Topic engine

seedpick hands you topics your market has not seen yet. Yours alone.

For the one-person business, coach, consultant or agency that has to decide what to publish every single week.

Good content still flops when the topic is the one everyone already used.

You automated it with AI. So why is the output underwhelming?

It is not the tool. The ceiling of any automation is the material you feed it, and a general-purpose AI can only hand you what it already memorised: the average, the same thing every competitor gets. Differentiation starts at the material, not the edit. That is why seedpick AI is not optional.

General-purpose AI vs seedpick AI

General-purpose AIseedpick AI
Information is fromUp to its training cut-off (the past)Mined live, after you ask
Where it looksWidely circulated public knowledgeThe live global web + local-language sources in your market
How unique the answer isYour competitor asks, gets the same thingFiltered through your business. Yours alone
EvidenceNo source, and sometimes inventedA source link per claim; weak findings are dropped
What you end up publishingWhat everyone else is publishingWhat nobody in your market has said yet

We asked the same question in three different businesses. The answers split like this.

Restaurant"What should I make about menu pricing?"
General-purpose AI

"5 ways to price your menu"

  • Keep food cost around 30%
  • Check what competitors charge, use charm pricing
The problem

No source, no number you can verify, and the same list already exists thousands of times. Your competitor's AI hands them the identical five points.

seedpick AI

"You hit a 30% food cost and still go broke: the number nobody told you"

Why this topic, now

Food cost alone really is around 30%. But food plus labour, the prime cost, takes 70~75% of revenue in a small kitchen. Hitting the number everyone repeats can still leave nothing at month end. For an owner about to sign a lease, that is the figure to see before the price list.

Evidence

US restaurant-industry cost data, with the source link attached to the card.

Hair salon"Regulars are coming back less often. What should I post?"
General-purpose AI

"5 ways to bring customers back"

  • Run a membership or a coupon
  • Send a reminder message, post more on social
The problem

Discount-shaped advice with nothing behind it. It also trains regulars to wait for the next coupon.

seedpick AI

"Why a regular who skips once never comes back: the one thing that took rebooking from 35% to 70%"

Why this topic, now

65% of first-time clients never return. Yet a loyalty programme with automatic rebooking prompts lifted the return rate from 35% to over 70%. The lever was not the size of the discount. It was whether the next visit was already on the book. Almost nobody in your market frames it this way.

Evidence

Overseas salon operations data, source link attached.

Online store"First orders come in, repeat orders do not. What should I make?"
General-purpose AI

"How to raise your repurchase rate"

  • Send a thank-you message and a coupon
  • Improve packaging, ask for reviews
The problem

Every store already does this, so nothing in it makes a buyer choose you. And none of it is tied to why they actually did not come back.

seedpick AI

"What one lost repeat customer really costs: 5 to 7 times your acquisition spend"

Why this topic, now

Winning a new customer costs 5 to 7 times what it costs to keep an existing one, and lifting retention by just 5% raises profit by 25~95%. So the question is not whether to send one more coupon. It is where the advertising money should sit in the first place.

Evidence

Overseas e-commerce cost data, source link attached.

Both columns are real output. The right one is a card seedpick actually produced during testing. Not a mock-up.

So where do these come from?

The work starts after you ask. Nothing is pulled off a shelf.

  1. 1. We read your business first

    What you sell, and which decision your customer is standing in front of right now. Only then do we set four angles that deliberately pull in different directions. Angles that lean the same way bring back the same thing.

  2. 2. We look at the world and at your market, at once

    Authoritative sources in English, and local-language sources inside your market, in the same pass. And we read the documents themselves, not the search summaries. The numbers worth having never survive a summary.

  3. 3. We cut like an editor, not a search engine

    Sources are weighted by how much they can be trusted. Anything merely interesting, that changes nothing about your customer's decision, is dropped. If nothing survives, you get nothing, and we say so. A weak topic is worse than an empty week.

  4. 4. We hand it over ready to make

    Not a one-line idea. The topic, why it lands now, the finding it rests on with its source link, three title options, the opening line, and the format that fits.

4 angles per runTwo language spheres at onceDozens of documents read in fullOnly what survives becomes a card
seedpickTopic engine
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