Scrape JustDial for Local Business Leads in India (2026)

Q: Can I prospect multiple categories in one run?

Yes. Pass an array of categories in queries — for example ['Restaurants', 'Hotels', 'Caterers'] — and the actor scrapes each independently in the specified city. Each category contributes up to maxResultsPerQuery records to the merged dataset, which makes a single run sufficient for full-funnel hospitality prospecting in one city.

Q: How do I push leads directly to my CRM?

The dataset returns CRM-ready fields: business_name, address, phone, category, rating, listing_url. Map each row to your CRM's Company schema and POST. HubSpot, Salesforce, Pipedrive, and Zoho all accept this shape with minimal field mapping. Most teams use Apify's webhook integration to forward each completed run's dataset directly to a CRM ingestion endpoint.

Published April 27, 2026 · 1541 words · For growth

Thirdwatch's JustDial Scraper returns structured Indian SMB lead data from JustDial.com — India's largest local business directory with 30M+ listings across 1,000+ cities — at $0.002 per business. Returns business_name, address, phone, rating, review_count, timing, and website per record. Built for B2B sales teams, lead-generation agencies, and growth marketers who need machine-readable Indian SMB contact data without manual directory browsing.

Why scrape JustDial for India SMB lead generation

JustDial is the dominant local-business directory in India. According to JustDial's FY24 annual report, the platform serves over 175 million unique users a year and lists more than 30 million Indian businesses across 1,000+ cities. For a B2B sales team selling into Indian SMBs — whether the product is accounting software, payroll services, fintech, or business loans — JustDial is where the long tail of Indian business contact data actually lives, indexed by category and city.

The job-to-be-done is concrete. A SaaS sales team needs 5,000 verified Indian restaurants in Mumbai with public phone numbers, sorted by rating. A direct-mail vendor needs every chartered accountant in Bangalore with an address. A fintech distributor needs jewellery shops in Delhi with high review counts as a proxy for transaction volume. All of these reduce to the same shape: search a category in a city, return business records, push into a CRM. Manual JustDial browsing scales to maybe 30 leads per analyst-hour; the actor returns 1,000 in two minutes.

How does this compare to the alternatives?

Three options for getting Indian SMB lead data:

Approach	Cost per 1,000 leads	Reliability	Setup time	Maintenance
Manual JustDial browsing	Effectively unbounded analyst time	Low (transcription error)	Continuous	Doesn't scale
Indian B2B lead provider (Lead Generation India, Easyleads)	$200–$2,000 per 1K leads	Variable, often stale	Days to receive	Vendor lock-in, license restrictions
Thirdwatch JustDial Scraper	$2 ($0.002 × 1,000)	Production-tested, monopoly position on Apify	5 minutes	Thirdwatch tracks JustDial changes

Indian B2B lead providers re-package JustDial and similar sources, marked up 100-1000x. The JustDial Scraper actor page gives you the live structured data; the CRM mapping is downstream pandas. There is no other maintained JustDial scraper on the Apify Store.

How to scrape JustDial for local business leads in 4 steps

Step 1: How do I authenticate against Apify?

Sign in at apify.com (free tier, no credit card), open Settings → Integrations, and copy your personal API token. Every example below assumes the token is in APIFY_TOKEN:

export APIFY_TOKEN="apify_api_xxxxxxxxxxxxxxxx"

Step 2: How do I pull leads for a category in a specific city?

Pass categories in queries and the city in city. Set maxResultsPerQuery based on how deep you need coverage — JustDial supports up to 500 per category.

import os, requests, pandas as pd

ACTOR = "thirdwatch~justdial-business-scraper"
TOKEN = os.environ["APIFY_TOKEN"]

resp = requests.post(
    f"https://api.apify.com/v2/acts/{ACTOR}/run-sync-get-dataset-items",
    params={"token": TOKEN},
    json={
        "queries": ["Restaurants", "Hotels", "Caterers", "Bakeries"],
        "city": "Mumbai",
        "maxResultsPerQuery": 100,
    },
    timeout=900,
)
df = pd.DataFrame(resp.json())
print(f"{len(df)} listings across {df.category.nunique()} categories in {df.location.iloc[0]}")

Four hospitality categories × 100 results per category = up to 400 leads, completing in under three minutes and costing $0.80.

Step 3: How do I filter to high-quality leads?

Filter on rating, review count, and phone availability. Categories with high rating and review count are validated businesses; phone availability is the gate for outbound.

QUALIFIED = df[
    (df.phone.notna() & (df.phone != ""))
    & (pd.to_numeric(df.rating, errors="coerce") >= 3.5)
    & (pd.to_numeric(df.review_count, errors="coerce") >= 10)
].copy()

# Sort by combined trust signal
QUALIFIED["score"] = (
    pd.to_numeric(QUALIFIED.rating, errors="coerce")
    * pd.to_numeric(QUALIFIED.review_count, errors="coerce") ** 0.5
)
top = QUALIFIED.sort_values("score", ascending=False)
print(top[["business_name", "category", "address", "phone", "rating",
           "review_count", "website"]].head(25))

Sqrt-weighting review count balances "high rating, many reviews" (the genuine quality signal) against pure rating from a thin review base. A 5.0 with 3 reviews shouldn't outrank a 4.5 with 200.

Step 4: How do I push leads to a CRM at scale?

