Someone once said that with great power comes great responsibility. That certainly applies to email marketing. In the current recession, the high ROI and low cost of email make us the "rock star" of the marketing team. Of course, along with that comes increased pressure to deliver higher results -- executives are demanding more and more.
Time to turn that demand to our benefit. Take advantage of your rock star status to make the case for increased budget to go with that increased revenue forecast. Econsultancy recently reported that nearly half (48%) of marketers plan to increase email marketing spending this year. The best place to put those dollars now is into access to the kind of data you need to make good business decisions, and the space and talent to do even simple analysis.
It's time we all stopped pretending that "investing in email" is the same as "doubling the frequency." Investing means using data to make intelligent decisions about how to improve results. Without that knowledge, we are all just groping in the dark to understand the true drivers of response and revenue.
There's plenty of data in email marketing. Everyone should have access to basic campaign-level data like bounce rate (reported as "delivered" in most broadcast systems), inbox deliverability (how many messages actually reached the inbox vs. going to junk or not delivered at all), and open/click response rate - these are standard reports from every legitimate ESP or MTA vendor. (If you aren't getting them, ask for them!)
But basic is not good enough today. It doesn't tell you enough about actual subscriber behavior so you can predict response and improve results. Instead, track data over time, in what I call "engagement measurement." It will give you new power to optimize and defend your strategy. In fact, the JupiterResearch "ROI of Email Relevance" report says marketers that leverage data from multiple online channels generate three times more revenue from their email programs.
Start to ask questions at the subscriber engagement level, and you'll immediately see the potential of trending analysis. For example:
1. Are buyers more likely to click during particular seasons or after a certain length of time since their last purchase? Then send more messages during those high response times and less at other times.
2. Are inquiries (non-buyers) very unlikely to click after 10 or 30 days? Then pay more attention to messages during the initial window of opportunity.
3. Are long-term customers more likely to complain at a 5x frequency than a 3x? Which segments have the highest tolerance for additional sale notices?
4. Is response from high-value customers actually lower than response from "low value" customers? Recognize that no one wants to be sold. Instead, respect the wishes of high value customers by adjusting message, frequency, cadence and offer strategy.
Engagement measurement also quickly reveals pockets of true activity. Consider that your open rate on each campaign may be 25%. You need to know if it's the same small minority opening every time (in which case, send something different to the other 75%!). However, when tracked over the space of a month or quarter, it may be that 60% of your subscribers open at least once. That would suggest the need for a relevancy or cadence adjustment.
Another key need for this data is the common occurrence of an individual campaign failing for no apparent reason. An offer that worked in the past suddenly bombs, and so, in the absence of other data, we can only blame the creative. Inbox deliverability helps explain erratic response rates.
Check your own junk folder. You'll see lots of branded senders that sometimes appear in your inbox. If you can't predict or manage inbox placement , then you can't understand your real response rates. Track your inbox deliverability (which is not the same as your bounce rate, but is the number of messages that actually reach the inbox) by campaign and ISP. When you see this data, you can change practices to correct any blocks.
This is our chance. While we have the executive team's ear, let's make the case for the staff, data and integration you need to automate as much of this trending as possible. It's pretty easy math: If you earn just 50 cents from every email subscriber this month, and you can improve inbox deliverability by 10%, you've just earned $50,000 on a file of one million. If you can segment out the non-openers and engage just 20% more subscribers at even $1 per, you earn $200,000 in additional revenue this month.
Only when you view the data over time can you accurately predict results, defend your decisions, focus executive attention, and improve the subscriber experience -- for both the short and long term.