Meet The AI Copilot That Serves As A ‘Purpose-Built’ GPT For Businesses
When it comes to AI adoption, 81% of sales teams are either experimenting with or have fully implemented the technology. While that implementation generally comes in the form of ChatGPT and similar tools, those large language models don’t allow salespeople to go much deeper than templated messaging. Considering how profoundly complex B2B selling is and the nuanced need for human-to-human interactions, leveraging generic outreach to capture buyers’ attention is no longer effective. Instead, practitioners need purpose-built AI copilots that amplify 1:1 human-centric selling.
Enter Tiga.ai, which uses the power of generative AI to amplify 1:1 human-centric selling and help sales teams research target accounts, relationally connect with buyers and conduct signal-based selling. To learn more about the platform’s launch and the role it’ll play in the B2B martech landscape, the Demand Gen Report team sat down with Andre Yee, CEO of Tiga.ai and a B2B industry veteran, to learn more about the solution.
DGR: Can you walk us through the factors that led to the creation of Tiga.ai?
Andre Yee: Early last year, I was talking with go-to-market (GTM) leaders in my network and discovered that about 80% of them were rethinking their GTM motion, particularly around the SDR function. While there were definitely some economic pressures around that shift, the bigger component was that cold outbounding seemed impossible — those mass market methods where you upload a list of 5,000 names and just blast them with a templated email isn’t working the way it used to.
So, we started exploring some of the habits of best sellers, and I found they did three things: They conducted deep account research, formed a relational connection with accounts and then deployed signal-based selling, which is when sellers reach out and have personalized interactions based on buyer signals or behaviors.
DGR: For our readers who might be unfamiliar with signal-based selling, can you expand on what exactly that entails?
Yee: The idea of signal-based selling is more of a warm approach to outreach. Instead of just blindly sending emails to everyone, you’re instead finding and focusing on the right signals that matter. As we started unpacking this, we realized that the most meaningful signals — those that indicated buying interest — were typically hyper-specific to each business.
For instance, I was talking to one of our clients that sells contract lifecycle management software, and he said that a real signal for them is when they see a company hiring for legal ops roles, because it shows that the legal and contract department is investing in technology.
Most companies are manually mining for those sort of signals, so we trained our AI to look for and detect specific signals.
DGR: Given the abundance of AI technology in the industry, what sort of unique capabilities does Tiga feature that sets it apart from other solutions?
Yee: If you look at a lot of solutions out there, most just focus on helping sales teams write emails and LinkedIn messages. We do that as well, but there are three things that set us apart. We offer:
- A purpose-built AI model that can uncover buyer signals;
- A platform designed specifically for teams, not the individual; and
- An AI that’s easily trainable to understand specific businesses and their nuances.
If you want an AI model to uncover signals, you essentially need to train it like a GPT for your particular business, and we make that accessible.
DGR: As we wrap up, can you share a look into the future of AI-based selling?
Yee: If you look at sales teams across the board, the most common tool they use is ChatGPT and its variants, such as Gemini. There are two problems with that: The first is that you have to be a prompt engineer to get effective results, and the second is that those type of models don’t understand your business or workflow. I’ve likened ChatGPT to an Excel spreadsheet: It’s a general-purpose tool that has a lot of functionality, but it needs to be supplanted with purpose-built applications. The dust is still settling on how to best use AI for sales, and it’s going to be profound when people figure out how to leverage AI inside of their daily workflow.
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