Map each row to your CRM's Company schema and POST. HubSpot example:

import requests as r
HUBSPOT_TOKEN = os.environ["HUBSPOT_TOKEN"]

for _, row in QUALIFIED.head(200).iterrows():
    r.post(
        "https://api.hubspot.com/crm/v3/objects/companies",
        headers={"Authorization": f"Bearer {HUBSPOT_TOKEN}"},
        json={"properties": {
            "name": row["business_name"],
            "city": row["location"].split(",")[0].strip() if row["location"] else "",
            "phone": row["phone"],
            "website": row["website"] or "",
            "industry": row["category"],
            "description": f"Rating: {row['rating']}, {row['review_count']} reviews",
            "lifecyclestage": "lead",
            "source": "JustDial",
        }},
        timeout=10,
    )

A 200-lead Mumbai-restaurants prospecting batch pushed to HubSpot in under five minutes — the entire workflow from raw scrape to qualified-and-loaded leads.

Sample output

A single record from the dataset for one Mumbai restaurant looks like this. Five rows of this shape weigh ~3 KB.

{
  "business_name": "Hotel Taj Palace",
  "category": "Restaurants",
  "location": "Mumbai, India",
  "address": "123 Marine Drive, Mumbai 400001",
  "phone": "+91-2212345678",
  "rating": 4.2,
  "review_count": 150,
  "timing": "11:00 AM - 11:00 PM",
  "website": "https://hoteltaj.com",
  "photos_count": 12,
  "listing_url": "https://www.justdial.com/Mumbai/Hotel-Taj-Palace/..."
}

phone is the action field — what your sales team or auto-dialer needs. rating and review_count are the trust filters. timing is the underrated field that lets you schedule outbound calls during business hours rather than spam the line at 7 AM. website populates for roughly 40% of listings — many Indian SMBs run their entire operation through JustDial without a separate website, which is itself a signal about the business's digital maturity and may guide your sales pitch.

Common pitfalls

Three things go wrong in JustDial-based prospecting pipelines. Phone-number stripping — JustDial occasionally returns phone in display formats with spaces or dashes; always normalise to a single digit string before passing to a dialer or SMS API. Category-level overlap — a "Restaurants" search and a "Caterers" search often return the same business twice (caterers list as restaurants too); dedupe on a normalised business_name + city before pushing to CRM. Rate limiting on aggressive runs — JustDial throttles repeat traffic from the same IP, so pulling more than 5,000 records in a tight burst from a single residential IP can trigger blocks. The default Indian residential proxy rotation handles most workloads; for very large pulls, split across multiple runs with cool-down gaps.

Thirdwatch's actor uses an Indian residential proxy rotation by default and conservative concurrency, so it stays well within polite-crawling norms for most lead-generation workloads. The pure-HTTP architecture means a 1,000-lead Mumbai pull completes in under five minutes and costs $2 — small enough to run without budget approval. A fourth subtle issue is that JustDial occasionally rotates a single business across multiple "category" pages (a hotel that also serves food shows up under both "Hotels" and "Restaurants"); when prospecting hospitality verticals it's worth grouping by business_name + first half of address to find these multi-category listings and decide whether to treat them as one lead or two.

Related use cases

Frequently asked questions

How much does it cost to scrape JustDial business leads?

Thirdwatch's JustDial Scraper charges $0.002 per business listing on the FREE tier and drops to $0.001 at GOLD volume. A 10-category lead-generation sweep across Mumbai at 100 results each — typical for B2B prospecting in a single city — costs $2 per refresh, small enough to run weekly without budget overhead.

Which Indian cities does JustDial cover?

JustDial publishes business listings across 1,000+ Indian cities including all major metros (Mumbai, Delhi, Bangalore, Chennai, Hyderabad, Pune, Kolkata, Ahmedabad), tier-2 cities (Indore, Surat, Coimbatore, Lucknow, Jaipur), and a long tail of smaller cities. The actor accepts any city name JustDial recognises in the city input.

Are phone numbers reliable for outbound sales?

Yes — JustDial publishes verified business phone numbers. Most listings expose a direct phone in the publicly visible data, although some businesses choose to hide it. The actor returns whatever JustDial publishes; expect 70-90% phone fill-rate per category. For categories where contact rate is critical (plumbers, lawyers), expect higher fill.

How does JustDial differ from Google Maps for India SMB data?

JustDial has materially deeper coverage of Indian small businesses — plumbers, electricians, tutors, local restaurants, chartered accountants — because Indian SMBs actively register on JustDial for visibility. Google Maps coverage is broader but shallower for Indian SMBs. For India-specific local services prospecting, JustDial wins; for global location data with GPS coordinates, Google Maps wins.

Can I prospect multiple categories in one run?

Yes. Pass an array of categories in queries — for example ["Restaurants", "Hotels", "Caterers"] — and the actor scrapes each independently in the specified city. Each category contributes up to maxResultsPerQuery records to the merged dataset, which makes a single run sufficient for full-funnel hospitality prospecting in one city.

How do I push leads directly to my CRM?

The dataset returns CRM-ready fields: business_name, address, phone, category, rating, listing_url. Map each row to your CRM's Company schema and POST. HubSpot, Salesforce, Pipedrive, and Zoho all accept this shape with minimal field mapping. Most teams use Apify's webhook integration to forward each completed run's dataset directly to a CRM ingestion endpoint.

Run the JustDial Scraper on Apify Store — pay-per-business, free to try, no credit card to test.