Amazon Web Services or in-house? Building technology infrastructure to enable success

Data is the DNA of the advertising industry, determining how brands, publishers, and media planners respond to changes in their surrounding environment. Automation and advanced technology play a critical role in harnessing data – and with 32% of CEOs developing more agile supply chains in response to consumer needs, there is increased demand for quick, informed decision making. 

But with different options available, the best approach can sometimes seem a complex and confusing decision for a business to make. Enrico Vecchio, Chief Technology Officer at Audiencerate, has experience of working with both Amazon Web Services (AWS) and in-house structures. As the first to market with its infrastructure service, Amazon’s legacy is instrumental in providing advertisers with robust, definitive technology to enable data-driven success; while in-house infrastructures offer the advantage of tailor-made solutions based on fixed traffic size. Enrico takes a deeper look at best practice, to help businesses build a structure that enables their success.
 

What can data platforms gain from building a technology infrastructure in-house?

When debating the build versus buy question, going in-house has several positives on its side. For instance, companies that opt to develop their own tech infrastructure have the advantage of flexible system features. Often, it makes sense for vendors to only add new features once demand justifies the investment that requires - but, from the customer perspective, the result can be that software options are limited to what the wider market wants.

Deciding to build systems independently brings the opportunity to include whichever features matter most for their business; with the potential further benefit that doing so could mean they have new capabilities in place before competitors think of asking for them. Equally, going in-house can also help companies avoid the opposite problem: acquiring overly powerful tech that they might not be ready to fully utilise.

The cost of external software isn’t just about offsetting operational overheads, it also covers customisation, configuration and ongoing support for a range of tools. Consequently, firms that don’t make full use of all features won’t realise maximum return on their outlay. Or to put it another way: purchasing sophisticated software packages but using just a small percentage of their features is like buying an advanced coffee machine for the sole purpose of boiling water. In such situations, it can be better for organisations to self-build instead of spending on high-capacity tech they don’t need.

What can data platforms gain from building a technology infrastructure on AWS?

The core attributes of AWS originate from its security model, scalability and efficiency. Data protection and compliance are high on the agenda for our industry, so having a streamlined service that automates security processes allows teams to dedicate more manpower to scaling technologies. Enabling global integrations – and being able to operate self-service accounts for clients from any region – is a necessity for data platforms looking to strengthen their support systems worldwide. Building a technology infrastructure on AWS grants teams the resources and flexibility to implement this, delivering data on demand which can then be transformed into relevant, actionable insights.

Additionally, the capabilities AWS offers are extremely cost-effective, which is an especially key asset right now. According to the latest IPA Bellwether report, advertising budgets saw yet another sharp decline in Q4 2020 and only 12% of firms expect upward revision across 2021/22 – meaning decision-makers need to optimise their outlays. By investing in efficient technology infrastructures, providers will be able to future-proof their data assets, even with the current pressure on spend. 

Ultimately, AWS managed services allow development teams to focus on building their product and infrastructure without thinking about service setup and scalability. Data teams can measure performance, gain visibility on what is and isn’t working within hours, then modify digital activities as needed. Data platforms traditionally collate revenue reports on a monthly basis, but this hampers proactive adjustments.

What’s more, its reliable infrastructure will let businesses, for example, match billions of IDs at scale, as well as linking data with key programmatic marketplaces and buying platforms. This comprehensive view leads to greater control over data processes, providing companies with the resources to pivot in response to customer-centric insights.

How to choose between AWS and in-housing?

There is an argument that businesses weighing up the positives and negatives on this decision should follow one key rule of thumb: software that is critical to achieve a competitive edge must be built in-house, while everything else is bought. This maxim, however, makes the choice sound much easier and less complicated than it is, in addition to overlooking the highly diverse nature of different business priorities, tech use cases, and implementations. 

For example, if software will play an essential part in differentiating a business then in-housing may indeed be the best way to ensure total control over systems that are vital to sustain its offering and market position. But there is a risk that the varied definitions of what counts as ‘business critical’ might encompass IT solutions that are already available via external cloud-based platforms and are not necessarily cheaper to build again from scratch. In fact, this could also create significant losses when it comes to opportunity costs - with valuable development skills and resources absorbed by re-making existing tools instead of building unique new tech that will drive greater rewards and revenue.

Then we come to the issue of versatility. On the one hand, tech ownership brings the capacity to code in desired features at any time, enabling organisations to quickly adapt as their needs evolve. But on the other, there is a chance that constantly bolting new pieces into systems might make them increasingly complicated and difficult to navigate, meaning vital capability gaps are harder to spot and fill. Moreover, the more unwieldy an in-house infrastructure becomes, the more future scalability options are restricted, such as moving over to different platforms.

Ultimately, picking the best route relies on considering all factors. Alongside business-specific operations, goals and tech requirements, companies must carefully review the trade-offs of both options and determine which one will deliver the best long-term benefits.

How does efficient data management translate into broader industry successes?

With a robust infrastructure, data platforms can exceed client expectations by creating manageable, transparent data collection products. It also opens the door to deeper, more collaborative integrations that generate ongoing value for users. Those with the ability to onboard major global programmatic data marketplaces, for example, allow data platforms to develop a seamless, accessible service for clients to achieve data-driven results.

While it’s notoriously difficult to predict change in the digital marketplace, advertisers who base their decision making on consumer-centric data are likely to thrive. Cost-effective infrastructures that deliver privacy, enable adaptability, and allow the potential for growth are powerful tools for ensuring industry success.