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Blog›Marketing

Know which content drives pipeline, not just page views

Page views and video plays tell you very little about whether content is earning its production cost. AnalityQa AI AI joins your GA4, CRM, and video platform exports to show which posts and videos actually move prospects through the funnel.

Try AnalityQa AI AI free →See live examples
Marketing analytics dashboard

The problem

  • →Page views are easy to measure but disconnected from revenue. Content teams report impressions and sessions while finance asks for pipeline contribution — a number nobody can produce without a multi-system data join.
  • →Video watch-time decay curves are only visible inside platform-native analytics. There is no way to compare drop-off rates across YouTube, Wistia, and Vimeo in a single view without manually exporting and joining each.
  • →Scroll depth and time-on-page data sits in GA4 but is rarely linked to whether a session converted, making it impossible to know whether deep readers are better prospects than skimmers.
  • →Topic clusters that perform well on organic traffic do not always convert well. Without joining traffic data to CRM conversions, content investment decisions are based on visibility metrics, not pipeline metrics.

Why the usual approach breaks down

GA4 does not expose scroll depth and conversion in the same row

GA4 records scroll events and conversion events separately in its event stream. Getting scroll depth alongside session conversion status requires either a custom BigQuery export or a complex Explorations report — neither of which is accessible to most content teams without analyst support.

CRM lead-source fields are inconsistently populated

Salesforce and HubSpot deals have a lead source field, but it is often filled in by sales reps with inconsistent values ('Blog', 'blog post', 'website — blog') that make aggregation unreliable. Joining CRM data to specific content pieces requires normalising those values before any analysis is meaningful.

Video platforms use incompatible engagement metrics

YouTube reports average view duration and audience retention percentage. Wistia reports play rate and heatmap engagement. Vimeo reports total plays and average watch time. None of these are directly comparable without a normalisation step, and none export in the same file format.

Content ROI requires joining three or more systems

A complete content ROI calculation needs production cost (from a project management tool or spreadsheet), traffic (from GA4), and pipeline contribution (from CRM). Three-way joins of this kind exceed what most marketers can do in a spreadsheet and require a data engineer to set up in a BI tool.

How AnalityQa AI AI solves it

Upload your data — or connect it live — and ask in plain English.

01

Upload GA4, CRM, and video exports together

Drop in your GA4 landing-page report, your CRM contact or deal export, and any video platform exports. AnalityQa AI AI detects each schema and proposes joins on landing page URL, UTM parameters, or contact email — whichever shared key is available.

02

Ask funnel contribution questions in natural language

Ask 'Which blog posts generated the most leads last quarter?' or 'Which topic clusters had the highest conversion rate from first touch?' AnalityQa AI AI joins your traffic and CRM data, runs the analysis, and returns a ranked table — no SQL required.

03

Analyse video watch-time decay across platforms

Upload retention data from YouTube and Wistia. AnalityQa AI AI normalises percentage-watched to a consistent scale and plots decay curves per video or per content type, showing where audiences drop off and how that varies between platforms.

04

Segment engaged readers from skimmers using scroll depth

Upload a GA4 event export that includes scroll depth events. Ask AnalityQa AI AI to group sessions by scroll depth bucket (0–25%, 25–50%, 50–75%, 75–100%) and compare conversion rates across groups. The result shows whether deep readers convert at a meaningfully different rate.

05

Measure content ROI by adding production cost data

Upload a spreadsheet with content production cost per piece. AnalityQa AI AI joins it to your traffic and CRM conversion data, calculates cost per lead per article, and ranks content by ROI — giving you a defensible number for content investment decisions.

You askedGenerated in 4.2s

"Which blog posts drove the most assisted conversions last quarter?"

MQLs

2,418+18.2%

CAC

€142−9.4%

ROAS

4.2×+0.6×

Table: top 20 blog posts by assisted conversions — Q1 2026, with deal value

Last 12 mo

Line chart: audience retention by video — product demos, percentage of video watched

Bar chart: conversion rate by scroll depth bucket — blog posts, last 90 days

Segment ASegment BSegment CSegment DSegment ESegment F

A dashboard built in AnalityQa AI — from question to chart, no SQL.

Real examples

Paste your data. Ask. Ship.

You

Which blog posts drove the most assisted conversions last quarter?

