What does MER tell a home goods store?
For a home goods store, MER is still total revenue divided by total ad spend. Read it monthly at the least, on net sales after returns, and against the same month last year. Big-ticket buyers take longer, and seasons move demand more than ads do.
By Joris van Huët, Founder & CEOUpdated 5 min read
Run the numbers for your store: the free blended ROAS (MER) calculator.
If you sell home goods, MER is still your revenue divided by your ad spend. What changes is how you read it. Bigger orders, slower decisions and seasonal peaks usually mean a weekly MER swings with timing, not quality. Read it monthly, on net sales after returns, against the same month last year.
If you sell home goods
If you sell sofas, rugs, lamps or bedding, your buyers rarely decide in one visit. A sofa gets measured, compared and shown to whoever shares the living room. Someone sees your ad in March, saves the page and buys after payday in April. MER books that sale in April, against April's spend.
Seasons pull hard as well. Moving house, the run-up to the holidays and the big sale weekends bunch demand into a few weeks. A month that holds a promotion flatters MER, and the month after looks worse, even if the ads never changed.
Then there is what happens after the sale. Bulky items cost a lot to deliver and to take back. And if few of your buyers order again within a year, MER mostly measures what it costs to win new ones.
What one store's data shows
One store's anonymised GA4 export, 1 January 2024 to 21 August 2026. It holds shares of revenue only: no ad spend, no order counts.
| What the export shows | Share of revenue | Source cell |
|---|---|---|
| Journeys with 1 touch (0.5 days to buy) | 79.5% | Journeys sheet, 1 touch row |
| Journeys with 4 to 9 touches (16.9 days to buy) | 5.4% | Journeys sheet, 4-9 touches row |
| Journeys with 10 or more touches (16.0 days to buy) | 3.0% | Journeys sheet, 10+ touches row |
| Direct, in last click, first click and touched views | 57.7% | Channels sheet, Direct row |
Store A is one store, and nothing in its export says it sells home goods. Read it as a contrast, not a forecast.
On the Journeys sheet, 79.5% of Store A's revenue came from one-touch journeys that took 0.5 days to buy. The long journeys on the same Journeys sheet were slow: 16.9 days for 4 to 9 touches, and 16.0 days for 10 or more.
If your own journeys look more like those slow rows, a weekly MER will mostly measure timing. Money spent in one week keeps arriving as sales a fortnight later.
Direct holds 57.7% of revenue on Store A's Channels sheet, in all three views. If your buyers browse for weeks and come back by typing your address, your Direct row can grow the same way. MER counts that revenue in full, which is why it stays calm while channel reports argue over credit.
What the export cannot tell you is any MER at all. It holds no spend, and nothing in it ties Store A to home goods.
What changes for a home goods store?
The window. Read MER monthly at the least, and quarterly if your prices are high. Compare each month with the same month last year, so the season sits on both sides of the comparison.
The top line. Use net sales, which take discounts and sales reversals off gross sales. Shopify shows a return as a negative number on the date the return was processed. So a dining table sent back in January dents January's MER, not December's. Total sales also adds shipping charges back on, and bulky delivery can make that a big slice.
The bottom line. Catalogues, photo shoots and showroom events are marketing too, if you choose to count them. Pick one cost list and keep it all year.
The question MER cannot answer. It cannot say which channel started the long journeys. For that, read the conversion paths report in GA4 and look at the first touches on your slow paths.
What to do this week
- Compare MER with the same month last year. In Shopify, open Analytics > Reports > Total sales over time and compare the two date ranges. Pass: both months use net sales and the same cost list. Fail: you compare October with September and blame the ads for the calendar.
- Measure what returns and discounts take back. In the same report, read gross sales and net sales for each of the last three months. Pass: you know how much of gross sales never stays with you. Fail: you judge your ads on gross sales and count furniture that came back.
- Pull last year's Google Ads cost for the same month. Click the Campaigns icon, then Campaigns, set the date menu to last year's month and read Cost in the totals row. Pass: a like-for-like MER for both years. Fail: this year's sales divided by last year's spend, or the other way round.
Check the homework. Your GA4 Attribution paths export already holds the evidence. Causality Engine reads that one file and shows what each channel caused next to what last-click gave it, in 1 to 2 minutes, for €99 once (excluding VAT), refundable within 30 days. Check the homework
Sources, 1 October 2026: Sales reports (Shopify Help Center); Account, campaign, and ad group performance (Google Ads Help).
Related answers
Frequently asked questions
Should a home goods store judge MER monthly or quarterly?
Monthly at the least, and quarterly if your buyers often take weeks to decide. Compare each period with the same period last year, so the season shows up on both sides of the comparison.Do delivery fees belong in a home goods store's MER?
Leave them out. Shopify's net sales excludes shipping charges, taxes, duties and fees, while total sales adds them back. Delivery money pays the courier, not the ads, so counting it flatters MER.How do large returns change MER for furniture?
They lower net sales in the month the return is processed, which can be weeks after the sale. Read MER over several months, so one returned sofa does not look like an advertising problem.
Go deeper: Causal attribution, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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Terms in this article
- Ad SpendAd Spend is the total amount invested in advertising campaigns. It is measured against Return on Ad Spend (ROAS) to evaluate campaign effectiveness.
- AnalyticsAnalytics is the systematic computational analysis of data. It reveals customer behavior and measures campaign performance.
- AttributionAttribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive conversions.
- CausalityCausality is the relationship where one event directly causes another, essential for identifying specific actions that drive desired outcomes in marketing.
- ConversionConversion is a specific, desired action a user takes in response to a marketing message, such as a purchase or a sign-up.
- Conversion PathConversion Path is the sequence of interactions a user has with various touchpoints before completing a desired action.
- Google AdsGoogle Ads is an online advertising platform where advertisers bid to display ads, service offerings, and product listings.
- RevenueRevenue is the total income generated by the sale of goods or services related to a company's primary operations.