Are Influencer-Acquired Customers Worth More? Thinking About LTV

The short answer

Yes — for many ecommerce brands, an influencer-acquired customer is worth more than the first order shows, if that customer buys again. But if your customers rarely repeat-purchase, the first order is close to the whole story: a channel that looks expensive on first-purchase ROAS actually is. Below: the LTV formula, the LTV:CAC ratio, and a worked example showing when the difference flips the picture.

Two numbers you need before you can answer this: CAC and LTV

The question can only be answered by putting two numbers against each other:

• CAC (Customer Acquisition Cost) for the influencer channel: total campaign cost ÷ number of new customers the campaign acquired — not number of orders.
• LTV (lifetime value): what the average customer actually generates over the full customer relationship, not just the first order.

CAC is related to CPA (cost per acquisition) from the CPM/CPE/CPA framework, but it's specifically calculated per new customer, whereas CPA is often calculated per conversion regardless of whether the customer is new or returning. If you haven't yet settled whether influencer marketing is the right channel for you at all, start with is influencer marketing worth it for ecommerce brands instead — this article assumes you're already running campaigns and need to judge whether the customers are worth more than the first order shows.

The LTV formula

Per Shopify's own definition, customer lifetime value is calculated as:

LTV = Average order value × Purchase frequency × Average customer lifespan

That gives a revenue-based LTV. To get a figure that can actually be compared against a campaign cost, multiply by your gross margin:

Margin-adjusted LTV = Revenue-based LTV × Gross margin

It's the margin-adjusted figure that belongs alongside CAC — not the raw revenue number. Comparing CAC against revenue-based LTV compares a cost against a revenue, not a profit, and the conclusion ends up too optimistic.

The LTV:CAC ratio — and why the "3:1" rule of thumb needs care in ecommerce

A widely repeated rule of thumb says a LTV:CAC ratio of 3 or higher is healthy. Per Harvard Business School Online's own writeup, quoting HBS professor Christina Wallace, "an LTV-to-CAC ratio of three or higher is attractive and indicates a scalable business."

The rule originates in SaaS and venture-backed business models, where payback periods are typically short and subscription revenue makes lifetime value relatively predictable. In ecommerce with influencer-acquired customers, those same assumptions rarely hold: repeat-purchase rate varies enormously by category, and customer lifespan is harder to predict early in a customer relationship. Use 3:1 as a reference point to reason from — not as a target your own business has to hit.

What holds almost universally across business models: retention is cheaper than acquisition. The same HBS Online writeup notes, citing research from Bain & Company, that acquiring a new customer costs 5 to 25 times more than retaining an existing one, and that a 5-percentage-point increase in retention rate can lift profit by 25-95%. That isn't an influencer-specific figure, but it's why repeat purchases from an already-acquired customer are worth counting, regardless of channel.

Make Influence's operational perspective: influencer-acquired customers can behave differently from search-ad customers

In our experience, part of the LTV difference comes from the customer journey: a customer who discovers a product through a creator they already follow and trust starts the relationship with a level of trust a search-ad customer doesn't necessarily have. That's an operational observation from our own campaigns, not a documented industry fact, and it doesn't hold in every category or for every creator. But it's one reason a pure first-purchase-ROAS view can undervalue the influencer channel for a brand with a decent repeat-purchase rate.

The reverse also happens: a creator who mostly drives impulse purchases from an audience with no real category interest can produce a low repeat-purchase rate — and there, first-purchase ROAS actually is close to the whole story. LTV is not an automatic bonus for the influencer channel. It's a question you have to measure your way to an answer on, not assume.

Worked example

All numbers below are hypothetical and for illustration only. This is not a real Make Influence customer case. Replace every number with your own.

An influencer campaign acquires 40 new customers for a total campaign cost of DKK 24,000.

• CAC = 24,000 ÷ 40 = DKK 600 per new customer

Those 40 customers have (based on the brand's own historical figures for similar customers) an average order value of DKK 350, buy 3.2 times a year, and stay customers for 1.5 years on average — and the brand runs a 45% gross margin.

