Leveraging data to better understand which specific post-COVID-19 marketing and sales strategy or activity will be most effective in the new normal is crucial to growth and success. In a recent interview with SalesTech Star, Scott Schlesinger, Global Data, Analytics and Practice Leader, dives into the key challenges B2B teams are facing as the roadmaps for several industries have changed in 2020.
Interview Highlights & Takeaways:
Platforms are Evolving
The advent of Artificial Intelligence, Machine Learning, and Robotic Process Automation all offer game-changing capabilities for many large, global organizations – and the data required for the success of these solutions is vast and ever-changing. Ness extends the value of these investments by leveraging, NessifAI, a hybrid AI acceleration solution built on industry standards and an open-source framework created to support our client’s respective journey towards AI self-sufficiency.
Challenges to Optimizing Use
Integrity challenges are among the largest challenges in the way of truly optimizing all available data and leveraging it for positive business outcomes. It is important to focus on a firm foundation with trusted data and establish a governance framework to mitigate related risks to address items such as access and control standards.
Understanding the Data
New sources and types of data are being acquired and analyzed all the time. Once trapped in emails, personal files, and unstructured formats are being integrated with traditional/legacy data for a more holistic view of the business. Leaders across nearly every sector and geographic region are leveraging new tools and processes – including Artificial Intelligence – that improve overall performance.
Tips to Help Marketing and Sales Drive Better Outcomes
From a sales perspective, it is more common to see large enterprise sales teams leveraging analytics than individuals in smaller organizations. This allows them to seek out data to uncover new insights about their clients and opportunities they may have otherwise missed.
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