MarTech Interview with Ulisse Sarmiento, Regional Vice President of Solution Consulting for EMEA at Tealium

Tealium is dedicated to advancing AI/ML technologies to enhance value delivery to customers, underpinned by a strategic approach to product development.

1. How does Tealium differentiate between the terms AI and ML, and where can one find a basic overview of these definitions in the context of Tealium’s strategy?

Tealium differentiates between AI (Artificial Intelligence) and ML (Machine Learning) as distinct but related technologies that are integral to its go-to-market strategy. A basic overview of these definitions and their distinctions can be found in the context of Tealium’s strategic discussions or educational resources provided by the company. AI generally refers to the broader concept of machines being able to carry out tasks in a way that we would consider “smart,” while ML is a subset of AI that involves the idea that machines can learn from data, identify patterns, and make decisions with minimal human intervention.

2. According to Tealium’s strategic plan, what is the company’s perspective on the necessity of AI/ML for businesses to remain competitive, and how does Tealium’s platform support companies in this endeavour?

Tealium views the use of AI/ML as critical for businesses to remain competitive in the face of the growing complexity and volume of customer data. The company’s strategic plan highlights a belief that the vast amount of customer data available today has surpassed human capacity for effective monitoring and management. As such, Tealium argues that companies must adopt AI/ML technologies to keep pace with competitors who are already leveraging these advancements. Tealium’s platforms are designed to help companies filter and condition their data to maximise its utility for any AI/ML solutions they choose to implement, thus positioning itself as an enabler of AI/ML adoption rather than a direct provider of these technologies.

3. What type of AI/ML product did Tealium release, and how does this reflect the company’s ongoing commitment to AI/ML, considering its primary function as a data platform rather than a dedicated AI/ML platform?

Tealium released an ML product, specifically an autoML tool, demonstrating its ongoing commitment to investing in AI/ML technologies. This release underscores Tealium’s role in the AI/ML ecosystem as a data platform that enables the use of AI/ML technologies rather than competing as a dedicated AI/ML platform. Tealium positions itself as an AI/ML enablement platform, suggesting that its core competency lies in facilitating the use of AI/ML by improving data quality and accessibility, rather than directly competing with dedicated AI/ML platforms, Customer Data Platforms (CDPs), Identity vendors, analytics tools, and other specialised technologies, even though it offers a small amount of overlapping functionality.

4. What market forces are creating urgency for companies to increase their maturity in using AI and ML techniques, and how do these forces relate to the overall need for adopting such technologies?

The urgency for companies to enhance their AI and ML maturity stems from several market forces, including the sheer volume, variety, and velocity of data, which has become overwhelming for traditional processing methods. Economic pressures for greater efficiency and quality decision-making also play a critical role, as companies seek to optimise operations and make more reliable decisions based on data insights. Additionally, increasing restrictions on personal data necessitate more sophisticated approaches to data management and utilisation, pushing companies towards AI/ML as solutions to navigate these challenges while maintaining compliance and safeguarding privacy.

5. How does Tealium propose utilising AI/ML at different levels of application, particularly in relation to Customer Data Platforms (CDPs) and enhancing customer experiences, and what specific functionalities does it offer to support AI/ML projects?

Tealium suggests a multi-level approach to applying AI/ML technologies. At a general level, AI/ML adoption can significantly vary across organisations but is crucial for staying competitive. Specifically related to Customer Data Platforms (CDPs), AI/ML can assist administrators in creating optimal CDP setups and enhance customer experiences by leveraging data insights for personalised interactions. Tealium itself offers a platform that can serve as a real-time source of high-quality data, providing basic propensity scoring with its Predict feature, and facilitating the activation of AI/ML project outputs. This structured approach enables businesses to implement AI/ML in a way that directly supports their strategic objectives, from backend data management to frontline customer engagement.

6. Considering the hype around Generative AI, how does Tealium advise companies to approach their AI/ML strategy in light of the rapid evolution and wide range of AI/ML solutions available, including built-in GenAI capabilities in commonly used software products?

