Marketing And Manufacturing Big DataTrends In 2020

Marketing And Manufacturing Big DataTrends In 2020

In November 2005, Google launched Google Analytics, perhaps the most well-known use of big data and the most widely used web analytics service. Conservative estimates put the number of worldwide users at 30 – 50 million.

Free insight

Google Analytics provides marketers insight into their websites, and the activities on it, user behavior, the buying funnel, how customers found their website, visitor demographics, and much more.

Google provides the analytics platform as a free tool to everyone—business owners, marketers, sales teams—anyone looking to gain insights into how their website is used by its visitors. It is a key tool in understanding how to improve customers’ experiences.

API integrations

Third-party developers access Google Analytics through the use of APIs and have created other marketing technologies to process, distill, and display this data within their own tools that may provide more meaningful insight for different types of users.

Large organizations such as YouTube, Twitter, GitHub, and Stack Overflow and smaller companies such as SEMrush, Funnelytics, and Hubspot access Google Analytics’ data through APIs. In many cases, this data is combined with in-house collected or generated data such as CRMs and activity.

In some cases, the data from Google is augmented with data from other sources, also through APIs or through a process known as web scraping.

Extraction vs. integration

Web data scrapers or extractors collect data from other websites but the receiving business is responsible for developing internal processes to cleanse, distill, and integrate the data into existing workflows.

In a similar, but a more extensive process, web data integration goes beyond data collection and uses APIs to fully integrate the collected data with in-house data or other third-party data. This process usually includes ongoing data additions, changes, and deletions, as well as maintenance of the data on a regular basis.

Data integration and marketers

Savvy digital marketers research competitors’ sites and marketing strategies, especially those that appear to be successful in order to pivot their own strategies. Learning about their competitors is made easier with tools such as SEMrush.

A SaaS (software as a service), SEMrush is an analytics tool that increases marketers’ visibility into their own and their competitors’ websites, advertising, backlink, search engine optimization, and marketing strategies. Unlike Google Analytics, the reports are generated using the alternative data of several websites, Facebook, Twitter, LinkedIn, and yes, Google Analytics.

SEMrush configures and reorganizes subsets of this data along with their own data in a way that is for many, a simpler-to-understand format than Google Analytics—especially for marketing intelligence.

Web data extraction

Web data extraction and web data integration make possible complicated tools such as SEMrush. Still, companies of any size can use these processes to provide data not practical to collect with in-house resources. The web is the world’s largest database, and the intelligence within it represents an unparalleled opportunity for any company to better understand its business by extracting data from other sites.

Using web data integration tools and services, organizations can identify, extract, prepare, integrate, and consume web data from any website. Moreover, these automated processes are far faster and more accurate than a person tasked with copy/paste. Programmed routines will extract, cleanse, and merge alternative data with in-house data ensuring accuracy—important for all but critical to financial organizations.

Product catalogs and extracting data

For product catalogs with thousands or millions of items and variations, scraping data isn’t enough. This is where web data integration services are required in order to automatically and routinely extract data matching competitors’ merchandise across categories, brands, prices, and other parameters defined by the business.

Machine learning minimizes incorrect matches as the web data integration processes automatically and routinely update data to reflect ongoing changes to products, including images.

Data integration for manufacturers

Manufacturers that need to monitor channels also benefit through insight into supply chain inventory, product performance, and whether their distributors and resellers are adhering to requirements, such as minimum advertised pricing agreements.

Web data extraction and web data integration services enable businesses to augment internal data with that of any website—or any number of websites—in order to create more massive datasets that provide business intelligence and enable stakeholders to make better decisions.

Syed Ali Hyder

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