https://github.com/jennifercutduk/ebay-feedback-reminder-bot
eBay Feedback Reminder Automation Bot
https://github.com/jennifercutduk/ebay-feedback-reminder-bot
accessibility-service adb-less-automation android-automation appilot appium bluestacks ebay-automation ebay-feedback-reminder-bot notifications-bot robot-framework ui-automator
Last synced: 3 days ago
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eBay Feedback Reminder Automation Bot
- Host: GitHub
- URL: https://github.com/jennifercutduk/ebay-feedback-reminder-bot
- Owner: jenniferCutduk
- Created: 2025-11-06T13:46:44.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-11-06T14:09:45.000Z (8 months ago)
- Last Synced: 2025-11-06T15:29:29.443Z (8 months ago)
- Topics: accessibility-service, adb-less-automation, android-automation, appilot, appium, bluestacks, ebay-automation, ebay-feedback-reminder-bot, notifications-bot, robot-framework, ui-automator
- Homepage:
- Size: 88.9 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# eBay Feedback Reminder Bot
The **eBay Feedback Reminder Bot** automatically identifies completed orders and sends timely, human-like nudges to buyers to leave feedback—so your store reputation grows without manual chasing. It eliminates the repetitive task of monitoring orders, drafting reminders, and tracking responses across multiple accounts and devices. Expect higher feedback rates, improved seller metrics, and a steady lift in search visibility.
Created by Appilot, built to showcase our approach to Automation!
If you are looking for custom eBay Feedback Reminder Bot, you've just found your team — Let’s Chat.👆👆
## Introduction
This bot streamlines post-purchase engagement by detecting shipped/delivered orders and dispatching well-timed reminders via eBay messages or buyer-friendly prompts.
It removes the tedium of manual follow-ups, ensures consistent tone, and scales outreach across multiple stores and devices.
The outcome: more positive feedback, stronger seller ratings, and better conversion.
### Automating eBay Post-Purchase Feedback Requests
- Auto-detects order lifecycle states (shipped, delivered, elapsed days) and triggers reminders at the right time.
- Uses human-like pacing, randomized delays, and template variation to avoid spammy patterns.
- Works across real Android devices and emulators with UI-level reliability—no brittle HTML selectors.
- Manages multi-account operations with profile isolation, proxy routing, and per-store schedules.
- Centralized dashboards, logs, and KPIs to track feedback rates and message performance.
## Core Features
- **Real Devices and Emulators:** Run on physical Android phones/tablets or emulators (Bluestacks/Nox). Device-level control ensures reliability across UI changes and app updates.
- **No-ADB Wireless Automation:** Control devices wirelessly without tethering. Ideal for racks and cloud farms; deploy, start, and monitor jobs remotely.
- **Mimicking Human Behavior:** Randomized delays, typing simulation, scroll variance, and dwell times to match organic usage and minimize platform suspicion.
- **Multiple Accounts Support:** Isolated profiles, per-account templates, schedules, and logs. Safe rotation rules to prevent cross-contamination.
- **Multi-Device Integration:** Scale to dozens or hundreds of devices with coordinated job queues and per-device rate limits.
- **Exponential Growth for Your Account:** Consistent reminders increase feedback velocity, improving seller reputation and organic ranking—compounding over time.
- **Premium Support:** Priority onboarding, SLA-backed responses, and tailored playbooks for feedback strategy and scaling.
**Additional Capabilities**
| Feature | Description |
| --- | --- |
| **Smart Trigger Windows** | Fire reminders based on delivery confirmation, elapsed-days thresholds, timezone-aware windows, and holiday quiet hours. |
| **Template & Tone Manager** | Rotate message templates, personalize buyer names/order details, and A/B test tones (friendly, concise, value-first). |
| **Compliance & Rate Limits** | Enforce per-account messaging caps, cooldowns, and country-specific timing to reduce flags and maintain trust. |
| **Analytics & KPIs** | Track send volume, open proxies, response rates, feedback growth curves, and per-template performance. Export CSV/JSON. |
| **Failover & Retries** | Auto-retry on network hiccups, UI hiccups, and app restarts with screenshot logging and Reason codes. |
| **Webhook & CRM Sync** | Push events to Slack/Webhooks/CRMs (e.g., when feedback received or reminder sent) for cross-team visibility. |
## How It Works
1. **Input or Trigger** — The automation is initiated from the Appilot dashboard with selected eBay accounts, reminder templates, timing rules, and device targets (real or emulator).
