Metrics

Aggregated metrics, breakdowns and timeseries across any dimension, with the attribution model you choose.

Endpoint	Method	Path	Permission
Get metrics Aggregate metrics, breakdowns and timeseries	GET	`/v1/metrics`	`metrics:read`

Base URL https://app.sourceloop.ai/api/v1

Get metrics

Aggregate metrics, breakdowns and timeseries

GET /v1/metrics

Requires metrics:read

Omit `group_by` for a single total. Add it for one row per dimension value, which also returns the window totals so the share each row represents is visible. Add `granularity` for a timeseries.

Note that a total and a timeseries are different queries: unique visitors cannot be summed across days without counting returning people twice, so the aggregate is computed once across the whole window.

curl -s -X GET "https://app.sourceloop.ai/api/v1/metrics?website=acme.com&period=last%2030%20days" \
  -H "Authorization: Bearer $SOURCELOOP_API_KEY"

const res = await fetch(
  "https://app.sourceloop.ai/api/v1/metrics?website=acme.com&period=last%2030%20days",
  {
    method: "GET",
    headers: {
      Authorization: `Bearer ${process.env.SOURCELOOP_API_KEY}`,
    },
  },
);

const data = await res.json();

import os, requests

res = requests.get(
    "https://app.sourceloop.ai/api/v1/metrics?website=acme.com&period=last%2030%20days",
    headers={"Authorization": f"Bearer {os.environ['SOURCELOOP_API_KEY']}"},
)
data = res.json()

Query parameters

websitestring

Website domain, e.g. acme.com. Required only when the key covers more than one.

periodstring

Plain-language period: "last 30 days", "yesterday", "July 2026", or "2026-07-01..2026-07-31". Ignored when from/to are given.

Example last 30 days

fromstring (date-time)

tostring (date-time)

metricsstringrequired

Comma-separated.

Allowed values25

visitors
sessions
pageviews
events
conversions
influenced_conversions
unique_converters
revenue
lifetime_value
customers
avg_ltv
repeat_rate
avg_orders
cohort_mrr
revenue_per_customer
milestones
conversion_rate
pageviews_per_session
revenue_per_visitor
spend
impressions
clicks
roas
cac
ltv_cac

Example visitors,conversions,conversion_rate

group_bystring

Split by one dimension, or up to four comma-separated for a nested breakdown such as channel,source. Omit for a single total.

Allowed values23

channel
source
medium
campaign
utm_term
utm_content
referrer_domain
page
landing_page
hostname
page_title
country
region
city
device_type
browser
operating_system
resolution
platform
ad_campaign
ad_set
ad
cohort

Three of those are answered by a different store and behave differently:

platform and ad_campaign join ad SPEND to the campaign that acquired each customer, which is what makes cac and ltv_cac available. They take one dimension at a time and cannot be crossed with traffic dimensions.
resolution splits outcomes by WHY they had no journey (unmatched, predates tracking, imported contact) and is only available alongside credited metrics.
cohort returns a retention curve instead of a ranking: rows are (cohort, period_index) and the window chooses which cohorts appear, never which payments count.

filterstring[]

Repeatable, ANDed. Form: dimension:operator:value.

Operators6

eq
ne
in
nin
contains
not_contains

Filterable dimensions30

channel
source
medium
campaign
utm_term
utm_content
referrer_domain
page
landing_page
hostname
page_title
country
region
city
device_type
browser
operating_system
resolution
event_name
event_type
identified
platform
ad_campaign
ad_set
ad
campaign_type
match_type
company_domain
crm_stage
crm_account_stage

Example channel:in:paid_search,paid_social

granularitystring

Return a daily time series instead of a single total. Only day is supported: the underlying store buckets by calendar day in the website timezone, so hour, week and month are rejected rather than silently returning days under another label.

Allowed values 1

day

attributionstring

Credit conversions to a touchpoint using an attribution model instead of counting the event where the conversion fired. One of first_touch, last_touch, linear, u_shaped, time_decay, or up to five comma-separated to compare them in one response, which guarantees every model saw the same window and filters. Requires group_by, and only conversions and revenue can be attributed: a visitor has one channel at a time. When several models are given, each row nests one object per model; a null metric means that model truncated before reaching this value (see meta.truncated_models), which is not the same as zero.

Example first_touch,last_touch

stagesstring

Count CRM and lifecycle milestones instead of tracked conversions: deal_created, deal_won, mql, trial_started, trial_converted, subscription_started, subscription_churned and the rest of the workspace stage vocabulary. A milestone is a different KIND of outcome from a conversion rather than a category of one, so the two are never blended. A milestone has no channel of its own, so this implies an attribution model and defaults to last_touch; the model used is echoed in meta.definitions. Deals are credited across the whole buying committee.

Example deal_won

conjunctionstring

How repeated filters combine. Default and.

Allowed values 2

and
or

only_paidboolean

Restrict to paid traffic: a paid medium, or the presence of an ad click id.

limitinteger

Default 50

Responses

200 Rows plus meta
400 Something was wrong with the request or the credential.
429 Too many requests for this workspace in the current minute. Wait Retry-After seconds and repeat the request unchanged.

const res = await fetch( "https://app.sourceloop.ai/api/v1/metrics?website=acme.com&period=last%2030%20days", { method: "GET", headers: { Authorization: `Bearer ${process.env.SOURCELOOP_API_KEY}`, }, }, ); const data = await res.json();

import os, requests res = requests.get( "https://app.sourceloop.ai/api/v1/metrics?website=acme.com&period=last%2030%20days", headers={"Authorization": f"Bearer {os.environ['SOURCELOOP_API_KEY']}"}, ) data = res.json()

# Get metrics

Query parameters

Responses

Track every conversion to its true source

Get metrics