Big Data Ads – Big data is being viewed as the next big challenge in marketing innovation. The digitization of the marketing and advertising industry leads to the accumulation of huge amounts of data that have to be processed and analyzed.

Businesses can leverage Big Data by making real-time, end-to-end, data-driven decisions that enable them to streamline processes and improve the ability to customize and personalize services.

Custom advertising software development offers effective solutions that are less expensive and more visible to the target audience.

Big Data Means Big Opportunities

Big Data Ads The Experience In The Design & Development

The ability to collect and analyze data from both internal and external sources is critical to successful digital advertising. The problem arises because 80% of data is unstructured.

Photos, videos and social media posts are pieces of information that say a lot about us but cannot be processed using traditional methods. Big data allows companies to analyze all the data collected and gain valuable insights.

Hyperlocal Advertising

The proliferation of mobile devices presents great opportunities for digital marketers and advertisers to offer mobile ads that target the right customers. For example, stores can send out advertisements promising discounts or other benefits to nearby customers and encourage them to walk through their doors.

Hyperlocal advertising has been shown to increase customer retention and conversion rates.

However, there is a risk of irritation as some consumers may be intimidated by the fact that advertisers know where they are in real-time. Consequently, marketers must make certain trade-offs in order to keep their ads profitable and minimize complaints.

Audience Predictions

Big data analytics is gradually becoming the first choice of many media organizations around the world. It creates an ecosystem that captures the attention of consumers.

Big data helps deliver the right content to the right people, on the right platform, at the right time.

With consumers now able to choose formats such as on-demand, pay-per-view, streaming media, subscription-based and more, content can now be distributed across a variety of digital channels, allowing media companies to easily collect, process and process it, and analyze user data effectively .

The amount of data collected daily provides ample opportunity for analysis to find out what content users want. Data collected from social media often shows underestimated patterns that can pique user interest.

Big Data and Branding

The purpose of branding campaigns is to build reputation or brand awareness. Historically, this was the domain of television advertising.

Online advertising therefore uses TV advertising indicators such as net reach and gross rating points. The effectiveness of a branding campaign is measured by maximum exposure to a specific audience.

In some cases, social and demographic factors determine which segments are important. Big data is used to accurately predict these characteristics for as many online users as possible.

Provided the data is correct, the advertiser can drastically reduce their costs. Advertising only reaches interested users, which leads to a significant cost reduction. Facebook is a prime example of this form of data usage.

Facebook has access to well-verified age and gender data and massive reach across multiple devices thanks to its users’ login credentials. The basic data is ideal for delivering targeted ads to the right people.

Using Big Data to Optimize Ads

The main goal of personalization is to target a campaign to a specific audience, using the information you have about their interests and preferences. Then big data becomes an extremely valuable source of reference information.

A key benefit of using big data in advertising is improved communication. With improved data accuracy, advertising becomes more relevant and cost-effective.

Name, email address, gender, age, location, payment history and search queries are just a small part of what is stored in the database.

Big data allows you to analyze, organize and organize information to further use the results to create eye-catching advertising algorithms and create appropriate personalized advertising content. As a result, each user receives a personalized message based on their selection, previously visited websites, related search queries, etc.

Since advertising is an integral part of the media industry, it has historically been done purely on the basis of speculation. Nowadays, with the help of big data solutions, advertising companies can better understand consumer habits and get a more detailed understanding of their behavior.

Big data solutions not only predict what customers want to hear from ads, but also predict the performance of high-load systems, making them an essential part of an outcome-based advertising system.

The Experience In Design and Development Of Advertising Systems

Switching to a system that runs under heavy load, handles thousands of requests per second and makes optimal use of big data will definitely increase the reach of your advertising campaign.

The solutions developed by SCAND include a highly loaded advertising system. A client came to our company with the goal of creating a system capable of handling hundreds of millions of user requests per day.

The solution is pretty simple and elegant to get the job done and scalable enough for future challenges. The customer currently has the idea of more frequent use of big data in mind, so this possibility had to be provided for in the design of the system.

SCAND engineers came up with the following scheme. The front-end cluster with SSL and load balancer is connected to the web server cluster. Next we should mention the DBMS in the cluster, but in our case the path to the data is a bit different.

First, the data appears in the Redis RAM cache. It is then passed to the stats parser before entering the database. When the database needs to return data, it passes it through the prefetcher before it reaches Redis, the web server, and finally the frontend.

This scheme allows the customer to:

A high-load solution that can remain operational with a large number of requests.
The data goes through a statistical analyzer that helps gather important advertising statistics.
The solution easily handles the collection and analysis of big data.

The latter option is implemented using Hadoop, which adds a new layer of analysis to views and click measurements in the system tree. In this way, the entire advertising system can be easily transferred to Big Data in a short time.

High Load Testing

The solution has been tested in the field. With an average system load of millions of requests per hour, it works stably and does not even reach the peak load.

Since the client has tens of millions of unique users per month, a true data set requires hundreds of gigabytes of RAM, even in cache, to count user actions.

That’s the job of the real Big Data that we have. The corresponding algorithms are already being developed and can be implemented in the shortest possible time.

Conclusion

Big data ads development services for marketing and advertising have become a real trend in recent years. Accurate targeting is hard to imagine without robust algorithms using large streams of data.

While the fundamentals of advertising remain the same, existing advertising system concepts, products, and services must connect sellers with potential buyers in an entirely new and data-driven way.

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