Store Performance

What is Store Performance?

The Shopify pages cited here do not define store performance as a single measure. In practice the phrase covers two groups of measures that Shopify documents separately. The commercial group appears in its analytics fields: net sales, orders, average order value, sessions (online store visits), conversion rate (sessions that completed checkout divided by sessions) and returning customer rate. The technical group appears in its web performance reports, which rate loading speed, interactivity and visual stability, known as Core Web Vitals. Shopify's page on web performance uses the phrase online store performance for this second group and says that optimizing it can increase conversion rates, but it gives no estimate, so the size of any effect on a given store has to be measured. This entry covers online stores only.

Most commercial measures are totals or ratios, so they move when any ingredient moves. Shopify adds data caveats: sessions are only counted when visitors consent to cookies, other analytics platforms calculate sessions differently, and bot traffic can make conversion rate look lower than expected.

For measuring marketing, store performance is the outcome side: orders, sales and new customers are what a campaign is judged against. It records what happened with every cause mixed together, including marketing, the season, promotions, stock and page speed. Shopify's marketing reports divide sales among channels with credit rules such as last click, first click and any click, and note that the any-click model allocates more credit than the orders received. A movement in store performance cannot be assigned to a marketing action without a comparison: a holdout, a control group or a model of the earlier trend.

For illustration, suppose a store has 1,000 sessions and 30 of them complete checkout, a conversion rate of 30 / 1,000 = 3%. Suppose a campaign then adds 1,000 sessions that produce 10 orders. The rate becomes (30 + 10) / 2,000 = 2%, so it fell by a third while orders rose by a third, and nothing about the store got worse.

Why Store Performance matters for ecommerce

Every marketing report ends in a store measure: orders, net sales, new customers, conversion rate. Those measures are totals and ratios that many things move at once, so a drop in conversion rate can come from a change in traffic mix, a gap in cookie consent, bot traffic or a slow page, and a rise in sales can come from the season. Shopify's own definitions show how much the answer depends on the definition: sessions exclude visitors who do not consent to cookies, and sales attributed to marketing can differ from sales in other reports because only trackable traffic is credited. Store performance is what needs explaining; it is not itself an explanation. A 2019 Marketing Science paper found that observational methods often failed to reproduce randomized ad experiments, which is why a comparison is needed before crediting a channel.

How to use Store Performance

1. Decide which meaning you need. For commercial performance, open Analytics, then Reports in Shopify admin and use net sales, orders, sessions, conversion rate and average order value. For technical performance, open the web performance reports for Largest Contentful Paint, Interaction to Next Paint and Cumulative Layout Shift.
2. Set a comparison in the report: Shopify's comparison menu compares a period with the previous period or the same period last year. Export the report to a spreadsheet and keep your own copy, because Shopify makes web performance data available for only the last 90 days and says it might be delayed by up to 36 hours.
3. Split every ratio into its parts before reading it. For conversion rate, put sessions that completed checkout and sessions in separate columns and see which one moved.
4. Check the known blind spots. Confirm the cookie banner works, because sessions are only counted with consent; filter conversion rate to human traffic; and do not compare Shopify sessions with sessions from another tool, which Shopify says calculates them differently.
5. Keep a dated log beside the metrics: campaign launches, promotions, price changes, theme and app installs. Shopify's web performance charts mark app installs, theme updates and new code with event annotations.
6. Judge a marketing effect only against a comparison. Pass: the measure moved after a dated change while a comparison group or the earlier trend did not, and both the numerator and the denominator moved the way the explanation requires. Fail: the move matches the season or a promotion, or only the denominator changed.

Common mistakes

1. Reading conversion rate as a verdict on the store. It is sessions that completed checkout divided by sessions, so added traffic that converts below the store's average lowers it with no change to the store. The cost is cutting campaigns that were adding orders.
2. Comparing Shopify sessions with sessions in another analytics tool as if they counted the same thing. Shopify counts sessions only with cookie consent and says other platforms calculate them differently. The cost is chasing a gap that comes from definitions.
3. Treating sales attributed to marketing as the total effect of marketing, or adding up channel credit. Shopify's report covers only trackable traffic, says its figures can differ from other reports, and notes that its any-click model allocates more credit than the orders received. The cost is double counting and missed sales.
4. Assuming every checkout follows an add-to-cart. Shopify notes that checkouts can exceed add-to-cart counts when customers buy directly from channels such as Instagram Shopping or Facebook Shops. The cost is misreading funnel rates.
5. Judging the site from one day's speed numbers or a few slow pages. Shopify points out that a customer's device, network and location are beyond the merchant's control and advises not to worry much if the overall metric is good. The cost is reacting to noise.
6. Crediting marketing for a movement in store performance without a comparison. Observational methods often failed to reproduce randomized experiments in a 2019 study of Facebook ads. The cost is budget moved on a coincidence.

Frequently asked questions

• What does store performance mean?

  It is a general phrase, not one defined metric. It can mean how well an online store sells (net sales, orders, sessions, conversion rate, average order value) or how well it loads (Largest Contentful Paint, Interaction to Next Paint, Cumulative Layout Shift). Shopify documents the two sets in separate reports.
• Which metrics does Shopify report for store performance?

  Shopify's analytics fields include net sales, total sales, orders, average order value, sessions, conversion rate and returning customer rate. Its web performance reports add the three Core Web Vitals: loading speed, interactivity and visual stability.
• Why did my conversion rate drop when sales went up?

  Conversion rate is sessions that completed checkout divided by sessions. If new traffic adds sessions faster than orders, the rate falls even as orders rise. Check the two parts separately, then bot traffic and cookie consent, before suspecting the store.
• Can store performance show whether marketing worked?

  Not by itself. It shows what happened with every cause mixed together. Showing what marketing added needs a comparison: a random holdout, a control group or a model of the trend that would have continued.

Further reading

• Analytics fields · Shopify Help Center
• Web performance reports · Shopify Help Center
• Marketing reports · Shopify Help Center
• A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook · Marketing Science, RePEc record

Related terms

Every term is listed in the glossary index.

Keep reading

Go deeper: Causal attribution, explained.

• Store Performance Metrics for Shopify: What to Track Beyond Revenue

All glossary terms

Have an audience of ecommerce operators? Earn 20% recurring commission by recommending the €99 read.