Influencer campaigns
In plain English
Influencer marketing is easy to spend money on and famously hard to measure. You pay someone, they post, some sales happen, and nobody can say for certain how much of it was them.
This screen is the tracker that makes it answerable. Every partnership gets a card that moves through five stages:
| Stage | What it means |
|---|---|
| Draft | You're considering them. Not contacted yet |
| Sent | You've reached out |
| Active | Agreed. The work is happening |
| Posted | Their content is live |
| Done | Finished, results recorded |
| Declined | Didn't happen |
Each card holds who they are, which platform, their follower count, their engagement rate, what you paid, and what revenue came back.
That last pair is the point. Most shops know what they spent on influencers and only have a vague sense of what they got. Putting both on the same card turns "that campaign felt good" into a number.
How to use it
- Click "Campaigns" in the left-hand menu.
- Click "New campaign" and add the influencer: name, platform, handle, follower count, engagement rate, and the fee you've agreed.
- Move the card along as things progress — Sent when you contact them, Active when they agree, Posted when it goes live.
- Before they post, go to Influencer SEO and optimise the product pages they'll link to. This matters more than it sounds.
- Give each influencer their own promo code. It's how the revenue gets attributed.
- Record the revenue when results come in, and mark it Done.
- Check the platform breakdown to see which platforms actually work for you.
⏱ ~5 min per campaign · 💳 Pro+ · 🎯 Know which partnerships paid for themselves
Why this matters for your business
The reason influencer spend is so hard to control is that the feedback loop is broken. You pay in advance, the results arrive weeks later in a form nobody attributes properly, and by the time anyone asks "did that work?" the details have been lost across DMs, spreadsheets, and someone's memory.
So the decision about who to work with next gets made on impressions — follower counts, how the post looked, whether the comments were nice. None of which is revenue.
Keeping fee and revenue on the same card fixes the loop. After a handful of campaigns you have a real list of which partnerships returned more than they cost, and the next round of decisions gets made on evidence.
The pattern that emerges is almost always the same, and it surprises people: follower count is a poor predictor of return. Smaller accounts with engaged, specific audiences routinely outperform large ones by a wide margin, because their audience actually trusts them and actually overlaps with your product. You can only see that if you're recording both numbers.
The other thing worth knowing is about timing. An influencer drop creates a burst of people searching for your product. If your product pages aren't optimised beforehand, that burst lands and disappears. If they are, you keep earning from it for months — frequently more than the campaign itself produced.
What this typically unlocks
| What you get | Typical result |
|---|---|
| Knowing which partnerships paid off | Per campaign, with real numbers |
| Return on influencer spend | Often improves substantially once decisions are evidence-based |
| Lost partnerships in DMs and spreadsheets | Eliminated — one board |
| Long-term value from each drop | Much higher when pages are optimised first |
| Platform choice | Based on your results, not on general advice |
What you actually get
What each campaign card holds
| Field | Why it matters |
|---|---|
| Influencer name and handle | Who, and where to find them |
| Platform | Instagram, TikTok, YouTube, X, or Pinterest |
| Follower count | Reach — but see the warning below |
| Engagement rate | Usually a far better predictor than follower count |
| Fee | What you're paying |
| Attributed revenue | What came back |
| Promo code | How the revenue gets tracked |
| Products mentioned | Which pages to optimise first |
| Notes | Terms, deliverables, anything agreed |
The pipeline, and why it's restricted
The board only offers moves that make sense from where a campaign currently is:
| From | You can move to |
|---|---|
| Draft | Sent, Active, Declined |
| Sent | Active, Posted, Declined |
| Active | Posted, Done, Declined |
| Posted | Done, Declined |
| Done | (finished) |
| Declined | (finished) |
A finished campaign stays finished. You can't accidentally move a completed partnership back to draft, which keeps your history — and your reported returns — trustworthy.
