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Did you ever think, why do I keep seeing ads of things I’m actually interested in? You’re not the only one. Behind the scenes, complex systems of data analytics and advertisement auctions are working hard to make you buy products or services that you are probably interested in.

How do online advertising auctions work?

When loading a web page, an extremely quick auction is taking place behind the scenes. In this auction, the highest bidder wins, and their ad will be shown to you. This is all based on complex algorithms that analyse data like your browsing history, device type and location. Companies like Meta also use data like likes and shares to determine your interests. When looking at the pricing system, Google for instance, uses a bidding system called “generalized second-price”, or GSP. With this bidding system, “each advertiser pays the next highest advertiser’s bid” (Edelman, Ostrovsky & Schwarz, 2007). Usually, companies bid on certain keywords for Google ads. This means that if you search “curtains” for instance, that the highest bidder for that keyword will be shown at the top of the results.

The price of personalization

While auctions for personalized advertisements make ads more relevant for users and help companies generate more revenue through their ads, they also come with great concerns about data privacy. It might be a bit scary to see ads about subjects that you just talked about 5 minutes ago. But also, how can you still be aware about what data is being used and for what? For users, transparency about this topic is becoming more and more important.

My take: is the system sustainable?

This discussion is a tricky one. I think it is very important that targeted ads keep existing. They are a very important revenue stream for companies like Google and Meta, which will eventually be used to improve the functionality of the platform. However, one of my main concerns is the so called “filter bubble” effect. This effect means that people’s existing opinions on certain topics will be continually reinforced, without exposure to different viewpoints. In my opinion, this is a very dangerous development, since this might lead to increasingly extreme opinions. Therefore, I think it is very important that the market for online advertising auctions stays regulated by governments, in order to prevent this development from escalating.

References

Edelman, B., Ostrovsky, M., & Schwarz, M. (2007). Internet advertising and the generalized second-price auction: Selling billions of dollars worth of keywords. American economic review, 97(1), 242-259.

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The world is becoming increasingly digital, sometimes too fast to keep up with. Therefore, startups are under massive pressure to keep innovating and scale quickly in a bid to keep up with big tech companies. Since startups don’t have the same access to capital and knowledge as the big tech players, they might not survive by trying to invent everything themselves. Because of that, sometimes it’s better to copy than to invent. Especially since some valuable lessons can be learned from big tech companies about leveraging digital ecosystems, data and customer-centric approaches.

Lessons from Big Tech
The most important lesson that can be learned from big tech companies is the importance of creating a digital ecosystem. As highlighted by Weill and Woerner (2015), companies that effectively build a digital ecosystem of services are outperforming their competition. To be specific, “companies that had 50% or more of their revenues from digital ecosystems and understood their end customers better than their average competitor had 32% higher revenue growth and 27% higher profit margins than their industry averages” (Weill & Woerner, 2015). An example of this is Amazon, which integrated third-party products, a branded platform and a match between customer needs and providers into a digital ecosystem.
This brings us to another important lesson, which is the shift from linear value chains to more collaborative ecosystems. Traditional businesses focus more on controlling as much of the value chain as possible. However, big tech on the other hand often chooses to let others participate (Weill & Woerner, 2015). Apple is a great example of this, because the company allows app developers to participate in their ecosystem by offering apps in Apple’s app store. This is a win-win situation because app developers can offer their apps to a big audience, and Apple increases the value of its ecosystem. Startups can utilize this by creating a plug-and-play solution where others can participate in their ecosystem or making a product that can be integrated with other platforms.
A third critical factor is customer knowledge. Google and Amazon, for instance, gather a lot of customer data and use this to deliver personalized experiences (Weill & Woerner, 2015). Even with limited resources, startups can use affordable analytics software to gather insights on customer behavior and use this to improve the overall experience for their customers.

My Take: Startups Should Think Ecosystem-First
In my opinion, it is of great importance that startups start adopting an ecosystem-first approach. While it is easier to just focus solely on more linear product development, it has been shown that companies can increase their growth potential significantly by adopting a digital ecosystem. A SaaS startup for instance, could start with a core product and expand it into other markets by integrating with other popular tools and platforms.
However, startups have to be careful. Building a digital ecosystem might require large investments in technology and partnerships. This can be difficult when your core product is not strong enough. Therefore, it might be the best option for startups to start with a niche product and then slowly integrate it into other markets and products to build an ecosystem. This way, startups can then start accelerating their growth exponentially.

References:

Weill, P., & Woerner, S. L. (2015). Thriving in an increasingly digital ecosystem. MIT sloan management review, 56(4), 27.