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Remove Fake Reviews Fast | Google Maps & Amazon ORM Expert
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‼️ Important reminder:
Submit the Custom Agent via the Notion Marketplace submission flow. If this is your first time using marketplace, first go to notion.so/profile to complete your profile. Please note that it can take up to 48 hours for the team to review and approve or reject the agent.
*As long as your submission is posted, by March 31st at 11:59pm PDT, your submission will be reviewed and considered for the prize.
notion.so
Notion – The all-in-one workspace for your notes, tasks, wikis, and databases.
A tool that connects everyday work into one space. It gives you and your teams AI tools—search, writing, note-taking—inside an all-in-one, flexible workspace.
Most restaurant businesses don’t realize this…
Your Google Business Profile is often the first place potential customers find you—not your website.
And if it’s not fully optimized, you’re losing leads every single day.
Here’s what a fully optimized profile actually does:
📍 Shows your business in top Google Maps results
📢 Drives more direct phone calls
🌏 Increases website visits from high-intent users
⏳ Builds trust through reviews and active engagement
But the difference comes down to a few key things:
- Complete and accurate business information
- Proper category and keyword optimization
- Consistent reviews and responses
Regular posts and updated photos When all of these work together, your profile becomes a 24/7 lead generation machine. Most competitors aren’t doing this properly—that’s the opportunity. If your business isn’t showing up in the top 3 on Google Maps, chances are your profile isn’t fully optimized yet. Want to know what’s missing? Send me a message and I’ll take a quick look.
Sentiment-Driven E-commerce Optimization: Amazon Review Analysis & Rating Prediction.
Project Overview ✅
This project serves as a machine learning proof of concept designed to transform raw Amazon product reviews into actionable business insights. By automating the prediction of review ratings and analyzing customer sentiment, the system enables brands to optimize product listings, proactively address customer pain points, and drive higher conversion rates.
Process ✅
I developed an end-to-end pipeline covering data acquisition, complex text processing, and model deployment. Automated Data Scraping, Integrated the Apify API to extract real-time customer feedback directly from Amazon product URLs. I configured the scraper to handle up to 100 reviews per run, capturing critical metadata including rating scores, review descriptions, and verified purchase status.
Data Refinement & Feature Engineering:
Cleaned a dataset of approximately 1,944 reviews by removing noise (punctuation/symbols) and stop words using NLTK. I implemented TF-IDF Vectorization to convert text into numerical features and applied SMOTE (Synthetic Minority Over-sampling Technique) to address class imbalance, ensuring the model could accurately predict rare negative reviews.
Model Benchmarking ✅
Developed and compared three distinct architectures to identify the most robust predictor:
Naive Bayes: High-speed probabilistic classification.
Support Vector Classifier (SVC): Optimized for high-dimensional text data.
Neural Network (MLPClassifier): To capture complex semantic patterns.
Web App Deployment: Built a dedicated Streamlit dashboard that allows non-technical stakeholders to input raw review text and receive instant rating predictions with confidence scores.
Technical Stack✅
Languages & Tools: Python, Apify Client.
ML & NLP Libraries: Scikit-learn (SVC, Naive Bayes, MLP), NLTK (Tokenization, Stopwords), Imbalanced-learn (SMOTE).
Deployment: Streamlit, Joblib (Model Serialization).
Visualization: Plotly, WordCloud, Matplotlib.
Key Results ✅
Achieved a peak accuracy of 95.27% using the Neural Network model, with the SVC model following closely at 94.46%.
Developed sentiment-based feedback loops within the app: high ratings (4-5 stars) trigger positive marketing recommendations, while low ratings (1-2 stars) alert teams to address product issues like battery life or build quality.
Enabled real-time competitive analysis by providing a user-friendly interface for cross-functional marketing and product development teams to audit customer sentiment at scale.
dashboardPythonmachinelearningMachine Learning EngineeringData AnalysisData VisualizationApifyStreamlit
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