Ciwi
Back to topic
Spark playbook scenarios · Spark: AI Store Assistant

Present genuine reviews and other supported social proof

Reviews and usage evidence exist but sit in one block at the bottom, far from the doubts that stop an order. In this case, the immediate task is to present genuine reviews and other supported social proof. The workflow should produce the selected proof with suggested placements and sources, matched to where each hesitation occurs on the page.

Topic
Product Page Trust and Purchase Information
Target keyword
shopify product page social proof
Copyable AI prompt

A prompt you can drop directly into Spark

First replace every [bracketed] placeholder with real store scope and constraints, then add any actual records or data you have, and paste it into your preferred AI assistant or Spark agent. Spark will follow this page's workflow to produce structured output and verification steps.

ai-prompt.txt
Act as a Shopify operations specialist.
Help me present genuine reviews and other supported social proof.
My store context is [describe the business, products and target audience].

My scope is [specify the affected products, pages, customers or reporting period]. Use these inputs: [dated reviews with verified status, the rating distribution, usage evidence such as customer photos and purchase counts, and the page positions where buyer hesitations occur]. Select proof items that speak to each hesitation, keeping a balanced mix that includes critical reviews, and trim only for length so neither meaning nor emphasis departs from the original wording.
Return the selected proof with suggested placements and sources, each item verified against the supplied records for the specified task.
Show the relevant evidence or before-and-after examples and explain how I can verify the result.
If essential data is missing, ask for it and mark unsupported conclusions as unknown.
Do not invent metrics, product claims or customer facts.
For any publication, message, account or store change, use only connected tools within my explicitly authorized scope and report success only after verification; otherwise provide the draft or proposed steps.
Use in Spark
How to solve

A recommended resolution workflow

Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.

01

Step 1

Collect the genuine reviews with their dates and verified status, the rating distribution, and any usage evidence such as customer photos or purchase counts, together with the page positions where buyer hesitations actually occur.

02

Step 2

Select proof items that speak to each hesitation, keeping a balanced mix that includes critical reviews, and trim only for length so neither meaning nor emphasis departs from the original wording.

03

Step 3

Deliver the selected proof with its suggested placement next to the hesitation it addresses plus its source and date, then verify each displayed item exists in the records word for word and the selection is not exclusively positive.

FAQ

Common questions when running this scenario

Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.

Can reviews be edited to read better?

They can be trimmed for length with ellipses, but not reworded, reordered to shift emphasis, or condensed into prose that alters the rating. The displayed text must match the stored review, because the page is quoting a customer, not writing marketing copy.

Should only positive reviews be shown?

No. A selection that includes critical reviews is more credible, and complaints often answer the exact hesitation blocking other buyers. Exclude a review only for relevance or verified-policy reasons, never for its rating.

Where should social proof sit?

Next to the hesitation it addresses, such as sizing doubt near the size selector or durability doubt near the specifications. Pooling all proof into one bottom block leaves those questions unanswered at the moment they arise.

Related scenarios

Continue with adjacent or same-topic scenarios

Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.

Next step

Want these AI scenarios embedded directly into daily operations?

Ciwi Spark builds Shopify-native AI tools and agents around the workflows merchants actually run: research, ads, translation, and customer support. Stop rewriting the same prompts by hand.

Open Spark product pageBack to Spark scenario library