Strategy
Experimentation Protocols: Your Practical Path to Better, Faster Testing
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Introduction
The competitive nature of ecommerce demands more than surface-level adjustments to stay ahead. As customer expectations rise and margins tighten, businesses must adopt smarter, data-driven strategies to optimize every possible aspect of the customer experience through systematic experimentation.
At Speero — an experimentation agency — we’ve learned over the years that simply improving conversion rates or average order value (AOV) — the usual focus of CRO teams — isn’t enough to drive lasting growth. Many ecommerce teams focus on shallow, tactical changes that fail to address deeper opportunities for increased profitability. The reality is that more meaningful results lie behind a holistic approach that leverages advanced tools and data systems to unlock the full potential of testing.
The Four Pillars of Ecommerce Experimentation
There are four critical pillars of on-site experimentation we recommend businesses focus on: Conversion, Spend, Frequency, and Merchandising. These pillars form a comprehensive strategy for driving growth from your hard-earned traffic.
There’s only one caveat: most testing tools are not designed to measure lower-funnel metrics, and without a robust data infrastructure and reliable metrics you won’t have the full visibility to drive lasting growth.
Another critical element here is understanding your unit economics, such as customer acquisition cost (CAC), gross margin, and lifetime value (LTV). Aligning these metrics with the four pillars ensures businesses can prioritize experimentation efforts strategically to achieve their goals.
The good news is that modern experimentation platforms, such as Eppo, facilitate seamless alignment with a data stack to ensure precise metrics and actionable insights that can also support your acquisition and retention initiatives.
Let’s break down each pillar to illustrate its strategic importance.
Pillar 1: Conversion - The Foundation for Growth
Conversion is the first and most fundamental pillar. Without conversions, none of the others are relevant. Yet, despite its importance, focusing solely on conversion rates doesn’t provide the full picture when it comes to a company’s financial performance. Many businesses prioritize this as an optimization criterion without considering broader goals like profitability and long-term growth, ultimately limiting the impact of their experimentation efforts.
For example, a brand might discover through experimentation that reducing friction in the checkout process —by enabling guest checkout or simplifying payment options— drives a significant increase in conversions. However, with the right instrumentation, they can also find that these changes, while increasing initial sales, fail to attract customers with strong lifetime value. This insight might allow them to pivot their conversion strategy toward tactics that attract repeat buyers rather than one-off deal hunters.
From a technical perspective, teams should focus on equipping themselves with tools and frameworks that enable precise tracking and analysis of long-term behavior. Goal tracking must extend beyond surface-level interactions to include server-side events, which helps mitigate inaccuracies caused by browser limitations or ad blockers. Ensuring these metrics are centralized and reliable makes experimentation data truly actionable and trustworthy.
Pillar 2: Spend - Boost Transaction Value
The second pillar, Spend, focuses on encouraging customers to increase their transaction value. This approach can significantly impact the bottom line without necessarily increasing traffic or conversions, but it demands a robust analytical framework to identify opportunities and measure success effectively.
For instance, an online electronics retailer might experiment with bundling accessories like phone cases with smartphones, discovering this approach significantly increases revenue per user (RPU). However, they might also find out that overly aggressive cross-selling prompts may frustrate customers and cause cart abandonment. This insight can allow them to fine-tune their upselling strategy to balance revenue growth with customer satisfaction.
From a technical standpoint, teams should prioritize measuring and optimizing non-binomial metrics —such as Revenue— with statistical rigor. By doing so, experiments can capture nuanced outcomes beyond simple pass/fail results, enabling teams to evaluate their impact across customer segments with precision, and ensuring revenue-impacting decisions are informed by reliable data.
Pillar 3: Frequency - Create Loyal Customers
As customer acquisition costs continue to rise, retention becomes a critical driver of long-term success. The Frequency pillar focuses on increasing how often customers buy from your store; either by opting in for a subscription offering or by placing repeat orders more frequently.
For example, a subscription-based meal kit company might discover through experimentation that their most loyal customers are those who receive consistent value updates, such as recipe personalization or exclusive subscriber-only deals. Testing retention initiatives like enhanced onboarding or loyalty rewards programs can reveal which features drive the highest frequency of purchases.
Customer Lifetime Value (LTV) is considered an ideal north star metric for retention-focused experimentation, but calculating it accurately requires a technical infrastructure that many businesses struggle to achieve. As an alternative, teams can rely on proxies like payback periods to gain earlier insights. A robust cohort analysis framework, powered by reliable data, is an excellent tool for identifying patterns in repeat purchases and their contribution to sustainable growth.
To succeed with measuring and improving customer retention, teams should equip themselves with tools that consolidate information from various sources. A data warehouse system is almost non-negotiable for unifying experiment reports from tools like subscription software, CRM systems, and ecommerce platforms. These tools enable teams to perform retention analysis and test initiatives like loyalty programs or subscription offers effectively to ensure data-driven decision-making.
Pillar 4: Merchandising - Optimize for Profitability
The Merchandising pillar focuses on optimizing your product catalog to maximize profitability by focusing on key metrics such as gross margins and product returns. Not all products are equally profitable —even with similar conversion rates, AOV, or purchase frequency— and conditions like inventory turnover or cash conversion cycles often dictate specific merchandising strategies.
For instance, a retailer might experiment with temporarily hiding certain brands or SKUs to see if customers substitute them with more profitable alternatives or if conversions drop. Such insights could inform product placement decisions or renegotiations with vendors to optimize profitability.
Effective merchandising optimization allows businesses to showcase high-margin products, address slow-moving inventory, and eliminate low-performing items that drive excessive returns. Additionally, testing product placements and pricing strategies can provide insights to increase engagement and conversions while ensuring alignment with financial goals.
Ultimately, tying merchandising experiments to financial outcomes ensures teams focus on strategies that drive long-term business impact and align with overarching company objectives.
Building a Culture of Strategic Experimentation
The true power of the Ecommerce Optimization Pillars Framework lies in adopting them as part of a strategic experimentation culture. While the technical infrastructure is non-negotiable, it’s equally important for data and growth leaders to align the organization on the most critical KPIs to optimize for, ensuring teams can generate meaningful insights and align experimentation efforts with overarching business goals.
Measuring the long-term effects of experiments is also critical to overcoming novelty and familiarity effects. While a test may yield immediate results, these initial reactions don’t always reflect sustained customer behavior, making long-term analyses essential for evaluating true impact. Achieving lasting growth requires a holistic approach that combines technical precision with strategic thinking.
Equip your team with the tools, data, and mindset necessary to optimize for Conversion, Spend, Frequency, and Merchandising. These pillars provide a framework to ensure your experiments deliver not just higher conversion rates, but meaningful, sustainable growth.
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