Zedosh and Datrics are changing the landscape of online advertising to get ready for a post-cookie internet, with their targeted data analysis algorithms that consider the historical and real-time buying patterns of individuals. Let's find out more about Zedosh's Attention® Engine.

Understanding Data Science Algorithms

Data science algorithms play a pivotal role in transforming raw data into actionable insights. These algorithms, ranging from regression models to neural networks, enable businesses like Zedosh to make informed decisions, predict trends, and enhance user experiences.

Tackling the Digital Advertising Hurdle

Millions of consumers shop online for everything from groceries to cleaning supplies, making online advertising the most competitive space for businesses. Many people still think that Facebook or Google ads are the silver bullet to their sales and digital marketing. But despite their size and dominance, iOS’ new privacy updates, and the upcoming replacement of 3rd party cookies, there is a huge opportunity to look outside of online behavior to find the right consumer at the right time.

With consumers now able to opt-out of being tracked on iOS and the increasing awareness of their privacy, the effectiveness of Google and Facebook ads is decreasing. The cost is going up and the ability to attribute spending is going down. As the ad is even less relevant to the people seeing it, the market is ready for a significant overhaul to finally rid itself of the many challenges it faces.

Zedosh's goal is to flip the ecosystem upside down. By placing the consumer at the forefront of the ad value chain, they are incentivized to share their most valuable attributes as consumers: their income and their spending habits. By enabling consumers to monetize their valuable attention to hyper-relevant ads, consumers can take back control of their online exposure to advertisers. . Although the engine is young, Zedosh has already managed to make a big difference.

The Power of Data Analysis Algorithms: The Solution

Datrics helped build and deploy data analysis algorithms to analyze customer purchasing behavior and their transactional history to optimize ads and target users with a high-interest probability in specific products or services at specific times.

• First, we implemented a static mathematical model that analyzes users' spending and scores them based on historical data such as how much they spent, their spending categories, and purchasing trends. Moreover, we simulated different purchasing behaviors to cover cases not addressed in the historical data we collected.
  
• Our data scientists analyzed hundreds of user profiles to find potentially influential categories and form user clusters based on their spending pattern similarities.
• We then built an ML-powered algorithm that could analyze and predict customer purchasing behavior with greater accuracy. With Datric's algorithms, Zedosh doesn't need to track users using cookies or pixels without users' direct consent to target and attribute the ad. Our static and ML algorithms access user spending habits via Open Banking to deliver live updates of user purchasing behaviors.
• Our data scientists have built several automated reports to help Zedosh analyze the effectiveness of ad campaigns and business metrics. With these reports, Zedosh can track where their Attention Exchange® Engine is thriving, which areas are struggling, and if they are on the right track to achieve the desired results.

Algorithms for Data Science: Beyond Traditional Analysis

Modern businesses use data science algorithms to stay competitive. These algorithms, enhanced by machine learning and AI, analyze past behaviors and predict future trends, enabling companies like Zedosh to remain ahead with accurate analysis.

Here's a brief mention of some of the top algorithms used in data science, particularly those that go beyond traditional analysis:

1. Supervised Learning: Analyzes structured datasets by utilizing training data to create a function that could be applied to other datasets.
2. Unsupervised Learning: Transforms raw datasets into a structured format, ideal for unlabelled data.Reinforcement Learning: Employs a trial and error approach to instruct agents to make optimized decisions within a given environment.
3. Decision Tree: A classification and regression tool that uses a tree-like model of decisions.
4. Linear Regression: Presumes a linear relationship between input and output variables, depicting this relationship through a linear equation.
5. k-Nearest Neighbors (k-NN): A memory-based algorithm used for classification and regression tasks.
6. K-means and K-median Clustering: Unsupervised algorithms utilized for clustering analysis, aiming to minimize variances within clusters and the sum of absolute distances respectively.

What is an Advantage of Using a Fully-Integrated Cloud-Based Data Analytics Platform?

Zedosh stands out by compensating consumers directly into their bank accounts for their undivided attention to video ads. This innovative approach enables brands to convey their message, values, and engage consumers, all while reducing costs per click and amplifying sales. For instance, a £500 campaign for Elliott Footwear yielded results comparable to a £13,185 expenditure on Facebook ads.

‍Datrics' Breakthrough: A Powerful Attention Exchange Engine for Online Advertising

Based on the Zedosh’s requirements, Datrics helped to establish a powerful Attention Exchange Engine for online ads. Datrics delivered a user-friendly and out-of-the-box data analytics platform that was fully deployed in the cloud.

With built-in analytics and reporting, Zedosh can perform complex data analysis to address a wide range of business needs. What’s more, Zedosh’s data analysts can customize their reports or change them without the need to write a new piece of code or wait for engineers to make the necessary changes.

In contrast, "conventional" data analytics tools typically require an average of 2-3 business days to fix a bug that could severely damage a company’s reputation. Datrics needs less than 20 minutes to get the system up and running. Since everything is running in the cloud, users don't need to re-install the app or download any updates.

Our cooperation with Zedosh has grown from occasional consulting and development services into a full-scale partnership. As for Zedosh, the company reports that with purpose-driven ad campaigns powered by Datrics' algorithms, their clients can save on advertising while significantly boosting their engagement and building a loyal community.

"Datrics has allowed us to gain very powerful insights about out audience’s behaviour as consumers. Using their platform, we were able to quickly turn those insights into hyper-target audience for our advertisers, placing the right as in front of the right consumer at the right time."

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