We set up the batch-and-schedule system described in our earlier post in early August: a Monday morning content batching session, Buffer for scheduling, daily engagement check, and a Make automation to repurpose blog post content into social drafts. One month later, here's what the data showed.
The Baseline (Before Automation)
Before the system, our social media was inconsistent. We posted when we had something to say, which averaged out to about two posts per week on LinkedIn and one post per week on X/Twitter. Sometimes we'd go ten days without posting. Engagement was low but steady. We had no scheduling tool, no batching process, no repurposing workflow.
The main cost wasn't the inconsistency itself — it was the mental overhead. Every day there was a background decision: "should I post today? What would I say?" That friction is small per instance but significant in aggregate. It meant posting was always reactive, not intentional.
What We Changed
- Added Buffer (free plan, then upgraded to Essentials at $6/month)
- Set a recurring Monday 9–10:30am calendar block for content batching
- Built a Make automation: new blog post published → Claude drafts 5 social posts from the content → posts saved to a Google Sheet for review → approved posts added to Buffer queue
- Committed to 5 posts per week on LinkedIn and 3 per week on X, consistent days
- Daily 15-minute engagement window, 8:30am, calendared
The 30-Day Numbers
| Metric | Before | After (30 days) | Change |
|---|---|---|---|
| Posts per week (LinkedIn) | ~2 | 5 | +150% |
| Posts per week (X) | ~1 | 3 | +200% |
| LinkedIn impressions/week | ~800 | ~2,100 | +163% |
| LinkedIn followers gained | +6/month avg | +31 in 30 days | +417% |
| Avg engagement rate (LinkedIn) | 3.8% | 2.9% | -0.9pp |
| Waitlist signups attributable to social | ~1–2/month | 7 in 30 days | +~4× |
| Time spent on social media (creation) | ~4 hrs/week (scattered) | ~1.5 hrs/week (batched) | -63% |
| Posts we were proud of | ~40% | ~65% | +25pp |
The Surprises
Engagement rate dropped, but total engagement went up. This is expected and worth understanding: when you post more, each post reaches a smaller percentage of followers (because the algorithm distributes each post more selectively). But total impressions and interactions increase because you're in the feed more often. The absolute engagement numbers are what matter for business outcomes, not the rate. Don't optimise for rate.
Batching produced better content than reactive posting. We expected the opposite — that content written in the moment, about something fresh, would feel more authentic. Instead, the Monday batching session consistently produced more thoughtful posts. Being in "content mode" for 90 minutes, with access to notes and data, beat trying to write something worthwhile in 10 minutes between client calls.
The Make/AI repurposing workflow needed more editing than expected. The automation drafted posts from each blog post, but about 40% of them needed significant editing before they were usable — either because the AI missed the most interesting angle, or because the tone was slightly off. We added a review step and now treat the AI output as a first draft, not a final post. Editing a draft is still much faster than writing from scratch.
The one thing that didn't work: Auto-publishing without review. We tried it for one week with posts the AI generated from blog content. Three of the seven posts felt noticeably generic. Readers noticed — one commented "this feels like it was written by a bot." We went back to a review-before-publish workflow immediately. The lesson: automation for drafting and scheduling, human judgment for approval.
What We Changed After 30 Days
The core system stayed the same. We made three adjustments:
- Added a "specificity check" before scheduling any post. One question: "Does this sentence contain a specific number, name, or example?" If the answer is no to any paragraph, we rewrite it. This added about 5 minutes per batch session and noticeably improved quality.
- Dropped posting frequency on X from 3 to 2 per week. The engagement data suggested quality was more important than frequency on X specifically — two strong posts outperformed three mediocre ones in every measurable way.
- Added a Friday "what happened this week" post format to LinkedIn. Unscheduled, written Friday afternoon about something specific from the week. These consistently outperformed the scheduled batched posts — because they're timely and specific in a way that batched content can't fully replicate. We kept the scheduled posts for volume and consistency, and the Friday post for peak performance.
The Honest Assessment
The system works. Volume is up, quality is up, time investment is down, and the metrics that matter for business outcomes (follower growth, waitlist conversions) are meaningfully better. The engagement rate dip is a distraction — ignore it.
The biggest win isn't in the numbers, though. It's the mental shift from reactive to intentional. We know every week what's going out, when, and why. We're not behind. We're not scrambling. The background noise of "I should be posting more" is gone. That's harder to quantify but worth at least as much as the follower count increase.
Recommendation: Start with the batching habit before any tools. Spend two weeks writing five posts every Monday morning and scheduling them manually. If you do that consistently, add the scheduling tool. Then add the repurposing automation. Build the habit first; the automation amplifies it.
Want to Set Up a System Like This for Your Business?
We help small businesses build content workflows and automation pipelines that run consistently without eating your week. Get in touch to see what we'd recommend for your situation.
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