FunnelKit Automations

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This project had the largest and most cross-disciplinary team I'd worked with — and the final product is directly shaped by it. Before the problem, the research, or the design, I want to name the collaborators who changed what we built.

The copywriter changed the core visual structure of every email template. My original layouts led with merchant branding. She pushed back: "You're leading with the store brand. Lead with the product." Redesigned to lead with the abandoned product image. Open rate: +12%. Click-through: +34%. Email design and copy are not separate disciplines. I understand that now.

The email deliverability specialist caught a fundamental flaw in my product concept. Emails that don't reach the inbox are worthless, regardless of design quality. My plan: merchants would configure SPF records, DKIM signing, and DMARC policies themselves. His response: "No merchant will do this. It's too technical." He was right. Authentication became a required part of activation. 94% of merchants now successfully authenticate their sending domain — versus under 30% industry average for self-serve. That outcome belongs to him.

The lead engineer and I co-designed the event-driven data architecture that made the product viable. Standard WordPress database queries are too slow for behavioural automation — if someone abandons a cart, the 1-hour email window is real, and a 90-minute delay makes it worthless. We built a custom optimised cache layer queried at sub-100ms. Without that conversation, the product would have shipped on a false premise.

I lead these collaborations. But this product is better than what I would have designed alone.

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The survey (800 merchants): I surveyed FunnelKit's merchant base with one open question: "What email automations do you want to set up?"

• 68%: "I don't know what's possible"
• 23%: "Whatever makes the most money"
• 9%: Had specific workflows in mind

Most merchants didn't have an automation problem. They had a discovery problem. They knew email could help. They didn't know what to build, what order to build it in, or how to measure success. Platforms handed them blank canvases. They needed a starting point.

The contextual sessions (10 merchants): I sat next to merchants while they tried to set up automations using Klaviyo. James, an outdoor gear store owner, had 40 minutes.

15 minutes later:

40 minutes later:

That exact exchange happened in 6 of 10 sessions. Almost verbatim.

The diagnosis: merchants think in outcomes ("email people after they abandon"). Platforms think in architecture ("create a list, build a flow, add a delay node, configure trigger conditions"). The translation between those two is where every merchant got lost.

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SaaS platforms (Klaviyo, Mailchimp, Drip): $50–500+/month, multi-hour setup, data living outside WordPress. API keys and webhooks required before a single email sends.

WordPress plugins: Free or cheap, but limited to basic transactional sends. No behavioural triggers. No real automation.

The merchants in between — growing stores wanting automation power without SaaS complexity — had no option.

Three specific failures compounded this:

Setup required fluency merchants don't have. Klaviyo's abandoned cart segment: "Users where Cart Abandoned Date/Time is in the last 1 hour AND Email is not blank AND Consent Status equals Subscribed..." One merchant: "I don't know what half these words mean. I just want to email people who left items."

Email templates were generic to the point of uselessness. Standard plugin abandoned cart email: "Hi {{first_name}}, you left something in your cart! [Button]." No abandoned products. No personalisation. Zero brand voice. "This looks like spam."

Nobody told merchants what to build. Platforms are tools. Merchants needed strategy — which automations matter most, in what order, how to measure them.

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The obvious starting point: drag-and-drop flow builder with trigger, delay, and email nodes.

Tested with 8 merchants across skill levels.

• Advanced (2): "Great. Very powerful."
• Intermediate (3): "I think I get it but I'm not confident."
• Beginners (3): "I have no idea where to start. Can you show me an example?"

The blank canvas is only useful when you know what to put on it. 75% of my target users didn't. The copywriter — who had joined to write email templates and was sitting in on testing — offered the question that changed my direction: "What if we show them finished examples first and let them edit?"

I hadn't considered this because I was thinking about the tool. She was thinking about the merchant.

A gallery of pre-built automations: Abandoned Cart Recovery, Welcome New Customers, Win-Back, Post-Purchase.

9 of 10 merchants activated in under 5 minutes. 7 of 10: "Way easier than I expected."

Remaining problem: 3 merchants asked "How do I change the emails?" They'd launched — but didn't know what to do next. Activated ≠ confident.

The final design started from the merchant's goal, not the tool's features.

Step 1 — Choose your outcome: Recover abandoned carts / Welcome new customers / Re-engage past customers / Increase repeat purchases.

Step 2 — See a recipe with expected results. This step required the most design care. Showing "Merchants recover 15–25% of abandoned carts. Average: $4,800/month" is only trustworthy if the numbers are real and the framing is honest.

The figures came from FunnelKit's internal merchant cohort data — stores that had connected external email tools, giving a baseline for recovery rates across store sizes — cross-referenced against three published e-commerce studies. I showed ranges, not points. And I designed a 30-day check-in: the dashboard shows the merchant's actual recovery rate alongside the benchmark, with "Here's what top-performing merchants do differently" for those below it. Transparency upfront, context when it matters.

