Truck Accessories Seasonal Sales Planning in New Zealand: Cash, Stock and Ads

Build the plan from your own order history

Start with your own completed order history, grouped by calendar month or by consistent seasons you define. Keep the period rules fixed: count delivered orders, units sold, realized revenue, and contribution using the same dates each time. ORVX calculates realized revenue from delivered orders only, excluding returned and cancelled orders, and keeps your trading currency separate.

Compare the measures together rather than using order count as a proxy for profitability. For illustration only, 40 orders can produce less contribution than 25 orders if the smaller set contains higher-margin products or lower advertising cost. ORVX computes product costs from your cost model, derives gross profit and margins, and reports contribution after advertising at product and collection level. That lets you identify which measure is relevant to the question: demand, sales value, product economics, or paid-growth efficiency.

• Orders: how many delivered purchases occurred in the period.
• Units: how many individual products sold; useful when orders contain multiple items.
• Realized revenue: the value retained from delivered orders after excluding returns and cancellations.
• Contribution after advertising: realized revenue less product cost and advertising spend; useful for comparing commercial value by product or collection.

Reading your own seasonal pattern

Separate timing from recognition. Use order date to see when demand arrived, then delivery date to assess realized revenue and profit. Compare the same calendar months across multiple years, recording orders, units, revenue, gross profit and return value. A peak that appears repeatedly is a planning signal; a single spike is an exception to investigate, not a new season.

Measure lead time by product and collection: the days between order and delivery, plus the spread between the earliest and latest orders in a peak. A product can show demand earlier than the wider store if customers need it fitted or delivered before a busy period. Keep that timing separate from the month in which revenue is recognised.

Then test what changed inside the peak. Compare each product’s unit share, gross profit, return rate and contribution after advertising with the prior comparable period. ORVX shows product- and collection-level profitability, return rate and advertising contribution, so revenue growth does not disguise a weaker mix. Its own-month forecast can provide a reference, with the method’s backtested error; treat one unusual period as a risk flag until later periods confirm it. See New Zealand seller guides for related context.

Planning stock before the peak

Use supplier lead time and reorder timing to answer “when must I buy?” If a supplier takes 30 days and peak demand starts in 45, the order needs to arrive with time for receiving and any delivery delay. The inventory reorder calculator can help test that timing. Lead time should guide the purchase date; it does not prove how many units will sell.

Use sell-through to answer “how quickly is this stock moving?” Compare units sold with units available over the same period. Strong sell-through supports a reorder when remaining cover is shorter than supplier lead time. Weak sell-through calls for a smaller order or no reorder, even if the calendar says the peak is near.

Use landed cost and cash tied up to test whether the purchase is affordable and profitable. Include product cost and relevant freight or import charges, and treat GST consistently; New Zealand GST is 15% (Inland Revenue, GST). Twenty units at a $200 landed cost tie up $4,000. ORVX reports remaining stock value, dead stock, product profitability and gross margins, helping compare a possible margin gain with the cash left in inventory (Source: Inland Revenue (Te Tari Taake)).

Set ad budgets around profitable demand

Set each month’s budget against four measures: ad spend, delivered orders, contribution after advertising and payback. Orders show volume, but not whether sales covered product and marketing costs. Contribution shows the dollars left after advertising; payback can be expressed as contribution after advertising divided by ad spend. For illustration only, $2,000 of spend producing $4,500 of contribution gives a 2.25x payback. Compare the same measures by product and collection, because a high-volume bull bar range can subsidise a low-margin accessory range.

Protect budget for periods that repeatedly produce strong contribution and payback, rather than increasing spend solely because order count is high. Use attributed ROAS to assess the advertising platforms’ credited sales, and MER to compare total store revenue with total advertising spend; the former is useful for channel decisions, while the latter checks whether the whole store is earning enough from advertising. In quieter months, reserve a defined test budget and judge it against contribution, not clicks or impressions. ORVX can bring Shopify revenue and advertising spend together, while keeping product and collection profitability visible, so a weak test can be reduced or stopped without cutting proven demand.

Read the worked planning example

Read the worked figures as a chain, not as six separate targets. Units explain volume; sales show the dollar value of those units; and gross profit shows what remains after product cost. For illustration only, 40 units sold at $250 creates $10,000 in sales. If product cost is $6,000, gross profit is $4,000, or 40%. That is the product economics before advertising and other operating costs.

Stock commitment is different: it is cash tied up in inventory you plan to purchase, not sales or an expense recognised when the order is placed. Ad spend is a separate cash outflow. Subtracting the $1,200 ad spend from $4,000 gross profit leaves $2,800 contribution after advertising. Cash can still be tight if the supplier requires payment before the peak, while customer receipts arrive later. Use units to test demand capacity, sales to plan turnover, gross profit to assess margin, ad spend to control acquisition cost, and cash timing to decide whether the plan is financeable. For a timing check, compare the commitment dates with the inventory reorder calculator.

Review what changed after the peak

Close the review only after the peak’s deliveries, returns and refunds have settled. Compare forecast units and delivered revenue with actuals: if the forecast was 200 units and 170 were delivered, the unit error was 30, or 15%. Then record stockouts by product and date. A stockout shows unavailable supply, not automatically lost demand, so separate proven missed orders from an estimate. Review leftover units, remaining stock value and dead stock, then identify which products tied up cash. Margin should use delivered sales and actual product cost, with returns excluded from realized revenue.

Review advertising efficiency in two ways. MER compares total store revenue with total ad spend and is useful for judging the whole acquisition budget; attributed ROAS assigns revenue to tracked campaigns and is useful for campaign-level decisions. Neither replaces contribution after advertising. Finally, map cash timing: when customers paid, when suppliers and ad platforms were paid, and when refunds left the account. Act on different evidence: fix recurring forecast error, change buying after stockouts or excess, reduce unprofitable ads, and protect cash before the next peak. ORVX can report these profitability, inventory and advertising measures from connected store data.

A useful seasonal plan connects the timing of demand with the timing of stock payments, advertising spend and cash recovery. Rebuild it from your latest order history, then record which assumptions held and which need changing before the next peak.