Mailchimp analytics for non-technical founders: What matters and what to ignore
Essential Mailchimp metrics non-technical founders should track, which metrics to ignore, and simple daily analytics routine requiring under 5 minutes.
Mailchimp displays 40+ different metrics across campaigns, automations, audience reports, and e-commerce tracking. Non-technical founders often feel overwhelmed reviewing analytics—unsure which numbers actually matter for business decisions versus which are interesting but irrelevant. This creates two common responses: either checking everything compulsively (wasting time on meaningless metrics), or avoiding analytics entirely (missing critical signals about campaign effectiveness).
You don’t need to understand every Mailchimp metric. You need to understand the 5-7 metrics that actually influence decisions for small e-commerce stores. This guide identifies exactly what matters for non-technical founders, what to ignore, and how to check key metrics in under 5 minutes without getting lost in Mailchimp’s interface complexity.
The only 6 Mailchimp metrics that matter for small stores
Focus on these six metrics. Ignore everything else until you’re consistently checking and acting on these fundamentals.
1. Revenue from email (most important)
What it is: Total dollar amount customers spent after clicking your email campaigns and automations.
Why it matters: Revenue shows whether email marketing actually drives sales, not just engagement. You can have great open rates and click rates but zero revenue—which means email isn’t working regardless of vanity metrics. Or you can have mediocre open rates but strong revenue—which means email is working regardless of so-called engagement problems.
Where to find it: Mailchimp organizes revenue data in campaign reports and e-commerce dashboard. Each campaign shows attributed revenue. Your e-commerce overview shows total revenue across all campaigns.
What’s good: Depends entirely on your store size and profit margins. As rough benchmark, email marketing should drive 15-30% of total store revenue for stores with engaged email lists. If your store does $10,000 monthly revenue, email should contribute $1,500-3,000 monthly. Lower than 10% suggests email underperformance. Higher than 40% suggests over-reliance on single channel.
How often to check: Weekly minimum, daily if you’re actively optimizing campaigns.
2. List growth rate
What it is: How many new subscribers you’re adding versus how many are unsubscribing or getting removed.
Why it matters: Email lists decay naturally—people change addresses, unsubscribe, or become inactive. If you’re not adding subscribers faster than you’re losing them, your list shrinks over time and email revenue declines. Growing list = growing revenue potential. Shrinking list = trouble ahead.
Where to find it: Audience dashboard shows current subscriber count, recent growth, and growth trend over time.
What’s good: Small stores should aim for 5-10% monthly list growth. If you have 1,000 subscribers, adding 50-100 monthly is healthy. Below 2% monthly growth suggests weak acquisition strategy. Above 15% monthly growth is strong but verify quality—rapid growth from low-quality sources hurts more than helps.
How often to check: Monthly. List growth is gradual—daily checking provides no useful insights.
3. Campaign open rate
What it is: Percentage of recipients who opened your campaign email.
Why it matters: Open rate shows whether your subject lines work and whether subscribers recognize your sender name. Consistently low open rates (under 15%) suggest subject line problems, sender name confusion, or list quality issues. But open rate alone doesn’t indicate success—you can have 40% open rate with zero revenue if email content doesn’t drive purchases.
Where to find it: Each campaign report shows open rate prominently near top of report.
What’s good: E-commerce email open rates typically range 30-35% in 2025. Below 20% indicates problems worth investigating (bad subject lines, sender name confusion, or disengaged list). Above 45% is exceptional. Note: Apple Mail Privacy Protection inflates open rates artificially—real engagement may be lower than reported.
How often to check: After each campaign send, within 24-48 hours when most opens occur.
4. Campaign click rate
What it is: Percentage of recipients who clicked links in your email.
Why it matters: Click rate shows whether email content interests subscribers enough to take action. Higher click rate = more engaged audience. Lower click rate = content doesn’t resonate or calls-to-action are unclear. Click rate predicts revenue better than open rate—clicks indicate purchase intent, opens just indicate curiosity.
Where to find it: Campaign report shows click rate below open rate.
What’s good: E-commerce campaigns typically see 2-5% click rate. Below 1% suggests weak content or unclear calls-to-action. Above 7% is strong. Note: Mailchimp shows two click rate types—unique clicks (what percentage of recipients clicked) and total clicks (counting multiple clicks from same person). Focus on unique clicks for clearer picture.
How often to check: After each campaign, same time you check open rate.
5. Unsubscribe rate
What it is: Percentage of recipients who unsubscribed after receiving campaign.
