E-Commerce Retail Price Tracking Product Research

AI agents that track competitor prices and automate e-commerce intelligence

Stay ahead of the competition. Twin monitors competitor pricing, tracks product listings, and delivers actionable e-commerce insights — so you always know when to adjust your strategy.

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Ready-to-use E-Commerce Automation Agent agents

Clone and run these agents in one click. Built by the Twin community.

AI employee

Storefront Revenue Operator

At the scheduled local time, resolve the reporting window for yesterday and the comparison windows (DoD, WoW, MoM)

Fetch metrics from the connected storefront: sessions, orders, gross revenue, refunds, AOV, conversion rate, top products, top traffic sources

Read the prior daily snapshots from the agent database to compute deltas and trend arrows

Have Twin AI draft an executive summary in the configured brand voice, including two or three recommendations grounded in the deltas

Build small trend charts and a ranked top-products table; assemble a branded HTML email

+1 more step

2 Uses

AI employee

Marketplace Price & Stock Tracker

Read agent state: last run timestamp, prior inventory snapshots, processed post IDs, and the run log

Skip the run if today already has a completed entry in the run log for the chosen cadence

For each monitored source, scrape product pages via the platform-specific scraper, falling back to generic scrape plus LLM extraction

Update the SQLite inventory_snapshots and price_history tables; insert new posts into processed_posts

Score changes against the focus list and the price-drop threshold; suppress alerts when price or stock is null

+3 more steps

2 Uses

AI employee

DTC Support Triage Operator

Read all unread support inbox messages received since the last successful run, skipping any whose message ID is already in the handled ledger.

For each new message, fetch the matching Shopify customer and most recent order(s) by email lookup so the classifier has order context.

Classify intent into one of the enabled categories with a confidence score; if confidence is below 0.7 or the intent is not in the enabled list, route the thread to human approval.

Apply the auto-action policy: execute the Shopify mutation directly when the intent is auto-approved and within the refund cap; otherwise present the proposed action for approval before executing.

Send a reply from the support inbox using the configured brand voice and signature, BCC the owner, and append the message ID and ticket outcome to the handled ledger.

+1 more step

0 Uses

AI employee

Marketplace Deal Hunter

Load previously surfaced URLs from the agent database to skip duplicates

Run web searches to build a fresh market brief with fair values and demand signals for the niche

Scrape each configured marketplace URL with summary then markdown, capped at 30 listings per source

Extract structured rows with one LLM pass per page: title, price, URL, seller signal, listing type

Score each candidate for estimated value, fees, margin, and composite rank using the market brief

+2 more steps

1 Use

AI employee

Investor Update Composer

On the 1st of each month at 09:00 local time, determine the reporting month as the previous calendar month

Check the agent database — if the month has already been reported, exit; otherwise reserve the slot

Pull all invoices issued and paid in the reporting month from the connected accounting platform

Aggregate Net Orders, Net Sales, Average Ticket, and compute MoM and YTD comparisons against prior periods

Create a Google Sheets report with a summary tab and breakdown tabs by tag, country, and product

+3 more steps

1 Use

AI employee

Supplier Catalog Sourcer

Load configuration: supplier URL, target categories, attributes to extract, dedupe key, language, markup, and row cap

Crawl category pages and collect every product detail URL, following pagination

Fetch existing catalog rows and build an in-memory set of seen dedupe keys

For each product URL, scrape the detail page and extract structured attributes in parallel

Translate text fields to the target language if different from the source

+3 more steps

1 Use

How e-commerce automation works

Go from zero to a working e-commerce agent in minutes.

Step 1

Clone an e-commerce agent

Choose an agent for price tracking, product research, or competitor monitoring and clone it.

Step 2

Tell it what to track

The agent asks about your products, competitors, and the metrics that matter — prices, stock, new launches.

Step 3

Connect your store and spreadsheets

Link Shopify, Amazon, Google Sheets, or any marketplace so the agent can pull and push data.

Step 4

Get competitive intelligence delivered

The agent monitors changes, detects price drops, and delivers actionable reports to your inbox or dashboard.

Run E-Commerce Automation Agent on Twin

Create, run, and monitor your agents from a single interface.

B2B Intent Intelligence

Workspaces

Send Twin live feedback to adjust the run...

Scrapers

Extract data from any website

Slide deck

Generate presentations instantly

Image & video

Create visual content with AI

Web search

Find information in real-time

Deep research

In-depth analysis on any topic

Any app

Connect to your favorite tools

Browser

Automate web interactions

Sharing

Share with colleagues or friends

Webhooks

Automate execution triggers

Workflow guide

Build a e-commerce automation workflow around real outputs.

The strongest e-commerce automation agent setup starts with a clear input, a repeatable decision rule, and a destination for the finished work. Twin agents can collect the data, use connected tools, and deliver a reviewable result instead of leaving the workflow as a loose prompt.

Web Scraper

Monitor competitor websites and marketplaces for pricing and product changes

Data Processing

Compare competitor prices against your catalog and calculate price gaps

Alert Engine

Trigger alerts when competitors drop prices below your threshold

Google Sheets

Update your pricing dashboard with daily competitive intelligence reports

e-commerce teams automate with Twin.

"I'm not technical at all and I built an agent that monitors competitor pricing and sends me a daily digest. It just works."

James K.

E-commerce Founder

"We track 500+ SKUs across 8 competitors. Twin caught a pricing war we would've completely missed — saved us from a 20% revenue drop."

Diana P.

Head of E-Commerce, DTC Brand

"Shopify + Twin is a killer combo. Price tracking, inventory alerts, and competitor analysis all automated. My margins have never been better."

Andre V.

Shopify Store Owner

FAQ

Common questions about e-commerce automation agent.

What is E-Commerce Automation Agent?

Stay ahead of the competition. Twin monitors competitor pricing, tracks product listings, and delivers actionable e-commerce insights — so you always know when to adjust your strategy.

How does Twin automate e-commerce workflows?

Clone an e-commerce agent: Choose an agent for price tracking, product research, or competitor monitoring and clone it. Tell it what to track: The agent asks about your products, competitors, and the metrics that matter — prices, stock, new launches. Connect your store and spreadsheets: Link Shopify, Amazon, Google Sheets, or any marketplace so the agent can pull and push data. Get competitive intelligence delivered: The agent monitors changes, detects price drops, and delivers actionable reports to your inbox or dashboard.

Do I need to write code to use these agents?

No. Twin lets you clone, configure, and run AI agents using natural language and connected apps.

Ready to automate e-commerce?

Set up this agent in minutes. No code required. Start automating your e-commerce workflows today.

Browse the full agent library