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Pentingnya Skala dalam Periklanan Terprogram

Pada bulan Oktober, The Trade Desk merilis iklan video ketika mereka menggunakan analogi yang menyamakan trik-atau-suguhan dengan pembelian media tampilan. Dalam iklan tersebut, raksasa pemasaran seperti FB digambarkan sebagai walled-garden, tempat mana anak-anak bisa mendapatkan permen di rumah yang jumlahnya terbatas. Sebaliknya, platform terprogram, seperti Trade Desk, digambarkan sebagai semesta rumah yang dapat dicapai.

It’s an interesting analogy, with some truth. While walled-garden platforms like Facebook provide scale, one could argue (and The Trade Desk does argue) - that their scale is limited in scope because they are a single publisher with a few properties. One of the greatest benefits of programmatic advertising, conversely, is the access to millions of publishers, as well as the autonomy to make real buying decisions regarding where an ad is placed.

There’s a problem with that argument on its own though, because in this commercial the Trade Desk essentially depicts a world in which all programmatic DSPs are scalable. The reality however, is that scale has been a buzzword for far too long, and the nuance matters.

Memahami skala

A simple definition of scale, in the context of programmatic advertising, would center on a DSP’s ability to reach many eligible consumers. The industry, thankfully, has a standardized form of measurement for scale called, QPS, or, queries per second. Essentially, QPS tells us how many opportunities a certain bidder has to serve an ad per second. More specifically, this measurement provides a sense of the infrastructure a DSP has, as well as the diversity of supply partners integrated.

Let’s use a tangible example to demonstrate scale. Let’s say an advertiser is choosing between two DSPs to run a retargeting campaign, DSP A has QPS measuring 2 million, and DSP B has QPS measuring 3.3 million. Both DSPs, in this instance, are above the industry average in QPS, and I’d argue the choice is somewhat obvious. If you have a target audience of 100,000 users, DSP B should have a 50%+ higher chance of reaching those users.

Of course, this example is an oversimplification of how buyers choose their partners. It doesn’t take into account customer service, experience, creative suite, etc., but there’s a challenge in buying based on these non-QPS attributes. If we were to scatter plot differentiation of possible attributes for a DSP, we’d likely see that differences in “creative services” and “experience” between different bidders would all land relatively close to each other. As a result, the advertiser mentioned above will frequently choose DSP A, or even DSP C with scale measuring 750K QPS. It’s an unfortunate manifestation of the consequences that arise when every platform’s website says “the most scale, with the best machine learning, and the best advertisers, and the best team.” The nuance of scale is lost in this context, but perhaps it’s lost because QPS (as a number) isn’t enough.

Bagaimana kita bisa menguji skala?

If QPS is insufficient on its own, as a method for examining scale, then we need to explore other facets of a DSP that allow it to bid at scale: specifically, supply diversity and infrastructure.

One of the Trade Desk’s core arguments in this commercial was that walled gardens provide a lack of publisher diversity, while programmatic DSPs offer a wide variety of publishers. It’s a reasonable argument, however, diversity of supply is not binary. It’s not a case of “you have it or you don’t,” rather, diversity of supply varies dramatically from one DSP to another, and those DSPs with higher volumes of supply integrations provide a greater service.

For example, let’s revisit the retargeting scenario from before, but now let’s say: DSP A has QPS of 2 million and access to 10 different SSPs while DSP B has QPS of 3.3 million and access to 20 different SSPs, including the same 10 as DSP A. Leaving QPS aside, if the target audience is 100K users, then DSP B is again an obvious choice.

Not only will DSP B have a greater opportunity to find more of the Advertiser’s users, but it will have a significantly higher volume of data points against which it can optimize. A DSP with more supply partners can better optimize for attributes like supply partner, publisher, creative iteration, creative type, OS version, bid rates, frequency, and so on. A DSP with more supply partners can reduce diminishing returns for an advertiser by offering different formats and publishers through which they can approach an audience.

Another important optimization process relates to the traffic pricing - with higher scale, a DSP can observe more auction outcomes and learn the market prices for different traffic components more efficiently, ostensibly it can buy the same amount of traffic at a lower price and yield better performance results for the advertiser. This capability has become far more important since most programmatic supply has transitioned to 1st price auctions this year. In a second price auction, if you bid too high you simply pay the price of the second-highest bid; while in a first-price auction you can end up overpaying for the same impression and wasting an advertiser’s money.

Therefore, if we make the argument that our goal is to “find the right user, in the right place, with the right ad, at the right price,” then variation in supply partners must matter. And while high diversity of supply is a straightforward concept, achieving variety at scale requires robust infrastructure which in turn requires money.

