Artificial Intelligence has revolutionized the landscape of digital marketing, online advertising, and search engine optimization: this is certain, as evidenced by the hype and experimentation that have been ongoing for months with these new technologies, capable of creating opportunities that allow companies to reach their audience in more targeted and effective ways.
At ByTek, we are developing methodologies and platforms that leverage new technologies and algorithms to integrate and enhance company data through new AI-based models, for truly data-driven marketing campaigns “empowered” by artificial intelligence.
This “new course” in the field of marketing and martech “mastery” requires mastering diverse knowledge and skills. That’s why, in collaboration with Talent Garden, we are also developing an educational program, starting in October 2023, a true Masterclass on AI for Marketing. Registrations are open at this link.
ByTek Platform: A New Approach to AI-Based Data Strategy for Marketing
Profound transformations are underway in the field of digital marketing, where the increasing automation of advertising platforms requires proper goal definition, care for first-party data, and creative management to maximize campaign effectiveness.
The focus on customer acquisition and the value of acquired customers drives companies to consider tools like CDP and DMP to better understand users. However, often these efforts get stuck in complex integration processes with corporate systems and external promotion platforms.
The approach to data usage is changing, as the focus on front-end attribution and tracking proves limited. The ByTek Platform solution aims to unify internal, navigational, and third-party data to gain overall understanding and strategic control.
The goal is to enhance the efficiency and effectiveness of marketing strategies through the use of hybrid and enriched data, across 3 phases:
- Data Collection: Enabling service for data collection and enrichment of existing data.
- Data Modeling: The true core of the solution, involving data acquisition from platforms and modeling for audience generation.
- Data Activation: Exposing and/or synchronizing data in marketing platforms for analysis and direct activation. In this phase, it’s under consideration (see “business model” section) whether the model should involve direct activation on certain preferred platforms.
Applications of AI in Marketing: Some Examples
Companies today gather a vast amount of data and aim to improve personalization, operational efficiency, and customer interaction. Implementing AI in marketing allows extracting value from data to achieve ambitious growth objectives.
And this is not exclusive to big brands; on the contrary, the opportunities for AI usage are becoming broader and accessible across various industries and business sizes.
Data Analysis and Audience Segmentation
AI can analyze large amounts of data quickly, enabling companies to gain a detailed understanding of their audience. Through machine learning, it’s possible to identify consumption patterns and preferences, helping businesses segment users based on demographic, behavioral, and purchase patterns. This allows for more accurate personalization of every marketing strategy, regardless of the channel.
Enriched Bidding for Paid Campaigns
Enriched Bidding is an advanced strategy in digital marketing that optimizes the use of first-party data in automated campaigns. This approach stems from the need to personalize bids based on specific user value, countering the negative impact of standardized offers. Traditional advertising platforms often overlook this differentiation, compromising overall campaign performance. Enriched Bidding, as proposed by ByTek, focuses on implementing personalized bids to maximize campaign results through more targeted data usage.
Campaign Result Measurement and Budget Allocation
A separate chapter is dedicated to the world of measurement, essential for understanding the quality of work being done and for acting towards continuous improvement. Through marketing mix models, it’s possible to evaluate the effectiveness of each of the numerous touchpoints that make up a marketing strategy today, which is increasingly multifaceted and varied. This enables the correct allocation of budget to each channel, identification of the most performing activities in terms of ROI, and more.