A marketing team was convinced their email program was underperforming. Open rates were decent, click rates were okay, but they couldn't prove emails drove revenue. When they finally implemented proper attribution, they discovered email was their highest-ROI channel—they just hadn't been measuring it correctly.
Attribution is the bridge between email metrics and business outcomes. Without it, you know how many people clicked but not how many converted. You can't calculate ROI, justify investment, or optimize for what actually matters. With proper attribution, email becomes a measurable, optimizable revenue driver.
What attribution means for email
Attribution answers a simple question: did this email cause this outcome?
When someone receives your email, clicks through, and makes a purchase, attribution connects those events. It says "this $50 purchase came from the Tuesday newsletter" or "this signup came from the welcome sequence."
The challenge is that customer journeys are rarely linear. Someone might receive your email, not click, but remember your brand and visit directly later. Or they might click, browse, leave, and return through a Google search to purchase. Which touchpoint gets credit?
Attribution models provide frameworks for answering these questions. Different models give credit differently, and the "right" model depends on your business and goals.
UTM parameters: the foundation
UTM parameters are tags added to URLs that identify traffic sources in analytics tools.
When you include a link in your email, you add parameters like utm_source=email, utm_medium=newsletter, utm_campaign=summer_sale. When someone clicks and lands on your site, your analytics tool captures these parameters and attributes the visit (and any subsequent conversion) to that email.
Standard UTM parameters include source (where traffic comes from—email, social, etc.), medium (the type of channel—newsletter, promotional, etc.), campaign (the specific campaign name), content (which link within the email), and term (rarely used for email, more for paid search).
Consistent naming conventions matter. If one campaign uses "email" and another uses "Email" and another uses "e-mail," your analytics will treat these as different sources. Establish conventions and enforce them.
UTM parameters work with any analytics platform—Google Analytics, Mixpanel, Amplitude, etc. They're the universal language of digital attribution.
Click-based vs view-based attribution
Attribution can credit conversions based on clicks, views, or both.
Click-based attribution gives credit when someone clicks an email link and later converts. This is the most common approach and the most defensible—the user took a clear action that led to conversion.
View-based (or impression-based) attribution gives credit when someone receives or opens an email and later converts, even without clicking. This captures influence that doesn't result in immediate clicks but might still drive conversions.
View-based attribution is controversial. Did the email really influence the purchase, or would it have happened anyway? The connection is less direct than click-based. But for brand-building emails or emails that drive store visits rather than online conversions, view-based attribution might capture real impact.
Most email programs focus on click-based attribution for its clarity and defensibility. View-based attribution can supplement but shouldn't replace click-based measurement.
Attribution windows
Attribution windows define how long after an email interaction a conversion can be credited to that email.
A 7-day click window means if someone clicks your email and converts within 7 days, the email gets credit. Convert on day 8, and it doesn't count.
Window length involves tradeoffs. Longer windows capture more conversions but risk crediting emails for conversions they didn't really influence. Shorter windows are more conservative but might miss legitimate delayed conversions.
Typical windows range from 1 day to 30 days, with 7 days being common for click-based attribution. The right window depends on your sales cycle—a quick impulse purchase might warrant a 1-day window; a considered B2B purchase might warrant 30 days.
Different conversion types might warrant different windows. A newsletter signup might have a 1-day window (if they didn't sign up immediately, the email probably wasn't the cause). A major purchase might have a 14-day window (people research before buying).
Attribution models
When multiple touchpoints precede a conversion, attribution models determine how credit is distributed.
Last-click attribution gives 100% credit to the last clicked touchpoint before conversion. If someone clicked an email, then a Facebook ad, then converted, Facebook gets all the credit. This is simple but undervalues earlier touchpoints that initiated the journey.
First-click attribution gives 100% credit to the first touchpoint. The email that introduced someone to your brand gets credit even if they converted through a different channel. This values awareness but ignores what actually closed the sale.
