How to Smoothly Turn Advertising Systems to Big Data
The role of advertising is growing on a par with the technologies. Big data solutions do not only predict what customers want to hear from advertising but also involve the efficiency of high load systems thus becoming an essential component of a results-oriented advertising system.
Generally, Big Data is data that is too complex to be effectively controlled by standard database solutions currently found in most organizations.
Hence, those companies that will be able to efficiently connect Big Data and marketing will take over the leadership.
How can Big Data boost click-through rates?
Providing the flawless collaboration between all parts of the advertising system is arranged and smooth and stable transition of data is made, the solution chosen will contribute to a click-through rate (CTR), the indicator of a successful advertising campaign.
Targeting the campaign to a certain audience by leveraging the information you have on its interests and preferences is a bottom line of personalization.That’s when digital Big Data is an utterly valuable source of reference.
Name, e-mail, gender, age, location, history of payments, and search stories could be a tiny part of the digital traces available that are stored in a database. Big Data technologies allow analyzing, systematizing, and organizing the information to further use the results for creating prominent advertising algorithms and generating proper personalized advertising content. As a result, every single user gets a personalized message based on its choices, previously visited websites, related searches, etc.
What should be fixed is the establishment of reliable bandwidth from a front-end to a server and from a server to a database. Choosing the right tools will prevent advertising system malfunctions caused by the high load.
Our experience in advertising system design and development
Switching to a system that works under high load, processes thousands of requests per second, and uses Big Data to the maximum will definitely empower an advertising campaign. Among the solutions created by SCAND is a high load advertising system. The customer has come to our company with the aim of building the system that can handle hundreds of millions of user requests per day.
The solution is quite simple and elegant to cope with the task and scalable enough for the future challenges. Currently, the customer is keeping in mind the idea of using big data more often, so this opportunity should have been initially provided in the systems design.
SCAND engineers have come to the following scheme. The front-end cluster with the SSL and balancer is connected to the web servers cluster. Next, we should mention the RDBMS in cluster but in our case the path of data is slightly different.
Firstly, data appears in the Redis In-Memory Cache. Then, it is transmitted to the statistics analyzer before achieving the database. When the database should return data, it guides it through the prefetcher before reaching the Redis, the web server, and finally the front-end.
This scheme allows the customer to get the following benefits:
- The high load solution that is able to remain functional with a large number of queries.
- The data goes through the statistics analyzer that helps gather important advertising stats.
- The solution easily deals with the Big Data collection and analysis.
The last option is fulfilled with the help of Hadoop that adds a new level of analysis to the views and clicks measurements in the structure of the system. So, the whole advertising system can easily be switched to Big Data within a short period of time.
High load testing
The solution has come through field tests. With the average system load of millions of requests per hour, it works stable and doesn’t even reach the peak load.
As the customer has several millions of unique users per month, a real data set needs hundreds of gigabytes of RAM, even in cache, to count user activities.
This is the task for real Big Data we have. The related algorithms are already in development and can be implemented in the shortest term.
The major takeaway from the article is that the transition from the traditional advertising system to Big Data is not so challenging as one can imagine. However, this step requires some preparations at the architecture design and development stages.
The result’s worth it. Big Data for marketing has become the real trend in recent years. It’s hard to imagine accurate targeting without reliable algorithms using Big Data streams. While the fundamentals of advertising remain unchanged, the present concepts, products, and services of the advertising systems should connect sellers with potential buyers in the brand new and data-oriented way.