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I realized most abandoned carts have nothing to do with price
They have a question that never got answered
Here's what changed my thinking on this
THE PATTERN:
Pulled session recordings from a client's store
A large chunk of visitors added a product, scrolled up and down the page multiple times, then left
Not confused about the product, looking for something specific the page didn't say
THE MOST COMMON EXAMPLE:
Shoe store, customer scrolling between the size chart and product images repeatedly
The obvious unspoken question was simple, will this fit my exact foot size
No chat option, no way to ask, no answer visible
WHY THIS QUIETLY KILLS CONVERSIONS:
The customer does not email support over one small doubt
They do not fill out a contact form for a question this minor
They just leave and buy from somewhere that made the answer easier to find
WHAT WE ADDED:
A simple AI chat widget trained on the store's actual product data, sizing charts, and shipping policies
When someone asked a sizing or fit question, it answered instantly using real store information
Not a generic bot, one that actually knew the catalog
THE RESULT:
Noticeably fewer people were leaving right at that scroll back and forth pattern
Conversations that happened almost always ended in a completed order
Because the doubt got resolved in seconds instead of growing into a closed tab
Here's the real insight behind this:
Most people don't abandon carts because they changed their mind
hey abandon because they had one small question and nobody was there to answer it in the moment
If your store has no way for a visitor to ask a quick question without leaving the page, that gap is probably costing you more than you think
#Shopify #ShopifyAI #ConversionRateOptimization #EcommerceGrowth #CustomerExperience #ShopifyTips #ShopifyPlus
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If you're a consultant or founder posting three times a
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you're not playing.
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Someone types a question into ChatGPT Search or Google AI
Overviews. The answer comes with sources. LinkedIn posts are on that list.
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ChatGPT Search answers.
Most of those citations went to individual profiles, not
company pages. Half came from accounts under 10,000 followers.
Quotability beat follower count.
What gets quoted (steal this):
1. One question per post
→ Line one is the
exact question a buyer would type into ChatGPT.
2. A plain-English definition inside 3 lines
→ AI lifts clean
sentences. It can't quote a vibe.
3. Your own dated numbers
→ "11
citations in August" gets cited. "Great results" doesn't.
4. A headline + About section that claim the topic
→ The model checks
who's talking before it trusts the post.
Check yourself in 5 minutes: type your ideal client's
question into ChatGPT Search and scroll the sources. If a competitor's post is
there and yours isn't, that's your next topic.
The feed forgets your post in 5 days. An AI citation keeps
answering for you for months.
(I'll say the uncomfortable bit: I think AEO beats the feed
algorithm for inbound by 2027. Most coaches selling algorithm hacks won't like
that.)
Two years from now: does a ChatGPT citation beat LinkedIn
reach for inbound, or is AEO just SEO in a new hat? Pick a side.
-- M Aadil A.
@Muhammad Aadil Ali AEO feels less theory and more math now. Clean sentences beating vibes every time is underrated. This is the kind of clarity LinkedIn actually loves. You turned boring acronyms into growth hacks. Citations keep answering for months, that’s the real flex.🙌
Customers tell you exactly what is broken in the product, nobody tells you what is broken on the site. The only people who could have told you already left.
my AI coding agent told me everything was done.
three weeks of work. report had green checkmarks
on every item. typescript passed. build passed.
I ran one command and found out the main migration
was never applied to any database.
not delayed. never.
Tweet 2:
the agent wrote 842 lines of SQL for a billing system.
described it in detail. said "verified ✓"
the columns it referenced didn't exist in the actual
table. first real user would've hit a crash on
signup.
[SCREENSHOT 1: agent report]
Tweet 3:
here's what I ran:
npx supabase db push
output: "Remote database is up to date"
that phrase means: nothing new to apply. the thing
it "completed" was never sent anywhere.
[SCREENSHOT 2: db push output]
Tweet 3.5 (yehi human touch):
(btw this is the SECOND time. first time it "verified"
a function that queried a column it never created)
Tweet 4:
since then my rule is dumb simple:
if the agent says done → I run the thing myself →
I look at the output with my own eyes → THEN it's done
my fake-done rate over 6 weeks: somewhere around 60%.
I stopped counting after it hurt.
Tweet 5:
weird part? the reports were beautiful. well written.
confident tone. proper structure.
beautiful fiction.
if AI is writing your code, who's checking the code?
genuinely curious what other people's fake-done rate
looks like. mine was bad.
#buildInpublic
#vibecoding
#AIcoding
The gap between green checks and a real migration is such a sharp reminder that verification has to reach the running system. I like the concrete failure mode here—schema reality beats confident generated SQL every time.