Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [continent] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [location] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [postal] => Array
                (
                    [code] => 43215
                )

            [registered_country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [subdivisions] => Array
                (
                    [0] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.213
                    [prefix_len] => 22
                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [locales:protected] => Array
        (
            [0] => en
        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.213
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

Introduction

India’s employment landscape has undergone rapid transformation over the last decade, driven by digitization, sectoral expansion, and evolving workforce expectations. Organizations today require reliable, data-backed salary intelligence to remain competitive in hiring, retention, and workforce planning. This Job Roles Salary Benchmarking Report presents a comprehensive view of compensation trends across India’s top 100 job roles using large-scale web scraping methodologies. By aggregating data from multiple online job portals, company career pages, and public listings, the report eliminates data silos and outdated assumptions. The analysis captures historical and real-time salary movements across industries, experience levels, and cities, offering decision-makers actionable insights. From HR leaders and recruiters to investors and policy analysts, this report enables informed decisions by translating raw employment data into structured, scalable salary intelligence aligned with market realities.

Mapping India’s Evolving Compensation Landscape

Between 2020 and 2026, salary structures in India have reflected economic shifts, remote work adoption, and demand for digital skills. Web-scraped data shows that technology, analytics, and product roles experienced salary growth of 18–32% post-2021, while traditional operational roles saw moderate increases of 6–10%. Using Salary Data Insights from Job Portals Scraping, Actowiz Solutions analyzed millions of listings to track salary normalization across metros and Tier-2 cities.

Key observations include:
  • Average IT salaries grew faster in Bengaluru and Hyderabad than Mumbai post-2022
  • Finance and compliance roles showed steady but conservative increments
  • Entry-level salaries stabilized after pandemic volatility
Sample Trend Table (2020–2026):
Role Category 2020 Avg (₹ LPA) 2023 Avg (₹ LPA) 2026 Projected (₹ LPA)
Software Dev 6.2 8.9 11.4
Data Analyst 5.8 9.1 12.2
Sales Mgmt 7.0 8.4 10.1

This section highlights how dynamic salary intelligence supports proactive workforce strategies.

Large-Scale Data Collection Across Job Platforms

Modern salary benchmarking depends on automation and scale. Through Web Scraping Salary Data for Indian Jobs, Actowiz Solutions continuously collects compensation data from leading job portals, company listings, and recruitment platforms. This approach enables near real-time updates while eliminating survey bias and manual errors.

Key advantages observed between 2020 and 2026 include:

  • 4x faster salary trend detection compared to traditional surveys
  • Higher accuracy due to cross-source validation
  • Continuous tracking of emerging job roles
Illustrative Coverage Metrics:
Metric 2020 2023 2026
Job Roles Covered 45 78 100+
Monthly Listings Scraped 0.5M 1.8M 3.2M
Cities Covered 12 28 45

This data-driven foundation ensures salary insights remain relevant as hiring demand evolves.

Structuring the National Salary Intelligence Dataset

Raw salary data holds limited value unless structured and standardized. Actowiz Solutions developed the India Employment Salary benchmark Dataset by cleansing, normalizing, and categorizing scraped compensation data. This process aligns salaries by role, experience, industry, and geography, enabling apples-to-apples comparisons.

Between 2020 and 2026, normalization helped uncover:

  • Salary compression in junior roles post-remote work adoption
  • Premium pay zones emerging in Tier-2 cities
  • Industry-specific pay gaps exceeding 22%
Dataset Attributes:
  • Role-level salary bands
  • City-wise compensation indexes
  • Experience-based salary progression curves

By transforming unstructured listings into enterprise-ready datasets, this section demonstrates how actionable intelligence is created at scale.

Role-Level Benchmarking and Pay Transparency

This section focuses on how the Job Roles Salary Benchmarking Report empowers organizations with clarity across compensation structures. Employers can compare salaries across peers, industries, and regions without relying on static reports.

Key findings from 2020–2026 include:

  • Product and engineering roles command 1.6x higher pay than operations roles
  • Senior leadership salary variance narrowed post-2023
  • Skill-based pay differentiation increased significantly
Example Benchmark Snapshot:
Role Min (₹ LPA) Median (₹ LPA) Max (₹ LPA)
Data Scientist 8.5 15.2 28.0
HR Manager 6.0 10.5 18.4
Supply Chain Lead 7.2 12.8 22.1

This level of transparency helps organizations design competitive yet sustainable compensation frameworks.

Tracking Salary Shifts Through Continuous Intelligence

Repeated analysis using Salary Data Insights from Job Portals Scraping revealed how quickly salary expectations shift due to skill shortages, economic cycles, and policy changes. Unlike annual surveys, continuous scraping captures live market signals.