• Revenue-based LTV = 350 × 3.2 × 1.5 = DKK 1,680
• Margin-adjusted LTV = 1,680 × 0.45 = DKK 756
• LTV:CAC ratio = 756 ÷ 600 = 1.26

That's well under the 3:1 rule of thumb — but it doesn't automatically mean the channel is bad. Look at the payback period instead:

• Margin per order = 350 × 0.45 = DKK 157.50
• Orders needed to earn back CAC = 600 ÷ 157.50 ≈ 3.8 orders
• At 3.2 orders/year, that's ≈ 1.19 years — inside the customer's average 1.5-year lifespan.
• Net profit per customer over the full lifespan = 756 − 600 = DKK 156

Looking only at the first order, the channel appears to lose money: DKK 157.50 in margin against a DKK 600 CAC is a DKK 442.50 loss per customer. Counting the full customer relationship, that flips to a DKK 156 profit per customer — a DKK 598.50 swing driven entirely by repeat purchases.

How to calculate this for your own influencer campaigns

1. Pull CAC from what you already track. Use your existing tracking (unique links or codes per influencer) to count the number of new customers, not just orders — see what is a good ROAS for influencer marketing for how to structure the cost side.
2. Build a cohort per campaign or creator. Take the customers who made their first purchase through a given campaign, and follow them specifically over the next 6-12 months.
3. Measure actual repeat-purchase rate and frequency on that cohort — not your store-wide average, which can mask large differences between channels.
4. Use your real gross margin, not an assumed industry rate.
5. Compare margin-adjusted LTV against CAC, and calculate the payback period — not just the ratio.

The first time you do this, you won't have 6-12 months of data yet. Start with a shorter window (e.g. 90 days), and update the figure as more history comes in — a provisional LTV based on 90 days is still more accurate than assuming the first order is the whole story.

Decision framework: when should LTV change your view of a channel's ROAS?

Situation	What LTV tells you	What it means for the decision
Low first-purchase ROAS, but good repeat-purchase rate	Margin-adjusted LTV can far exceed CAC even though the first order looks expensive	The channel can easily be profitable — don't judge it on first-purchase ROAS alone
Good first-purchase ROAS, but low repeat-purchase rate	LTV ≈ the value of the first order — there isn't much more to gain	First-purchase ROAS is close to the real picture — use it as your headline metric
Unknown repeat-purchase rate	You can't tell the two scenarios above apart	Build the cohort before concluding anything from LTV
Very long payback period (close to or beyond the customer lifespan)	CAC never gets earned back, or only just does	Lower CAC, improve the repeat-purchase rate, or accept the channel as a brand investment rather than a performance channel

Common mistakes

• Comparing CAC against revenue-based LTV instead of margin-adjusted LTV — this overstates how profitable the channel actually is.
• Using the store's overall repeat-purchase rate instead of the actual rate for customers acquired through the influencer channel specifically.
• Calculating LTV over too short a window and extrapolating too aggressively from a few months of data.
• Applying the 3:1 rule uncritically, without considering whether your payback period and business model resemble the one the rule comes from at all.
• Assuming influencer-acquired customers automatically have higher LTV than other channels — that has to be measured, not assumed (see the operational-perspective section above).

Checklist before you use LTV to judge an influencer channel

• Do you know your CAC per new customer for the channel — not just campaign cost per order?
• Have you built a cohort of customers acquired specifically through influencer campaigns?
• Are you using margin-adjusted LTV, not revenue-based LTV, when comparing against CAC?
• Have you calculated the payback period, not just the ratio?
• Do you have enough cohort data for the figure to be reliable — or are you still in a provisional 90-day window?

FAQ

Is LTV always higher for influencer-acquired customers than other channels?

No. It depends on whether the creator drives customers with genuine category interest or impulse purchases with no follow-on relationship to the brand. It has to be measured on your own cohorts, not assumed.

How long do I need to wait before I have a reliable LTV figure?

There's no single right answer, but a provisional figure after 90 days is better than assuming the first order is the whole story — update it as the cohort ages.

Does LTV:CAC always need to be above 3?

No, that's a rule of thumb from the SaaS world. In ecommerce, payback period is often a more accurate measure, because the customer relationship isn't necessarily subscription-based.

How does LTV affect how I should pay influencers?

A high repeat-purchase rate can justify a higher upfront investment or CAC than first-purchase ROAS alone would allow — see upfront vs commission and how to set an influencer marketing budget for how that factors into budget and payment model.

Is LTV the same thing as ROI?

No. ROI typically looks at one campaign's cost against its direct return; LTV looks at the value of the full customer relationship, regardless of which campaign triggered later orders. See how to calculate influencer marketing ROI for the ROI formula.