In light of the significant attention Generative AI (GenAI) has received, Tealium advises companies not to confuse the specific applications of GenAI with the broader discipline of AI/ML. While GenAI represents a transformative technology that has been democratised, AI/ML solutions encompass a broad and quickly evolving field that offers various vectors of value. Tealium emphasises the importance of strategic planning and avoiding hasty decisions in adopting AI/ML technologies. The company points out that many software products, including those from OpenAI, Google, and Microsoft, are increasingly integrating GenAI capabilities, suggesting that companies may not need to invest in dedicated products to benefit from AI/ML advancements. However, larger enterprises or those requiring more in-depth analysis and higher levels of security and privacy will need to consider a range of AI/ML approaches to unlock the full value of these technologies.

7. Can you explain how Tealium’s approach to AI enables businesses to enhance their AI initiatives?

At Tealium, we’re focused on providing businesses with the high-quality, consented, and filtered data they need in real-time. This capability is crucial for fueling AI initiatives. By ensuring the data is immediately available, we enable businesses to apply AI insights across any part of the customer journey effectively.

8. How does Tealium help in breaking down data silos, and why is this important?

Breaking down silos is a key aspect of our approach. Data silos create barriers within organisations, leading to inefficiencies and missed opportunities. By integrating data across various sources and platforms, we reduce data latency and enable instant activation of insights. This seamless integration helps businesses own each moment that matters by being more responsive and personalised in their customer interactions.

9. What impact does reducing data latency have on businesses?

Reducing data latency has a transformative impact. It means that the insights derived from data are fresher and more relevant, allowing businesses to act on opportunities in real-time. This immediacy can be the difference between winning or losing a customer, making an impactful decision, or missing the mark. In today’s fast-paced environment, being able to quickly leverage AI-driven insights can significantly enhance a business’s agility and competitiveness.

10. Can you give an example of how businesses can use Tealium to fuel instant activation and own moments that matter?

Let’s say a retail company wants to personalise offers for their customers based on browsing behaviour and past purchases. With Tealium, they can instantly capture and analyse this data, apply AI to predict future buying behaviours, and deliver personalised offers in real-time during the customer’s next visit to the website or app. This level of personalisation and timely engagement ensures the business capitalises on the moment, potentially increasing sales and improving customer loyalty.

11. Could you elaborate on how “Tealium for AI: Collection” specifically supports AI models with data collection?

“Tealium for AI: Collection” is crafted to ensure that both internal and external AI models have access to the right data exactly when they need it. It’s an enterprise-grade suite of tools tailored for the collection, standardisation, enrichment, and streaming of clean, trusted customer data directly to any AI platform, including all the major cloud services.

12. What makes this set of tools enterprise-ready, and why is that important?

Being enterprise-ready means our tools are scalable, secure, and capable of handling the complex data needs of large organisations. This is crucial because enterprises often work with vast amounts of data across different sources and systems. Our solution ensures that this data is not only accurately collected but also harmonised and enriched to provide a comprehensive view of the customer. This facilitates more effective AI-driven insights and actions.

13. Can you discuss the importance of standardising and enriching data for AI models?

Standardising and enriching data are fundamental processes for ensuring the quality and usability of data in AI initiatives. Standardisation brings consistency to how data is formatted and structured, making it easier for AI models to process and analyse it effectively. Enrichment enhances the data by adding relevant context or combining data points to create a richer dataset. Together, these processes ensure that AI models are fed high-quality data that is reflective of the real-world scenarios they are meant to interpret or predict, leading to more accurate and actionable insights.

14. How does Tealium ensure the cleanliness and trustworthiness of the data streamed to AI platforms?

Our approach to ensuring data cleanliness and trustworthiness involves multiple layers of validation, standardisation, and verification processes. Before data is streamed to any AI platform, it undergoes rigorous checks to remove inaccuracies, duplicates, and irrelevant information. We also implement consent management practices to ensure that the data is not only clean but also collected and used in compliance with privacy regulations. This comprehensive process guarantees that the data our clients rely on for their AI initiatives is both clean and compliant, fostering trust and reliability in their AI-driven outcomes.

15. Can you give us a brief overview of what “Tealium for AI: Activation” offers?

“Tealium for AI: Activation” is our modern platform built for activating AI insights and outputs across various tools and channels. It’s highly composable, meaning it can adapt to different customer needs and scenarios, whether that involves real-time AI outputs, creating targeted audiences, or generating batch-based lists for marketing and operational activities.