Observed trends include:

  • Sharp salary spikes for cloud and AI roles (2021–2024)
  • Stabilization of remote-work premiums after 2023
  • Gradual correction in inflated startup salaries
Trend Highlights:
  • 27% salary volatility reduction after 2022
  • Faster alignment between demand and compensation
  • Improved forecasting accuracy for HR planners

This section highlights the strategic value of always-on salary intelligence for enterprises.

Real-Time Market Alignment for Hiring Decisions

Using Web Scraping Salary Data for Indian Jobs, organizations can respond instantly to market changes rather than reacting months later. This capability supports proactive budgeting, offer optimization, and retention planning.

From 2020 to 2026, companies leveraging real-time data achieved:

  • Faster hiring cycles
  • Reduced offer rejections
  • Improved employer branding
Performance Comparison:
Metric Traditional Survey Real-Time Scraping
Data Refresh Cycle Annual Daily
Market Accuracy Medium High
Decision Speed Slow Fast

This reinforces the importance of automation-driven salary intelligence in modern HR ecosystems.

Why Choose Actowiz Solutions?

Actowiz Solutions stands out by delivering enterprise-grade workforce intelligence powered by the India Employment Salary benchmark Dataset. Our advanced scraping infrastructure, scalable pipelines, and data governance frameworks ensure accuracy, compliance, and reliability. We combine historical depth with real-time updates, enabling organizations to benchmark salaries confidently across roles, industries, and geographies. With customizable dashboards, API integrations, and analytical support, Actowiz Solutions transforms raw employment data into strategic insights that drive smarter hiring, compensation planning, and workforce optimization.

Conclusion

In a rapidly evolving employment market, static compensation reports are no longer sufficient. The Job Roles Salary Benchmarking Report enables organizations to stay aligned with real-world salary dynamics using automated, scalable intelligence. By leveraging web scraping, data normalization, and continuous monitoring, Actowiz Solutions empowers businesses to make confident, data-backed compensation decisions.

Partner with Actowiz Solutions today to unlock next-generation workforce insights through our Web Crawling service and Web Data Mining solutions.

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape Structure Analyze Visualize

Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.

Find Insights Use AI to connect data points and uncover market changes. Meanwhile.

Move Forward Predict demand, price shifts, and future opportunities across geographies.

Industry:

Coffee / Beverage / D2C

Result

2x Faster

Smarter product targeting

★★★★★

“Actowiz Solutions has been instrumental in optimizing our data scraping processes. Their services have provided us with valuable insights into our customer preferences, helping us stay ahead of the competition.”

Operations Manager, Beanly Coffee

✓ Competitive insights from multiple platforms

Industry:

Real Estate

Result

2x Faster

Real-time RERA insights for 20+ states

★★★★★

“Actowiz Solutions provided exceptional RERA Website Data Scraping Solution Service across PAN India, ensuring we received accurate and up-to-date real estate data for our analysis.”

Data Analyst, Aditya Birla Group

✓ Boosted data acquisition speed by 3×

Industry:

Organic Grocery / FMCG

Result

Improved

competitive benchmarking

★★★★★

“With Actowiz Solutions' data scraping, we’ve gained a clear edge in tracking product availability and pricing across various platforms. Their service has been a key to improving our market intelligence.”

Product Manager, 24Mantra Organic

✓ Real-time SKU-level tracking

Industry:

Quick Commerce

Result

2x Faster

Inventory Decisions

★★★★★

“Actowiz Solutions has greatly helped us monitor product availability from top three Quick Commerce brands. Their real-time data and accurate insights have streamlined our inventory management and decision-making process. Highly recommended!”

Aarav Shah, Senior Data Analyst, Mensa Brands

✓ 28% product availability accuracy

✓ Reduced OOS by 34% in 3 weeks

Industry:

Quick Commerce

Result

3x Faster

improvement in operational efficiency

★★★★★

“Actowiz Solutions' data scraping services have helped streamline our processes and improve our operational efficiency. Their expertise has provided us with actionable data to enhance our market positioning.”

Business Development Lead,Organic Tattva

✓ Weekly competitor pricing feeds

Industry:

Beverage / D2C

Result

Faster

Trend Detection

★★★★★

“The data scraping services offered by Actowiz Solutions have been crucial in refining our strategies. They have significantly improved our ability to analyze and respond to market trends quickly.”

Marketing Director, Sleepyowl Coffee

Boosted marketing responsiveness

Industry:

Quick Commerce

Result

Enhanced

stock tracking across SKUs

★★★★★

“Actowiz Solutions provided accurate Product Availability and Ranking Data Collection from 3 Quick Commerce Applications, improving our product visibility and stock management.”

