Klaviyo and Shopify: Revenue by Flow vs Campaign

Flows run on their own and campaigns take your time. Splitting attributed revenue between them, then checking it against Shopify, tells you where the next hour of email work should go.

To compare flow and campaign revenue, put both on a monthly basis, split Klaviyo-attributed revenue between them, then check the total against Shopify so you know how much of the business email actually touches. Rank both by revenue per recipient to decide where effort goes. This post gives the method, the checks, and what Quiriz's Klaviyo and Shopify connectors, both in beta, can and cannot do for it.

Why split flows from campaigns

Flows and campaigns are different kinds of work. A campaign is a single send that costs your time each time. A flow is built once and then earns until it decays. If you lump them together, a strong sale-day campaign hides a broken welcome series, and the welcome series keeps leaking revenue every month for a year.

The comparison answers a resource question: of the revenue email is credited with, how much comes from work already done, and how much depends on you hitting send. A store where flows are a small share of attributed revenue has an obvious backlog. A store where flows are most of it, and are shrinking, has a maintenance problem.

The method

Step 1: common grain. Flow revenue is reported by month. Campaign revenue is attributed to the send date. Sum campaigns to months using the send date so both sit on the same axis. Campaign events are counted only inside the reporting window, so a campaign sent just before the window shows a partial total. Leave the earliest month out of any trend you draw.

Step 2: shares. For each month: flow revenue, campaign revenue, and the sum. Illustrative example only: flows 60, campaigns 40. Then compute the shares and see whether the mix is stable.

Step 3: tie to the store. Divide the email and SMS total by store revenue. Which store figure you use matters. Klaviyo's own view of all order revenue (attributed or not) gives the attributed share inside Klaviyo's world. Shopify net sales gives the share of the business, but its definition deducts returns and excludes shipping and tax, so the ratio will not equal the first. Choose one, label it, and keep using it. See net sales vs gross sales in Shopify for the definitions.

Step 4: efficiency. Rank flows and campaigns by revenue per recipient, since totals favor volume. A flow reaching 8,000 people a month with low revenue per recipient is a bigger opportunity than a small flow with a high one, because the same improvement applies to more people.

Three checks before you act on it

• The unattributed bucket. Revenue Klaviyo sees but does not attribute is a legitimate share of the store. If it is shrinking while attributed share grows, attribution rules or sending volume may have changed rather than performance.
• Overlap. A customer can receive a campaign and a flow message in the same week. Attribution gives the order to one, so flow and campaign revenue are not independent.
• Rates and sums. Add counts across campaigns, then divide. Averaging campaign click rates weights a 500-person send like a 50,000-person one.

Doing it with Quiriz

The Klaviyo connector (read-only, daily refresh, in beta) supplies [Klaviyo] Flows by month, [Klaviyo] Campaigns and [Klaviyo] Attributed revenue by day. Defined metrics include Klaviyo flow revenue, Klaviyo campaign revenue, Klaviyo revenue per recipient, Klaviyo attributed share and Klaviyo store revenue. The Shopify connector supplies [Shopify] Sales with net sales on Shopify's definition. Questions to ask:

• "Flow revenue and campaign revenue by month for the last 12 months."
• "Which flows earn the most, and are they growing?"
• "Which campaigns have the highest revenue per recipient in the last 90 days?"
• "Klaviyo revenue as a share of Shopify net sales by month."

The last question crosses two datasets from different connectors. It works because both are datasets in the same workspace. The ratio mixes definitions, since Klaviyo's revenue and Shopify's net sales are not the same measure, so Company Context is where you write down which pairing you use, and the answer then stays comparable from month to month.

Turning the result into a plan

An illustrative reading. If flows are a minority of attributed revenue and the welcome flow is the largest by recipients but low per recipient, rewrite it before the next big campaign. If flows are the majority but their monthly revenue has slipped for three months in a row, audit triggers and list quality. If campaigns dominate and campaign revenue per recipient is falling as you send more often, you are buying volume with audience goodwill. Check unsubscribes in the audience dataset before sending more.

For the Shopify side of ad spend, joining Shopify and ad exports covers the same joining problem for paid media.

A worked reading

Illustrative numbers. Say a store has 40 percent of attributed revenue from flows and 60 percent from campaigns, and attributed revenue is 22 percent of Shopify net sales. Over three months, the flow share drops to 31 percent while campaign share rises to 69 percent, with the 22 percent unchanged. Total email influence did not change, but its source shifted toward work that needs your time every week. That is a prompt to look at which flows slipped. A common cause is a product or discount change that left a flow pointing at something out of stock or expired.

Honest limits

• Flow data is by flow, channel and month. Step-level results inside a flow are not read.
• The reporting span is about 12 months because that is what Klaviyo allows.
• Revenue figures need a store connected to Klaviyo. Without one, they read zero and the connector says so.
• Attribution is Klaviyo's, and revenue credited to email is an upper bound on what email caused.
• The two connectors do not share a customer key in this comparison. It works at the level of dates and totals, not individual customers.

See Klaviyo AI: Ask Your Email Data Questions for first questions, and Quiriz for ecommerce for store workflows.

Frequently asked questions