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Author Archives: Ric Riley

  1. Why Your Average Order Value is Lying to You

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    Average Order Value (AOV) is one of the most popular metrics in eCommerce. It’s plastered across dashboards, referenced in strategy meetings, and utilsed for key business decisions. But you need to be careful, AOV is misleading you.

    AOV is Just a Middle Point, Not the Full Picture

    Most brands assume that their customers place orders somewhere around their AOV. That’s logical, right? If your AOV is £75, you’d expect a large share of customers to be ordering close to that amount.

    But when you actually visualise order value distribution, you quickly see a different story:

    • A huge volume of orders sit below the AOV
    • Another set of high-value transactions sit well above it
    • AOV? It’s simply the midpoint and not a true reflection of where orders actually fall

    Instead of being a reliable benchmark, AOV often distorts reality.

    AOV is Driving Flawed Strategies

    Because AOV is widely accepted as a guiding metric, businesses frequently use it to set key pricing tactics most notably, the free shipping threshold.

    For example, if your AOV is £75, you might decide to set your free shipping threshold at £80, assuming it nudges customers to increase their cart size. But here’s the catch: if the majority of your orders are actually around £40-£50, your threshold is completely misaligned.

    This means:
    ✅ You’re missing an opportunity to encourage more incremental increases.
    ✅ You’re setting a target that many customers simply won’t stretch to reach.
    ✅ You’re potentially losing out on conversions from customers who see the free shipping threshold as too far out of reach.

    Instead of setting free shipping based on AOV, businesses should be looking at the most common order value ranges and adjusting their pricing strategies accordingly.

    Breaking AOV into Order Value Buckets

    To truly understand your customers’ purchasing behaviour, bucket your orders into meaningful value ranges.

    For example, instead of relying on a single AOV number, look at:

    • Orders under £xx (low-value, high-frequency purchases)
    • Orders between £xx-£xx (mid-tier, balanced buyers)
    • Orders above £xx (higher-end, big spenders)

    By doing this, you can make more data-driven decisions when it comes to pricing strategies, upsells, and incentives. You might find that:

    • Most of your volume sits around £45, meaning a free shipping threshold of £50 makes far more sense than £80.
    • Customers in the mid-tier range respond well to bundling incentives.
    • High spenders have different behaviours entirely and should be treated as such.

    We also recommend visualising ‘revenue’ per bucket, as this can tell a completely different story to ‘order count’. You might be surprised how much revenue comes from your higher-end big spenders.

    The Bottom Line

    AOV alone is not enough to guide strategy. Without understanding the actual distribution of orders, businesses risk miscalculating incentives, pricing, and marketing efforts.

    If you haven’t broken down your AOV into order buckets yet, now is the time to do it. The insights you uncover could completely change how you drive more revenue from your customers.

    Want help to visualise your order value distribution? Let’s chat. 🚀

  2. The Hidden Cost of Discount Code Leaks

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    In the world of e-commerce, discount codes are a popular and effective way to attract new customers and reward loyal ones. However, what started as a targeted marketing tool has, in many cases, spiralled into an unexpected challenge for online retailers. Automated discount platforms such as Honey and Karma now aggregate and share discount codes across their networks. While these platforms are convenient for consumers, they can cost businesses far more than they might realise.

    What is a Discount Code Leak?

    Discount code leaks occur when the codes, originally intended for a specific purposes, become widely accessible on automated platforms.

    For example, you might run a targeted email campaign offering a 20% discount to your most loyal customers. But thanks to automation tools and code-sharing platforms, this discount can suddenly become accessible to anyone visiting your site, including users who would have happily paid full price.

    The Scope of the Issue

    Our recent data suggests that, depending on the industry, 5-10% of all discount code redemptions on e-commerce websites come from automated sources like Honey or other browser extensions. This isn’t just a minor inconvenience—it’s a direct hit to your bottom line. When consumers who would have purchased anyway find and apply leaked codes, businesses end up giving away discounts unnecessarily.

    For industries where profit margins are already tight, such as fashion or consumer electronics, this unintentional discounting can add up quickly. The cumulative effect can erode revenue, diminish campaign effectiveness, and reduce the perceived value of your products.

    Why This Matters for Conversion Rate Optimisation (CRO)

    At first glance, one might assume that leaked discount codes could boost sales conversions. After all, discounts are enticing. However, the reality is more complex.

