This video is part of a series with Jill Konrath, Bestselling Author and LinkedIn Top Sales Influencer and Rudy Agovic, Chief Analytics Officer at Clarity Data Insights. Agovic discusses the three biggest mistakes he sees people making in AI from a marketing perspective. The first mistake is a lack of proper metrics, which can lead to a disconnect between what the business wants and what the technology delivers. The second mistake is buying into the hype around AI without doing proper research or having realistic expectations. The third mistake is treating AI as something that you build and forget, without considering the need for continuous reevaluation, retraining, and reassessment.

This video is part of a series with Jill Konrath, Bestselling Author and LinkedIn Top Sales Influencer and Rudy Agovic, Chief Analytics Officer at Clarity Data Insights. This episode is about the application of Artificial Intelligence (AI) in B2B marketing for manufacturing. Rudy suggests three key questions marketers should ask when considering AI: 1) What problem should AI be applied to? 2) Do I have the right data to tackle this problem? 3) Are my expectations with respect to this application of AI realistic? He emphasizes the importance of choosing low-risk, high-return problems, ensuring the availability of quality data, and setting realistic expectations for AI outcomes.

This video is part of a series with Jill Konrath, Bestselling Author and LinkedIn Top Sales Influencer and Rudy Agovic, Chief Analytics Officer at Clarity Data Insights. This episode is about the key strategies marketers can use to assess the value of their AI investments. Agovic suggests four dimensions to consider: assessing the current value of the AI approach, assessing the ongoing value of the AI use, considering HR costs, and considering infrastructure costs. He emphasizes the importance of defining measurable metrics, monitoring the performance of AI models over time, considering the high turnover rate in AI and data science fields, and the potentially high costs of maintaining AI solutions in the cloud.

This video is part of a series with Jill Konrath, Bestselling Author and LinkedIn Top Sales Influencer and Rudy Agovic, Chief Analytics Officer at Clarity Data Insights. Agovic discusses the three biggest mistakes he sees people making in AI from a marketing perspective. The first mistake is a lack of proper metrics, which can lead to a disconnect between what the business wants and what the technology delivers. The second mistake is buying into the hype around AI without doing proper research or having realistic expectations. The third mistake is treating AI as something that you build and forget without considering the need for continuous reevaluation, retraining, and reassessment.

This video is part of a series with Jill Konrath, Bestselling Author and LinkedIn Top Sales Influencer, and Rudy Agovic, Chief Analytics Officer at Clarity Data Insights. They discuss the importance and benefits of knowledge graphs, especially in the field of marketing. Agovic explains that knowledge graphs are an emerging technology that can help marketers understand and visualize the relationships between different aspects of their business, such as marketing campaigns, sales cycles, and product cycles. He also highlights that knowledge graphs can provide valuable insights, drive business decisions, and serve as training data for machine learning models. 

In this era of data-driven decision-making, organizations increasingly turn to AI-enabled analytics to extract valuable insights from vast amounts of data. However, the journey toward successfully implementing these advanced analytics solutions can be fraught with challenges.

One of the primary hurdles faced by companies is ensuring the quality and accessibility of data. This article delves into the intricacies of data quality and accessibility, explores their impact on AI-enabled analytics, and discusses strategies for overcoming these challenges.

I recently attended CONEXPO, the construction industry trade show held every three years. In my conversations with multiple marketing leaders, the big question was:

I love marketing technology. As a sales enablement professional with over thirty years of applying new technologies to help salespeople succeed, the last few years have been exhilarating. 

You may not have heard about knowledge graphs or graph databases, but they have been around for a while. They are a part of AI and have been used to identify patterns in lots of interconnected relationships.

Knowledge graphs are now becoming mainstream as a way to glean insights from tangled or interconnected relationships such as customer, marketing, and sales enablement data. It is much slower and harder to find patterns in these connections with a SQL database.