Analytics that answer author questions, not marketer questions

Most analytics dashboards are built for marketers with quarterly reports to file. Impressions, reach, engagement rate to two decimal places. Numbers that make a slide deck look thorough and tell an author absolutely nothing about what to do on Thursday.

So when we built the Analytics tab, we organized it around the questions authors actually ask me. There are five tabs, Overview, Posts, Timing, Audience, and Accounts, but I'd rather walk you through the questions.

"What's working?"

The Overview tab gives you the tiles and the daily trend line, with a platform breakdown so you can see at a glance whether Instagram or Threads is pulling the weight this month. The Posts tab turns that into a grid of your actual posts with their numbers attached, so "what's working" stops being a vibe and becomes a list you can sort.

The chart I want you to pay attention to, though, is content decay. It shows how long your posts keep earning attention after they go out. A TikTok might spike and die in two days; a Pinterest pin from last year might still be quietly working. Once you see your own decay curves, two decisions get easier: what's worth making more of, and which platform deserves your long-tail slot.

Everything exports to CSV if you're the spreadsheet type. No gatekeeping your own data.

"When should I post?"

The Timing tab has a best-time heatmap built from your audience's actual behavior, days of the week down one side, hours across the top, darker cells where your readers actually engage. Not a generic "post at 9 AM" listicle. Your readers, your data.

Next to it, the posting frequency chart holds up a mirror: how often you actually posted, week by week. I've had authors swear they post three times a week, look at this chart, and discover the real number was three times a month with occasional bursts of guilt-posting. No judgment. The chart isn't there to shame you, it's there because consistency questions are impossible to answer from memory.

"Who's reading?"

The Audience tab is where follower stats live: growth over time, per platform, so you can see whether that viral week actually turned into readers who stayed. Platforms that report demographics feed panels here too. Instagram gives age, gender, and location breakdowns; YouTube reports its own audience demographics. So when you're deciding whether your readers skew toward the platforms you're actually posting on, you have real numbers instead of a hunch.

Fair warning: not every platform reports the same depth. We show you what each platform actually provides rather than padding the gaps with estimates. If a panel is thin, that's the platform being thin, and I'd rather show you a thin truth than a thick guess.

"What happened to that post?"

This is the unglamorous corner of analytics that I might value most. Every post has a timeline: created, scheduled, published, and everything in between, with timestamps. And when something goes wrong, every post has publish logs, the actual record of what the platform said when we tried to deliver it.

Because sometimes a post doesn't fail loudly. Sometimes Instagram just quietly declines, or a video gets stuck processing, and on most tools that post just... doesn't exist anymore, and you find out when a reader asks why you went dark. Here, you open the post, read the log, and see exactly what happened and when. Pair that with the failure alert emails and "silent failure" stops being a thing that can happen to you.

The Accounts tab rounds this out with connection health for every account, so a token that's about to expire gets caught before it takes a week of posts down with it.

The honest note about pricing

All of this is included in the base plan. Follower stats, decay, timing, demographics, timelines, logs, exports, all of it. Not a "Pro analytics" upsell, not a fourteen-day teaser.

I want to be straightforward about why, because it's not charity. Analytics is how you find out what's working, and customers who know what's working stay subscribed and tell their friends. Paywalling the feedback loop would be good for one quarter's revenue and bad for everything else. The only paid add-on in the product is ads, because ad-platform access carries real per-user costs. Understanding your own posts will never be extra.

How to actually use this (fifteen minutes a month)

Don't check analytics daily. Truly. Daily numbers are noise, and authors have better uses for their attention. Instead, once a month:

1. Posts tab, sort by the last 30 days. Note the top three posts. Ask what they have in common.
2. Timing heatmap. Are your queue slots sitting in the dark cells? If not, move them.
3. Follower stats. Trending up, flat, or down per platform. Flat on a platform you love is fine. Down on a platform you're pouring effort into is a conversation with yourself.
4. Accounts tab. Ten seconds. Everything green? Close the tab and go write.

That's the whole ritual. And if even that feels like too many clicks, you can literally ask for it in a sentence: the Claude plugin can pull your analytics and summarize the month in chat.

The point of analytics isn't to make you a data person. It's to make three or four of your decisions per month slightly less blind, and then get out of your way.