We help your SEM campaigns by cutting spend and/or
bringing in growth.
Whether your objective is to increase conversions or revenue, or spend more efficiently, we build custom models for every client to match your data and business objectives. Historically, we can deliver up to 30% of campaign improvement. And that's our core product.
As a part of bid optimization, we also provide bid multiplier optimization through data science. Today, ad platforms such as Google Ads offer many bid multipliers, and it's increasingly challenging to manage them all correctly. We can analyze your campaigns and optimize multipliers for you.
We support bid optimizations for search (keyword) as well as shopping (product) campaigns.
While we optimize bids down to keyword level for search campaigns, we also support atomic level of bid optimization in shopping campaigns: product item. If you have different yields for the same product group (e.g. different seller ratings, item freshness), for example, we adjust our bids to more granular level than predefined product groups.
In addition to multiple channels, we also support multiple platforms: Google Ads (AdWords) and Bing Ads. Using our UI, you can monitor and manage both campaigns in one place.
We support international accounts on those platforms as well. If you have multi-currency and/or multi-timezone accounts, we are supporting them today.
Once we obtained agency access from your accounts, our application seamlessly and automatically integrates your data from platforms, builds models, and performs bid updates directly through platform APIs. While all of our activities are transparent to you, heavyliftings are done by us behind the scene.
Our platform has been built with scalability from day one. We are handling hundreds of millions of bid updates everyday.
We provide UI application so that you can monitor and manage campaigns closely as well as guide our models to your desired objectives and target numbers.
Through agency access, we obtain your historical campaign performance data from platforms automatically. Custom data such as internal funnel data, revenue data, and non-SEM data also help us train our models more intelligently.
These data sources are examples that we support today: