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Here’s How Returns are Inflating Your Marketing Numbers

How to Use Returns Data to Improve Your Business

Your Marketing Numbers Are Wrong

The truth about e-commerce returns and inflated campaign results.

It worked! That precisely timed newsletter blast, those clever influencer-driven Instagram posts, and the 15% off today only retargeting ad all came together last week, and now the marketing team’s newest campaign is being celebrated for increasing transactions by X%.

Except it didn’t – those numbers are inflated and inaccurate due to one simple fact: nearly one-third of all fashion and apparel items ordered online are returned.

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Think about that! If one out of every three vehicles a car salesman sold ended up back on the lot, would their sales record say they sold thirty cars last month or would it more accurately reflect the twenty cars the dealership earned revenue from? It may seem unfair to penalize marketing numbers for sales that didn’t stick. After all, marketing’s job is to get customers to your Shopify store and convince them to convert.  If a customer is making a return, then surely marketing managed to do their job in order to get them to make the initial purchase. Why should their stats be punished for a decision that comes after the fact?

Well, because those sales actually lost you money and, no matter how good marketing’s intentions were if they ignore returns they’re going to do much more harm than good for your business.

The Cost of a Return

An average return costs retailers 30 percent of the purchase price. Every single return being processed is actually costing money if a business’ margin is lower than 30% once additional costs like shipping labels, customer service labor, and your warehouse restocking the items are factored in.

Marketing analytics can easily identify that a shop had 300 conversions this week versus 275 last week. They can easily pin down which marketing campaign contributed most significantly to this growth. A returns management solution like ReturnLogic can sort out a stores return rate, an extremely difficult number to determine, and combine it with other powerful data to paint a clear picture of a business.

The majority of e-commerce marketing metrics are built using conversion data (conversion rate, number of transactions, average order value, etc) – but recognizing that a large chunk of what was sold will also be returned by the customer, wouldn’t it be beneficial for a business stakeholder to fully comprehend how these temporary transactions correlate with their marketing efforts?

Ignoring returns doesn’t make them go away, but facing them head with analytics across an entire organization will open businesses up to understanding the true financial implications of a return – and how to stop them.

How Should You Measure?

Here are some of the most powerful marketing metrics and how they can be skewed when returns are accounted for.

# of Transactions
It isn’t difficult to see where the problem is with this figure: not every sale was final when you’re acknowledging returns. Slash it down by whatever percent were returned.

Conversion Rate
The number of conversions divided by the number of visitors to your store. Now factor in the discrepancy in the number of conversions above and you’ll find your CR take a hit.

Average Order Value
The average amount customers spend per transaction. Another simple formula made complicated by the existence of returns and exchanges, something I’ve been hesitant to broach in this post. For simplicity’s sake, we’ve been operating with the assumption that a return is 100% of the purchase coming back. Partial refunds and uneven exchanges make AOV quite hard to figure out.

Customer Acquisition (CAC)
Calculated by taking the marketing campaign costs related to acquisition divided by the number of customers acquired. If items are returned, you’ll need to adjust to account for those who weren’t truly “acquired.”

Customer Lifetime Value
The Holy Grail of eCommerce marketing! Every CEO wants to present it to their investors – but very few actually factor in customer returns and those who do are simply removing those transactions from a customer’s history and not recognizing the cost associated with each one.

Putting It All Together

There are many ways to go about factoring returns into marketing analytics. The simplest method is to identify the store’s average return rate and simply remove that percentage from marketing’s revenue and conversions. This quick and dirty method will give a ballpark idea of what marketing is providing while you learn to cope with the disheartening fact that your $4000 campaign really only brought you $2800 after 30% of it gets sent back.

All of the above assumes an accurate average return rate was calculated for an entire store. That data can be broken down further into product categories, colors, sizes, or individual SKUs.

For marketing, access to these numbers will uncover even more accurate business representations for reporting and also influence key campaign objectives. For example, a sale on glassware may seem like a great opportunity to move pint glasses before St. Patrick’s Day – but glassware breaks easily no matter how well your warehouse packages it. You may discover that your catalog has a 33% return rate, but your glassware is actually returned or refunded at a 55% rate. That is an expensive problem if your big marketing budget isn’t being used to push other more profitable items during this time.

Being able to identify categoric return rates and then determine the potential profitability of promotions within that category has larger business implications than a small glassware promotion. Categories that once appeared to sell well and drive marketing efforts may turn out to have high return rates in comparison to other items.

Are you ready to use the most important metric an eCommerce business has (or should have) to improve your store’s marketing? A return rate represents failure somewhere within the buying journey and being able to quantify a companies problems suddenly makes them much more manageable by informing adjustments to return policies, improving catalog photography and size charts, user experience, and a dozen other influential areas. Evolving your marketing program to understand how to identify, track, and ultimately reduce expensive returns is key in growing your Shopify store in 2019.

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