Understand where your data comes from - Are you running highly successful campaigns?

Posted by Jo Woodward on Sep 26, 2017 10:00:00 AM

customer data.jpg

It’s a simple truth that the quality of data can directly affect the efficient deployment of marketing budgets and campaign success. So, it’s all the more baffling that many online advertisers don’t question the origin, accuracy or scale of the audiences they buy programmatically. 

Right next to fraud and viewability, measurement and audience validation should be at the foundation of marketing success metrics for 2017. 

Defining Data

Firstly, it’s important to understand some basic truths about data in order to understand it’s role in programmatic advertising.

  • Offline data
  • This tends to be derived from PII (personally identifiable information)
  • Online data
  • Anonymous data even if it was derived from PII originally
  • 1st Party Data
  • Data which marketers collect and own e.g. site registrations, surveys. This data is often deterministic meaning it has one-to-one correspondence with the actual attributes and behaviours of individuals and their devices. This data has greater accuracy but can often lack scale.
  • 3rd Party Data

Data owned by another source who then sells it to marketers. This data can be deterministic or probabilistic (based on inferred or modelled attributes rather than one-to-one correspondence). When probabilistic, this data is easy to scale but can be less accurate 

What are the data dilemmas? 

  • Accuracy Drops

Many companies strive to move their offline customer personas and models online. However, this process typically causes data segments to retain only 20-50% of their accuracy. To compensate, companies then over-model, leading to poor online targeting performance.

  • Time Sensitivity

On-boarded data (and most 3rd party) is time sensitive. The time needed to integrate data into a DMP/DSP usually causes additional data decay. Using this stale data causes results to suffer.

  • Weak Models

The more attributes you have on consumers the better you can predict their behaviour. However, if using 1st party data – which can suffer from a lack of scale - modelling platforms will not have enough data to provide accurate models

Applying the Wrong Measurement Methodology

Data measurement is not a one size fits all process. Programmatic systems use either panel or predictive measurement. Panel measurement relies on small deterministic data to infer coverage while predictive measurement scores the entire internet with a probability score for greater granularity. While panel measurement works well for targeting large samples, accuracy drops when measurement requires more granularity.

 The data you need

 Online advertisers need to constantly optimise their campaigns to drive the success of their campaigns. This means not only using quality data but also quality measurement methodologies. Advertisers should seek to leverage data that is: 

  • Fresh – data that was recently collected
  • Massive – smaller data can make modelling difficult and inaccurate
  • Accurate at scale – to target large samples, it should not loose accuracy when scaled

This means that as a marketer you should:

  • Never assume your programmatic partner’s data meets your standards
  • Ask lots of questions
  • Know the methodology used and the source of all the data that powers your targeting and measurement

Contact Anthony Ord from Acquire Online to see how to use data most effectively to maximum ROI. Ph 027 649 9198

Source: Huffingtonpost

 

 

 

Topics: programmatic, DATA

Predictive Marketing and Adoption

Posted by Nikhil Elayat on Jul 25, 2017 1:00:00 PM

Marketers are looking at user behaviour in the online eco-system. They're implementing AI and machine learning tools to predict how likely a prospective user is to interact based on past actions and behaviours.

Technology plays a big role in marketing and a recent study found that certain tech is more widely used in the US than in other countries. A survey of 620 marketers in the US, Australia, France, Germany and the United Kingdom clearly shows how technology usage compares across these countries.

70% of the marketers in the United States said that predictive marketing is the primary tech they're planning on using in 2017. Below is a chart showing the kind of tech that marketers plan on using in selected countries in 2017.

 

technologies that marketers Include.png

 

Cross Channel measurement technology

Half of all marketing and media executives in North America believe predictive technologies and associated analytics help them gain better value from the data. In addition to this 40.6% of the respondents said that cross-channel measurement and channel attribution would further help.

As adoption of technologies such as predictive analysis and DMPs rise, the focus will be on customer data and not platforms. This enables marketers to provide customers with a personalised brand experience across channels.

 

important technologies.png

An interview with Alex Weinstein, the Director of Marketing Tech and CRM at eBay emphasised the importance of real-time data and how it helps eBay power their campaigns. Capturing data immediately enables them to build a profile and target their clients immediately when a product they’ve shown interest in drops or changes.

Alex concludes that machine learning and it's ability to assist in personalising messages has become a strong foundation to grow eBay. He suggests companies start by using a light machine learning model to improve newsletter delivery and assure positive results. *

Contact Acquire Online to see how to use data most effectively to maximum ROI.

http://www.acquireonline.co.nz

 

*Source: www.emarketer.com

Topics: DATA

Data Driven Marketing? The difference between 1st, 2nd & 3rd party data

Posted by Zane Furtado on Feb 19, 2015 11:11:50 AM

image001

First-party data, third-party data, even second-party data are all used to help target ads and offers to the right users at the right time. 

Typically, when marketers talk about first-party and third-party data, they’re referring to information they can use to target or tailor ads or offers. This often comes in the form of cookie information they can use to target and track specific users. This data is often “plugged in” to a demand-side platform to help it decide which ad impressions it should buy from exchanges.

First Party Data: The Holy Grail

First-party data is any information that’s collected by an advertiser or a publisher through a direct relationship with a consumer.  In the context of display advertising, first party data is most often cookie-based data, and it can include information gathered from website analytics platforms, CRM systems, and business analysis tools.

 

An advertiser’s first-party data might include things like customers’ email addresses, purchase histories and behaviors demonstrated across its site. Amazon, for example, uses its first-party data to show users products it thinks they might buy on its homepage. That information can also be used to target and tailor advertising elsewhere across the Internet. 

First party data is always the most useful and valuable, but eventually you’re likely to find yourself in a position where you want to reach an audience that you don’t have first-hand information about. This is where second party and third party data become useful.


Second Party Data:  The Turkey Gravy

Second-party data is a newer concept, but it basically refers to a situation in which one “first-party” gives data to another. For example, a large advertiser such as P&G might strike a deal with a large publisher to gain access to its audience information. As far as P&G is concerned, that information isn’t “first-party” data because it didn’t collect it itself. But it isn’t third-party data, either, which is typically gleaned from a variety of places. The possibilities of 2nd party data are endless, and the key is to seek out, form, and maintain mutually beneficial partnerships.

Third Party Data:  Free for all, well not "Free" but for 'ALL'

Third-party data, as the name implies, is data that a marketer acquires from a multitude of outside sources. It’s basically anything that isn’t first-party data. For example, a third-party data provider might pay publishers to let it collect information about their visitors, and use it to piece together detailed profiles about users’ tastes and behaviors as they move around the Web. This information can then be sold to advertisers to help them target their ad buys. Third party data is great for demographic, behavioral, and contextual targeting, and can be used to remove bot traffic

Advertising will continue to change. And the only long pole is getting publishers and agencies and advertisers to wrap their brains and their cultures around a world that looks very different from the one Don Draper grew up in.

Viewability, personalization and engagement - not impressions - are the new measures of success, and companies can no longer afford to ignore the role that data plays in the success of their campaigns.

 


Source: Digiday & Retargeter

 

Topics: DATA