2. **Core Logic** — Appilot orchestrates UI flows using UI Automator/Appium to open eBay, read order statuses, and prepare messages. Anti-pattern heuristics add natural delays and small UI gestures.
3. **Output or Action** — The bot sends context-aware reminders referencing the buyer, item, and order. Results are logged and surfaced in dashboards; optional webhooks notify external tools.
4. **Other functionalities** — Built-in retry logic, per-step screenshots, structured logs, and parallel processing enable smooth, debuggable execution at scale.
## Tech Stack
- **Language:** Kotlin, Java, JavaScript, Python
- **Frameworks:** Appium, UI Automator, Espresso, Robot Framework, Cucumber
- **Tools:** Appilot, Android Debug Bridge (ADB), Appium Inspector, Bluestacks, Nox Player, Scrcpy, Firebase Test Lab, MonkeyRunner, Accessibility
- **Infrastructure:** Dockerized device farms, cloud-based emulators, proxy networks, parallel device execution, task queues, real device farm
## Directory Structure
```
ebay-feedback-reminder-bot/
│
├── src/
│ ├── main.py
│ ├── automation/
│ │ ├── triggers.py
│ │ ├── reminder_flow.py
│ │ ├── device_controller.py
│ │ └── utils/
│ │ ├── logger.py
│ │ ├── proxy_manager.py
│ │ ├── template_engine.py
│ │ └── config_loader.py
│
├── config/
│ ├── settings.yaml
│ ├── schedules.yaml
│ ├── templates/
│ │ ├── friendly.txt
│ │ ├── concise.txt
│ │ └── value_first.txt
│ ├── credentials.env
│
├── devicefarm/
│ ├── docker-compose.yaml
│ └── emulator_profiles.json
│
├── logs/
│ ├── run.log
│ └── screenshots/
│
├── output/
│ ├── kpis.csv
│ └── audit.json
│
├── scripts/
│ ├── start_cluster.sh
│ └── rotate_proxies.py
│
├── tests/
│ ├── test_triggers.py
│ └── test_templates.py
│
├── requirements.txt
└── README.md
```
## Use Cases
- **SMB eBay sellers** use it to send polite reminders after delivery, so they can improve feedback rates without manual follow-ups.
- **Agencies managing multiple stores** use it to coordinate messaging across dozens of accounts, so they can scale operations with guardrails.
- **Growth teams** use it to A/B test templates and timings, so they can optimize response rates and reputation metrics.
- **Ops teams** use it to centralize logs and alerts, so they can audit message quality and quickly troubleshoot issues.
## FAQs
**How do I configure this automation for multiple accounts?**
Add each account profile in `config/settings.yaml` with unique session data, proxy, and schedule. The bot loads profiles at runtime and enforces per-account limits and cooling windows.
**Does it support proxy rotation or anti-detection?**
Yes. Use `proxy_manager.py` to assign residential/mobile proxies per account/device. Randomized delays, UI gestures, and template variation reduce automated footprints.
**Can I schedule it to run periodically?**
Absolutely. Define cron-like windows in `schedules.yaml` (e.g., run after expected delivery + 48 hours, skip weekends). The scheduler respects timezones and quiet hours.
**What happens if the app UI changes?**
UI Automator/Appium selectors are layered with fallbacks and image-matching hints; the bot retries steps, captures screenshots, and escalates when heuristics fail.
**Is message content customizable?**
Yes. Place variations in `config/templates/` and map them to triggers (delivered, shipped+5d, no response). Variables like `{buyer_name}`, `{item_title}` are supported.
## Performance & Reliability Benchmarks
- **Execution Speed:** 150–250 reminders per hour per device (typical mid-range emulator farm), with smart batching to keep the UI responsive.
- **Success Rate:** ~95% end-to-end completion on stable networks with recommended device settings.
- **Scalability:** Horizontal scale from a handful of devices to **300–1000** devices via Appilot queues and containerized device farms.
- **Resource Efficiency:** Lightweight workers (<250MB RAM footprint per headless emulator); adaptive sleep to minimize CPU spikes.
- **Error Handling:** Exponential backoff retries, annotated screenshots on failure, structured JSON logs, Slack/webhook alerts, and auto-resume from last stable checkpoint.
##