Linear attribution distributes credit equally across all touchpoints. If there were four touchpoints, each gets 25%. This acknowledges that multiple touches matter but doesn't distinguish their relative importance.
Time-decay attribution gives more credit to touchpoints closer to conversion. The final touchpoint gets the most; earlier ones get progressively less. This balances acknowledging the full journey while emphasizing what closed the deal.
Position-based (U-shaped) attribution gives significant credit to first and last touchpoints (often 40% each) with the remainder distributed among middle touchpoints. This values both introduction and conversion while acknowledging the nurturing in between.
Data-driven attribution uses machine learning to determine credit based on actual conversion patterns in your data. This is the most sophisticated approach but requires significant data volume and advanced analytics capabilities.
Implementing email attribution
Practical implementation involves several components.
Tag all email links with UTM parameters. Every link in every email should have appropriate tags. Most email platforms can do this automatically based on templates or rules.
Configure your analytics platform to capture and report on UTM data. Ensure conversion tracking is set up so you can connect traffic sources to outcomes.
Define your attribution model and windows. Document these decisions so reporting is consistent. Different stakeholders might want different views, but have a primary model for decision-making.
Build reports that connect email campaigns to conversions and revenue. Your email platform's native analytics show opens and clicks; your web analytics show conversions. You need to connect these, either through platform integrations or manual analysis.
Consider a customer data platform (CDP) for sophisticated attribution. CDPs unify customer data across touchpoints and enable advanced attribution modeling. For complex, multi-channel businesses, this investment often pays off.
Common attribution challenges
Several issues complicate email attribution in practice.
Cross-device journeys break tracking. Someone opens email on mobile, clicks, browses, then converts on desktop later. Without cross-device tracking, these appear as separate users, and the email doesn't get credit.
Ad blockers and privacy tools can strip UTM parameters or block analytics tracking. Some portion of your email-driven conversions won't be tracked regardless of your implementation.
Offline conversions are hard to attribute. If your email drives someone to visit a physical store, standard digital attribution won't capture it. Connecting online and offline requires additional infrastructure.
Multiple emails in a journey create attribution questions. If someone received five emails before converting, which one gets credit? Your attribution model should address this, but the answer is never perfectly satisfying.
Attribution and incrementality are different questions. Attribution asks "which touchpoint gets credit?" Incrementality asks "would this conversion have happened without this touchpoint?" Attribution can overstate email's impact if conversions would have happened anyway.
Using attribution data
Attribution data should inform decisions, not just fill reports.
Identify high-performing campaigns and understand why they work. What content, timing, or audience drove strong attributed revenue? Do more of what works.
Identify underperforming campaigns and decide whether to improve or eliminate them. Low attributed revenue might mean the campaign isn't working—or might mean attribution isn't capturing its impact.
Calculate email ROI using attributed revenue. Total revenue attributed to email minus email program costs equals email profit. This justifies investment and guides budget allocation.
Optimize for attributed outcomes, not just clicks. A campaign with lower clicks but higher attributed revenue is more valuable than one with high clicks and low revenue.
Frequently asked questions
Which attribution model should I use?
Start with last-click for simplicity and defensibility. As you mature, consider time-decay or position-based to acknowledge the full customer journey. Data-driven attribution is ideal if you have the volume and capabilities.
How do I attribute revenue to a specific email?
Use UTM parameters on all links, configure conversion tracking in your analytics, and build reports connecting campaign parameters to conversion values. Most analytics platforms support this natively.
What attribution window should I use?
7 days is a common starting point for click-based attribution. Adjust based on your sales cycle—shorter for impulse purchases, longer for considered purchases. Test different windows to see how results change.
How do I handle attribution across email and other channels?
Use consistent UTM conventions across all channels. Choose a multi-touch attribution model that distributes credit appropriately. Consider a CDP or marketing attribution platform for sophisticated cross-channel analysis.