Step 3 — Customise only essentials: Sender name, discount amount, preview emails.

Step 4 — Activate: "Your automation is ready. It will run automatically starting now."

Step 5 — Optimise later (optional): "Want to go deeper? Edit timing, add emails, or modify copy."

15 merchants tested the final design. All 15 activated. Average: 4 minutes 12 seconds. 13 of 15: "Easiest automation tool I've used."

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47 templates across 7 automation types. This one shows the thinking most clearly.

Email 1 (1 hour): Exact abandoned products with images. Direct "Complete Your Order" CTA. Why 1 hour? Cart is still top of mind. Why images? CTR was 67% higher than text-only in testing.

Email 2 (24 hours): Customer reviews of the abandoned products. No discount. Why social proof? At hour 24, customers have second-guessed their decision. Other people's confidence reduces purchase anxiety without requiring a price reduction.

Email 3 (72 hours): 10% discount code. Why save the incentive? Discounting immediately trains customers to abandon carts expecting discounts. Email 3 reaches people who genuinely needed a nudge — not everyone. Why 3 emails and not 5? Testing across 500 merchant accounts showed emails 4 and 5 recovered under 2% additional revenue while meaningfully increasing unsubscribes. 3 is where the ROI turns.

All 47 templates were built to a consistent standard before launch. Alt text on every product image (the actual product name and context, not "image"). Plain-text fallback versions. Minimum 14px body text. 4.5:1 contrast ratio. Single-column layout for screen reader compatibility.

I tested rendering across 60+ clients using Email on Acid — including NVDA on Outlook and VoiceOver on Apple Mail. Three templates failed the initial screen reader test: product names were embedded in images without alt text. Fixed before launch, not after.

The deliverability specialist's insight reframed what kind of problem authentication was. It wasn't a technical configuration. It was the gate between "sent" and "received" — and if I treated it as optional, the entire product was built on a false premise.

I designed an authentication wizard that detects which DNS records exist, explains what's missing in plain language, provides copy-paste instructions for the domain registrar, and verifies configuration before allowing any sends. I tested the explanation copy with 8 non-technical merchants: all 8 successfully authenticated without external help.

94% of merchants now authenticate successfully. Industry average for self-serve: under 30%.

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For a store with 500 monthly orders: 350 abandoned carts × 18.7% recovery × $67 avg value = $4,355/month. $52,260/year from one automation.

Automation stacking: Average of 2.7 active automations per merchant, tracked via FunnelKit Analytics at 30-day intervals. Smaller stores most often added the welcome series as their second automation. Larger stores most often added win-back. That segment difference now informs how V2 sequences recipe recommendations in the wizard.

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International merchants were an afterthought. 31% of installations from non-English markets. English-only templates. US timezone defaults. "Complete Your Order" translating awkwardly. Two tiers of experience: the merchants I'd imagined, and everyone else. Internationalisation from day one — locale-appropriate timing, translated templates, regional payment gateway coverage. (Shipping V2, March 2025.)

I should have built the email editor in V1. 47% of merchants wanted to customise layout, colour, or fonts. 12% of 1-star reviews mentioned template inflexibility directly. I'd treated customisation as advanced when it was core — and I hadn't measured what that gap cost in lost power users. The email builder was complex to build, but the cost of not having it was also real. (Shipping V1.5, February 2025.)

Individual contact visibility was not edge case. Second most-requested feature post-launch. The use case I hadn't imagined: a customer emails the store asking why they received a message. Without visibility into which automation a specific customer is in, a routine support question becomes a 20-minute investigation. (Added December 2024.)

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Activation is not retention — and I only learned that after launch. I should have built retention dashboards from day one. Post-launch: 91% of activated automations still running at 90 days, 84% at 180 days. Good numbers — but I didn't have them until 6 months after launch. If they'd been bad, I'd have had no early signal.

What those dashboards would have tracked: 7-day activation rate, 30-day stacking rate, 90-day revenue per merchant. Each metric maps to a specific intervention. Activation is the starting line — these metrics tell you whether anyone is actually running.

The deliverability specialist changed the whole product. I'd have shipped with authentication as an optional setting. He caught that this made the entire product promise hollow. The fact that a specialist without a UX background reframed a fundamental design problem is the most useful reminder I got on this project: the best insight can come from anywhere on the team. Staying open to that is part of the job.

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• AI subject line generator (Q1 2025)
• Send-time optimisation — ML learning when each individual customer opens email
• Predictive churn detection — proactive win-back before the customer leaves
• SMS coordination — email and SMS in the same workflow

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Live product: funnelkit.com/wordpress-marketing-automation-autonami · Full email template library (47 templates), A/B results, and architecture documentation available on request.