16. How does this platform adapt to different activation methods?

Our platform provides customers with an extensive toolkit that supports multiple activation methods. This flexibility ensures that whether our customers need to deploy AI insights instantly, target specific audiences with precision, or manage large-scale, batch-based activations, they can do so efficiently and effectively. It’s about giving businesses the capability to leverage their AI models in the most impactful way, regardless of the tool or channel they’re using.

17. What makes “Tealium for AI: Activation” essential for businesses using AI?

It bridges the gap between AI insights and actionable outcomes. By providing a platform that simplifies and streamlines the activation of AI models, businesses can more quickly and effectively implement AI-driven strategies. This means not just understanding what your data is telling you, but being able to act on it in a timely manner to enhance customer experiences, improve operational efficiency, and drive business growth.

A Customer 360 Strategy – Tealium and Cloud Data Warehouses

The enterprise data landscape has significantly changed with the widespread adoption of Cloud Data Warehouses (CDWs) and Customer Data Platforms (CDPs). CDWs, primarily managed by IT and data teams, serve as a central data repository, whereas CDPs, originally utilised by marketing teams, have gained such popularity that IT departments are frequently involved. Given the overlap in functionalities between CDPs and CDWs, it’s crucial to refine the messaging towards a more technical audience. Instead of viewing CDPs as redundant, they should be presented as complementary to CDWs. The key is to focus on the unique advantages of CDPs, such as enabling real-time data activation and improving data collection quality, thereby enhancing the overall capabilities of the CDW architecture.

1. To start, could you explain the “RAM and Hard Drive” analogy in the context of Tealium’s data strategy?

Absolutely. In this analogy, the Customer Data Platform (CDP) represents the RAM, enabling real-time data activation with features like ID resolution, consent adherence, data transformation, and activation in under 200 milliseconds. It’s about quick access and real-time processing. On the other hand, the cloud data warehouse (CDW) or other data storage solutions act as the Hard Drive, providing a lifetime storage solution for CRM, transactional, analytical, and historical data, which we refer to as the “Golden Customer Record”. Together, they create a comprehensive view of the customer, combining immediate access and long-term storage for a full 360 customer strategy.

2. What are the limitations of having all data pass through a data warehouse before activation, and how does Tealium address these challenges?

The primary limitation is the inability to engage customers in real-time. If data needs to go through the warehouse first, it delays actionable insights, hindering timely customer engagement. Tealium’s approach, by directly connecting the CDP with cloud data warehouses, bypasses this bottleneck, enabling real-time data exchange. This allows businesses to engage with customers at critical moments without the lag associated with data processing and warehousing.

3. Can you delve into the unique benefits of Tealium’s “minimal copy” approach to customer data?

Our “minimal copy” philosophy strikes a balance between the need for real-time engagement and the efficiency of data storage. Instead of duplicating all data within the CDP, we only copy what’s necessary for immediate activation. This not only reduces storage and processing requirements but also ensures that data is used efficiently for enhancing customer experiences. It’s about providing the best customer experience (CX) by leveraging real-time data without the overhead of unnecessary data replication.

4. How does Tealium’s approach differ from the “warehouse native” or “composable” CDP models advocated by others?

Tealium’s model is designed to offer the best of both worlds. Unlike “warehouse native” models that might delay real-time engagement or “composable” models that can introduce complexity and potential flaws, our approach focuses on rapid, real-time data exchange. By establishing direct connections with cloud data warehouses and using unique streaming technologies, we offer unmatched real-time capabilities. This enables immediate customer engagement and insights enrichment without the drawbacks of other models.

5. Finally, what future enhancements can we expect from Tealium in enhancing the customer 360 data strategy?

We’re continuously innovating to enhance real-time data capabilities. Our immediate focus is on expanding direct connections with leading cloud data warehouses like Snowflake, Databricks, AWS, and Google. Additionally, we’re exploring advanced data sharing and querying capabilities between the CDP and CDWs for even more seamless activation. Our goal is to remain at the forefront of providing tools for businesses to engage with their customers in the most relevant and timely manner.

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