It’s almost impossible to have a conversation today about digital advertising that doesn’t include Google and Facebook. Together, these digital powerhouses, or walled gardens as we like to call them, account for nearly 60% of total digital advertising, and a quarter of all global ad spend. It’s even estimated that they pocket somewhere between 75 and 90% of every new dollar that flows to digital.
And despite recent concerns over privacy and brand safety, their share of the pie grows seemingly unabated. What does such market dominance mean for digital advertising as a whole? What are the implications for the brands, publishers and vendors that rely on this channel for business growth? And most importantly: how can the ad world’s Davids ever hope to challenge its Goliaths?
Customer choice is a critical component of any vibrant, successful industry. It forces competition and powers innovation. This is especially true when thinking about digital media, which continues to command more and more consumer attention (and therefore advertiser interest and dollars). It’s also a medium that evolves rapidly, expands constantly, and fragments endlessly.
Such a slippery channel requires diverse tools and approaches and constant experimentation to tame. That’s why many of today’s biggest advertisers and agencies are increasingly turning to advanced machine learning and finely-tuned algorithms to plan and optimize their media buys in real-time, chasing specific audiences and business outcomes at maximum efficiency.
But what happens when more than 80% of those digital buyers are using the same technology to execute their media buying strategies as everyone else, including their competitors? That’s four-fifths of the market tied to the same capabilities, feature sets, data assets, and product roadmap.
Marketers spend valuable manpower and man-hours developing smart media strategies and plans designed to outwit their rivals and engage their target with the right message at the right time in the right context – only for that strategy to end up being deployed and executed in exactly the same software that their competitors are also using.
Who wins in that scenario is unclear, but buyers arguably have the most to lose when the dominance of the duopoly results in the fastening commoditization of ad tech. For a start, a duplicate, one-size-fits-all bidding strategy can result in artificially inflated media costs and an unintended over-messaging to users, causing some to become disenfranchised by what they perceive as repetitive ads.
By contrast, imagine the advantages of being able to create and execute a fully customized buying strategy. By linking a diverse range of technologies with automated processes, buyers can start to unlock differentiated value and create real competitive advantage. Marketers can start to add their own 1st-party data and insights to the buying algorithms and align those models to specific metrics relevant to their unique business goals and priorities.
Recently, we worked with a client in the tourism sector to enhance their bidding algorithm with their own unique data, along with data from seasonal local events, historical bookings, and multiple other local sources. This extra data informed a more advanced approach to what the ‘right’ advertising space looked like for that brand, as well as the right cost to pay. Within two months, this customized approach was already showing improved ROI and an increase in bidding efficiency.
It is often thought that this level of customization requires significant technical know-how and resources. In most situations, this is not the case – at least, not since the rise of APIs. In earlier days, data analysts were manually processing unlinked offline and online data, then using that intelligence to optimize settings within the buying platform itself. In short, it was a labor-intensive process that needed constant monitoring.
Much of this work has now been standardized through API connections, custom dashboards, and automatic data pushes to the programmatic bidder, giving marketers more performance potential than ever before.
While most platforms are capable of such customizable setups, very few allow it. After all, customization at scale increases technical burden, system instability, and hardware costs for the largest platforms – so what’s in it for them? Plus, how do you think they earned the name ‘walled garden’ after all?
Such limits placed on technical innovation, or custom connections, don’t serve the interests of the marketers. Today’s advertiser needs more choice, not less. Brands and agencies have the most to lose if the current trends toward tech commoditization and inflexibility continue, but also the most to gain by pushing platforms to open up their gates, or perhaps more apt, tear down their walls.