Medium vs Substack Analytics: Which Platform Tells Writers More?
Medium and Substack analytics answer different questions. Medium gives writers stronger evidence about recommendation exposure and on-platform reading...
By Ian Kiprono
Medium and Substack analytics answer different questions. Medium gives writers stronger evidence about recommendation exposure and on-platform reading: presentations, views, 30-second reads, feed clickthrough, audience activity and Partner Program earnings. Substack goes deeper after someone enters the publication's audience: email and app opens, subscriber sources, free-to-paid movement, individual subscriber activity, revenue, churn and cohort retention.
My view is that Medium tells you more about how a story travels, while Substack tells you more about what a reader relationship becomes. Neither dashboard is universally better. Choose the platform by the decision you need to make, and never compare metrics merely because they share a familiar label. Narrareach can keep the resulting content decision and cross-platform publishing work together, while each platform remains the authority for its native statistics.
The comparison at a glance
| Writer's question | Medium is stronger | Substack is stronger |
|---|---|---|
| Was my story shown inside the platform? | Presentations and distribution context | Network and Notes signals exist, but there is no equivalent presentation funnel |
| Did an arrival become a meaningful read? | Views, 30-second reads, read ratio and member read ratio | Opens, views and engagement across email, web and app use different definitions |
| Which source produced a subscriber? | Follower/subscriber impact and traffic sources provide context | Post, Note, sharing, traffic and subscription-source reports go deeper |
| Are subscribers staying? | Audience growth and engagement | Free and paid cohort retention, churn and renewal context |
| What did the content earn? | Eligible Partner Program earnings by story | Subscription revenue, upgrades, paid growth and annualized revenue |
| Who should receive the next message? | Followers and email subscribers are visible at audience level | Subscriber-level fields, filters and dynamic segments support direct action |
The right dashboard is the one that contains the denominator and outcome for the decision. A bigger collection of charts does not compensate for asking the wrong question.
Medium analytics is built around exposure and reading behavior
Medium's current Stats guide organizes performance around stories, audience and Partner Program earnings. Its central story sequence is:
- Presentations: how often Medium suggested a story on tracked platform surfaces.
- Views: how many people accessed it and stayed for at least five seconds.
- Reads: how many stayed for at least 30 seconds.
- Audience impact: followers and email subscribers attributed after reading.
- Earnings: eligible paywalled-story results for Partner Program writers.
That structure is useful when the problem is discovery. If presentations are low, the story had limited tracked exposure. If presentations are available but feed clickthrough is weak, examine the title, subtitle, image and audience match. If views arrive but reads lag, inspect the promise-to-opening transition.
Medium also reports traffic sources, member read ratio, engagement and audience interests on the detailed story page. These signals help separate an internal recommendation story from one carried by search or social traffic. They do not reveal the platform's private recommendation formula, and presentations are unavailable for stories published before 2025.
Use Medium analytics when you need to answer, “Where did this story lose momentum inside Medium?” For the complete funnel, see Medium Analytics Explained.
Substack analytics follows the subscriber relationship
Substack's current metrics guide covers posts, the network, audience, retention, sharing, Notes, email, traffic, unsubscribes and earnings. Its Growth view connects visitors, subscriptions and revenue to sources and publishing dates. Top-source reports show where visitors came from and how many subscribed.
The subscriber dashboard goes further into the audience record. Writers can inspect free and paid status, subscriber activity, opens over defined windows, subscription source, paid upgrade date and revenue, then filter or segment readers for follow-up.
Paid publications also get retention analysis. Substack reports paid cohorts after 30 days, six months and 12 months, as well as paid growth, cancellations, expiration and free-subscriber retention. Those measures answer a business question that a story-level discovery funnel cannot: did the acquired audience stay?
Use Substack analytics when you need to answer, “Which channel produced the subscriber, what did that reader do later, and is the cohort durable?” Substack Analytics Explained covers the native reporting model in more detail. The deeper Narrareach Substack analytics workflow can help turn those signals into the next article, Note and distribution decision.
Current Narrareach data shows two different measurement shapes
On September 20, 2026, Narrareach had native analytics caches refreshed within the previous 48 hours for 85 connected Substack publication records and 13 connected Medium accounts. Every Substack snapshot contained subscriber total, email open-rate and paid-subscriber fields. The Medium snapshots contained 332 distinct stories, and all 332 carried the presentation, view and read fields that form Medium's story funnel.
These counts describe current product coverage, not platform size, adoption or quality. The connected accounts are self-selected, some fields can legitimately be zero, and the numbers should not be compared as 85 publications versus 13 accounts. The useful finding is structural: the Substack records center subscriber and newsletter measures, while the Medium records repeat story-level exposure and reading measures.
That is why a single “cross-platform engagement score” would discard useful information. I would preserve two native scorecards and connect them only at a small set of shared editorial decisions.
Similar metric names do not make the numbers comparable
The most common analytics mistake is placing two columns side by side because both are called views, subscribers or earnings.
