Dominik Facher, Chief Product Officer at ZoomInfo talks about the platform’s latest AI-powered Copilot and the growing influence of AI across marketing and sales:

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Hi Dominik, tell us about yourself and more about your role at ZoomInfo

As ZoomInfo’s Chief Product Officer, I oversee our product management, data and product operations teams and I’m responsible for building the modern go-to-market platform.

We’d love to hear more about ZoomInfo’s AI-powered Copilot, how does it enable sales and marketing teams?

ZoomInfo Copilot brings together companies’ go-to-market data — including first-party CRM data and ZoomInfo’s best-in-class data. It employs generative AI to analyze the data and pinpoint valuable insights sellers want and share AI-driven suggestions on who to reach out to, when to initiate contact, and what to communicate across various channels. By offering a number of innovative actions, such as AI-guided prospecting, dynamic buying committees, AI email assistants, unrivaled data quality, and personalized go-to-market strategies, sellers can change the way they discover and engage with buyers.

What would you say are the top challenges and lags faced by modern GTM teams and how can AI-powered sales intelligence and salestech be deployed more smartly to boost processes and output?

The biggest challenge that GTM teams face today is the extent to which buyers are conducting product research on their own. There are so many peer groups, communities, social networks, and online review sites (like G2) at their disposal that buyers are better prepared than ever to go through the vendor shopping process. At the same time, they’re also leaving a trail of digital breadcrumbs or buying signals, in the form of key term research, behaviors that indicate buyer intent, competitive research, and many more, which indicate a propensity to buy.

These signals create a huge opportunity for companies to run more efficiently, by having sellers focus on the right accounts and spend more time with what the signals tell them are the right customers, ultimately leading to accelerated deal cycles. And AI – at its best when processing large amounts of data and deriving insights – is perfectly suited to ingest all of these buying signals and provide GTM teams the intelligence they need to act on them. Companies able to master the implementation of AI in this way will likely enjoy a leap in efficiency and hit their target buyers at the right time and with the right message.

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How are you seeing new advances in AI transform the sales/marketing experience today: can you highlight examples that have piqued your interest

The biggest impact AI has had is the speed at which go-to-market efforts are executed. Crafting that well-written email, drafting copy for landing pages, creating visually compelling images, writing talk tracks for outbound calls, recapping a conversation with a buyer – these are all sales processes where AI’s strengths will prove to be most beneficial. While these still require human oversight, AI can create the first few drafts much faster than a human could, and with the right data fueling the AI engine, can do so both at scale and in a hyper-personalized way. We’re seeing with our own ZoomInfo Copilot solution how relevant and in-context the personalization is when the AI has access to a complete data set of first-, second-, and third-party data and buying signals such as intent, website visits, and third-party research. The advances in generative AI give sales and marketing teams the edge in being first to a buyer, and creating a value-based experience.

Also catch: Episode 175 of The SalesStar Podcast: Go-to Market and Marketing Best Practices with Bryan Law, CMO at Zoominfo

When deploying AI as an early user, what should B2B teams keep in mind?

AI should still be treated as an evolution, not a revolution. Don’t try to overhaul the way you work because you think AI is going to come in and solve a bunch of new use cases. Look at GTM motions you already have in place and focus on areas that most need an improvement in efficiency. Use AI to incrementally get a little bit smarter, a little bit faster. While AI is powerful, it can also quickly pull your team in the wrong direction; that’s why it’s imperative you feed your AI accurate data to avoid large-scale mishaps.

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Can you share five thoughts/trends that will define the martech and salestech segment in 2024?

1. Focus on retention: Even if the worst of the economic downturn is behind us, it’s quite certain buyers are going to be more cautious when making new purchases. Retaining and growing customers has always been the most cost-effective way to grow a business, but in 2024 it will be essential.
2. Adapting to AI: There’s no denying that AI is going to be a part of how businesses operate, and organizations will have to learn to incorporate AI into how they work or risk getting left behind. This isn’t a matter of if you’re going to use AI, it’s about when.
3. Value selling to adapt to the new buyer’s journey: With buyers now doing most of their own research and so many buying signals readily available to sellers, there’s no excuse for sellers to not be fully prepared and educated when speaking with buyers. Buyers – especially new ones – expect the sales experience to be informative and do not want to be sold to. Considering how much research buyers have already done, they expect their interactions with sellers to be additive, which means value selling and a highly informed sales team are table stakes. Yes, the pandemic forced some of this new practice, with every seller becoming a remote seller, but it’s clear that the buying process isn’t reverting back, and organizations need to adapt their GTM motions to cater to this reality.
4. The multichannel pitch: The buying process doesn’t follow a linear funnel, it involves buying groups all conducting research across multiple channels and all in various stages of decision making. Which means sales and marketing efforts need to be tightly aligned and executed across all the channels delivering a consistent high quality customer experience.
5. Avoiding data mess: GTM teams are often slowed down in their efforts to get the best out of their tech stack because of data hygiene issues. Data gets messy in every organization but there’s no reason it should still be causing GTM inefficiencies. Technology is at the point where the ability to capture and aggregate data and act on it is possible. In 2024, we’ll see RevOps teams really take advantage of solutions that help create better data hygiene and give frontline sales teams the ability to harness and act on these signals. I believe we will see RevOps teams play a far more strategic role in GTM in 2024.