Self-publishing books is hard.

And I mean, really hard.

But data science and artificial intelligence (AI) make it a little easier!

By leveraging data, I've created two powerful tools: a manuscript drafter and an ads optimiser.

These tools have streamlined operations and significantly boosted my success.

Let me walk you through how each of these innovations works and the impact they've had.

Manuscript Drafter

Drafting a manuscript is tough.

Have you ever tried writing a 30,000-word book? 1k-articles in school were long enough.

But seriously—writer's block, time constraints, and the sheer complexity of storytelling can be overwhelming.

My manuscript drafter removes these challenges by providing a complete and comprehensive draft for my book.

With the latest advancements in generative AI, I’ve used GPT-3, followed by 3.5, 4, 4.5, and 4o (just released today as of writing) to power my application.

How does it work? I put in a keyword, and a 30,000-word manuscript is generated.

Dead simple.

Of course, you can’t forget about the countless late-night hours coding it up.

But hey, that’s the power of automation.

Do the hard work up front and reap the rewards down the track.

But is the quality of the draft manuscript any good?

Previously, I used to pay $1500 to a ghostwriter to draft it up.

Then, wait two months for the first draft.

I did this a few times.

But was never satisfied.

Now, with AI, it costs me $5 and about four and a half minutes to get the first draft.

Even though it’s not perfect—I’d say it’s pretty good.

And especially since it’s reduced my iteration time from two months down to 4.5 minutes.

And my costs from $1500 to $5.

How’s that for operational efficiency?

Ads Optimizer

Advertising is very important.

Especially for self-published authors!

But seriously, dear Amazon KDP: managing your ad campaigns sucks!

It’s bulky, slow, tedious, time-consuming, boring, etc, etc.

So, I built a script to:

1. Create ads in 12 different marketplaces.

2. Optimise ads based on past performance.

I used data from the last 14 days to either:

1. Increase the bid (if the return is good)

2. Decrease the bid (if the return is okay)

3. Drop the ad (if the returns are bad)

4. Leave it alone (if fully optimised)

This ads optimizer has significantly improved my ad performance.

By automating and optimizing my campaigns, I’ve seen a 20% decrease in average cost of sale (ACOS).

To wrap it up—integrating data science into my publishing business has been transformative.

These tools have improved efficiency and driven significant growth in sales.

The manuscript drafter and ads optimiser have both played a crucial role in my success.

I'd love to hear your thoughts or experiences with data science in publishing.

If you found this post interesting, please get in touch!

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