A Medium read is not a Substack open
Medium counts a read after at least 30 seconds. Substack's open rate measures the percentage of recipients who viewed a post after receiving it through email or the app. Substack explains that image loading, previews, blocked images, text-only email and app behavior can affect capture.
A Medium read therefore reflects a time threshold after landing. A Substack open reflects recipient-level access across delivery surfaces. Comparing the percentages as though both measure article completion creates a false winner.
A Medium subscriber is not the whole Substack subscriber record
Medium distinguishes followers from people who opt into email notifications. Substack centers the publication around free, paid, founding, gift, comp and trial subscriptions. Its subscriber dashboard can add source, activity, payment and upgrade information.
The word “subscriber” exists on both platforms, but the available lifecycle context differs. Count each platform's audience using its own definition, then compare the editorial outcome you care about: repeat reading, email permission, paid conversion or retention.
Earnings represent different businesses
Medium Partner Program earnings depend on eligible paying-member activity, reading time, engagement, source bonuses, Boost status, conversions and member read ratio. Substack revenue comes from subscriptions to the writer's publication, with recurring-plan, cohort, churn and annualized-revenue context.
Do not compare dollars per Medium read with Substack annualized revenue. One is a platform-program result attached to eligible story activity. The other estimates a direct subscription business at its current monthly and annual plan mix.
A worked example: one essay, two dashboards
Imagine the same core essay is adapted for both platforms during a 28-day review window.
| Platform | Native evidence | What it can support | What it cannot support |
|---|---|---|---|
| Medium | 10,000 presentations, 400 views, 180 reads | Diagnose exposure, opening response and the view-to-read transition | Claim that 180 readers joined or remained in an owned audience |
| Substack | 1,000 recipients, 640 opens, 24 new subscriptions, 6 unsubscribes | Diagnose delivery response, subscriber acquisition and net list movement | Claim that 640 people spent 30 seconds reading |
The Medium story has a 45% total read ratio: 180 divided by 400. The Substack post has a 64% open rate: 640 divided by 1,000 recipients. Saying “Substack engagement was 19 percentage points better” would be wrong because the denominators and events differ.
A useful comparison asks whether each platform did its assigned job. Medium might be responsible for discovery among new readers. Substack might be responsible for retaining and converting an opted-in audience. The figures become comparable only after you name a shared outcome, such as qualified email subscriptions attributed within the same window.
Build a cross-platform scorecard without flattening the metrics
Keep three layers.
Layer 1: platform-native funnel
For Medium, record presentations, feed clickthrough, views, reads, member activity, followers/subscribers and eligible earnings. For Substack, record recipients, delivery/open response, views, subscriber source, free and paid subscriptions, upgrades, unsubscribes and retention.
These measures diagnose the platform on its own terms. Do not transform them into one index.
Layer 2: shared editorial outcomes
Use outcomes that can be defined consistently:
- Did the article reach the intended type of reader?
- Did it create a follow, email subscription or paid relationship?
- Did readers continue to another useful piece?
- Did the topic justify a follow-up after a fixed 28-day window?
- How much production time did the adaptation require?
Some outcomes will remain partly qualitative. That is preferable to a precise-looking score built from unlike inputs.
Layer 3: the next decision
Translate the evidence into one action. A Medium story with strong reads and limited presentations may need a more relevant publication or topic match. A Substack post with strong opens but weak subscription growth may need a better public landing path or clearer reason to subscribe. A topic that works on both platforms may deserve a deeper guide, webinar or paid edition.
Which platform tells you more for your goal?
Choose Medium analytics if your main question is about recommendation exposure, story-level reading behavior, internal versus external discovery or Partner Program performance.
Choose Substack analytics if your main question is about subscriber acquisition, email/app engagement, source attribution, paid conversion, churn, retention or audience segmentation.
Use both if Medium is a discovery channel and Substack is the owned reader relationship. In that model, do not expect Medium's dashboard to explain Substack retention or Substack's dashboard to reconstruct Medium presentations. Assign each platform a job and measure the handoff explicitly.
This division also prevents the “which platform is better?” question from swallowing the real decision. A writer seeking a direct paid newsletter business needs different evidence from a writer testing article topics inside a recommendation network.
Turn two dashboards into one publishing workflow
Review each platform natively, then write a one-sentence diagnosis for each. For example: “Medium shows enough reading once the story opens, but limited presentation volume.” “Substack shows strong opens among existing subscribers, but few new subscriptions from the public page.”
Choose the shared topic only after those diagnoses. Draft the core argument, adapt the opening and call to action for each audience, review formatting and links, and preserve the canonical source when republishing. Narrareach's Medium integration can carry the adapted article into the Medium queue, while its Substack workflow keeps the article, Notes and audience follow-up connected.
Narrareach can reduce the operational distance between measurement and publication. It cannot make unlike metrics equivalent, replace native retention or earnings reports, or prove that one cross-post caused subscriber growth.
Open both dashboards and write the single decision each is qualified to answer. Keep the original denominators beside every percentage. If a number cannot survive that sentence—because its event, audience or window is different—leave it out of the comparison. The goal is not to crown the dashboard with more charts. It is to make the next article easier to choose.