What is app store conversion rate?
Definition
App store conversion rate is the share of product page views that turn into installs, with impressions-to-page-views as the upstream step. It is not one metric across stores: App Store Connect reports impressions, product page views, and its own conversion rate, while Play Console reports store listing acquisitions against visitors. The data is aggregated by the stores with no user-level join, so treat it as a funnel of counts, never as something you can attribute to individuals.
What data do you need?
- Daily store metrics per app, store, and territory: impressions, product page views, first-time installs, re-downloads
- Source dimension where the store provides it (search, browse, referral, web)
- A stable app and store key so Apple and Google rows never blend silently
- Release and store-listing change dates to annotate the trend
- Subscription starts if the funnel continues past install
SQL pattern
WITH daily AS (
SELECT
store,
app_id,
date_trunc('week', metric_date) AS week,
SUM(impressions) AS impressions,
SUM(product_page_views) AS page_views,
SUM(first_time_installs) AS first_time_installs,
SUM(redownloads) AS redownloads
FROM app_store_daily_metrics
-- Both stores restate recent days. Cut the unstable tail or every
-- Monday review will show a fake decline.
WHERE metric_date < CURRENT_DATE - INTERVAL '3 days'
GROUP BY 1, 2, 3
), rates AS (
SELECT
store,
app_id,
week,
impressions,
page_views,
first_time_installs,
redownloads,
100.0 * page_views / NULLIF(impressions, 0) AS view_rate_pct,
-- First-time installs only. Re-downloads are returning users and
-- belong in a retention view, not in an acquisition conversion.
100.0 * first_time_installs / NULLIF(page_views, 0) AS conv_pct
FROM daily
)
SELECT
week,
store,
app_id,
impressions,
page_views,
first_time_installs,
redownloads,
ROUND(view_rate_pct, 2) AS impression_to_page_view_pct,
ROUND(conv_pct, 2) AS page_view_to_install_pct,
ROUND(conv_pct - LAG(conv_pct) OVER w, 2) AS conv_change_pp,
-- 4-week trailing mean smooths feature placements and paid bursts.
ROUND(AVG(conv_pct) OVER (
PARTITION BY store, app_id ORDER BY week
ROWS BETWEEN 3 PRECEDING AND CURRENT ROW
), 2) AS conv_pct_4w_avg
FROM rates
WINDOW w AS (PARTITION BY store, app_id ORDER BY week)
ORDER BY store, app_id, week;Common pitfalls
Where does this metric apply?
This metric commonly uses data from Apple App Store Connect, Google Play Console, AppsFlyer, Adjust, plus any warehouse models built at the same grain.