Lifetimely alternatives: cohort LTV in contribution terms, inside the daily P&L

Lifetimely by AMP leads with cohorts and LTV. nouz computes the same cohort curves in revenue and contribution terms on a 34-line P&L. How they compare, prices dated.

Comparisons31 Aug 202610 min read

Ibrahim Ölmez

Founder, nouz

Lifetimely, now part of AMP, is the customer-economics specialist: cohort LTV curves, payback windows, purchase-behaviour analysis, with a P&L beside them and an AI profit agent on the paid tiers. The stores searching for a Lifetimely alternative are usually reaching for two things at once: yesterday's profit every morning, and cohort curves they can trust because they stand on real costs. nouz does both in one product. Its LTV tab computes cohorts by first-order month in revenue and in contribution terms, after COGS, logistics and fees, on top of a 34-line daily P&L with dated cost rules and one flat price per plan. nouz is one of the tools compared here; every competitor price was checked 31 Aug 2026 on the vendor's public pricing page.

  • Lifetimely is free under 50 orders a month; published paid tiers run $149 (up to 3.000 orders) to $999 (above 25.000), with some tiers' prices not published at all.
  • Its cohort LTV and payback analysis are the product's centre of gravity, with an Amazon add-on at $75 a month for sellers who need it.
  • nouz measures LTV in contribution terms as well as in revenue, so a cohort's payback is judged against CAC on margin, not on sales.
  • Both tools teach the same discipline; they differ on what the curves are built from and on what the bill does as orders grow.
  • An unpublished tier price is information: a price you learn on a call can be different for you.

Why stores go looking

The first reason is the pricing ladder: order-tiered, from free to $999, with two tiers' prices not published and a $75 a month Amazon add-on on top. A store growing from 3.000 to 25.000 orders climbs that ladder as a direct consequence of doing well. The second is the base the curves stand on. An LTV curve in revenue says how much a cohort bought; an LTV curve in contribution says how much it earned after the goods, the parcels and the payment fees, which is the number that decides whether the acquisition paid back. The third is the one that sorts the whole market: whether the P&L's numbers hold still, which day refunds land on, and what a supplier price change does to history.

What Lifetimely does well

The cohort work is the product. Payback windows by acquisition month, LTV curves split by product or channel, and purchase-behaviour views that answer questions like when a first-time buyer becomes a repeat one. The free tier under 50 orders is the most generous entry in the niche, the AI profit agent on the paid tiers is a distinct way of reading the data, and the Amazon add-on brings a second marketplace into the same view. Those are the facts about fit: a store under 50 orders a month, Amazon beside Shopify, or a team that wants the agent.

The alternatives, mapped quickly

For cohort LTV on a P&L that holds still: nouz, where the LTV tab sits beside the statement it is computed from, flat per plan with unlimited orders. TrueProfit is the category default with the widest connectors and real-time mobile numbers, covered in TrueProfit alternatives; Kleio at $29 and Bloom at $20 to $80 are the budget picks; BeProfit is the multi-channel consolidator. The whole market, priced at 500, 5.000 and 50.000 orders, is in the best Shopify profit tracking apps comparison.

Lifetimely vs nouz, where it actually differs

Lifetimely by AMPnouz
Centre of gravitycohort LTV, payback, behaviourthe daily 34-line P&L, with cohort LTV computed from it
Pricingfree under 50 orders; $149 to $999 by order tier; some tiers unpublishedflat per plan: Base 69 euro, Pro 99 euro and Scale 249 euro a month, net, volume-independent
LTV measureLTV curves and payback windowscumulative LTV curves in revenue AND in contribution terms, 90, 180 and 365-day horizons, right-censored and labelled so
Cohort viewsby acquisition month, split by product or channelby first-order month; LTV by first product, by first-order promotion and by country; the cohort triangle
Paybackpayback windowsa CAC payback verdict against blended CAC, on contribution
Cost changescost inputs per productdated rules; history never reprices
Refund timingP&L view within the analyticsrefund-day recognition; closed months stay closed
EU specificsgeneral purposeVAT-inclusive logic, DACH formats, store timezone, packaging EPR per parcel
Fixed-cost planningwithin reportsdaily proration and a break-even day on the overview
The structural comparison, prices checked 31 Aug 2026 on public pages.

Two rows carry the argument. The LTV measure row is the reason to compute cohorts inside a P&L at all: a cohort that looks strong in revenue can be flat in contribution once its returns and its parcel costs are counted, and nouz draws both curves so the difference is visible rather than assumed. The payback row follows from it: the LTV tab draws blended CAC as a reference line and states whether, and in which month, a cohort's contribution crosses it. The CAC payback calculator runs that arithmetic publicly with your own numbers, and the glossary's payback period entry defines the term the way the tab uses it.

What the customer analysis holds

Beyond the LTV tab, the Customers tab reads repeat purchase rate by cohort at 30, 90, 180 and 365 days, right-censored so a window reports only when every member has had that long; order cadence with a winback timing line drawn from the median gap between first and second orders; and purchase journeys from the first order's lead product through the second and third, with drop-off drawn rather than hidden. The repeat rate and the one-and-done rate sit on the LTV by first product table, with a flag on products that win the first order and lose the second. Guests are excluded from cohorts and counted separately, and refunds are not netted, which the tab states beside the figures. Below all of it is the same 34-line statement, four cost engines, ten exports, custom reports on any subset of the lines, and multi-store on Pro and Scale. Out of scope, on purpose: attribution and a pixel, channels beyond Shopify, multi-currency consolidation and forecasting.

Choose Lifetimely, choose nouz

  • Choose Lifetimely when: you are under 50 orders a month and the free tier fits, Amazon sits beside Shopify, or the AI profit agent and the breadth of behaviour segmentation are what your team reads weekly.
  • Choose nouz when: cohort LTV has to be measured in margin, the daily P&L is the job, your costs have structure that must survive time, you sell in the EU, and a flat bill matters as volume grows.
  • Run both in the trial, not for good: the overlap is large enough that paying twice buys the same curves. Compare them on one cohort and keep the tool whose numbers you can trace to a cost.

Switching, and what to test in the trial

The risk in switching an LTV tool is losing a discipline, and the test is whether the new tool keeps teaching it. So test three things in parallel trials. Whether yesterday's profit matches between the tools, and which cost explains any gap. Whether a refund of an old order moves a closed month. And whether one acquisition cohort reads the same in both: take the March cohort, read its 90-day value in each, then read it in contribution terms on nouz and see how far the two curves sit apart. That gap is the returns, the parcel costs and the fees, and it is the reason the curve belongs on a P&L.

Prices move; the dates stay

Lifetimely's own pages are the source of truth for its tiers, including the ones without public prices, which is why every figure here carries the day it was checked. The nouz side is one sentence: Base 69 euro, Pro 99 euro and Scale 249 euro a month, net, flat, with a 14-day trial and the full history backfilled from the first sync, everything listed under nouz's flat pricing. If neither of these is quite the question, the market comparison covers all seven tools at once.

Written by

Ibrahim ÖlmezFounder, nouz

Builds the P&L engine behind nouz. Writes about the costs that decide whether a Shopify store is actually profitable.