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How to Set Monthly Sales Targets for a Shopify Store

Build a monthly sales target from sessions, conversion rate and average order value, adjust it for the season, track pace, and respond when behind.

A monthly sales target that holds up is built from three numbers you can each influence: sessions, conversion rate and average order value. Multiply them together, adjust for the time of year and for what you have planned, and you have a target with a reason behind every part of it. This guide shows how to build the target with a worked example, how to shape it for seasonality, how to track pace during the month, and what to do when you are running behind.

How do you build a target from sessions, conversion and order value?

Sales = sessions × conversion rate × average order value. Start from last month's actual figures, then change only the inputs you have a plan to change.

Here is an example with made-up round figures. Say last month looked like this:

  • 20,000 sessions;
  • a 2.0% conversion rate, giving 400 orders;
  • a $60 average order value;
  • sales of 400 × $60 = $24,000.

For next month you plan two extra email campaigns and a higher ad budget, which you expect to lift sessions to 22,000. You have no reason to expect conversion to move, so it stays at 2.0%, giving 440 orders. You are launching a bundle that you expect to nudge average order value to $62.

  • Target: 440 × $62 = $27,280.

The value of building it this way is that each input has an owner and an action. A target of 'last month plus fifteen per cent' gives nobody anything to do. A target that needs 2,000 more sessions and $2 more per order tells you where the month will be won or lost. Our guides to how Shopify calculates conversion rate and to calculating and raising average order value cover the two inputs that are hardest to move.

Which sales figure should the target use?

Net sales, in the same definition as your reports. In Shopify, net sales are gross sales less discounts and returns, before shipping and tax. If the target is set in one measure and the dashboard shows another, you will look ahead or behind for reasons that have nothing to do with trading.

Should the target be the same every month?

No. Twelve equal targets set you up to miss the quiet months and coast through the busy ones, and both teach you to ignore the number.

If you have a full year of history, use its shape:

  1. Work out what share of last year's sales fell in each month.
  2. Set the goal for the coming year.
  3. Multiply the annual goal by each month's share.
  4. Adjust individual months for things that will differ: a sale you are moving, a launch, a holiday that falls in a different week.

If you have less than a year, build each month from the three inputs as in the example, and be explicit about which sessions figure assumes a seasonal lift. For a fuller treatment of the baseline, see forecasting sales for a small Shopify store.

How do you track pace through the month?

Compare sales to date with where you should be by this day, and do it at least weekly.

The simplest measure is straight-line pace: target × days elapsed ÷ days in the month. Continuing the example, on day 10 of a 30-day month the pace figure is 27,280 × 10 ÷ 30 = about $9,093. If actual sales are $8,200, you are about $893 short, close to 10% behind.

It helps to turn that into a required daily rate. You have $19,080 left to find in 20 days, which is $954 a day against the $820 a day you have averaged so far.

Straight-line pace has a flaw: months are not flat. A promotion planned for the last week means you should be behind until it starts. A better pace line uses the share of the month's sales that had normally arrived by this day in previous months. If the first ten days usually bring in less than a third of the month, being under the straight line on day 10 is not a problem.

What should you do when you are behind?

Find out which input is short before doing anything, because the response differs for each.

Sessions are short. Look at traffic by source against last month. A campaign that did not go out, an ad account that under-spent, or a fall in one channel will show up quickly. The fix is usually to do the thing that was planned.

Conversion is short. Check the basics first: is a best seller out of stock, did a theme change break something, has a payment method stopped working? Then look at where visits are ending. A drop concentrated in one step or on one device points to a fault, not to weaker demand.

Order value is short. Look at product mix and discounting. Heavier use of a discount code, or a shift towards cheaper items, lowers order value without any change in the number of customers.

Then choose a response in proportion to the cause.

  • Bring forward something already planned, such as an email or a launch.
  • Fix the fault if there is one.
  • Accept the miss if the cause is outside your control, and adjust next month's assumptions.

Be slow to reach for a sitewide discount. It can close a sales gap while opening a profit gap, and it teaches customers to wait.

Where should the target live?

Where the people who can affect it will see it: beside the sales figure, and beside a profit measure, so that nobody hits it by spending more than the sales are worth. At month end, compare each input with the assumption you made for it. Marka Metrics includes monthly sales targets on its free plan, alongside its sales dashboards.

A short checklist

  1. Build the target from sessions, conversion rate and average order value.
  2. Change only the inputs you have a plan to change.
  3. Set the target in net sales and say so.
  4. Shape monthly targets to last year's seasonal pattern.
  5. Check pace weekly and work out the daily rate still required.
  6. When behind, identify the short input before acting.
  7. Review assumptions against actuals at month end.

Targets are only as good as the figures they are measured against; our guide to Shopify analytics beyond the built-in reports explains how Shopify defines them. To set monthly targets in the same place as your sales reports, take a look at Marka Metrics.

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