A high percentage of DSPs today leverage Amazon Web Servers to power their infrastructure and bidding. The challenge, however, is that the cost of scaling up your capacity with cloud infrastructure, like AWS, is extremely high; so if a DSP wants to increase its supply diversity, or bid request volume from a certain SSP, they need to pay significant money for their AWS. To fund these necessary investments, these DSPs will either need more advertisers, or higher margins associated with their existing advertisers to make up the cost.

Alternatively, some DSPs invest in building their own infrastructure, and manage their own custom hardware and network, optimized for their needs. As a result, their costs are dramatically lower compared to those using AWS, and they can extend those cost savings to their clients in the form of lower traffic costs and subsequently lower cost per conversion. These DSPs can easily toggle new supply partners, increase bid rates on certain SSPs, and provide a service to their advertisers that has greater upside for scale at lower cost.

Ultimately, robust infrastructure will yield higher bid rates and a wider variety of supply access, which in turn will manifest as high QPS. That being said, because QPS is not an important enough buying factor today, advertisers should investigate these attributes more thoroughly.

Mengapa skala begitu penting di masa depan?

Dengan konten apa pun yang ditulis hari ini, ada peringatan yang melekat "apakah ini akan menjadi masalah di masa depan?" Bayangkan masa depan ketika kita tidak dapat lagi menargetkan ID perangkat seluler. Masa depan dengan model yang mirip, grafik perangkat, penargetan pengecualian, dan penargetan ulang tidak dimungkinkan bagi sebagian besar pengguna aplikasi (Tentu saja, kami tidak tahu seperti apa masa depan nantinya, tetapi anggap saja sebagian besar konsumen tidak akan melakukan opt-in tracking iklan). Dalam masa depan versi ini, skala akan menjadi atribut terpenting yang tersedia bagi advertiser (pemasang iklan).

Dalam dunia terprogram saat ini, kami menawar secara giat pada IDFA khusus berdasarkan kumpulan data yang kami miliki. Kami memiliki bidder yang sangat dinamis yang memungkinkan kami menjangkau konsumen tertentu dengan iklan tertentu, dan melalui prediksi dan pengoptimalan persentase konversi, kami dapat menerapkan tawaran CPM yang sesuai demi memenangkan peluang dan menayangkan iklan. Namun, jika kita menghapus IDFA, kemampuan untuk menerapkan penawaran cerdas di tingkat pengguna menghilang dan kita ditinggalkan dengan lanskap yang memiliki kepastian yang jauh lebih sedikit.

Jika advertiser (pemasang iklan) memiliki sedikit kepastian akan harapan hasil dari penayangan iklan, advertiser (pemasang iklan) tersebut tidak dapat membayar harga tinggi untuk iklan tersebut. Namun, advertiser (pemasang iklan) yang sama tersebut perlu menjangkau calon pengguna dan pengguna lama untuk mengembangkan dan mempertahankan bisnis mereka - mereka perlu mendorong hasil yang serupa dengan yang mereka lihat sekarang, tetapi dengan biaya yang lebih rendah. Jadi, pada akhirnya kita akan sampai pada lanskap ketika penawaran yang luas, berskala tinggi, dan berbiaya rendah akan memberikan tingkat keuntungan tertinggi bagi advertiser (pemasang iklan)

Bayangkan skenario ini

Dan karena kita memulai bagian ini dengan sebuah analogi, mari kita akhiri pula dengan sebuah analogi untuk mengilustrasikan skala di dunia dengan akses rendah ke IDFA: Bayangkan sekarang Anda ingin membeli rumah yang terjangkau. Anda mungkin akan memulai proses pada sebanyak mungkin platform, seperti Zillow, Redfin, Realtor, dll., dan, melalui informasi yang disediakan di platform ini, Anda secara fisik akan menghadiri open house untuk properti yang sesuai dengan kriteria spesifik Anda. Jika Anda mencari rumah dengan cara ini dalam waktu cukup lama, pada akhirnya Anda akan beruntung dan menemukan properti yang terjangkau.

Kini bayangkan platform ini tidak ada- bagaimana Anda akan membeli rumah?

Anda mungkin perlu berkeliling lokasi yang Anda inginkan dengan mencari tanda "dijual" sampai Anda menemukan open house. Namun, karena Anda akan beroperasi dengan anggaran rendah, Anda akan perlu mencari open house bervolume tinggi sampai Anda menemukan open house yang sesuai dengan kebutuhan Anda, dan tawaran Anda tidak kalah.

Ini adalah proses yang melelahkan, tetapi masa-masa pencarian rumah yang tepat Anda akan jauh lebih mudah daripada pembeli rumah ceroboh yang melihat-lihat di lingkungan sekitar.

Dalam skenario ini, jelas Anda berdua sama-sama pembeli rumah, tetapi kemampuan Anda untuk membeli rumah yang tepat dengan harga yang tepat tidaklah sama.

Tommy Yannopoulos

Director Sales US EAST

Berbasis di NY

Bertanggung jawab untuk North American