AI

AnalityQa AI AI joins your GA4 landing-page export to your CRM deal export via UTM landing page, counts assisted conversions per page, and returns the top 20 posts ranked by conversion count and deal value.

Table: top 20 blog posts by assisted conversions — Q1 2026, with deal value
You

Show me video watch-time decay curves for our product demo videos.

AI

AnalityQa AI AI normalises watch-time retention data from your video platform export, groups by video title filtered to your demo tag, and plots average percentage retained at each 10% interval.

Line chart: audience retention by video — product demos, percentage of video watched
You

Do visitors who scroll past 75% of a blog post convert at a higher rate?

AI

AnalityQa AI AI groups your GA4 session export by scroll depth bucket, calculates the conversion rate for each group across the specified period, and returns a comparison showing conversion rate at each scroll depth threshold.

Bar chart: conversion rate by scroll depth bucket — blog posts, last 90 days
You

Which topic clusters have the highest conversion rate from organic traffic?

AI

AnalityQa AI AI applies your cluster mapping to the GA4 landing-page export filtered to organic medium, joins to CRM conversions, and calculates conversion rate per cluster.

Bar chart: organic conversion rate by content cluster — Q1 2026
You

Rank our top 10 blog posts by cost per lead using production cost data.

AI

AnalityQa AI AI joins your production cost spreadsheet to your GA4 and CRM exports on article URL, calculates cost per lead for each post, and ranks the top 10 by that metric.

Table: blog posts ranked by cost per lead — last 6 months, with traffic and conversion columns

What teams get out of it

✓Content teams that shift budget allocation within one reporting cycle after gaining a cost-per-lead number per article rather than relying on traffic alone.
✓Video production decisions informed by watch-time decay data, with drop-off points identified early enough to adjust scripts before the next production.
✓A shared content ROI metric that gives content teams a revenue number to present to finance, replacing traffic reports that finance cannot act on.
✓Topic clusters deprioritised or accelerated based on pipeline contribution data rather than SEO ranking alone.

Frequently asked questions

Which data sources does AnalityQa AI AI support for content performance analysis?+

AnalityQa AI AI works with CSV or Excel exports from GA4, Google Search Console, YouTube, Wistia, Vimeo, HubSpot, Salesforce, and any other tool that produces a file export. For teams with GA4 data in BigQuery or content metadata in PostgreSQL, a live connection is available. Direct API integrations for other platforms are on the roadmap.

Does AnalityQa AI AI connect to GA4 directly or do I need to export data?+

Today the recommended path is to export from GA4's Explorations or the GA4 BigQuery export and upload the file. For teams that have GA4 data synced to a PostgreSQL database, a live connection is available. Native GA4 API integration is on the roadmap.

Scroll depth events in GA4 only fire at the 90% threshold by default. Can I still do meaningful analysis?+

GA4's enhanced measurement fires a scroll event at 90% scroll depth by default. If you have configured custom scroll depth events at 25%, 50%, and 75% thresholds via Google Tag Manager, AnalityQa AI AI will use those. With only the default 90% event, the analysis becomes a binary split — scrolled vs. did not scroll — which is still actionable for conversion rate comparisons.

Our CRM lead source data is inconsistent. Can AnalityQa AI AI clean it before joining?+

Yes. Tell AnalityQa AI AI how you want to normalise the values — for example, 'treat Blog, blog post, and website-blog as the same value' — and it applies the mapping before running any join. You can also ask it to show you all unique lead source values first so you can decide which ones to group.

How should CRM data containing contact details be handled?+

Your uploaded files are stored in your isolated tenant. Contact-level CRM data should be exported with personal identifiers removed or pseudonymised before upload. Aggregate analysis on anonymised exports is the recommended approach.

Can AnalityQa AI AI forecast future traffic or conversions based on content trends?+

Yes. Once your historical traffic and conversion data is loaded, you can ask for a forecast — for example, 'Forecast organic sessions for the SEO cluster over the next 8 weeks.' AnalityQa AI AI fits a trend model to your historical data and returns a projection with a confidence range.

What does it cost? Is there a limit on how many articles or exports I can analyse?+

Pricing is based on the number of users and data volume, not the number of files or queries. You can upload as many article exports, video reports, and CRM files as your plan's storage allows. A free trial is available with no credit card required — details are on the pricing page.

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