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Attribution for founders

You asked one question. Four dashboards gave four answers.

You do not want to learn a query language to find out whether last month worked. You want the number, and the evidence behind it, in the time you actually have between everything else.

Meta reports Your orders
W1W2W3W4W5W6

Every tool has its own version of the month. One total, no footnote.

Credit is divided once across the whole path, so the figure you put in front of a board is not one you have to caveat with which tool produced it and why the others disagree.

  • 09:41:22purchasevalue: 128.00
  • 09:41:19checkout_starteditems: 3
  • 09:38:04add_to_cartsku: MC-04
  • 09:37:51product_viewedsku: MC-04
  • 09:36:12pageviewpath: /products

The answer is a ticket for someone else. Ask it in plain English.

Soran AI reads the same data the reports do, so a question about repeat purchases returns the chart rather than a place in a queue.

Cost of goods
42%
Shipping
11%
Fees
9%
Profit
38%

Growth that was costing you money. Every report can answer in margin.

Once your costs are in, the campaigns that were buying revenue at a loss stop reading as the ones that are working.

unmeasuredmeasured

Attribution was a quarterly project. Connect a store, read a report.

There is no warehouse to stand up and no model to commission first. The history starts the day the connection is made, which is the argument for making it early.

None of this works on data Soran cannot see. It reads the platforms you already run.

See all integrations

You should not need an analyst to find out whether the month worked.

Stop guessing which ads worked. Start seeing it.

  • No credit card to start
  • Every report and all ten models from day one
  • Your data exports whenever you want it
  1. 01

    Connect your store

    Shopify authorizes in a click and checkout tracking installs itself.

  2. 02

    Pick a goal

    The conversion you actually get paid for. Soran credits every touch that led to it.

  3. 03

    Read your first report

    Spend against the revenue it earned, on all ten attribution models.