How do I track influencer sales for an electronics store?
If you sell consumer electronics, give each creator a tagged link and a capped discount code, then judge them over weeks, not days. Buyers compare before they pay, so a review often opens the journey while a search or an email closes it and takes the credit.
By Joris van Huët, Founder & CEOUpdated 5 min read
Run the numbers for your store: the free attribution window calculator.
If you sell consumer electronics, give each creator a tagged link and a discount code with a usage limit. Then judge them over weeks, not days. Gadget buyers usually compare reviews before paying. A creator's video often opens that research, and a search or an email closes it and takes the credit.
If you sell consumer electronics
If you sell headphones, cameras or smart home kit, your buyers are spending real money, and they behave like it. They read spec sheets, watch more than one review and check the price elsewhere before they pay. A creator's video is often where that research starts, not where it ends. And research takes time. Someone watches an unboxing on Sunday and compares two models all week. They buy after payday, on a laptop, by typing your brand into a search bar. By then the creator's link is nowhere near the sale.
Codes behave differently here too. On an expensive gadget, a discount code is worth hunting for, so a tech creator's code makes tempting deal-site material. And if you also sell through marketplaces or big retailers, some viewers will buy there, where your GA4 and Shopify reports cannot see.
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 2 to 3 touches (12.5 days to buy) | 12.2% | Journeys sheet, 2 to 3 touches row |
| Journeys with 4 to 9 touches (16.9 days to buy) | 5.4% | Journeys sheet, 4 to 9 touches row |
| Journeys with 10 or more touches (16.0 days to buy) | 3.0% | Journeys sheet, 10+ touches row |
The export does not say what this store sells. Read it as one store's pattern, and not a benchmark for electronics.
On the Journeys sheet, journeys with 1 touch hold 79.5% of revenue and took 0.5 days to buy. Those buyers moved fast, as if they arrived knowing what they wanted. A review could have planted the idea weeks earlier, and the export would never know, because it only sees visits to the site.
If you sell electronics, the longer rows are the ones to study. On the Journeys sheet, journeys of 2 to 3 touches took 12.5 days to buy, and journeys of 4 to 9 touches took 16.9 days. Add the 10 or more row, and multi-touch journeys hold 20.6% of revenue in the export (12.2% + 5.4% + 3.0%), about a fifth.
A creator who opens a journey that long is more than a fortnight away when the sale lands. Last click hands the sale to whatever closed it, often a search, an email or a typed address.
On the Journeys sheet, 3,656 of the 3,670 distinct path sequences have more than one touch. That says the long journeys vary a lot. It does not say how many people took them, because a path sequence is not a purchase.
What the export cannot show is which journeys began with a creator. It holds channels and touch counts, not the reviews behind them.
What changes for an electronics store?
Keep GA4's lookback long. GA4's default lookback window for key events such as purchases is 90 days, and you can shorten it to 30 or 60. If you sell electronics, leave it at 90, so a creator click early in the research still counts.
Expect Meta's report to miss the long tail. Meta's standard settings count purchases up to 7 days after a link click, or 1 day after a view. A partnership ad that opens a fortnight of research falls outside both windows.
Cap every code. In Shopify's discount settings, Limit to one per customer and a total use limit slow down a code that escapes to deal sites. Give each creator a fresh code per launch, so last year's code cannot keep collecting credit.
Count the review's whole life. A good review can keep getting watched long after launch week. Keep the creator's link live, and compare its sessions month by month, not just in the first week.
What to do this week
- Check your lookback window. In GA4, go to Admin > Data display > Events > Attribution settings. Pass: the key event lookback window is 90 days. Fail: it is shorter, so early creator clicks drop out of credit; changes apply going forward only.
- Find creators in long paths. In GA4, click Advertising, open Key event attribution paths under Key events and switch the drop-down to Campaign. Then filter the path length to greater than 3 touchpoints. Pass: creator campaigns show up among early touchpoints. Fail: they never appear, so creator clicks arrive untagged.
- Cap your next creator code. In Shopify admin, go to Discounts, open the creator's code and find Maximum discount uses. Pass: Limit to one per customer is ticked. Fail: the code is unlimited, so one deal-site post can bury the creator's real numbers.
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: Select attribution settings (Google); Key events attribution paths report (Google); About attribution models and attribution settings (Meta); About partnership ad permissions (Meta); Amount off discounts (Shopify)
Related answers
Frequently asked questions
How long should I track a tech reviewer's video?
Longer than launch week, if your buyers research for weeks. A good review can keep getting watched for months. Keep the creator's link live, leave GA4's lookback at its 90-day default, and compare the link's sessions month by month.What if my electronics also sell on marketplaces?
Then some viewers will buy there, and GA4 and Shopify never see it. Before you judge a creator, check your marketplace sales in the weeks after their review. Put them next to the link and code results from your own store.Why do tech creators' codes end up on deal sites?
Because on an expensive gadget, a code is worth hunting for. Once a code is posted on a deal site, anyone can use it, and the creator collects credit for shoppers they never reached. Cap uses per customer and issue a fresh code for each launch.
Go deeper: Causal attribution, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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Terms in this article
- 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.
- Attribution ModelAn Attribution Model defines how credit for conversions is assigned to marketing touchpoints. It dictates how marketing channels receive credit for sales.
- Attribution WindowAttribution Window is the defined period after a user interacts with a marketing touchpoint, during which a conversion can be credited to that ad. It sets the timeframe for assigning conversion credit.
- Causal AttributionCausal Attribution uses causal inference to determine which marketing touchpoints genuinely cause conversions, not just correlate with them.
- CausalityCausality is the relationship where one event directly causes another, essential for identifying specific actions that drive desired outcomes in marketing.
- InfluencerAn Influencer affects purchase decisions due to their authority, knowledge, or relationship with their audience. They drive consumer behavior.
- TouchpointTouchpoint is any interaction a customer has with a brand throughout their journey. In marketing attribution, each touchpoint is a data signal to understand marketing impact.