2 key challenges:
To understand our client’s business better, we used Somin’s proprietary omni-sourced machine learning algorithm - Omni-Sourced User Profiling to compile anonymized audience data from multiple sources.
The Omni-Sourced User Profiling analyzed more than 166.5K social accounts across multiple platforms that are associated with the brand and its industry. From there it analyzed approximately 2,844,766 posts through both computer vision (CV) and natural language processing (NLP). This resulted in the collection of 5,604,442 data points used for the collaborative filtering (CF) process.
We then used our AI User Analysis to help Citibank CEE’s campaign managers understand and cluster their audience personas better with machine-observed interests, behavior, and traits. They were then able to use these insights as a guide to inform their creatives and messaging.
Through the analysis of the data collected, we defined the targeting for 1 campaign through 124 ad sets with 525 ads. This was only made possible with AI.
Personas were then grouped together through long-tail targeting based on their highest probability of conversion. Once these groupings were defined, they were tested through an automated A/B optimization process that was geared towards the brand’s goals.
124 ad sets and 525 ads were optimized every 30 mins. Automated and tuned towards achieving our business goals. Listed are the number of actions taken by the platform and the estimated time saved to generate the improvements in campaign results.
Citibank CEE increased their spends through SoMin by 2x and applied the technology to other lead generation activities such as personal loans.
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