Follower count vs. engagement rate
The most common expensive mistake in influencer marketing is paying for followers.
| Influencer | Followers | Engagement | Typical outcome |
|---|---|---|---|
| Large, general | 500K | 0.8% | Big reach, weak response |
| Mid-size, specific | 40K | 6.2% | Fewer people, far more buyers |
Engagement rate tells you whether the audience is listening. Follower count only tells you how many people scrolled past.
A 40K account at 6.2% engagement produces roughly 2,480 engaged views. A 500K account at 0.8% produces about 4,000 — only 1.6× more, from an audience 12× larger and usually costing several times as much.
Record both, and after a few campaigns your own data will tell you which matters for your category.
Attribution, and its honest limits
Revenue is attributed mainly through promo codes. Give each influencer their own.
| Method | Catches | Misses |
|---|---|---|
| Promo code | Anyone who uses the code | People who buy without it |
| Tracked link | Direct clicks | People who search for you later |
Both under-count, and it's worth knowing by how much. Someone who sees a post on Tuesday, thinks about it, and searches for your brand on Saturday is a genuine result that neither method captures.
Practical approach: treat attributed revenue as a floor. Use it to compare campaigns against each other — that comparison is fair, because every campaign is under-counted similarly.
Platform performance
The board aggregates by platform, so you can see where your money actually works.
Results vary enormously by category, and general advice is usually wrong for any specific shop. Some brands find TikTok returns three times Instagram; others find the reverse. Your own numbers after five or six campaigns are worth more than any benchmark.
How it works (without the technical bits)
Real merchant scenarios
Scenario A — The small account that beat the big one
Setup. Skincare brand ran two campaigns in the same month.
| Influencer A | Influencer B | |
|---|---|---|
| Followers | 480,000 | 31,000 |
| Engagement rate | 0.9% | 7.1% |
| Fee | £4,200 | £650 |
| Attributed revenue | £1,890 | £4,340 |
| Return | 0.45× | 6.68× |
The smaller account returned nearly 15 times better on a fee that was a sixth the size.
Why. Influencer B's audience was specifically people with sensitive skin — exactly the brand's customer. Influencer A's was general beauty, where most viewers had no particular reason to care.
What changed. They stopped filtering prospects by follower count and started filtering by engagement rate and audience fit. Over the following two quarters, average return went from 1.2× to 4.1× on roughly the same total spend.
Scenario B — Optimising the pages first
Setup. Apparel brand, two similar campaigns three months apart, similar fees and similar creators.
The difference: for the second, they ran the Influencer SEO pass on the linked product pages a week beforehand.
| Campaign 1 | Campaign 2 | |
|---|---|---|
| Fee | £3,000 | £3,200 |
| Spike-week revenue | £11,400 | £12,100 |
| Revenue, following 90 days | £1,800 | £14,600 |
| Total return | 4.4× | 8.3× |
The spike was almost identical. The tail was eight times larger.
Why. Campaign 1's traffic landed on pages that weren't indexed well and had thin content. When the creator's audience moved on, so did the revenue. Campaign 2's pages ranked for the terms the campaign created demand for, and kept earning.
One week of preparation nearly doubled the total return.
Scenario C — Recording what was actually spent
Setup. Homeware brand tracked influencer work in a spreadsheet. Fees were recorded; product gifted was not.
When they moved to campaign cards and included the retail value of gifted product in the fee:
| Spreadsheet view | Full cost | |
|---|---|---|
| Recorded spend, 6 months | £8,400 | £19,100 |
| Attributed revenue | £24,600 | £24,600 |
| Return | 2.9× | 1.29× |
Still positive, and a completely different picture. Gifting had been more than half the real cost and was invisible.
Action. Reduced gifted quantities, focused on fewer partnerships, and required a promo code from everyone. Return recovered to 2.4× on genuine full-cost accounting.
Scenario D — Platform results contradicting the advice
Setup. Merchant told repeatedly that TikTok was where their demographic was. Ran eight campaigns, six on TikTok.
