We are building a prospecting platform for deep research so anyone can understand their prospects deeply and send better outreach instead of spray and praying a generic message.
Sales landscape is pretty crowded. Most solutions focus on sending the same email or Linkedin message to thousands of people.
This approach worked between 2010 to 2020 at best, however it became such a big habit that everyone started doing it. When you receive an outreach email that talks about the solution they offer without inferring how the solution could solve your problem, you automatically mark it as spam.
Now with AI, people started personalising. However this personalisation goes to the extent of where someone graduated from or if they shared a pic of eating ice cream on Instagram. This makes the outreach personal but still useless.
At GodmodeHQ, we implemented AI agents in form of columns in a spreadsheet. This resembles Perplexity integrated into a spreadsheet.
The agents recognise your website and embeds your ICP and context. So the only thing you need to do is ask:
"What are some of the pain points we can solve for the company?"
"Does the company have SOC Type 2 certification?"
"What are the recent feature launches they did?"
and more.
The agent automatically starts filling the information for you. Then you can use this information to really understand what problems you can solve for the customer.
Last step is reaching out to the customer using email and Linkedin. You can automate this part in GodmodeHQ as well however we do not deal with domain warmups or other similar practices that aim to let you send 10k emails on a day.
By design we encourage the users to go through the information agents have uncovered.
Our belief is that everyone sells. Whether it is your code or simple ecommerce products, you are a seller. You need to understand how you can sell.
Our vision is to turn non-salespeople into successful salespeople using the help of AI.
We hope you enjoy GodmodeHQ as much as we do.
I would love to hear your feedback.
Best,
Mert
