Big data analytics in ad tech: Discover the opportunities & talking points
As Big data continues to impact diverse sectors, it’s impossible to think about advertising technologies without appreciating the role of big data analytics.
With the growth in the advertising market expected to soar above $700 billion, there is no doubt that data is becoming the new gold mine of the twenty‑first century, especially in this industry.
The AdTech industry is fast‑paced, and we’re seeing big companies like Facebook and Google continuously needing to respond with data insights that enable advertisers to reach their target audience more effectively.
What is big data analytics?
Big data analytics involves the use of advanced techniques and analytics tools to process different types of data that are in structured, unstructured, or semi‑structured formats to collect valuable information useful for various purposes.
With big data, we can discover unique patterns that inform decision‑making, predictions, and innovative ideas to improve advertising efficiency.
But what role will big data analytics play in the future of advertising?
Before we explain the potential impacts of big data in the ad tech industry, let us delve a little into its history.
We are constantly generating data by using applications, searching Google, booking a service, buying a product, or doing anything online that leaves data footprints.
The term “big data” has been in existence since the early 1990s. Although it was not entirely new then, the dawn of the digital age and the need to store the growing amount of data in hybrid systems necessitated its use.
The last two decades have seen an explosion in data generation. To put that into perspective, the total amount of world data was 4.4 zettabytes in 2013, compared to 44 zettabytes by 2020. This means we need to integrate analytics solutions to help process the growing volume of unstructured data in our world today.
Opportunities for advertisers in big data
Advertising is becoming increasingly crucial for business growth and AdTech companies are at the forefront of helping businesses reach their audiences.
Using big data analytics, the advertising industry can become more effective at getting better results from ad campaigns and impacting the bottom line.
With AI changing traditional advertising approaches with accurate predictions and insights into audience needs, big data continues to fuel this impact.
Today, advertisers can leverage the results received through big data analytics to determine audience behavior and measure their response to ads.
Additionally, because these insights inform effective decision‑making in advertising, the value it provides is even more beneficial to the ad tech industry.
Cutting‑edge advertising is just the tip of the iceberg of what big data analytics can do for the advertising industry.
It’s also become critical for businesses looking to leverage cloud computing to eliminate the need for ad management services by using ad platforms as a service (PAAS) to achieve great advertising results.
Can analytical tech help AdTechs make the best use of big data?
Big data unlocks predictive intelligence and insights that empower advertising platforms to deliver their services.
But this data comes in many forms, requiring the processing made possible through analytics. With big data analytics, AdTech platforms can present advertisers with key indicators and valuable information that influence the success of their advertising campaigns.
Here are a few cases where adtechs can leverage technology to deliver improved advertising results…
Actionable Insights
Who to target: The answer to the question “who to target” is one of the most important items in an advertiser’s arsenal.
Thanks to big data, ad tech platforms can provide the answers, and with analytics, ads can be carefully tailored to the right audience to improve performance.
Beyond this, having an idea of whom to target allows marketers and sellers to segment their target groups into locations, social demographics, and interests. And with this information, advertisers can create a unique value proposition that resonates with them.
For example, advertisers can personalize their ads by creating a unique value proposition for selling a product to women and men through the actionable insights provided by data analysis.
That may include ad images, messaging, and other factors that help sway the audience in the advertiser’s favor.
What ad to show: Developing an accurate customer profile depends on the precise use of big data.
Analytics technology helps combine data from different sources to provide insights into demographics, interests, and preferences.
Studies show that most marketers believe that personalized ads enable them to gain better results. It’s essential to leverage the insights that big data analytics provide to deliver targeted information to the different audience segments to improve engagement. For instance, advertising platforms like Facebook allow advertisers to show different ad image sizes and formats. You can add up to ten different creative and text options to optimize them for different target audiences.
When to target: Analytics provide important data insights on when it’s best to reach your target audience for a better conversion rate. With these insights, advertisers can learn what days of the week and times of day their potential target audience is active online. It also helps optimize ad spending and improve campaign performance because the ads reach customers when they are most likely to convert.
Predictive Intelligence
How to improve performance: Data analytics provide key indicators from previous ads that enable advertisers to improve performance. This massive chunk of data is largely unstructured and needs analytical technology to make it easier to understand and utilize for better advertising success.
How to measure results: By learning from the past outcomes and accurately measuring results, advertisers can gain the insights they need to plan, strategize, and invest more wisely.
Cost‑effectiveness is critical to any advertising campaign, and ad tech can leverage analytics to provide information that allows advertisers to evaluate their best options. With important metrics like ad interactions, impressions, devices with the most engagement and best‑performing ad creatives, advertisers can make strategic decisions that will impact their return on investment.
How AdTechs can take advantage of big data analytics
As the amount of data continues to rise, there is a greater need to store, analyze, and interpret this big data effectively.
Analytical solutions are essential for ad techs looking to make the best use of the data at their disposal. Investing in solutions designed to help advertisers maintain an edge in the market will be critical to the growth of the ad tech industry.
At DoubleCloud, we provide highly efficient big data analytics solutions that combine data from advertising platforms like Facebook, Google, LinkedIn, and others with internal data from ad techs to improve their advertising solutions.
We’ve pre‑built connectors with these big advertising platforms to manage this data so you can focus on big data analysis.
AdTech solutions that improve an advertisers' ability to analyze and keep track of data have become more important since the big data boom.
An AdTech industry driven by big data and efficient analytical technology will have all it needs to serve users.
When big data is carefully collected, aggregated, and analyzed, there are endless possibilities for what can be achieved.
To ensure your AdTech users always have their finger on the pulse and can scale their ad performance, you must implement an efficient big data analytics infrastructure that supports your platform’s solutions.
If you are looking to build an intelligent advertising or marketing solution that utilizes the power of big data, our team is ready to become your analytics partner.
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