Clicky

Targeted Data Crawling for Digital Ad Marketing | Bigdata | PromptCloud
 

How big data is revolutionizing traditional ad targeting

How big data is revolutionizing traditional ad targeting

Precision ad delivery is all about getting the right message in front of the right person at the right time, even better when they’re not expecting to see your message. For example, let’s say you just visited your favorite sports team’s page on ESPN.com and moved on to surfing other websites. All of a sudden you notice that most of the banners on these sites are showing ads related to your favorite team. This seemingly mysterious phenomenon is called behavioural targeting, which is the past decade’s most disruptive innovation in the digital advertising space.

Targeting-Big-data

Targeting Big data

Targeted ads have now become the norm in the digital advertising industry, as the advertisers who were earlier hooked on to the demographic details such as age, income, sex and location are now moving on to more precise and technologically advanced ways to promote themselves in a relevant way to their end users. While such targeting comes with its own set of challenges with regard to user privacy, it’s definitely something that’s here to stay – like it or not. The primary reason for this is that top-level executives (especially the CFOs) have always fixated on ROI – the Return On Investment for every other marketing activity, and such highly targeted and personalized advertising gives a higher ROI than the traditional forms of ad targeting.

“Ad targeting especially in the digital realm means taking messages, offers and ads which are extremely relevant to an individual and personalizing it. That’s a win-win situation for both – the advertisers & consumers.”Krishnan Parasuraman, CTO, Big Data & Digital at IBM

Data is always good to have while making a decision, though good data or bad data directly impacts the decision, and the subsequent outcomes. Marketers who are equipped with the ability to know as much there is to know about there customers will naturally make better decisions about targeting their interests.

(You can read more about how to use data for understanding your customers in this article by David Norton, published at SoftwareAdvice)

Advertisers buy consumer data, which is categorised in ‘clusters’ from data brokers such as Acxiom. Acxiom is also believed to have the largest database of consumers collected from sources such as public records, supermarket loyalty cards, mail order catalogs, magazine subscribers list etc.

Customer retention we love customers

Avoiding an Overkill

Instead of sending the same message to a large chunk of the target audience, targeted messages are more likely to lead to higher conversion rates. Advertisers must be cautious about ending up over-targeting a small set of audience by bombarding them with the same messages over and over again, leading to higher CPA’s and lower ROIs. If 100 million impressions are to be targeted towards 1 million people in a given month, theoretically it implies that every person is being exposed to the ad 100 times a month. Instead, if they are shown an ad 20 times a month (which should be enough for mostly all the segments), the same 1 million people can be targeted using just 20 million impressions. This leads to high levels of cost optimization, avoids redundancy, doesn’t end up being an overkill and also results in higher CTRs in most of the cases.

Is Demographics Dead?

So are the traditional demographics about consumers such as location, age, sex, income are not relevant any more? Yes, and no, because while working in silos any of these parameters are not as useful as when they’re combined with others, resulting in more knowledge about the consumer – and a higher potential match. Data brokers have huge datasets of consumer information which they’ve categorised into various segments, based on a combination of demographics, buying patterns, web surfing behavior etc. These clusters such as ‘Android preferrer’, ‘Versace preferrer’ or ‘BMW preferrer’ present a ready market for the advertisers. Adding related segments here is a good idea, as it’s not necessary that an ‘Apple preferrer’ will always be the ideal target for an iPhone. Including a ‘Louis Vuitton preferrer’ to the target set will expose a larger audience set, which was yet untapped.

Though the vendors would like you to believe that targeting works flawlessly, a lot of questions still remain unanswered. For instance, it happens a lot of times that the product you just bought is again being marketed to you through ads. The technology needs to evolve in order to show things that are relevant to you as a consumer and have the highest likelihood of serving your present needs.

Related Posts

No Comments

Post A Comment

Ready to discuss your requirements?

REQUEST A QUOTE
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.

Price Calculator

  • Total number of websites
  • number of records
  • including one time setup fee
  • from second month onwards
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.
  • This field is for validation purposes and should be left unchanged.