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RevOps Unveiled: Navigating Trends, Challenges, and Innovative Synergies

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Shownotes

In this episode of Sunny Side Up, host Devan Cohen interviews Ken Lorenz, the VP of Global Sales at Riva International, where he oversees the company’s customer-facing sales team members. With a developer background, Ken’s passion lies in aiding customers in using technology to address business challenges. Over his extensive 30-year career, Ken has been pivotal in helping countless customers globally to select and implement ERP and CRM solutions. A seasoned member of ITA, Ken has contributed significantly to many content committees and has made numerous presentations at ITA collaboratives. Throughout the episode, Ken delves into the evolution of RevOps, the intersection of generative AI like ChatGPT in sales, and the importance of clean data in CRM. He also sheds light on the potential challenges and implications of integrating AI with customer data, emphasizing the importance of caution and privacy.


About the Guest

Ken Lorenz is currently the Vice President of Global Sales at Riva where he looks after all of Riva’s customer-facing sales team members. A developer by background, Ken is passionate about helping customers leverage technology to solve business problems. Over the past 30 years, Ken has personally helped tens of thousands of customers evaluate, select and implement ERP and CRM solutions, globally. As a long-standing member of ITA, Ken has contributed to many Content Committees and has presented numerous sessions at ITA Collaboratives.

Connect with Ken Lorenz

Key Takeaways

  • RevOps is a sector that has dramatically evolved from basic personal information managers to complex systems impacting sales and marketing processes over 30 years.
  • Modern technology advancements, including generative AI like ChatGPT, are poised to revolutionize sales processes, changing how businesses interact and transact.
  • The key differentiator in sales remains human touch and relationship-building, even as advanced AI tools gain prominence.
  • Data quality is paramount; without clean, accurate data, no amount of technology can yield successful results in the RevOps field.
  • Recent years have seen a proliferation of add-on technologies around CRM systems, increasing the complexity and cost of integration.
  • Organizations often grapple with data “swamps” instead of efficient data “lakes,” complicating the process of gaining insights and actionables.
  • ABM platforms have emerged as crucial tools to aggregate, analyze, and provide actionable insights, focusing on genuinely engaged accounts for businesses.
  • Integrating ChatGPT with RevOps systems presents opportunities and challenges, especially when handling sensitive, customer-specific data.
  • In regulated industries like banking and insurance, there is heightened caution about introducing any customer data into AI models, ensuring strict compliance and data protection.
  • Bad actors can exploit data, and with evolving large language models, there is a potential risk of data breaches or misuse, necessitating stringent safeguards.
  • Regulations might become stricter, with businesses potentially needing to disclose when content is AI-generated, emphasizing transparency in communication.

Quote

“I think it’s going to be very interesting to see how the next generation of salespeople leverage that technology and allow themselves to differentiate from their competitors.”

– Ken Lorenz

Highlights from the Episode

Could you share with us the fascinating journey of how the RevOps function has evolved?

Ken reflects on a time 30 years ago when CRM systems hadn’t been given their modern name yet. The focus was on personal contact information rather than group-oriented data. Over time, technology has advanced significantly, leading to the rise of the RevOps job description. What’s notable is the increased attention that IT has dedicated to the sales profession and marketing to ensure the right tools are provided. He contrasts ERP systems, which are vital and structured, with the evolving needs of salespeople and their customer management.

What exciting newer trends are catching your attention in the realm of RevOps?

Ken believes that the advancements in generative AI, like ChatGPT, will lead to significant changes in business, especially in sales. A friend of his, Tony Hughes, emphasizes the need for salespeople to harness technology while retaining human intuition and relationship-building. Ken stresses that even if two competitors use the same technology, like ChatGPT, to craft a pitch, the unique advantage and differentiation each brings will matter the most.

What about challenges for RevOps professionals? How is Riva as a company helping them address these challenges?

Ken has observed a significant increase in the number of add-on technologies that work around systems like Salesforce. While these technologies added functionalities, they also brought complexity. The real challenge RevOps professionals face is determining which of these technologies are essential and which ones offer the best ROI. Riva assists by focusing on data quality. Dirty or noisy data can lead to misinformed strategies. By integrating aspects like calendars and email from platforms like Outlook or Gmail into CRM, Riva ensures that the data used in CRM systems is clean and relevant.

How do you perceive the influence of ChatGPT and its integration with different RevOps systems? What opportunities does this convergence present for companies?

Ken acknowledges the potential of ChatGPT in aiding tasks like pitch creation. However, he also cautions about the risks involved when introducing customer-specific data into large language models. There’s the challenge of ensuring that Personally Identifiable Information (PII) doesn’t get into the models, and even when providing data to the model, it should be de-identified. While he believes there will be solutions to address these challenges, he expects regulations and safeguards to be in place for a long time.

How crucial is it to exercise caution when integrating data with large language models in regulated industries?

Ken pointed out the challenges posed by regulated industries like banking and insurance when it comes to integrating with large language models, stressing the need for caution. He shared concerns about the potential misuse of data by bad actors and highlighted the increasing stringency of data privacy regulations. In some sectors, there’s a requirement to disclose when content has been generated in part by AI.

Shout-outs

Tony Hughes CEO and Co-founder at Sales IQ Global

Justin Michael – CRO Coach & Co-Founder at Hard Skill Exchange

 


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Sunny Side Up
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