Data asset management is an integral part of modern digital publishing. It enables the online newspapers and magazines to better manage and organize the information at their disposal, and utilize it in their strategies.
To build their revenues, publications need to balance both the reader’s and the advertiser’s interests. Breaking this balance may result in losing both traffic and profits.
Furthermore, this equilibrium is very fragile, because readers tend to ignore ads if they are not relevant, and may even stop trusting the publisher if said content becomes too intrusive or out of place. That’s what makes this complicated – to ensure profits, both sides need the readers to click on the ads. And for this to happen the ads should be on point.
In fact, research shows that 69% of users nowadays demand a contextual approach and want the ads they see on pages to be relevant to the content.
As digital publishers usually have hundreds of unique pages, the only way to achieve this is through accurate data analysis, enhanced automated placement, and programmatic advertising. And that’s where data asset management comes in.
In this article, we’ll talk about the importance of adequate data governance for publishers, and provide actionable tips on how to improve your data culture. Read on to find out!
What Is Data Asset Management?
While companies nowadays have enormous amounts of information at their disposal, data as an asset is still a relatively new concept. It means that data should not be viewed as the byproduct of processes but as a type of capital that is valuable and, if managed properly, can multiply its ROI incrementally.
Data asset management is the process of organizing, cleaning, and grouping data, so it can be operational and useful. Proper management allows information to be utilized fully and purposefully.
Once the data is processed and grouped based on parameters, each group becomes an asset that contains a number of data sets.
In digital publishing, data assets are mostly relevant when it comes to ad inventory placement, and content distribution targeting. When you are able to accurately segment your audience into cohorts based on different factors, you make it possible to cross-reference the information from all your digital channels, to create information-rich data sets and data assets. Leveraging these, you can implement a contextual approach and show the ads your readers want to see and are more likely to click on.
Most forms of contextual advertising were popular before Real-Time Bidding strategies took over the market. However, as we are looking at the end of the “cookie” era, the idea behind contextual advertising is resurfacing.
At one time, we used to show ads for VW and Mercedes in articles about automobiles – based on tags or context. Then we started targeting auto heads based on their interests and showed them ads wherever they went on the internet.
However, due to restrictions on third-party cookies, this model has become challenging. One approach is to mix these two – segment people who read about vehicles on your website, group them with other people, make it anonymous, and show them VW ads through your network or share the information with user identity companies. These companies can then batch them together and sell them to platforms.
However, despite the competitive advantage the above presents, most publishers still have a long way to go before they can make the best of it.
Why Publishers Should Care About Data Asset Management?
While publishers rely heavily on data to build their revenues, even modern digital native publications struggle with utilizing the full potential of their data. The issue goes even deeper for established newspapers and magazines, because more often than not they still employ complex and outdated legacy data management systems.
In fact, recent research by DoubleVerify shows that 73% of publishers waste time manually processing their data. Furthermore, 80% say that the resources they spend on collecting and processing data hurt their ability to improve their revenue and optimize ad performance.
Steven Woolway, EVP of Business Development in DoubleVerify, says that:
Publishers have to pull disparate data from all of these scattered connections, including DSPs, SSPs, and exchanges, then they have to consolidate, organize and normalize that data. It’s a cumbersome and repetitive process that takes resources away from more revenue-producing initiatives.
Nowadays, demand-side platforms (DSPs), supply-side platforms (SSPs), and ad exchanges make buying and selling ad spots much easier. However, for these systems to function properly, they require the right type of data so they can match the ad inventory and the publisher’s content to the advertiser’s goals.
As a publisher, you need to collect information about your readers and understand their behavior and demographics on a deeper level, so that you can build accurate and detailed profiles yourself. This way, you can attract the right kind of marketing agencies to advertise on your pages, and encourage higher bids.
If your data is insufficient, incomplete, or incorrect, your website will be populated the wrong type of advert-related content, and neither the advertiser, nor you will make a profit.
Tips on Handling Data Asset Management
In order to handle data efficiently, publishers need to utilize data asset management and use a data management platform where they can store their assets.
While this may sound straightforward, implementing the approach successfully is rather complex. However, there are a few factors that can make the process more efficient:
1. Hire a Chief Data Officer
Data asset management is complicated and time-consuming, and hiring a chief data officer will make things easier and more productive. An expert will have the skills and knowledge required to clean up the data, structure it, and reorganize it into assets.
Furthermore, they will know how to standardize and organize the data from different streamlines and bring it into the data management platform.
In addition, when you have an expert in charge, they can teach and guide the rest of your team on how to best handle the data they use. This will reduce both the time and the load of the team and will increase their productivity. As a result, they will be able to focus on optimizing campaigns, and working on other revenue-producing activities.
A chief data officer can help you promote a data-driven culture. People will view data as a valuable asset that informs, rather than a resource that they don’t know how to fit into their day-to-day work.
2. Map Your Data
If you’ve been in business for a while now, you have probably already accumulated a significant amount of data. So in order to know how to approach it, what tools you need, and how to organize and correlate it, you first need to map it.
This means that you need to find out:
- What types of data do you have?
- What state is it in?
- Where is it stored and how?
- What processes is it relevant to?
- Who’s in charge of it?
Implementing a data audit will enable you to properly map out your resources and set a course of action.
3. Enable Automation
When handling large amounts of data, automation is a must. Repetitive manual processes can be exhaustive, and more often than not result in frustration and mistakes. Furthermore, as the DoubleVerify study shows, they can take massive amounts of time and prevent publishers from managing campaigns property and distorting their focus.
Furthermore, that’s what machine learning algorithms are for. They can be trained how to organize and group information as well as handle tedious tasks. While their accuracy may not be as good as that of a human, they process the data faster and with better efficiency.
However, you shouldn’t completely take the human factor out of the process. Experts can oversee the process, double-check the results, and handle difficult cases. This way, you will ensure the quality of your data assets and minimize bias and mistakes.
4. Don’t Rely Only on Your Data
First-party data, i.e. the data you’ve gathered from your own customers, is always the best type of data. It’s top quality, you know where it comes from, you have the user’s permission to use it, and you have immediate access to it.
However, there is still a limit to the type of data you can collect. Therefore, to expand your audience, you can power up your first-party data with second-party data. This means acquiring access to someone else’s first-party data. This can be from organizations in your partner network whose audience has touchpoints in common with yours.
With databases combined, you can understand the customer even better and obtain information about them that you wouldn’t be able to otherwise.
Furthermore, you can also purchase third-party data. However, keep in mind that the information in such databases is usually too general and may not respond to your needs or standards.
5. Be Mindful of Privacy Issues
That said, one of the most important aspects of data asset management is to follow the privacy legislations that apply to your customers. The data of users is protected by the GDPR and the CCPA and thus should be stored and secured accordingly.
Furthermore, you should always ask for permission when collecting any type of data, regardless of the user’s location, and make sure that your partners do the same. Respecting the customer’s privacy and their position on sharing their personal information is the key to acquiring their trust and retaining it.
Data is a valuable asset for digital publishers and managing it properly provides them with a competitive advantage and an opportunity to increase ad inventory monetization. However, while its importance is not called into question, adequate data management remains a hot issue in the industry.
By automating the process and hiring data management talent, digital publishers can improve the efficiency of their ad marketplace performance and revenues. Furthermore, they should be able to streamline things so that their team can focus their energy on optimizing campaigns, and improving monetization.