Why it matters: Unsubscribes are normal and healthy—not everyone will want your emails forever. But sudden unsubscribe spikes signal problems: overly promotional content, too frequent sending, or mismatched audience expectations. Some unsubscribes are good (disengaged people leaving improves list quality), but mass unsubscribes damage your ability to reach customers.
Where to find it: Campaign report shows unsubscribe rate alongside open and click rates.
What’s good: Under 0.5% per campaign is normal and healthy. 0.5-1% suggests minor issues worth monitoring. Above 1% indicates significant problem requiring immediate attention (content mismatch, frequency too high, or sending to wrong segment).
How often to check: After each campaign. If you see rate above 0.5%, investigate why.
6. Automation performance
What it is: How your automated email series (welcome series, abandoned cart, post-purchase) perform over time.
Why it matters: Automations run continuously in background, generating revenue without ongoing effort. Well-performing automations often drive more revenue than one-time campaigns because they target high-intent moments (new subscriber welcome, cart abandonment, recent purchase). But broken or ignored automations waste opportunity.
Where to find it: Automations section shows each workflow’s performance including emails sent, revenue generated, and conversion rate.
What’s good: Abandoned cart automations should recover 10-15% of abandoned carts into completed orders. Welcome series should generate 2-5× more revenue per email than regular promotional campaigns because new subscribers are highly engaged. Post-purchase series should drive 15-25% repeat purchase rate within 60 days.
How often to check: Monthly. Automations compound over time so daily checking provides little insight.
Metrics non-technical founders should ignore
These metrics appear in Mailchimp but provide little actionable insight for small stores:
Bounce rate (unless consistently above 2%): Percentage of emails that couldn’t be delivered. Under 2% is normal noise (people change email addresses, inboxes fill up). Above 5% indicates list quality problem or purchased list (which you shouldn’t do). Between 2-5%, monitor but don’t obsess.
Abuse complaints: Number of recipients marking your email as spam. Obviously you want this near zero, but checking constantly doesn’t help. Mailchimp alerts you if complaints spike—trust the alert system rather than checking manually.
Social sharing: How many people shared your email on social media. Interesting but rarely actionable for small stores. Email drives revenue through direct clicks, not through social shares. Focus on clicks and revenue, not shares.
Top links clicked: Which specific links in your email got most clicks. Useful for large stores doing extensive A/B testing, but small stores rarely act on this data. Knowing button A got 60% of clicks while button B got 40% doesn’t change your next campaign unless you’re testing systematically.
Subscriber engagement score: Mailchimp’s proprietary rating of how engaged each subscriber is. Sounds useful but provides little specific action. If someone has low engagement score, what do you do? Remove them? Send them more emails? Send them fewer? The score doesn’t answer these questions clearly enough to guide decisions.
Click maps showing exactly where people clicked: Visual representation of email with heat map. Impressive looking but rarely actionable. You already know whether people clicked (click rate metric). Knowing exactly where they clicked in visual format doesn’t typically change your approach unless you’re obsessively optimizing design.
Time-of-day analytics: When subscribers open emails. Sounds useful but misleading because open time doesn’t equal send time. Someone might receive your 10am send but open it at 7pm. The data shows 7pm open, leading you to incorrectly conclude you should send at 7pm. This metric creates more confusion than insight.
Daily analytics routine for non-technical founders
You don’t need to spend 30 minutes daily in Mailchimp. Here’s realistic routine:
When you send a campaign (2-3 minutes next day):
Check open rate 24 hours after sending—is it above 20%?
Check click rate—is it above 2%?
Check unsubscribe rate—is it under 0.5%?
Check revenue attributed to campaign—does it justify send effort?
Done. Move on unless numbers look problematic.
Weekly check (5 minutes Sunday evening or Monday morning):
Review total revenue from email for past 7 days
Compare to previous week—up, down, or flat?
Check list size—did it grow or shrink?
Glance at automation performance—any obvious problems?
Make one decision based on trends (send more campaigns if revenue declining, adjust content if click rates dropping, etc.)
Monthly review (15 minutes end of month):
Calculate total monthly email revenue
Calculate email revenue as percentage of total store revenue
Review list growth—did you add more subscribers than you lost?
Review automation revenue—are workflows generating expected returns?
Identify one thing to improve next month (send more frequently, improve welcome series, fix low click rates, etc.)
Total time investment: 10-20 minutes weekly, 15 minutes monthly = roughly 1 hour monthly total. Far less than many founders spend checking analytics without clear routine.
