What is Log-Level Data and How Does it Help Publishers?

Reading time: 5 minutes

User data[7] can be an effective resource to enhance the effectiveness of your marketing strategies. It is also often used in analytics and decision-making that impact economic growth, jobs, and welfare.

Therefore, publishers and advertisers wish to get their hands on as much user data as possible to make their marketing decisions better. 

Most websites collect data through cookies and pixels. However, vendors cannot say no to more data. As a publisher[8], you may have been requested to acquire log-level data. So, if you don’t know what log-level data is, we will tell you what it is and how you can benefit from it.

What is log-level data?

Log-level data is a granular form of data collected through ad requests. It includes:

  • Geodata
  • Transactional data[1]
  • URLs
  • Cookie[9] IDs
  • Timestamps
  • Visibility levels
  • Bidding prices
  • Connectivity and bandwidth

In short, log-level data is data retrieved from server logs tied to specific events such as ad requests and bidding requests. Log-level data comes in raw form and is converted into advanced reports. With this data, publishers can control how to sell their impressions.

Log-level data starts getting collected from the moment an ad appears on a person’s screen till it remains or is removed.

How is log-level data different from other data?

Log-level data is similar to other forms of data. However, its granular details offer accurate time information. Additionally, unlike different types of data, it only comes in raw form. Then it is converted into group data with the help of analytical tools and SSPs.

This data provides a significant amount of information to publishers and advertisers. They use log-level data to launch highly benefitting campaigns on targeted areas.

Commonly, vendors store log-level data and share some parts of it with publishers and advertisers. However, most publishers accumulate this type of data on their own.

How publishers use log-level data?

Log-level data represent different meanings to everyone. From buyers to publishers to sellers, everyone uses and benefit from it differently.

However, publishers use it to create a detailed buyer’s persona for their users. They also use it to track changes in their supply chain and may even sell it to advertisers and sellers. They also tweak auction dynamics with log-level data.

Log-level data also allows demand tracking as publishers can adjust their prices if the bidding increases or decreases. Because publishers receive a detailed report, they optimize price floor[4] and price rules to parallel their prices according to demand. For example, publishers can drive traffic towards a particular site or product. 

So, if log-level data states something is in demand, they will direct significant traffic towards it.

How advertisers use log-level data?

Advertisers look for log-level data because of multiple reasons, some of which are:

  • To gain higher visibility into auction mechanics
  • To check and improve inventory[10] quality
  • To find out users interacting with their ads
  • To pick out other competitors

Moreover, advertisers look to find out what other participants are bidding and what causes them to win or lose an auction. This data is crucial as it can provide them with future successes.

Log-level data also help advertisers in evaluating the performance[5] of various supply sources. Due to this, advertisers only work with suppliers that can supply reasonable rates and high performance. Advertisers may overlook prices if a vendor provides quality inventory, excellent campaign[11] performance, and return on investments.

Why is log-level data in high demand now?

Publishers, buyers, sellers, and advertisers can access a vast[2] amount of information with log-level data. This information helps them create good strategies to increase customer engagement, IT security, and cloud operations.

There is greater-than-ever demand for insights into business processes. This, in turn, has significantly increased the need to access log-level data for businesses. The current market value of log analytics is above 1.9 billion dollars, and it is expected to grow to 3.7 billion dollars by 2025. Therefore, it is not surprising that publishers want to get their hands on as much log-level data as possible.

How to use log-level data?

Here are just some of the ways publishers deploy log-level data for some great results:

Support business operations

Log-level data is used for supporting business operations. You can drive better business outcomes than your competitors and improve conversion. As the data provides details about the high traffic areas, you can promote them and increase revenue.

Overcome growth challenges

One of the biggest challenges during business expansion is cost management. Higher costs can freeze up business growth. However, with log-level data, you can overcome this challenge. As the data holds info about numbers of users, devices, applications, IT environments, and infrastructure elements, you can easily find out users’ pain points.

Manipulating pain points is very important in marketing and product selling. So, designing campaigns around it will increase sales numbers.

Why aren’t publishers using log-level data?

As much as log-level data is coveted for its benefits, some publishers and advertisers stay well away from its reach because it is hard to implement. In addition, as the information is collected in raw form, it isn’t easy to interpret correctly. Many publishers use analytical tools to translate data, but you still need basic knowledge to use them.

Moreover, converting raw logs into comprehensible data is pretty expensive due to its complexity. Not all publishers and advertisers can afford to pay that much money. That is why only a handful of advertisers use log-level data as they have resources to access it.

Another reason is that vendors do not use the same format to collect data. Therefore, not every vendor shares the same thing. Also, some specific demand-side platforms limit the information shared by clients.

In addition, log-level data requires a separate cloud system as storage. It consists of millions of rows and hundreds of columns, making it difficult to export to other systems.

What’s next?

Data is the basis for becoming an excellent publisher. However, after acquiring and storing terabytes upon terabytes of data, you need to figure out how to incorporate it in your advertisement campaigns to reap the fruits.

However, we understand that it is not easy to do it on your own. Therefore, we offer a unified analytics dashboard to consolidate data from multiple SSPs. We also provide programmatic monetization products for header-bidding and in-stream video ads[12][3] to ensure transparency[6].

Terms
1. Transactional data. Purchase history associated with audiences/segments, it is often provided in aggregate and used to determine interests and needs in support of target segmentation.
2. Video Ad Serving Template [VAST] ( vast ) Video Ad Serving Template is an industry-standard script that helps provide video players with information on which ads to display, how to display it, when and functions it should offer.
3. in-stream video ads. In-stream video ads are shown before, during or after a video gets played.
4. price floor. A fixed CPM rate that prevents an ad partner from serving campaigns that pay below a certain price threshold. For example, if you set your price floor to $1 your ad partner shouldn’t serve any campaigns with net CPM rates below that amount.
5. performance. A form of advertising in which the purchaser pays only when there are measurable results.

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