How Big Data Analytics Is Solving Big Advertiser Problems
Big data can help make sense of the information gathered, such as retention cost, average transaction value and even customer satisfaction.
After several years of cautious enthusiasm, the marketing and advertising technology sector is now embracing big data in a big way. That's the good news. The obstacle is that most companies and brands still lack the expertise necessary to analyze huge amounts of data and make it actionable. According to a 2015 survey, most companies seek a specialized skillset that is normally not found in most a typical ad agency. In plain English, these companies are collecting data they don't yet know how to use. That's the bad news.
Not surprisingly, new companies that specialize in big data analytics have started to fill this void. For instance, SQream Technologies made a name for itself with rapid, petabyte-scale (that's a million gigabytes to you and me) big data analytics. For the marketing and advertising sector, this has meant more sophisticated analysis of things such as online activity, point-of-sale transactions and on-the-fly detection of dynamic changes in trends. But why is this so crucial?
Gaining insights into customer behavioral patterns plays a crucial role in creating focused and targeted campaigns. Big data can help make sense of the information gathered, such as retention cost, average transaction value and even customer satisfaction. After all, consumers who spend the most money are not necessarily the most valuable. There's some evidence that the big spenders may be "the most expensive to keep and are the least loyal over the long term."
What role does big data play in advertising?
Big data can be used to help create targeted and personalized campaigns that ultimately save money and increase efficiency by targeting the right people with the right product. How exactly? By gathering information and learning user behavior.
A consumer's digital footprint today is increasingly valuable in this personalized era of marketing and advertising. There is such a vast amount of information from every interaction one has, whether Googling or Facebook liking the new Samsung smartphone, both online actions will lead a consumer's social media and digital world to be flooded with ads about this phone.
How can big data be used for advertising?
With this information, companies can target users in existing online communities, and then use the data to better understand and identify patterns in user behavior. Advertising agencies are able to gather information about consumers' motivations: Are customers motivated by the latest tech trends? Is there a subgroup within your client base that are more reserved when it comes to spending?
These are the types of insights that can be gained from big data.
The secret lies in measuring impressions and learning user behavior. We already know that almost a quarter of video ads are viewed by bots and not humans. This means that for the biggest advertising companies in the world, a significant proportion of impressions aren't being shown to human beings. The implication is substantial as ad campaigns are not being exposed to the very audience which will be spending money. As a result, there is a growing and crucial demand to expose ad fraud and non-human impressions.
The solution to the huge ad fraud problem is predictive analytics big data platforms. This technology allows brands to define the type of consumers being targeted, thus enabling businesses to have the appropriate and most effective reach and impact.
Tel Aviv-based Optimove, for example, is a marketing automation platform that uses predictive analytics to prioritize a company's existing customers, rather than use their resources to acquire new ones. Through the company's predictive analytics platform, customers are presented with the best and most targeted deals and services tailored to them specifically, significantly raising the chance of conversion. With this type of information, marketers can create and target relevant customers at the relevant time.
Big data equals big ideas.
Traditional advertising once involved circulating ideas and pitches through various departments. Today, working with big data companies, advertisers can use these collaborations and partnerships to create original campaigns, and at a faster pace.
Advertising firm 360i, for example, did exactly that during the Super Bowl in 2013 with its Oreo campaign. After a blackout halted the game, within a matter of minutes the phrase, "Power out? No problem. You can still dunk in the dark," was circulating around major social media channels. The campaign garnered immediate media attention and increased Oreo's social media following.
Innovation in big data.
Another example comes from one of the world's most innovative companies, Netflix. The company advertises TV shows and movies based on what the customers have previously watched. By collecting data on metrics such as the genre of TV shows a user watches, the amount of time spent on a single show, preferences for particular actors for example, Netflix is able to use this information to accurately calculate how much a user is worth.
Despite this sense that a lot of businesses are sitting on data but lack the infrastructure or the capabilities to understand and analyze, need will continue to drive better analytics and new technology.
Using the power of data analytics, advertisers can identify emerging trends and provide real-time live ad options. Since the key component of advertising is reaching the right audience at the right time, big data will help predict purchases, identify and analyze consumer behavior and the type of performance that certain segments of your audiences will perform against.
The emergence of new technologies will also permit companies the leisure of using data in a smarter, safer way. In other words, companies can now actually mine their data to improve both the bottom line and customer service, instead of just sitting on a undeveloped gold deposit.
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