    While conversion rates might increase slightly, the quality of these conversions could decrease. Customers who rely on leaked codes may not be as loyal or engaged as those who buy without incentives. Additionally, the inflated use of codes can skew campaign analytics, making it harder to assess the actual effectiveness of promotional strategies.

    For CRO teams like ours, the impact of discount code leaks represents a critical blind spot in the optimisation process. Ensuring that discounts are used strategically—and not applied unnecessarily—is key to maximising revenue and customer lifetime value (CLV).

    Understanding the Size of the Problem


    To understand the size of the problem, businesses need actionable insights into how discount codes are being used. That’s where Fabric Analytics comes in. Our solution enables you to track discount code usage through advanced custom JavaScript that integrates seamlessly with Google Analytics 4 (GA4).

    By implementing this tracking, you can:

    • Identify the source of discount codes, including whether they originate from automated platforms like Honey or are applied manually by users.

    • Quantify the percentage of transactions that involve leaked codes.

    • Measure the revenue impact of unauthorized discounts to see how much they are cutting into your profits.

    • Segment users based on their behavior, enabling more refined audience targeting in future campaigns.

    This data gives businesses a clear understanding of how widespread the issue is and equips them with the insights needed to develop tailored strategies to mitigate it.

    How to Combat Discount Code Leaks

    To mitigate the issue, businesses must adopt proactive measures to safeguard their promotional strategies:

    1. Use Unique, One-Time Codes: Generating codes that are unique to each user and expire after one use can significantly reduce the risk of leaks.

    2. Segment Your Audience: Limit discount code distribution to specific customer groups or loyalty tiers. This not only reduces exposure but also creates a sense of exclusivity.

    3. Implement Server-Side Validation: Ensure discount codes are verified server-side, allowing you to track their source and prevent unauthorised sharing.

    4. Restrict Code Usability: Set specific terms for your codes, such as time limits, product category restrictions, or minimum purchase thresholds.

    5. Monitor Code Usage: Regularly review your analytics to detect unusual patterns of code redemptions that may indicate leaks.

    6. Blocking Automated Activity: At Fabric Analytics, we’ve developed scripts that can gracefully block automated services like Honey without disrupting the customer experience. These scripts detect the presence of browser extensions and other automation tools, offering you the ability to prevent unauthorised discount application at the source.

    The Future of E-Commerce Discounts

    While discount code leaks are a frustrating challenge, they are also an opportunity for businesses to reevaluate their promotional strategies. By focusing on targeted, data-driven approaches, retailers can reduce unnecessary discounts while still fostering customer loyalty and driving sales.

    For CRO specialists, addressing this issue is a vital part of optimising the user journey and protecting revenue. With the right strategies in place, businesses can strike a balance between offering discounts that convert and preserving their profitability.

  3. The Rise of Predictive Analytics: The Future of Business Intelligence

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    Predictive analytics has emerged as one of the most powerful tools in the world of business intelligence. By leveraging large amounts of data and advanced algorithms, predictive analytics enables companies to make informed decisions and anticipate future outcomes with a high degree of accuracy. The rise of predictive analytics has been driven by several factors, including the proliferation of big data, the growth of cloud computing, and the increasing availability of advanced analytics tools.

    The benefits of predictive analytics are many, and they extend to a wide range of industries and applications. For example, in the retail industry, predictive analytics can be used to optimize inventory management, predict customer buying patterns, and personalize marketing campaigns. In the financial sector, predictive analytics can be used to detect fraud, manage risk, and optimize investment strategies. In the healthcare industry, predictive analytics can be used to improve patient outcomes and streamline operational processes.

    The future of business intelligence lies in predictive analytics, and companies that embrace this technology will have a significant competitive advantage. Predictive analytics is no longer the domain of data scientists and mathematicians. With the rise of cloud-based analytics tools, companies of all sizes can now leverage predictive analytics to gain a competitive edge. By leveraging the power of predictive analytics, companies can turn their data into actionable insights and drive growth and innovation.

    In conclusion, the rise of predictive analytics represents a major shift in the world of business intelligence. By harnessing the power of big data and advanced algorithms, companies can now make informed decisions and anticipate future outcomes with unprecedented accuracy. Whether you are a large corporation or a small business, the future of business intelligence lies in predictive analytics. Embrace this technology, and stay ahead of the curve!