Q3 Optimization Strategy

Proposed A/B Testing Framework for the Checkout Funnel

[Your Name]

2026-04-10

The Current Bottleneck

We are losing high-intent users at the final billing step.

Overall checkout conversion is down 2.4% MoM.

Cart abandonment spikes explicitly on the /payment route.

Customer support tickets regarding “promo codes” have doubled.

The Hypothesis

If we simplify the billing form by hiding the “Discount Code” field behind a clickable link…

Then conversion will increase.

Why? Users are leaving the page to hunt for coupon codes on Google, getting distracted, and failing to return to complete the purchase.

Experimental Design

Here is the proposed statistical framework for the test:

Metric

Target

Notes

Primary Metric

Checkout Completion %

Guardrail: AOV

MDE

1.5%

Minimum Detectable Effect

Significance

95% (\(\alpha = 0.05\))

Standard threshold

Power

80% (\(\beta = 0.20\))

Required Traffic: 45,000 users per variant (Approx. 14 days of traffic).

Current vs. Projected Impact

Let’s look at what a successful 1.5% lift means for the bottom line.

Estimated ROI: +$1.2M Annualized

Next Steps {transition=“slide”}

Engineering: Implement the UI toggle for the promo code field (Sprint 4).

Data Science: Configure the split allocation in Optimizely.

Marketing: Ensure active promo codes are communicated via email to prevent cart abandonment.

Questions?