Big data is a term used to describe large amounts of data that can be analyzed to reveal patterns, trends, and associations, especially relating to human behavior and interactions. In the world of digital marketing, big data is an invaluable resource that allows companies to better understand their customers, target their marketing efforts more effectively, and improve their return on investment.
One company that has leveraged big data to great effect is AdBoost, a digital marketing firm that specializes in Google Ads campaigns. According to their website, AdBoost was able to increase conversions by 32% in just 15 days by collecting and analyzing data from over 10,000 Google Ad accounts.
But how did AdBoost achieve such impressive results? To understand this, it’s important to first understand what a conversion is in the context of a Google Ads campaign. A conversion is a specific action that a user takes on a website, such as making a purchase, filling out a form, or signing up for a newsletter. In order to measure the success of a Google Ads campaign, businesses track the number of conversions that occur as a result of the ads they are running.
AdBoost was able to increase conversions by 32% in just 15 days by collecting and analyzing data from over 10,000 Google Ad accounts.
To achieve this increase in conversions, AdBoost first had to collect data from a large number of Google Ad accounts. This required a significant amount of time and resources, as the data had to be collected, cleaned, and analyzed. However, the payoff was well worth it, as the data provided AdBoost with a wealth of insights into how users were interacting with their ads.
Once the data was collected, AdBoost used a variety of techniques to analyze it and identify trends and patterns. This included machine learning algorithms, which are able to automatically identify patterns in data and make predictions based on those patterns. By using machine learning, AdBoost was able to identify which factors were most likely to lead to conversions and then optimize their ads accordingly.
In addition to machine learning, AdBoost also used other techniques, such as A/B testing, to further optimize their ads. A/B testing involves running two different versions of an ad and comparing their performance to determine which version is more effective. By running multiple A/B tests, AdBoost was able to identify the most effective elements of their ads and incorporate them into their campaigns.
The results of AdBoost’s efforts were impressive, with the company achieving a 32% increase in conversions in just 15 days. This demonstrates the power of big data in the world of digital marketing, as well as the importance of collecting and analyzing data in order to optimize campaigns and achieve better results. By leveraging the insights provided by big data, AdBoost was able to significantly improve the performance of their Google Ads campaigns and drive more conversions for their clients.
