About 20-24% of buyers don’t purchase on their first visit—they complete checkout days or even weeks later. Customers who take over 7 days to decide show 1.3-1.7x higher repeat purchase rates than same-day buyers. Consideration periods stretch from an average 5-9 days to 10-15 days during summer and holiday seasons. Kill your ad budget during these windows, and you’ll lose customers who were one step away from payment.
Soulpapamarketing’s branding and marketing insights.
Cut ad spend because sales dipped this week, and your losses won’t end there. The root of unstable revenue and low repeat purchases lies here. Open 10 years of GA4 and BigQuery data from dozens of brands we’ve run, and the pattern becomes clear.
1 in 5 buyers doesn’t purchase on day one
Every buyer takes a different amount of time from seeing your ad to checking out. Real data shows 20-24% of purchases happen days or weeks after the first visit—not the same day. 1 in 20 will wait over a month. The moment you kill your ads, those customers-about-to-pay disappear with them.
Read each path line and you’ll see where time gets spent. The first one went through Naver search 6 times, then powerlinks 14 more times, before finally converting. The third path shows search → powerlink → search → Naver Pay → search again 9 times—a customer who reached checkout, came back, and checked one more time. The last one cycled through Instagram 5 times, visited the profile, then Instagram 13 more times before ordering.
Long consideration periods exist because of the verification steps buyers run. They compare prices, hunt for reviews, and search again days later to double-check the same product. The average on this report: 8.97 days to checkout, 3.38 touchpoints. Each additional touchpoint adds a day or two of gap between them.
Seasonality lengthens consideration time through the same mechanic. During vacation and holiday periods, the pool of competitors and spending trade-offs both expand. The same person revisits the same touchpoint and pushes their purchase decision out a week. Kill your ads during this window, and the repeat touchpoints that used to bring them back vanish, and the path snaps right before checkout.
Why customers who think longer become repeat buyers
Conventional wisdom says a buyer who deliberates is weak. The real data flipped it. Customers taking 7+ days from first visit to purchase showed 1.3-1.7x higher repeat purchase rates than same-day buyers. Three anonymized brands we run all showed the same direction.
| Brand | Same-day purchase repeat rate | 7+ day consideration repeat rate |
|---|---|---|
| A | 6.8% | 11.5% |
| B | 10.4% | 14.0% |
| C | 10.6% | 15.6% |
Customers who compare thoroughly and build trust before buying become repeat customers. Kill your ads and you’re throwing out this entire cohort.
The gap is 3-5 percentage points per brand. It looks small, but repeat revenue needs no acquisition cost. Thin this layer and it’s not a few conversions this month—next month’s revenue shrinks with it. The cost of turning off your ads gets billed again on next month’s P&L.
Purchase consideration windows stretch and shrink by season
Time-to-purchase follows the calendar. A 5-9 day average consideration window in March stretches to 10-15 days during summer, vacations, and holidays. The seasonal curve ignores brand boundaries.
| Brand | March avg days to purchase | Jun-Jul avg days to purchase |
|---|---|---|
| A | 9.1 days | 14.5 days |
| B | 5.5 days | 11.5 days |
| C | 5.6 days | 10.5 days |
This is when customers want to buy, but cash flow, vacations, or other life events delay checkout.
What happens when you kill ad spend during this window
You abandon customers one step from payment and have to rebuild trust with someone new from scratch. That person will take time to decide too, and if another seasonal variable hits meanwhile, the entire recovery window disappears. Turning off ads doesn’t cost you this week’s revenue—it costs you weeks ahead.
You’re not just losing customers. Toggling ads on and off repeatedly forces the ad platform’s machine learning to start learning from zero each time. If your conversion data thins out during the off period, the next learning cycle will be that much less accurate.
Why early-funnel ads look like they’re not working
The attribution path report we saw earlier also breaks down how credit flows. Early touchpoints get 9.61%, mid touchpoints 11.00%, late touchpoints 79.39%. Almost all credit concentrates at the end. The #1 converter is (direct) at 28.39%, with 0.00 days to conversion and 1.00 touchpoint—customers who’ve already decided and typed the URL straight in.
Credit loss is mixed in here. Cross-domain jumps through Naver Pay or Kakao login break the session, and that conversion drops to (direct). Late-stage credit and direct attribution may be artificially inflated. But the 0.00 days value itself is telling. Whether earlier touchpoints were lost or never existed, that conversion got attributed entirely to the final touchpoint.
