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Advantages of First-Party-Data for companies

It is now more important than ever to invest more in your own data sources and to have a reliable data governance in place. Getting there seems complex and costly, but standing still is usually more expensive and inefficient.

Inaccurate data with a high price

Advertising platforms like Google, Facebook and Co. collect customer data, advertisers buy it. The form and content of the packages vary depending on the current needs of the campaigns. Every day, vast amounts of user data are collected and processed via social media platforms, user tracking systems and elsewhere. It is fed to algorithms, which in turn create segments and profiles about consumers. This is how we mostly get our target group data. But the validity of this data is rarely questioned by companies.

The amount, characteristics, as well as the process of data collection is largely opaque. The reasons for this lie in the rules of competition; something secret does not have to be protected, only guarded. Since no one likes to reveal their sources and methods, the tech giants conceal the methodology. 

The problem

  • Available data sets of the known advertising platforms are inaccurate and partly expensive.

The solution

  • It is usually more efficient to rely on own data sources and a reliable data management systems.

The way to the solution

  • Careful selection of technical solutions
  • Involve, educate and sensitise employees
  • Show consumers the benefits of data sharing
  • Pay attention to the protection of data and privacy
  • Keeping legal changes and developments on the radar
 

But this is precisely where the problem lies. A joint study by Catherine Tucker (MIT) and Nico Neumann (Melbourne Business School) sets it’s questions right here[1]. The accuracy of popular target group segments was tested, based on regular data sets of well-known advertising platforms. This revealed a strong variance in the quality of the data sets offered.

The reliability of demographic data was particularly disappointing, according to Tucker and Neumann. Only 42.5% of the datasets returned reliable data related to the gender of the users. Even if 80% of users actually had the interests indicated by the advertising platforms, this does not speak for the validity of the data. Those interests that were measured are particularly common in the population and therefore do not guarantee successful addressing of potential customer segments.

The fact that advertisers blindly rely on this data ensures a constant increase in advertising costs due to price competition. According to the study mentioned above, this has even led to a doubling of the amounts. Therefore, we can cautiously conclude that it would be more efficient and sustainable to use our own data sources and reliable data management systems.

The use of internal data sets is currently almost exclusive to large companies and often in a very limited form. This raises the question of why this is so. Decision-makers are often reluctant to relinquish control and are slow to trust new sources. The data sets of large advertising platforms, on the other hand, are often blindly trusted. However, there are plenty of current and past success stories that confirm that it is precisely one’s own data that can conjure up a business advantage. But of course it is also a challenge to evaluate more precisely where and how best to use it for this purpose.

 

The path to your own data solution

Where the focus lies:

In order to bring efficiency to the internal use of data, it is necessary to find good technical solutions, to compare and evaluate them and consequently integrate them in a way that is tailored to the needs. The most important thing to consider here is the compatibility of the systems. You can have the best systems in the world, but if they can’t be connected, you end up with data silos that don’t add value, but extra work.

Employees are key

To make this possible, employees must be educated and sensitised about the use and maintenance of data, i.e. an internal data awareness must be integrated more broadly in the company. Furthermore, the choice and filling of a reliable and suitable technical solution is a necessity. Until then, all attempts to establish a comprehensive and successful data strategy remain difficult. By involving the employees in the process, they can jointly write clear goals based on the needs evaluated in parallel, which also promise long-term success without causing a mood of protest. Only then is the door open for them to use their internal data in a way that brings value.

Quid pro Quo

The willingness to share data with a service provider or retailer increases significantly if, in return, the service provider or retailer offers its customers advantages in fulfilling their own needs. Show your customers the benefits of sharing their data with you. Find out what their target group is concerned about, what they value so much about your product and how you can extend this benefit even further. You’ll probably get more reliable data faster than before and maybe even create a new portfolio of services that your customers really value and use loyally.

Responsibility for trust

But with this work comes a clear responsibility. Protect your customers’ data well and implement sound data governance before embarking on this adventure. Offer clarity and transparency in the handling of data and also put in place obvious opt-out options through which customers can withdraw. This takes the pressure off and creates an honest willingness to share information. In this way, you create a new business, based on highly valid and concrete data, to which customers are happy to commit for a long time.

Armed for the future

Therefore, we should not lose sight of the future. Upcoming regulations such as the e-privacy regulation, for example, which we Europeans have agreed on, present us with new challenges. Aspects such as blocking data storage without explicit consent are significantly changing the processes of data acquisition. However, with an internal data-oriented way of working that can adapt flexibly on the one hand, and a customer base that has a solid relationship of trust and benefit with their products on the other, it is much easier to meet this challenge. This puts them miles ahead of the competitors.

Planning, evaluation, planning, selection, planning… Implementation

However, the most important thing is to plan, always look for new opportunities and approach integration in a structured way.

Even an infinite budget pot is not enough if the process is not worked out. No one is forcing your company to immediately integrate all available solutions. It is also important not to fall into the trap of persisting with expensive, inefficient or inappropriate implementations due to the bias of the “sunk cost fallacy”.

Priorities are often decided by costs and benefits, which is usually a good way to shape this long-term project.

 

In conclusion…

Data offers more than complexity and cost. We tend to prefer the things we are already used to, but they are usually no less complex and usually cost more.

[1]Neumann, Nico; Tucker, Cathrine (2019): „How Effective Is Third-Party Consumer Profiling and Audience Delivery?: Evidence from Field Studies”,[online] https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3203131 [08.07.2020].

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