Ad Management platforms have recently appeared in the monetisation field and are competing with the in-house setups built by larger publishers, both in terms of performance and reliability.
However, Ad Management platforms do so for only a fraction of the cost, while protecting these publishers’ revenue from being overly dependent on the professionals managing the advertising stack in-house.
First off, we need to understand what managing an ad stack in house involves to fully grasp the “build or buy?” dilemma that publishers are facing. An in-house setup at a large publisher usually implies:
The value of Ad Management platforms as a replacement to in-house setups lies in keeping full control over their monetisation process, without the technical and operational risks such as pushing stack-breaking updates or revenue drops caused loss of stack knowledge (following an expert employee’s departure for instance) and the consequential knowledge loss. Ad Management platforms allow publishers to fully or partially relieve these responsibilities for both of these teams:
In-house setups necessarily imply a certain level of maintenance (externalised or not), which usually doesn’t concern the implementation aspect of the advertising stack. However, when technical updates are needed (such as a Prebid update for example), publishers will need to spend time verifying and proof-reading their updates in a time-consuming process which usually requires the full attention of all programmatic advertising-dedicated staff. Even then, changes usually require testing to make sure stack-breaking updates are not pushed too quickly.
With an Ad Management platform, the previously mentioned testing phase is handled by the platform itself, relieving the publisher’s team of an intense and stressful part of the operational workload. In a similar way, setting up an Ad Unit is also made much simpler by Ad Management platforms as this process no longer requires any development resources and can easily be done through a dedicated interface and specially-designed templates.
However, while Ad Management platforms assume a large share of the technical risk as seen above, and human risk as we’re about to see, it’s important to remember that full control over the monetisation process and the ad stack remains in the hands of the publishers with these platforms, which simply provide the complete toolset to build, track and optimise your advertising stack.
In-house setups are dependent on the people operating it, which at the same time can cause its own downfall. Most of the time, developers in these large structures are not necessarily advertising experts and require the guidance/leadership of someone specialised in monetisation. And whenever this person ends up leaving the publisher, this can cause serious organisational problems for the publisher, and ultimately revenue loss.
Ad Management prevents this by enabling the sharing of knowledge over time and making sure that none of the publisher-specific details about the advertising stack are lost over time. Considering how companies are struggling with higher turnover rates in all industries, preserving yourself from any issues caused by an employee departure seems like the best option, or the safest at the very least.
Whether it’s to avoid faulty implementations or loss of knowledge about their stack, it seems that Ad Management platforms are definitely the obvious solution for publishers looking to avoid revenue-breaking events by all means.
In-house setups that require complex ad behaviours such as Ad Refresh or Lazy Loading will require the publisher to internalise the technical skills required to implement such ad behaviours. This can turn out to be quite a costly move, as these types of skills are not wide-spread on today’s job market. It can also end up costing you both time and money by making your monetisation depend on the manual coding skills of your team as well as their schedules and availability (as mentioned above, most developers working for publishers are not specialised in advertising and usually assume a variety of development-related tasks).
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With Ad Management platforms, these same publishers and their monetisation teams can rely on tried and tested processes provided by the platform and allowing them to focus solely on their revenue strategy rather than its implementation. But what will bring the most value when replacing an in-house setups is the possibility to scale their top-performing setups across a multitude of sites, which can hold incredible value for publishers that own and operate several websites and their monetisation.
As a conclusion, publishers should bear in mind that if they want to develop their solution entirely in-house, this will require becoming an expert in every single aspect of their monetisation which is a near-impossible feat.
On the other hand, Ad Management platforms that are dedicated to programmatic advertising have the teams and the means to become experts on a given topic and to provide top-notch advice to publishers, tailored to their individual needs.
While in-house setups do give a bigger sense of “freedom” to publishers, keep in mind that this freedom comes with some very heavy responsibilities. On the flip side, Ad Management platforms give publishers the same exact “freedom” to define their own strategy, while adding the bonus of not worrying about the technicalities of their advertising stack. This allows them to focus on what matters most: making revenue!
If you're still unfamiliar with the novelty of Ad Management platforms and would like to learn more about their features and how they're changing the advertising game, we've got you covered! Read our latest article "What is an Ad Management platform?'" to learn all there is to know about these new tools for advertisers.
However, if you’re looking for new ways to leverage your ad stack and generate more revenue, you may be surprised by just how useful powerful analytics can be! Read our dedicated guide “The complete guide to boost ad revenue with analytics” and stop relying on your gut feeling by making all your stack changes data-motivated!
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