Even accounting for that loss, the conclusion stays the same. The trigger that pulls someone to checkout is last-click attribution—the final touchpoint. The first-click and mid-funnel touches that built those 9 days of consideration barely register in the numbers. That’s why awareness-stage ads always look inefficient, and when teams allocate budget by last-click alone, the first touchpoints are always the ones that get cut.
The “weeks of revenue ahead” I mentioned earlier splits into two losses. Kill your ads now and this week’s last-click conversions drop first. Then 1, 2, or 4 weeks later, the revenue that first-click and mid-funnel should have been building arrives missing. The second loss is so far removed from the decision point that it never looks connected to what caused it.
Flip it and you see why this structure has to hold. High late-stage credit means this week’s sales are the result of touchpoints laid down weeks ago. The reason this week’s numbers lag and why next month’s will recover are in the same table.
Revenue stability comes down to customer layers
Keep ads running and as the season shifts, customers convert. Toggle them and that customer layer collapses every time, and you start over from nothing. This is where revenue stability diverges between brands.
How to check your purchase consideration window in GA4
Your brand’s consideration period is visible right inside GA4.
- Navigate to Advertising → Key events → Key event attribution paths.
- Look at the “Days to key event” and “Touchpoints to key event” columns to see how many days elapsed from first touch to purchase and how many times the customer returned.
- If your average days exceed 7 or touchpoints exceed 3 across many sources, you’re in a structure where killing ads means losing revenue in the weeks that follow.
Ad budget isn’t money to toggle based on this week’s number. It’s capital you deploy to read seasons and build customer layers. Once you know how many days it takes, reacting to one week of numbers becomes less tempting. When your decision ground shifts from gut to data, you can hold the line without anxiety.
Frequently asked questions
When should I cut ad budget?
Not from day-to-day revenue swings, but when cost-per-sale (CPS) exceeds your target breakeven for multiple consecutive weeks. The longer your consideration window, the more you need to look at a 2-4 week rolling average. During peak seasons, consideration windows stretch from 9 to 15 days—so one or two weeks of variance is normal seasonal noise. React to short dips by cutting and you’ll lose potential customers who were already decided.
How do I check my purchase consideration window?
Pull the key event attribution paths report from GA4’s Advertising menu and look at “Days to key event.” If you’re using BigQuery GA4 export, you can calculate the gap between each user’s first visit and first purchase timestamp directly, then aggregate by month or cohort for more precision.
Should I turn ads off if revenue drops?
Usually no. First separate whether the drop is from a structural problem in creative, landing page, or targeting—or if the consideration window simply lengthened due to season. If it’s the latter, keep the budget running while you keep testing and refining creative and landing pages. That gives you better position for the revenue rebound that follows.
Aren’t slow-buying customers less loyal?
No—our actual data from 3 brands shows the opposite. Customers taking 7+ days to decide had 1.3-1.7x higher repeat purchase rates than same-day buyers. GA4 attribution paths also show customers visiting powerlinks and search 10+ times before converting, suggesting that deliberation signals higher loyalty. But this cohort can’t reach checkout if ad exposure drops, and if you judge by short-term ROAS alone, long-consideration creatives will always look undervalued.
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- Growth marketing: why staring at dashboards never surfaces your next move
→ About Soulpapamarketing—performance and growth marketing agency building brands with data
Frequently asked questions
Is it OK to cut ad budget when sales slow down?
Better not to. About 20-24% of buyers don’t purchase on their first visit—they convert days or weeks later. Kill ads during that window and you lose the revenue from customers who were days away from paying. In summer and holidays especially, when consideration windows stretch from 5-9 days to 10-15 days, cutting spend is even riskier.
Do customers with longer consideration periods show higher repeat purchase rates?
Yes. Our actual data showed customers taking 7+ days to decide had 1.3-1.7x higher repeat purchase rates than same-day buyers. GA4 and BigQuery attribution also show customers cycling through powerlinks and search 10+ times before converting—proof that deliberation customers can be more loyal. This means lengthy consideration-period customers may actually be your highest-value repeat buyers.
Insights from Soulpapa Marketing — Korea’s digital marketing agency.
Original Korean article: https://soulpapa.co.kr/2026/08/26/ad-budget-consideration-period/
