Revolutionizing Digital Marketing in B2B: Insights from Pixis AI’s Latest Research

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As we usher in the New Year, the Pixis AI team stands at the forefront of a significant breakthrough in digital marketing. Vivek Vishwas Vichare,  Head of Data Sciences along with Humeil Makhija, Data Scientist, and S. Sreyas Chaithanya,  AI Product Manager, have co-authored the seminal paper titled, “Modeling Approach for Enhanced Market Expansion in Digital Marketing in B2B Space”.

A digital marketing research by the Pixis team promises to revolutionize the B2B space.

This work introduces a novel methodology in lookalike modeling, a game-changer in identifying and targeting potential B2B customers.

We caught up with Vivek Vichare, one of the key authors and the conversation delved into how this research can help revitalize a brand’s approach to digital marketing campaigns, particularly in terms of scalability. Here are a few insights on the research and its impacts:

Delving into the Objective of the Research

Vivek explained, that the core of this research lies in expanding market reach by pinpointing potential customers who mirror the behavioral, demographic, and socioeconomic attributes of existing high-value customers. The methodology is rooted in creating a ‘seed set’ of existing customers, notable for their high lifetime value or robust brand engagement. Utilizing advanced machine learning techniques, the team uncovers commonalities within this seed set and a larger pool of customers. This approach is theoretical and intensely practical, suggesting lookalike users from extensive datasets, employing a fast, multi-graph-based approach. It’s a blend of efficiency and scalability, capable of processing datasets with up to 80 million interactions.

What sets this model apart is its remarkable features. It’s designed for large-scale deployment, maintaining a consistent recommendation throughput of 500 recommendations per second. The experimental results are equally impressive, showing a significant improvement in precision performance with a 90% precision rate with the seed set. Moreover, its innovative pipeline can operate even in the absence of an actual first-party client seed set, pre-processing various customer sources to generate an authentic seed set.

Impact on Digital Marketing

This research is a milestone in digital marketing, particularly in its application to B2B marketing. It ensures that advertising efforts are laser-focused on the most relevant audience segments. Especially in the digital marketing domain, where computational efficiency and data complexity are major challenges, this methodology stands out. It presents an alternative approach to generating an authentic seed set in the absence of first-party client data.

It showcases the importance of precision targeting in digital marketing, offering a  sophisticated solution that elegantly navigates the complexities of user data and the need for computational efficiency.

Importance for Brands and Targeting

Previously, strategies were mainly focused on leveraging platforms like LinkedIn, which offered a data-rich environment for targeting professional audiences. However, this approach had inherent limitations in terms of reach and diversity of platforms. This new method utilizes a broader spectrum of data, including third-party sources and product reviews, to identify and understand high-value customer profiles. The crucial innovation in this research is the ability to extrapolate these profiles to formulate lookalike audiences that can be targeted across various social media platforms, moving beyond the constraints of a single platform like LinkedIn.

This expansion to a cross-platform approach significantly bolsters the effectiveness of marketing campaigns. It allows for the design and execution of strategies that are not only more inclusive in terms of audience reach but also more precise and efficient. As a result, B2B clients benefit from engaging with a broader and more specifically targeted audience pool, which can lead to improved campaign performance, including higher engagement, better lead generation, and increased conversions.

Conclusion: The Possibilities That Await

In terms of future developments for this model, there’s a clear path toward expanding its application beyond the current focus on B2B campaigns. The plan is to adapt and test this framework in the B2C space, where the dynamics of customer engagement and targeting differ significantly from B2B outreach. This expansion would not only diversify the model’s utility but also allow for a more nuanced understanding of consumer behavior across various market segments.

Moreover, there’s potential for evolving this research into a holistic, cross-platform lookalike audience platform. Such a platform would integrate various social media and digital channels, offering a unified solution for creating and deploying targeted marketing campaigns. This development would be a major leap forward, as it would enhance the capability to tailor marketing strategies across different platforms, ensuring a more seamless and efficient reach to diverse audience groups. The envisioned platform would represent a significant enhancement, making the model an indispensable tool in the arsenal of digital marketing, catering to a wide range of clients and marketing needs.

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