Module 03 · Content Production With AI
Caption and Discovery-Term Systems You Can Test
Open lesson + course map
On this lesson
Course outline
Module 1 · Building Your Content Engine
Module 2 · Trend Analysis
Module 3 · Content Production With AI
Module 4 · Platform-Specific Growth Tactics
A useful caption does three jobs: it earns attention, explains why the post matters, and gives the viewer a sensible next action. A discovery term is a phrase a real viewer might use to find that topic. Neither is a magic switch for reach.
In this lesson, you will build three caption variants and a discovery-term test sheet. You will keep the post itself fixed, change one caption variable, and judge the result with first-party analytics—not hashtag folklore.
// concept
Give Every Caption Three Parts
Use hook → value/context → call to action (CTA). The weight changes by platform.
| Platform | Practical caption pattern |
|---|---|
| TikTok | Search-shaped hook; one context line; question or save CTA |
| Early hook; scannable context; save, share, or reply CTA | |
| Professional observation; useful detail; specific question | |
| YouTube | Clear title; description naming the problem and payoff |
These are sample captions for a hypothetical Karachi baking tutorial, not performance claims.
- TikTok sample A: “Buttercream melting during Karachi delivery? See three packing checks. Which should we test next?”
- TikTok sample B: “Karachi cake packing: chill the base, check box clearance, shorten delivery. Save this checklist.”
- Instagram sample A: “A neat cake edge starts before piping: chill, crumb-coat, smooth. Save this carousel.”
- Instagram sample B: “Planning a Karachi birthday cake? Confirm servings, finish, and delivery time. Which is hardest?”
- LinkedIn sample A: “A written cake brief can reduce revision confusion. What order detail is often omitted?”
- LinkedIn sample B: “Try this home-bakery brief: date, servings, flavour, finish, delivery area.”
- YouTube sample A: “Pack a Buttercream Cake for Delivery | Karachi Workflow. Chilling, clearance, and handoff checks.”
- YouTube sample B: “Birthday Cake Brief: 5 Details to Confirm. Servings, flavour, finish, date, area.”
Hashtags are a minor field. Guidance changes, so verify the official Sources. Use the clearest phrase naturally in the caption, title, speech, or on-screen text where supported.
Inspect native evidence: TikTok Creator Search Insights/post analytics, Instagram Insights, LinkedIn post analytics, or YouTube Studio traffic sources and search terms. Availability and definitions can change.
// concept
Turn Search Language Into a 20-Term Hypothesis List
Collect phrases from native search suggestions, customer questions, comments, and first-party reports. Give AI this observed language; never ask it to invent what is “trending.”
For the hypothetical bakery, a sample 20-term list is: custom birthday cake Karachi; chocolate birthday cake Karachi; buttercream cake Karachi; fondant cake Karachi; bento cake Karachi; one-pound cake Karachi; cake delivery Karachi; birthday cake order Karachi; birthday cake price Karachi; minimalist cake Pakistan; kids birthday cake Karachi; anniversary cake Karachi; eggless cake Karachi; cupcake box Karachi; wedding cake consultation Karachi; cake near Gulshan; cake near DHA Karachi; Karachi home baker; buttercream cake delivery; cake order on WhatsApp.
Classify terms as learn, compare, buy, or local. Keep only phrases the post answers. Repetition cannot rescue an irrelevant term.
// concept
Generate Variants and Log One Variable
Give AI the script and approved terms, not a request for a “viral caption”:
You are editing captions, not predicting performance.
Platform: [TikTok / Instagram / LinkedIn / YouTube]
Audience: [specific viewer]
Post script: <script>[paste the final script]</script>
Approved discovery terms: [paste 5–8 observed phrases]
Write 3 caption variants. Keep the factual message and CTA identical.
Change only the hook:
A = problem-led, B = search-led, C = outcome-led.
Use one primary discovery phrase naturally in each caption.
Do not add claims, prices, hashtags, urgency, or results not in the script.
Return a table: variant | caption | primary term | words copied from source.Sheet columns: post ID, platform, date, fixed asset, variant, primary term, hook type, CTA, window, first-party metrics, result, confounders, next hypothesis. Run variants sequentially under similar conditions. The evidence is directional, not causal; audience and distribution can differ.
// worked_example
Worked Example
Bad draft: “Sweet moments await! Order now! #fyp #viral #trending #cakes.” It hides the topic, stuffs tags, and invents availability.
The prompt produces three sample hooks while holding body and CTA fixed:
- Problem-led: “Cake revisions can start with a missing detail. Confirm date, servings, flavour, finish, and delivery area. Which field would you add?”
- Search-led: “Custom birthday cake brief: date, servings, flavour, finish, and delivery area. Which field would you add?”
- Outcome-led: “Make the cake handoff clearer with five fields: date, servings, flavour, finish, delivery area. Which would you add?”
The fix names the tutorial and makes no reach claim.
| Post ID | Variant | Primary term | Window | Result | Confounder / next step |
|---|---|---|---|---|---|
| CAKE-01 | A | cake order detail | 72 hours | Not run—record native analytics | Baseline |
| CAKE-02 | B | custom birthday cake brief | 72 hours | Not run—record native analytics | Keep video and CTA fixed |
| CAKE-03 | C | five-field cake brief | 72 hours | Not run—record native analytics | Compare only after all windows close |
“Not run” is the honest pre-publication state. Replace it only with native platform data.
// failure_cases
Failure Cases to Diagnose
6 cases to diagnose
Caption and video disagree
pricing is promised, but packing is taught. Remove the term or change the content.
Every field changes
a new hook, CTA, posting time, and audio make the comparison unreadable. Change one planned variable.
Hashtag pile replaces context
delete broad tags such as
#fyp; write the topic in a sentence first.AI invents demand
remove “trending,” “most searched,” or similar claims unless a dated first-party view supports them.
Raw views become the verdict
use the metric tied to the goal and any available search/discovery evidence.
Cross-platform numbers are treated as equal
compare variants within the same platform; metric definitions differ and can change.
// pakistan_angle
Pakistan Angle
Test English, Urdu script, and Roman Urdu separately. A Karachi query may say “birthday cake price Karachi,” “cake ka order,” or “cake near Gulshan.” Use customer language, not twenty spellings in one caption. A WhatsApp CTA may ask for date and area; never expose a customer’s phone, address, CNIC, or chat screenshot.
Load-shedding and mobile data affect tests. Prepare uploads when connectivity is stable, keep the sheet offline, and log interruptions. Activity around work, Maghrib, Isha, Ramzan, or Eid can shift; use your analytics instead of declaring a universal Pakistani posting time.
// hands_on
Hands-On Exercise
6 steps
Choose one existing post and copy its final script into a private working document.
Collect twenty real phrases from native search suggestions, comments, FAQs, or first-party reports; label their source and date.
Select five relevant terms and run the caption-variant prompt.
Edit the output into three variants with one fixed body and CTA; change only the hook.
Add three rows to the test sheet, including a fixed measurement window and blank result fields.
Publish only if appropriate, then enter native analytics after each window closes.
// completion_rubric
Completion Rubric
5 checks — tick as you verify
// sources
Sources
// check_yourself
Check yourself
4 questions · answers and options are taken word-for-word from this course
1 / 4 · diagnose
Your work shows this failure mode: “Caption and video disagree.” The lesson describes it like this: “Pricing is promised, but packing is taught.” What does the lesson tell you to do about it?