SalesTechStar Interview with Clay Sharman, Founder and CEO of Krateo AI

Clay Sharman, Founder and CEO of Krateo AI chats about the impact of AI copilots and how they are enabling modern marketing and sales functions in this interview with SalesTechStar:

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Tell us about yourself and the story behind Krateo.AI?

My background is a blend of creative efforts mixed with practical experience in the government acquisition arena – where I spent nearly 20 years working to deliver network and software solutions. I started imagining the bones for what became Krateo.AI back in 2020, while working for an enterprise intelligence platform that served national security agencies to deter insider threats. I saw potential for a commercial application aimed at delivering better information on anonymous web visitors, which led to the founding of Krateo.AI in April, 2022. Now, two years later, we have a full product with paying customers. But, as we continue down our roadmap, we are seeing how AI can be applied to greater effect when it comes to front-end marketing efforts, particularly in retail and e-Commerce. Creatively, I’m a published fiction author, film producer, and hack drummer for a pop rock band here in the DMV.

We’d love to hear about your new AI copilot (Hermes) and how it enables end users in sales?

Hermes was created to serve as a customer-facing “helper” for marketers looking to optimize efforts to drive visitors to their web pages, whether to a corporate site or specific campaign-focused landing pages. Hermes can help shape strategies for what types of audiences to build within our platform and thereby optimize sales channel impact.

What’s great about Hermes is that more interactions translates to increased learning at AI speed, and Hermes becoming a part of the marketing team. He’ll share recommendations on how to build the most engaged audiences across channels, resulting in reduced acquisition costs, and increased customer trust, lifetime value and overall sales revenue.

How can modern sales and marketing teams use AI copilots more effectively to drive future impact and goals?

First, AI is great for handling tedious, manual, repetitive daily tasks, and freeing up teams to be more productive in terms of strategy and execution. Consider that up to 70% of a marketer’s time can be spent vetting and qualifying prospects. AI can speed this process by huge multiples, which means marketers can get to campaign execution much faster, so sales teams can follow up and close that much faster too. Where copilots come into play here is in helping to understand how customers interact, or don’t, and want to be approached, or not, and when, and how ( ie. what sales channels). AI can also spot trends and patterns that humans can’t (or at least can’t in a timely fashion). If AI can free up more than half of a marketer’s day to boost productivity, then using AI copilots to engage the 98% of anonymous web visitors is an effective way to apply the same marketing strategies used for the 2% of visitors who share their information – but on a much larger scale and with greater speed. And obviously, AI is already in use for a high percentage of companies for content generation, but adding prospect understanding in front of content generation is another critical element in delivering brand success.

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What about AI and sales today needs more thought and optimization?

I actually think that the use cases are pretty clearly defined for how AI can, and should, be used in the sales cycle today. Where more thought needs to come into play is how to “aim” AI properly to get the best results in the shortest amount of time. We’re not talking about magic. AI is all about logic and data volume. So, getting access to more quality first-party data is critical to AI success. In this regard, optimizing all areas of data collection and validation play a major role in making the most of AI technology. The old adage “garbage in, garbage out” definitely applies.

Furthermore, having too many disparate tools in a tech stack can ironically derail the overall “decision based on data” approach. So, I would recommend thinking about all the goals to lower costs, generate new customers and increase revenue, and see if the current tools help with those or if they just collect more sets of incomplete data. I see value shifting away from simple conversions to overall customer satisfaction and lifetime value. And that can only be achieved by understanding needs at scale, which begins with better prospect data and volume.

Can you talk about some of the most unique and interesting ways in which you’ve seen SaaS marketers and sales teams use AI-powered salestech and martech to scale output?

I think that AI has already changed the game in terms of content generation and copy writing. Where I’ve seen some companies take it recently is in building highly tailored landing pages or storefronts that serve specific campaign strategies. This is a really cool and effective way to use AI. It addresses the need for personalization without being invasive because the creation comes after the campaign interactions. And of course, I’d be remiss if I didn’t say that Krateo.AI is the perfect compliment to this type of AI use case. We can score and build audiences based on the interaction data of the visitors once they hit the landing page, even if they remain anonymous and leave the funnel before conversion, which is another super cool way to use AI.

Five thoughts and predictions on the current state of AI and salestech before we wrap up?

• AI is the least intelligent it will ever be right now.
• The potential for advancements in almost every area of science and technology is closing in on becoming limitless, which is both awesome and terrifying at the same time.
• Commerce companies that adopt AI the best, not necessarily the fastest, will be the ones that are inoculated from global and national market volatility because AI will have the best odds at “seeing things coming” first.
• AI will reset what it means to lead by intuition because in the not too distant future, there will be very few scenarios, if any, that AI hasn’t already considered, which means decisions will become almost exclusively “data supported,” eliminating the guesswork behind gut-decisions.
• Brands need to prioritize better data ownership and management practices in today’s AI-driven landscape. By controlling their first-party data, brands can effectively harness AI for enhanced personalization and customer engagement.

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