Today it’s not enough to know how an individual email campaign performed on a one-time basis. To learn whether or not your company is deriving true value from email marketing, you need the both broader and deeper perspectives offered by program- and list-level analyses.
While standard email campaign performance metrics like delivery, open and click-through rates have their place, without looking beyond them the true impact of your email marketing – and opportunities for continuous improvement – will go undetected.
It’s high time email marketers assess email marketing performance in terms of the goals, objectives, and contribution expectations that matter.
So what matters?
Determining what matters most requires a clear understanding of your organization’s strategic objectives and goals for email as a marketing channel. In other words, why are you using email marketing for and what do you want it to do for you?
- Do you want it to accomplish softer marketing goals like generating brand impressions, communicating with customers and influencing purchase decisions? – or –
- do you want it to drive harder revenue-producing goals like generating new leads, inquiries and direct sales?
Whether your purpose for email marketing is “soft”, “hard” or a combination thereof, here are three types of email marketing analyses that, in my opinion, should become standard practice because they’re so powerfully effective in measuring the impact of your investment in this channel regardless of how you use it:
1) Responder Segmentation Analysis
Are you analyzing who your email responders are by unique attributes such as gender, age, geography, past buying behavior, time on list, source of name, or social media connections? If not, you should be!
The beauty of this “back-end” analysis is you DON’T have to divide your list into multiple segments before deploying a campaign. Provided your email database is searchable by the subscriber characteristics mentioned above (and more), you could categorize responders post-campaign to begin developing a detailed profile of who they are.
For this type of analysis, you could create responder profiles by different response actions (open, click and conversion), but to keep it simple, define what your desired call to action is (the thing you MOST want people to do) and profile only those who completed that call to action (your “converters”).
Also, don’t stop at conducting responder analysis for individual campaigns. Conduct it in aggregate for all campaigns deployed quarterly, semi-annually, and annually.
For example, a responder-analysis by time-on-list might reveal that established subscribers (who signed up more than six months ago) convert at a higher frequency than new subscribers (say, those who signed up within the last six months). Knowing this might mean you step up the frequency to new subscribers, or test an onboarding campaign to new members as a way to get them familiarized, engaged and converting faster.
Or, you might find that analysis by age indicates that subscribers 45-55 years old are more responsive than those aged 25-35. Knowing that would change how you position your offers and could affect your creative choices for email copy, images, font sizes, etc.
What do you do after this analysis? Use responder profiles to:
- Understand how demographic or geographic differences affect response
- Improve targeting and segmentation on future campaigns
- Vary offers and creative to improve response on less active segments
- Test and/or adopt different frequency for different segments
2) Email Subscriber Engagement Analysis
It’s great to have a performance report for each email message you deploy, but you’ll also want to know how your entire subscriber base behaves in response to your email over longer periods of time. This type of analysis relies on measuring cumulative actions by subscriber (opens, clicks, conversions) during defined time periods (usually quarterly or annually) to uncover both the best, most active subscribers as well as identify inactive members for re-activation or suppression.
Unlike a responder segmentation analysis which tries to “paint a picture” of who certain subscribers are, an email subscriber engagement analysis is more concerned with measuring the total reach and effectiveness of your email marketing.
For example, how many of your subscribers have ever clicked on an email? How many have done so more than once? How many click on every message? Analyzing the frequency distribution of response actions like open, click and conversion across your list over time tells you a lot about both the depth and breadth of your email program’s impact.
(Want more on this type of analysis? Get this excellent free discussion paper co-authored by some of my UK email marketing colleagues. I highly recommend it)
What do you do with the results from this analysis? Use the data to:
- Offer incentives to increase response from infrequent openers, clickers or converters
- Increase frequency on less active segments to see if it improves engagement
- Identify weak or non-responsive subscribers for reactivation campaigns, or suppression
- Create a “premium” program for your most engaged subscribers. Reward them with exclusive offers, content or other special treatment
- Cross-match your most engaged email subscribers to your best customers (highest or most frequent spenders); reserve your best offers for them
3) Channel Contribution Analysis
What’s the bottom-line impact of email as a marketing channel for you? This analysis seeks the answer in terms of economic impact. “Economic impact” doesn’t have to mean direct sales revenue. It could, but it might instead be measured in increased site traffic, leads generated, new subscriptions attained, social media connections made, or gross brand impressions. Or, it could be measured in the cost savings and efficiency gains of email vs. more expensive marketing channels like direct mail.
So, understanding the economic value of each response action that an email marketing message generates is key! For example, what do you have to pay to get a page visit? What about a qualified lead? How about a new customer? Or a purchase from a repeat customer?
Do you know your allowable maximum cost for any of those actions (known as your cost-per-action or CPA)? If you do, you can attribute it to those your email marketing program generates. For example, if an email campaign produced 1,000 unique site visits that would normally cost you $0.25 each if using paid search marketing to drive traffic, then your email campaign just saved you $250 on search (or contributed $250 in value, depending on how you want to measure it).
How do you benefit from this analysis? Use the data to:
- Determine Return-On-Investment (ROI): Is email generating more economic value than it costs or is it costing more than it contributes?
- Determine Average Response/Order Value (AOV): How much economic value – in soft or hard dollars – does a conversion via email contribute? If it’s a sales what’s the average order amount from email?
- Calculate Revenue-Per-Email: If your email marketing directly generates actual sales, how much is each name on your list producing in revenue per year?
- Calculate Value-Per-Email: if your email marketing does not generate sales but does drive site traffic, social media connections or new leads, what would each of those be worth to you if you had to pay to get them? Assign that value to each name on your list and add it up annually.
Remember, measuring what matters is not necessarily as easy as just glancing at those simple email campaign reports that come your way after every message you send, but it’s not rocket science either. And at budget time, when you’re making your case for more staff or money, having the results of these analyses at hand is absolutely worth it.
If you need help measuring what matters – or setting up a system to do so – one of these programs is for you.Tags: analysis, engagement, measuring results, response, ROI, subscriber engagement, subscriber profiling