After six months:
| Platform | Campaigns | Spend | Revenue | Return |
|---|---|---|---|---|
| TikTok | 6 | £9,800 | £7,100 | 0.72× |
| 1 | £1,400 | £5,900 | 4.21× | |
| 1 | £600 | £3,200 | 5.33× |
Their two cheapest experiments outperformed six TikTok campaigns combined.
Why. They sold high-consideration home furniture. TikTok drove awareness and very few purchases; Pinterest reached people actively planning a room.
Action. Shifted the mix toward Pinterest and Instagram. Overall return went from 0.94× to 3.6× over the next two quarters.
The general advice was right about where the audience was and wrong about where the buyers were.
Scenario E — Attribution floor, honestly used
Setup. Merchant frustrated that attributed revenue seemed low against an obvious traffic spike.
What they measured. Total site revenue in the campaign week against a normal week:
| Normal week | Campaign week | |
|---|---|---|
| Total revenue | £18,200 | £26,700 |
| Attributed to the code | — | £3,100 |
| Unexplained uplift | — | £5,400 |
Attribution captured roughly 36% of the likely effect.
How they used it. Not by inflating the numbers, but by recognising that every campaign was under-counted by a similar factor — so comparing campaigns against each other remained fair, and the reported return was a conservative floor rather than the truth.
Best practices
✅ Filter prospects by engagement rate, not follower count. Scenario A.
✅ Optimise the product pages a week before the drop. Scenario B — it's the cheapest way to double your return.
✅ Give everyone a unique promo code. Without it you're guessing.
✅ Record the full cost, including gifted product. Scenario C.
✅ Test two or three platforms before committing. Your results will disagree with general advice.
✅ Treat attributed revenue as a floor, and compare campaigns against each other rather than against an absolute target.
❌ Don't pay for reach you can't convert. Big accounts with low engagement are the most common way to lose money here.
❌ Don't run a campaign without preparing the landing pages.
❌ Don't judge a platform on one campaign. Creator quality varies more than platform does.
❌ Don't leave campaigns sitting in Active. Record the result and close them, or your reporting drifts out of date.
Plan tiers
| Capability | Free | Starter | Pro | Agency | Enterprise |
|---|---|---|---|---|---|
| Campaign pipeline board | — | — | ✓ | ✓ | ✓ |
| Fee and revenue tracking | — | — | ✓ | ✓ | ✓ |
| Five platforms | — | — | ✓ | ✓ | ✓ |
| Platform performance breakdown | — | — | ✓ | ✓ | ✓ |
| Promo-code attribution | — | — | ✓ | ✓ | ✓ |
| Link UGC to a campaign | — | — | ✓ | ✓ | ✓ |
| AI campaign briefs | — | — | ✓ | ✓ | ✓ |
| Multi-store campaign roll-up | — | — | — | ✓ | ✓ |
Frequently asked
How is revenue attributed? Mainly through the influencer's unique promo code, plus tracked links. Both under-count, so treat the figure as a floor.
Why can't I move a completed campaign back to draft? Finished states are final so your historical returns stay trustworthy. Create a new campaign for a repeat partnership.
What engagement rate is good? It varies by platform and size, but broadly: under 1% is weak, 3%+ is solid, and 6%+ is excellent. Smaller accounts tend to score higher.
Should I include gifted product in the fee? Yes — at retail value. Scenario C shows what happens if you don't.
Can I link customer photos from a campaign? Yes. Make sure you have proper permission — see UGC library.
How many campaigns before I can judge a platform? At least three per platform. Creator quality varies more than platform does, so one result tells you very little.
What if an influencer won't use a promo code? Use a tracked link and accept weaker attribution. If neither is possible, measure total revenue in the campaign week against a normal week — see Scenario E.
Where do I write the brief? There's a dedicated brief tool that generates one from your campaign and product details.
See also
- Marketing signals — the Influencer SEO pre-pass
- UGC library — using their photos legally
- Social publishing — amplifying the content
- Attribution & revenue — how revenue is credited
- Referral program — a related acquisition channel
- Affiliate program — commission-based partnerships
- Revenue command center — campaign revenue in context