by looking closely at the channels that high-value customers prefer — and the types of products they're interested in — marketers can customize their messaging to match customer preferences. For example, if marketers know that high-value customers engage more with mobile emails, then its communication with them should be optimized for that particular channel.

How to leverage customer-centric metrics

Here's 3 specific ways brands can better assess their customers' interest — and likelihood of making a purchase:

1. Personalize messages to customers and offer high-reward content across channels. For example, if past behavior shows that a customer is interested in jeans, marketers should send that customer a special coupon for 20% off jeans. And, this promotion shouldn't just be delivered via email. If the customer has downloaded the brand's app, she could receive a push notification about the promotion when she's close to the store. Or, if she never opens the email about the promotion, she could be targeted with a display ad about the promotion.

2. Build an effective customer acquisition strategy by understanding high-value customers. If marketers pinpoint what the general profile of high-value customers is and which channels they tend to interact on, they can learn how to win them over. For example, marketers may notice a trend that high-value customers are males between the ages of 25 and 35, who like to open emails on their smartphones. With that information in hand, marketers can court like-minded customers and optimize email promotions for mobile.

3. Predict customer activity and automate marketing programs to influence customer behavior. For example, email subscribers tend to follow a behavior pattern after they opt-in to an email program. By applying customer analytics to better understand this engagement lifecycle, marketers can predict certain behaviors, like when a customer is more likely to buy or opt-out. Leveraging technology to pay attention to these “signals” is an effective way to send an automated, relevant message tailored to the customer behavior. By knowing which segment of customers is at-risk (more likely be become disengaged), marketers can test different messaging opportunities to re-engage them in the email program.

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