First-Party Data Analysis
Put your data to work for you.
The demise of third-party cookies threatens to disrupt targeted advertising, but we are determined not to let that happen. As a result, first-party data is more valuable than ever.
Using the data your company collects itself, we can create a more holistic customer view by tying together individual data sources such as web/app behavior, purchase history, and others to develop more robust marketing experiences.
Since first-party data is aggregated from a reliable source (you) and is generated by an audience relevant to your business (your customers), we can predict future patterns with confidence.
We use your first-party data to improve targeting accuracy, create holistic customer views, make content more relevant, improve custom data science applications, build more robust audiences, and close the attribution loop.
If you want a sustainable and constantly improving customer database, you need a strategy to collect consumer data yesterday. We’ve got the talent and the tech to deliver a consistent customer experience across your entire organization.
Propensity Modeling
Helps predict the likelihood that website visitors, leads, or customers will take certain actions.
Cluster Analysis
Grouping sets of data objects (customers, locations, etc.) into clusters based on the similarity of different variables.
Audience Segmentation
Layer criteria spanning first, second and third-party data sources for precision targeting and bespoke campaigns.
Algorithmic Personalization
Uses data from the behaviors and interests of the target audience to provide filtered digital content, targeted advertising, and differential product pricing.
Our Partners & Channels
63%
Of consumers expect personalization as a standard of service
47%
Marketers with fully-integrated marketing stacks are 47% more likely to use audience-level data to personalize customer experiences
58%
Of smartphone users feel more favorable toward companies whose mobile sites or apps remember who they are and their past behavior
Related case studies.
Portillo's Restaurant
Using cluster analysis to establish subsets of restaurants for more accurate benchmarking.
