Problem
In our understanding of Turtledove we believe it only supports 2 types of advertising: Retargeting and contextual. This will incentivize advertisers to follow one of the following strategies:

• Create ads that will follow people around the web.
• Take a shot gun approach with contextual and buy low CPM ads to bombard users with ads.

According to Nielson, retargeting is one of the most disliked forms of advertising among consumers (link). Another report (link) shows that 79% of users think they are being tracked due to retargeting ads. Even though retargeting is an important use case for a lot of brands, it represents a small percentage of total data-driven advertising spend (think about the last time you went to tide.com).

That’s because most sophisticated advertisers have already progressed from retargeting. For the most part, they want to leverage their own first-party data, much of which has been volunteered to them by long-term consumers, through loyalty programs, etc. This data can be used to model the characteristics of their most loyal customers, and find where those same characteristics may be present elsewhere in the market – where are their next 100k most loyal customers?

Therefore, we believe the focus should be on allowing brands to find users who might be interested in buying their products. There are several key methodologies that turtledove doesn’t address:

1. Audience Modelling: We should be trying to preserve sophisticated targeting methodologies, that leverages a brand’s valuable first party data to find the next 100k users most likely to be interested in a product, show it to them with reasonable frequency, and pay a healthy price. Audience modeling helps consumers discover new products, and it allows small brands to get traction and cut through the noise with the consumers that are likely to be interested in their new products.
2. Audience Intersection: Another methodology that helps brands find new users is using combination of audiences. Brands use sophisticated models to understand the type of users they want to reach. If they are limited to a single interest-based segments, they will end up wasting money on buying ads they don’t need. A good example here is: A small real estate firm is looking for highly affluent individuals with an interest in real estate in a specific DMA. They try to target "interested in real estate and finance" in the Denver DMA that uses 2 ands, and a geo target. Without these intersections they will need to spend precious marketing dollars just to figure out what works.

Publisher and User Impact
Today publishers of all sizes can realize value in the ad space on their sites because advertisers believe that they can find their customers on these sites. Data driven advertising especially helps bring value to publishers with a smaller footprint (local news, sport blogs, etc). However as described above, brands leverage tools beyond just site visits and context to figure out where they can reach their potential customers. If advertisers lose the ability to easily discover new customers, they will not know how to effectively value publisher inventory. Since advertisers still need to reach their customers, this will either lead to them taking a shotgun approach and pay less per ad or move their budgets to a few big publishers (CNN, NYT, ESPN etc). To make up for the lost revenue, publishers will either have to show more ads per page or erect paywalls, neither of which are ideal or economically feasible outcomes for the end user or the long-term future of the internet.