Growth Analyst, TheBakersDozen.in

✓ Improved rank visibility of top products

Trusted by Industry Leaders Worldwide

Real results from real businesses using Actowiz Solutions

★★★★★
'Great value for the money. The expertise you get vs. what you pay makes this a no brainer"
Thomas Gallao
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
Product Image
2 min
★★★★★
“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”
Thomas Gallao
Iulen Ibanez
CEO / Datacy.es
Product Image
1 min
★★★★★
“Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing highly recommended!”
Thomas Gallao
Febbin Chacko
-Fin, Small Business Owner
Product Image
1 min

See Actowiz in Action – Real-Time Scraping Dashboard + Success Insights

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

Price Drop + 12 min
in 6 hrs across Lel.6

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & planning

Monitor Prices, Availability & Trends -Live Across Regions

Actowiz's real-time scraping dashboard helps you monitor stock levels, delivery times, and price drops across Blinkit, Amazon: Zepto & more.

✔ Scraped Data: Price Insights Top-selling SKUs

Our Data Drives Impact - Real Client Stories

Blinkit | India (Retail Partner)

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

US Electronics Seller (Amazon - Walmart)

With hourly price monitoring, we aligned promotions with competitors, drove 17%

✔ Scraped Data, SKU availability, delivery time

Zepto Q Commerce Brand

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

Actowiz Insights Hub

Actionable Blogs, Real Case Studies, and Visual Data Stories -All in One Place

All
Blog
Case Studies
Infographics
Report
thumb
Jan 07, 2026

Amazon India vs Flipkart vs Snapdeal Product Data Mapping – Comparing Prices, Seller Networks, and SKU Match Rates

Amazon India vs Flipkart vs Snapdeal Product Data Mapping helps compare pricing, seller networks, and SKU match rates to uncover marketplace trends and drive smarter ecommerce decisions.

thumb

Real-Time Rental Intelligence in London’s Prime Property Market How Actowiz Solutions Empowered a Real Estate Fund with Granular Market Data

See how Actowiz Solutions helped a London property fund track 10,000+ rental shifts daily using AI-driven web scraping for real-time market intelligence.

thumb

Driving Smarter Marketplace Decisions with Seller Competition & Pricing Intelligence on Amazon India and Snapdeal

Seller Competition & Pricing Intelligence on Amazon India and Snapdeal helps brands optimize pricing, track rivals, and make smarter marketplace decisions.

thumb
Jan 07, 2026

Amazon India vs Flipkart vs Snapdeal Product Data Mapping – Comparing Prices, Seller Networks, and SKU Match Rates

Amazon India vs Flipkart vs Snapdeal Product Data Mapping helps compare pricing, seller networks, and SKU match rates to uncover marketplace trends and drive smarter ecommerce decisions.

thumb
Jan 07, 2026

How Web Scraping Grab Taxi Data Helps Brands Decode Real-Time Ride Prices, Routes & Demand Trends?

Learn how web scraping Grab Taxi data reveals real-time ride prices, popular routes, and demand trends to help brands make smarter mobility decisions.

thumb
Jan 06, 2026

How Daily Liquor Pricing & Availability Monitoring Fixes Inventory Blind Spots for Modern Beverage Brands?

Daily Liquor Pricing & Availability Monitoring helps brands track stock levels, spot price changes, and reduce revenue loss across competitive retail markets.

thumb

Real-Time Rental Intelligence in London’s Prime Property Market How Actowiz Solutions Empowered a Real Estate Fund with Granular Market Data

See how Actowiz Solutions helped a London property fund track 10,000+ rental shifts daily using AI-driven web scraping for real-time market intelligence.

thumb

Powering India's Quick Commerce Revolution with 1 Million SKUs Daily Real-time Data Intelligence for Hyperlocal Delivery by Actowiz Solutions

Actowiz Solutions powers India’s quick commerce revolution with real-time data intelligence, tracking 1 million SKUs daily for hyperlocal delivery success.

thumb

Navigating the Luxury Watch Gray Market in France Precision Price Tracking and Market Intelligence by Actowiz Solutions

Explore the luxury watch gray market in France with precision price tracking and market intelligence powered by Actowiz Solutions for smarter decisions.

thumb

Driving Smarter Marketplace Decisions with Seller Competition & Pricing Intelligence on Amazon India and Snapdeal

Seller Competition & Pricing Intelligence on Amazon India and Snapdeal helps brands optimize pricing, track rivals, and make smarter marketplace decisions.

thumb

Scraping Top-Selling GrabMart Products - Top Categories & SKUs Across Singapore, Malaysia & Thailand

Detailed research on GrabMart’s top-selling products, highlighting leading categories and SKUs across Singapore, Malaysia, and Thailand for market insights

thumb

City-Wise Demand & Delivery Time Analysis for NIC Ice Cream - Solving Last-Mile Challenges in Quick Commerce

City-Wise Demand & Delivery Time Analysis for NIC Ice Cream reveals how data improves stock planning, delivery speed, and customer satisfaction across markets.

phone
Quick Connect
phone
Quick Connect