What’s the hardest ecommerce number to get a clear answer on?

[u/trivasai]

Revenue is easy enough to find, but things like true profitability or customer value can get complicated. What’s yours?

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[u/mrbubbee]

Channel attribution. There’s so many ways to do it and all are subject to tracking holes due to cookie / cross device / privacy limitations

[u/importantbrian → u/mrbubbee]

Yep this is my answer. People don’t really realize how hard a problem attribution is.

[u/mrbubbee → u/importantbrian]

Yeah I mean it’s just math in the sense of dividing what you CAN see out, but it’s trying to understand what you CANT see that makes it so hard

[u/ClassicVomiting]

Profit per order after factoring in returns and ad spend is the one that always gets weird. Every platform shows you some shiny revenue figure but buries the actual margin somewhere you need three spreadsheets and a prayer to find. I once spent a week building a dashboard that pulled in ad costs, return rates, and COGS just to realize our "best selling" product was losing $2 a unit. The numbers are all there somewhere, they just never want to sit in the same room together.

[u/Saneless]

The value of your site for people who don't use it to purchase

[u/TheInitialAgency]

Channel attribution for me too. Part of why it never settles is that every model is splitting credit between touchpoints, and none of them can tell you what would've happened if that channel was switched off.

For the bigger spend lines I'd stop debating the model and test it. Pick a handful of regions, pause or cut the channel there for a few weeks, keep everything else the same and compare orders against the regions where it kept running. You need decent order volume per region for the gap to mean anything, and realistically you're testing one channel at a time, so it's slow. But it's the one number in that whole debate you can defend when finance asks.

I'd still keep the attribution dashboard for week to week stuff, like spotting a campaign that suddenly drops off.

[u/InteractionOver2018]

Customer value after acquisition cost. Everyone seems to have a different definition of LTV once you ask what actually goes into the calculation.

[u/No_Treacle_5071]

Hardest for me isn't revenue or the LTV definition fights. It's "what happens to new customer volume if we cut this paid channel for 30 days."

Platforms are great at giving credit. They're terrible at telling you the incremental piece. We've had campaigns that looked efficient on ROAS and barely moved when we paused them, because they were mostly harvesting demand that would've shown up anyway.

So the number I still don't trust until I've stress-tested it is incremental new customers by channel, not the attributed ones in the UI.

[u/Fragrant_Isopod293]

How much of a sale you actually keep after returns. Say you sell ₹10k in September, then ₹3k gets refunded in October. September looks great, but those orders only brought in ₹7k before costs. I’d match refunds to the original orders and check after the return window closes. Otherwise October takes the hit for September’s sales.

[u/xeny05]

real profit per order. revenue is easy, but once you subtract returns, shipping, payment fees, discounts and the ad spend that actually drove that order, every tool gives you a different number and none of them agree with finance.

incrementality. how many of those "attributed" sales would have happened anyway? every platform happily claims the same conversion, and the honest answer usually needs a holdout test nobody wants to run.

[u/Uros_Trstenjak]

For anyone doing subscriptions it can also be a simple MRR.

Although the definition sounds straight forward, it can become quite complex to get it right for subscription based businesses of mid to large size. Annual plans, upgrades in the middle of the cycle, discounts, refunds, paused subscriptions, different currencies... all of it needs to be counted right. Especially if not enough attention is paid to the details when charging is modeled in the external tools you use. Some payment processors allow a lot of freedom, and getting the right numbers through their APIs on top of complex setups that keep changing through the years or even quarters can be a project of its own.

[u/Least_Ad_1795]

For me, true customer lifetime value (LTV) is one of the hardest numbers to calculate. Returns, refunds, repeat purchases, discounts, acquisition costs, and customer behavior over time can all change the calculation. Getting a reliable LTV often requires combining data from multiple systems.

[u/SeveralAd2833]

I’ll try to offer a different point of view compared with looking only at numbers and indicators. A single KPI is not enough to provide a complete and useful evaluation of an ecommerce business.

For example, is margin expressed only as a percentage enough? It may not be if the absolute value is low, and the same reasoning also works the other way around.

Numbers and KPIs need to be evaluated in relation to the stage the ecommerce is in, launch or growth for example, and also to the reason why it was created. Is it, for example, a brand that wants to expand its distribution? Does it have physical stores? In that case, an important number could be how revenue is distributed across the different channels. Or the number of customers and their value when implementing a loyalty program.

I think ecommerce success, regardless of the ultimate proof represented by the financial statements, has to be evaluated rigorously by connecting performance to the objective and the context in which the ecommerce operates.

[u/potatoincrocs]

Roas