Data analytics & AI.
As a renowned data analytics agency, we offer comprehensive data strategy and activation across a variety of platforms while offering a full transparent basis for our clients.
With our Google Cloud and Adobe certification we are able to leverage CDP and other data warehouses for multiple use cases for brands. Contact Bidmath for a full consultation and data discovery
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Custom algorithm
A custom algorithm is a set of bidding dynamics that are generated on an individual campaign basis and designed to deliver outcomes that are aligned to a specific advertiser’s goals.
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Customer data platform
A Customer Data Platform (CDP) is a technology that helps organizations centralize, manage, and activate customer data from various sources.
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Google Cloud for Marketing
Utilize the suite of tools across analytics, data warehouse and AI modelling for marketing
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Google Analytics
Implement and make the most out of the analytics platform, resulting in cost efficiencies
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Machine learning & AI
Leverage machine learning models for better optimisation of digital media campaigns
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Data strategy
Deploy audience segmentation, activation and compliant collection of first-party data.
Why should a brand leverage AI for marketing?
- 01Faster optimizations and decision-making versus human involvement.
- 02Predictive algorithms based on a machine learning-fueled data set.
- 03More accurate lookalike audiences based on models.
- 04Dynamic Personalization leads to better customer experience.
- 05A variety of analytical models to extract insights from campaigns
- 06Increase media efficiencies to an optimal level
What solutions does Bidmath offer?
Technology consultancy & data analytics
Our platforms experts implement and manage DMP/CDPs for clients, Orchestrate and activate data pipelines and run advanced analytics.
AI custom algorithm
We develop AI driven custom first party data algorithms for programmatic display and video across multiple platforms
First-party data strategy
Responsibly build and activate first-party data at scale to enable audience first and personalized marketing. Leveraging a tech agnostic approach to ensure data collection, segmentation and activation across multiple platforms.
Data partnerships
Leveraging valuable 2nd party data segments are more suited to the campaign goals compared to 3rd party aggregated sources. Access to unique data, specific partnerships hold access to unique customer data that cannot be accessed through a marketplace.
CDP for marketing
Our data hub has deep knowledge in pushing the boundaries of marketing technology such as customer data platforms. A Customer Data Platform (CDP) is a technology that helps organizations centralize, manage, and activate customer data from various sources. Some benefits of leveraging a CDP for marketing include:
A CDP can help you create a single, unified view of each customer, allowing you to create more targeted and personalized marketing campaigns.
By centralizing customer data, a CDP can help you streamline your marketing efforts and reduce the time and resources spent on managing customer data.
A CDP can help you deliver a more seamless and personalized customer experience across channels, leading to higher customer satisfaction and loyalty.
By providing insights into customer behavior and preferences, a CDP can help you optimize your marketing spend and drive better returns on investment.
A CDP can help you quickly test and iterate on marketing campaigns, allowing you to quickly respond to changes in the market and customer needs.
What is a custom bidding algorithm?
A custom algorithm is a set of bidding dynamics that are generated on an individual campaign basis and designed to deliver outcomes that are aligned to a specific advertiser’s goals. It allows advertisers to own not only the data they input, such as the log level data file or data transfer found in DV360 or Campaign Manager, but also the resulting learnings.
How does it work using AI?
Usually, these algorithms are supplied by demand-side platforms and so can’t be finely tuned to an advertiser’s customized goals. Advertisers use their own first-party data to power their custom bidding algorithms, which makes it possible to focus on factors relative to impression level data and therefore optimization based on historical data.
Understanding, evaluating and bidding on the variables or attributes of an impression at the price that makes sense to the advertiser can be achieved through multiple optimization methods, but it becomes most scalable through the development of custom models designed to achieve the advertiser’s business objectives.