Understanding Metrics: Offline Revenue

Nov29
By Joe Izenman

Learn the Pitfalls and Struggles of Linking Online Behavior Directly to Offline Revenue

This is part three of our series on Understanding Metrics. Our data scientist Joe Izenman is sharing why metrics matter and how to choose the right ones to measure success on your website. Check out the introduction blog.

The Goal: Connect Online Visitors to In-Person Sales

Online revenue is a wonderful, data-friendly thing and is well-cemented as a primary business model, but brick-and-mortar sales remain the bedrock of retail, large and small.

If your business relies on in-person sales, the natural instinct is to attempt a meaningful connection from website investment directly to the revenue stream. To be considered successful, website updates and online promotions would measurably drive foot traffic and purchase volume. But, this is easier said than done.

The Metrics

The core metrics for revenue are fundamentally the same, online and off. Sales and revenue, per product and customer, remain key measures of success. But, a lot can happen between the door and the register. Defining website success by how well it gets customers on to your sales floor is still potentially quantitative, while putting the onus of the final sale on your store layout and staff.

Unfortunately, real world actions are separated from online activity by a healthy dose of time and space. Foot traffic and sales are up, but how much confidence can you have that a change to your website was responsible?

One key to this kind of insight is creating a link between online user and offline customer. Large retailers achieve this with a rewards framework. By soliciting a phone number or a card swipe with every purchase, big box stores build up a comprehensive transaction history. If you also use their website for orders or browsing, you can bet they’ve connected the two.

Small retailers hit roadblocks to implementing the same strategy. They may not have the profit margins to let them offer the kinds of discounts customers expect with this level of tracking, or a web presence with uniquely identifiable accounts.

One alternative is to work in the aggregate, requesting a ZIP code at the register. By roughly geolocating the customer, while simultaneously geotargeting ads and promotions, some conclusions can be drawn, though they’ll be increasingly rough approximations. Beyond this, we’re limited to the most macro level of overall sales. This far out from individual behavior, the causal link between site and metric is so tenuous that any conclusions are irresponsible.

The truth is, however precise your user-customer link, however robust your data, the core separation still isn’t accounted for by any of these strategies: time and what happens in it. Unless your customer is on your website or app inside the store—not unheard of, but also not reliable—any number of confounding factors between their last website visit and when they step through the door may contribute to their behavior.

Next Up

So, if you’re not extracting money directly from your site’s visitors, are you out of luck? What about cases where the sales process is more hands-on for bigger ticket items and services?

Next week, we’ll cover measurement strategies for websites that focus on customer acquisition and sales lead generation before wrapping up the year with some non-revenue metrics.


Data Science

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