Hey {{first_name}},
Pairing these two questions will give you an incredible amount of data.
But the volume is not even the best part.
It’s the quality and the breadth of what’s disclosed that really makes this exercise worth your time.
I am referring to a post-purchase survey.
On the thank you page.
Right after they’ve paid.
On a scale of 1 to 10, how would you rate your purchase experience today?
What almost stopped you from buying today?
That second question is where the money is.
People will happily tell you what annoyed them because they love to moan.
You’ll get things like this.
“Your shipping costs surprised me, but I managed to find something low-cost to reach the free shipping threshold”
“I didn’t know what size I should buy and wasn’t sure what your returns policy was if it didn’t fit. I eventually found it on your footer”
“Spotted the discount code field at checkout, went to try to find a code and realised I could sign up to get 10% off”
“Didn’t have my credit card handy, and you had no Apple Pay option. Came back later to buy.”
And those things are amazingly useful.
Basically, a list of things that almost stopped them.
And will definitely be stopping others.
Run it for 7 to 14 days, export the responses, then drop them into an LLM with the prompt below:
I have attached raw survey answers from a post-purchase survey with two questions:
1. An NPS survey: “On a scale of 1 to 10, how would you rate your purchase experience today?”
2. Open-ended question: “What almost stopped you from buying today?”
Your Role:
Act as a Conversion Rate Optimisation Strategist from Blend Commerce.
Tasks:
1. Create a table of the top friction themes from Question 2, grouped into clear categories (for example: shipping, pricing, trust, product info, sizing, payment, discount codes, delivery timing, checkout usability, tech issues).
2. For each theme, include:
* frequency (count and percentage)
* 3 representative quotes (verbatim, short)
* severity score from 1 to 5 (5 = likely to stop a purchase)
* confidence score from 1 to 5 (5 = lots of consistent answers)
3. Identify any themes that show up mainly in low NPS scores (0 to 6) versus high scores (9 to 10).
4. Recommend the top 10 actions to take next, prioritised using this rule:
High severity + high frequency + high confidence = top priority.
5. For each recommended action, tell me:
* where it should be fixed (product page, collection page, cart, checkout, shipping page, FAQs, support)
* the simplest first fix we can make in 7 days
* a stronger follow-up fix if we have more time
* how to measure impact (which metric changes should we watch)Now rinse and repeat.
You’ll have a backlog of optimisations for months.
Chat soon,
Peter
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