Shopping Extensions Are Here to Stay — Learn to Measure and Test Their Impact

Consumers love bargains. At the time of this writing, 12 of the 13 top Chrome extensions in the Shopping category offer some flavor of automated coupon codes, price comparisons or cashback.

For consumers, these browser-based tools are a way to find the best bargains at a time of global belt-tightening. For online stores, they're a means to drive bottom-funnel traffic and sales in exchange for an affiliate commission (hence they're often referred to as affiliate extensions).

The rising popularity of shopping extensions — along with both Google and Microsoft integrating similar features into the native browser experience — can have both pros and cons for retailers.

Good for Sales, Messy to Measure

Most larger online stores partner with shopping extensions. According to survey data, e-commerce marketers would usually view these tools as a net positive — coupons and cashback offers can secure sales from consumers who might otherwise have shopped elsewhere, while price comparisons drive ready-to-buy traffic.

However, certain difficulties can arise when it comes to the way these tools alter the shopping experience, and when trying to isolate their impact amidst other marketing efforts.

Impact can be hard to discern in "last touch" attribution models. One of the primary concerns, in any affiliate model, is determining when affiliates actually contributed to a sale. Affiliates operate on a last-touch attribution model, where a commission is paid based on the last tracked link that the customer clicked on. Affiliates are thus incentivized to funnel users into making that click, which will allow them to take credit for a sale — even in cases where it might have happened anyway

Browser-based shopping tools have ample opportunities to present clickable elements to visitors very close to the end of their site journey. For example, think of a customer who discovers a product through organic search and is interested in purchasing it, even at full price. However, just before they proceed to checkout, their affiliate extension prompts them to check for discounts or coupons. The extension then presents a 5 percent coupon code, and the customer uses it to complete the purchase. The retailer pays twice: once in the value of the sale, and once in the commission paid to the affiliate. Without doing anything malicious, the extension has essentially intercepted a sale that was very likely to have happened anyway.

What’s the ROI?

In addition to the "false positives" issue described above, retailers also lack visibility into the potential downsides of visitors using affiliate extensions. The last-click model makes it very easy to see where affiliate extensions contributed to a sale; it’s much more difficult to see the cases where they prevented a sale from happening (e.g., by directing traffic to a competitor website, slowing down page load times, or sowing hesitance by displaying competing offers). A complete picture needs to take both costs and benefits into account.

UX Concerns

Browser extensions can alter the browsing experience in meaningful ways. They might present overlays and banners that hide website elements, or simply distract shoppers with alerts and notifications. It’s hard to predict how these types of interruptions will impact the overall visitor experience on a specific site (e.g., an overlay might display over empty space or critical product information).

These concerns are universal and might manifest even when the extension is doing its best to be nonintrusive. And not everyone is well-intentioned: smaller, less scrupulous apps might employ aggressive interruption tactics or dark patterns to draw the coveted click from a visitor, potentially leading to a disjointed journey and hurting conversion rates.

Embracing Extensions Without Losing Control

Retailers can’t prevent visitors from using shopping extensions — nor should they. The key is to look beyond last-touch metrics and adopt smarter ways to measure and understand their impact. Here are three techniques you can implement to help with this:

1. Monitor short- and long-term engagement metrics.

Don’t look just at clicks that led to a sale. To get insight into the full impact of affiliate extensions on buyer behavior, you’ll need to compare metrics such as exit rate, dwell time, and pageviews between extension users and their extension-free counterparts.

Where you have the data, check whether extensions change shopping patterns over the long term — e.g., are users less likely to return to your site over a three-month period? You can also use tools such as heatmaps and session recordings to identify specific pages or areas where extensions are detracting from the user experience.

2. Use multitouch attribution models.

Every attribution model has limitations, but a last-touch model is particularly narrow and obscures much of the "heavy lift" involved in acquiring a new customer through marketing activities.

Multitouch attribution models take all points of interaction into account and assign each a portion of credit for the final sale. These models can be more complex to implement, but they help you understand the value of each touchpoint in the journey to the final purchase, giving a clearer idea of which revenues you can and can’t attribute to your partnerships with affiliate extensions.

3. Incorporate A/B testing.

As with many other questions related to user experience and conversion rate optimization, experimentation is the best way to reach a qualified answer. See what happens when you prevent a randomized cohort of shoppers from being exposed to certain types of extensions. Doing so will give you a strong indication as to whether these extensions are actually driving sales (or merely taking credit for them).

You Can’t Improve What You Don’t Measure

Whether a specific shopping extension is good for your business depends on the nature of the extension and the nature of the business. Data and experimentation can help you shape better partnerships with affiliates while maintaining a close eye on the shopping experience and preventing unwanted interruptions.

Elena Librich is senior product manager at Namogoo, pioneer of the world’s first digital journey continuity platform.