In the fast-paced world of online food delivery, understanding customer sentiment and feedback has become vital for business growth. With millions of users posting opinions on food quality, delivery speed, hygiene, and customer service, platforms like Zomato and Swiggy are rich sources of actionable insights. Through Zomato and Swiggy review scraping, brands can monitor reviews in real time and derive powerful insights that shape reputation, customer engagement, and market share.
This process forms the backbone of Brand Intelligence Services, enabling companies to stay ahead in a highly competitive ecosystem. From identifying common complaints to spotting positive sentiment around specific dishes or restaurants, review scraping for brand intelligence helps decision-makers refine their offerings.
In this blog, we’ll explore how businesses can extract, analyze, and apply review data using Swiggy review data and Zomato customer reviews, ultimately leading to smarter and more responsive brand strategies.
Customer reviews influence decisions. Whether it’s a new restaurant or a major QSR chain, consumers often rely on peer feedback before placing an order. With over 1 million reviews posted monthly across both Zomato and Swiggy, scraping this data helps build a dynamic feedback system.
Between 2020 and 2025, the online food delivery market in India is expected to grow at a CAGR of 12%, reaching over $25 billion in GMV. In this landscape, Zomato and Swiggy review scraping is more than just a data collection tactic—it’s a competitive intelligence weapon.
| Year | Zomato Reviews | Swiggy Reviews | Total Growth |
|---|---|---|---|
| 2020 | 6.5M | 5.8M | - |
| 2021 | 7.1M | 6.5M | +10% |
| 2022 | 8.3M | 7.7M | +16% |
| 2023 | 9.8M | 8.9M | +18% |
| 2024 | 11.2M | 10.5M | +14% |
The increase in user engagement highlights the importance of Customer Review Scraping for detecting brand risks early, understanding new taste trends, and managing PR crises effectively. Through review scraping for brand intelligence, brands can detect whether customers are dissatisfied with packaging, portion size, or delivery timing and take real-time corrective actions.
Scraping restaurant reviews from Zomato and Swiggy gives you more than just ratings—it uncovers detailed text feedback, emotional tone, and emerging consumer concerns. This qualitative insight is the foundation of competitor benchmarking.
For example, a pizza chain using Zomato and Swiggy review scraping found that competitors in the same region were consistently praised for quicker delivery and cleaner packaging. These review sentiments prompted operational changes that improved NPS by 18% in three months.
| Complaint Type | Swiggy % | Zomato % |
|---|---|---|
| Late Delivery | 32% | 27% |
| Food Temperature | 21% | 24% |
| Incorrect Orders | 19% | 22% |
| Packaging Issues | 15% | 13% |
| Rude Behavior | 13% | 14% |
By extracting feedback from your own listings and from competitors, you can deploy Swiggy vs Zomato Web Scraping Restaurant Reviews to compare sentiment trends and enhance brand experience. This type of intelligence is crucial for local outlets, cloud kitchens, and national franchises.
Understanding how customers feel about your brand is central to staying relevant. Review scraping for brand intelligence captures emotional indicators—positive, negative, and neutral—to visualize how public perception shifts over time.
This approach supports:
Using AI-driven text analytics, brands can transform raw Zomato customer reviews and Swiggy review data into actionable dashboards. For instance, a leading North Indian food chain detected a sharp increase in negative reviews tied to one packaging supplier—an insight that would be missed without consistent scraping.
| Quarter | Positive % | Negative % | Neutral % |
|---|---|---|---|
| Q1-2023 | 64% | 22% | 14% |
| Q2-2023 | 61% | 25% | 14% |
| Q3-2023 | 69% | 18% | 13% |
| Q4-2023 | 72% | 16% | 12% |
These insights help improve brand perception using review data and empower brands to personalize responses, optimize menus, and address delivery gaps proactively.
To extract reviews from Zomato and Swiggy, you'll need reliable scraping technologies that work around dynamic JavaScript and infinite scroll challenges. Using automation tools and proxies ensures high accuracy and uninterrupted data flow.
| Step | Tool/Method |
|---|---|
| Request Handling | Rotating Proxies |
| Data Parsing | XPath/Regex |
| Sentiment Engine | TextBlob/VADER NLP |
| Output Format | CSV / JSON / API |
These tools automate the process of Web Scraping Zomato Datasets and offer end-to-end customization for region, language, cuisine, or specific keywords.
For businesses with no coding background, Restaurant Data Scraping Services offered by Actowiz can handle everything from setup to delivery with minimal overhead.
The benefits of scraping food delivery reviews go far beyond ratings. They offer deep insight into customer preferences, recurring issues, menu favorites, and pricing expectations. It also helps with localized marketing.
| Keyword | Frequency | Sentiment Weight |
|---|---|---|
| "cold food" | 23,100 | -0.8 |
| "on time" | 35,900 | +0.7 |
| "bad packaging" | 12,000 | -0.6 |
| "tasty biryani" | 28,500 | +0.9 |
These insights are crucial for brand monitoring with review data, especially when launching new locations or scaling cloud kitchens.
When engaging in scraping restaurant reviews, it is essential to follow legal and ethical data practices. This includes respecting site terms of use, ensuring no private user data is collected, and throttling requests to avoid platform disruption.
| Practice | Status |
|---|---|
| Follows Robots.txt | Yes |
| Avoids Rate Overload | Yes |
| No PII Scraping | Yes |
| Source Attribution | When needed |
Following ethical practices ensures your Customer Review Scraping operations remain sustainable, trustworthy, and legally sound. It strengthens brand intelligence without risking integrity.
At Actowiz Solutions, we offer enterprise-grade tools for Zomato and Swiggy review scraping that are fast, reliable, and compliant. Our custom dashboards and APIs are designed to streamline review scraping for brand intelligence across multiple geographies and languages.
Whether you're launching in a new city or tracking performance across hundreds of outlets, we deliver:
Our experts can help you extract reviews from Zomato and Swiggy, integrate them with your BI tools, and build predictive models for brand planning. With scalable systems and 24x7 support, Actowiz is the go-to partner for Restaurant Data Scraping Services and Brand Monitoring with Review Data.
In the digital age, customer opinions are your brand’s loudest voice. Platforms like Zomato and Swiggy offer unparalleled access to real-time sentiment—but only if you know how to tap into it.
With ethical, structured scraping methods and actionable analytics, you can turn reviews into results. From online food delivery sentiment analysis to operational improvements and brand defense, Zomato and Swiggy review scraping is essential for modern brand success.
Let Actowiz Solutions empower your business with powerful review scraping for brand intelligence and unlock new layers of customer understanding. Contact us today to start your journey toward smarter, data-driven branding! You can also reach us for all your mobile app scraping, data collection, web scraping , and instant data scraper service requirements!
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