How to actually use Mailchimp data for decisions
Data without decisions is wasted effort. Here’s what to do with the metrics you’re tracking:
If revenue is declining week-over-week for 3+ weeks:
Send more campaigns (frequency too low)
Review product selection in emails (featuring products people don’t want)
Check list growth (shrinking list = declining revenue)
Verify e-commerce tracking still works (technical issue preventing attribution)
If open rates consistently under 20%:
Test different subject line approaches (less salesy, more curiosity-driven)
Check sender name (using confusing business name instead of recognizable person/brand name)
Review send frequency (sending too often causes people to tune out)
Clean list by removing consistently non-opening subscribers (improves overall engagement)
If click rates under 2%:
Review calls-to-action (are they clear and compelling?)
Check email design (is primary action obvious or buried?)
Test different content approaches (more product focus, less editorial content, or vice versa)
Verify you’re sending to right audience (maybe segmentation is off)
If list is shrinking month-over-month:
Add more signup opportunities on your store (popup, footer, checkout)
Improve signup incentive (better first-time discount or content offering)
Reduce send frequency if unsubscribes are high (people leaving faster than joining)
Review email content quality (if it’s not valuable, people leave)
If automations aren’t generating expected revenue:
Check if automations are active (easy to accidentally turn off)
Review triggers (are automations actually sending?)
Test email content (maybe calls-to-action are weak)
Adjust timing (abandoned cart emails might work better at 4 hours rather than 24 hours)
Common mistakes non-technical founders make
Mistake 1: Checking 20 metrics but making zero decisions
Spending 20 minutes reviewing Mailchimp, noting numbers, then closing dashboard without changing anything. Data consumption without action wastes time.
Fix: Every time you check analytics, make one decision or take one action based on what you see. Even small decisions (adjust next campaign’s subject line based on what worked this time) turn analytics from spectating into improvement.
Mistake 2: Comparing your metrics to other stores
Seeing someone else posts about 50% open rates and feeling bad about your 28% rate. Different industries, audiences, and sending patterns create vastly different baseline metrics. Jewelry stores see different metrics than software stores. Comparing across contexts is meaningless.
Fix: Compare yourself to your own baseline. Is your 28% better or worse than your 25% last month? That’s what matters—your trend, not someone else’s numbers.
Mistake 3: Panicking over single campaign underperformance
One campaign gets 15% open rate instead of usual 30% and you spiral wondering what went wrong. Single data points fluctuate randomly—maybe half your list was traveling that week, or Gmail had deliverability issues, or timing coincided with major news event.
Fix: Look at 3-4 campaign pattern before concluding anything. One underperformer is noise. Three consecutive underperformers is a trend requiring investigation.
Mistake 4: Ignoring automations entirely
Focusing exclusively on campaign performance while automations run in background, broken or underperforming. Automations often drive 30-50% of email revenue but get checked far less frequently than campaigns.
Fix: Monthly automation review. Verify they’re active, generating expected revenue, and functioning correctly. Fix broken automations before optimizing campaigns—fixing something that runs continuously has bigger impact than optimizing one-time sends.
Frequently asked questions
Do I need to understand how Mailchimp calculates all these metrics?
No. You need to understand what each metric means practically (what it tells you about business health), but you don’t need to understand technical calculation details. Open rate = percentage who opened email. That’s enough knowledge to use the metric for decisions.
What if I don’t have time to check analytics even weekly?
If you genuinely can’t spare 5 minutes weekly for analytics, either email marketing isn’t priority for your business (which is fine—focus elsewhere), or you need automated reporting that delivers metrics via email so checking happens passively. Automated reporting eliminates dashboard checking entirely—metrics arrive in inbox, you read in 2 minutes, done.
Should I hire someone to manage Mailchimp analytics?
For stores under $200k annual revenue, probably not worth the cost. Basic analytics checking (6 metrics, 5 minutes weekly) is simple enough for founders to handle. Above $200k revenue or if you’re sending 10+ campaigns monthly, hiring help for campaign creation and optimization makes sense, which includes analytics interpretation.
Can I trust Mailchimp’s revenue numbers or should I verify in my store?
Trust as directional estimate, not exact accounting. Mailchimp revenue attribution misses some email-influenced orders due to cross-device issues and attribution window limitations. Treat reported revenue as minimum floor—actual email impact is higher. Use Mailchimp numbers for trends (is revenue growing or declining?) rather than precise financial reporting.
What’s the fastest way to check these 6 metrics without navigating Mailchimp?
Automated email reports deliver key metrics daily without requiring dashboard access. Setup takes 5 minutes, then metrics arrive in inbox every morning automatically. Eliminates navigation complexity entirely—you read email instead of logging into dashboard. Most time-efficient approach for non-technical founders who want visibility without dashboard friction.
Peasy delivers daily analytics directly to your team’s inbox—no dashboard logins required. Starting at $49/month. Try free for 14 days.
