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The world of software is transforming faster than ever before since AI became mainstream, and every company is looking for new ways to get ahead of their competition, either through product differentiation or go-to-market efficiency. We've designed Gem AI to help companies improve go-to-market efficiency by generating more pipeline and winning more business with a much leaner team.
Gem AI works through three core pillars:
These are the 3 pillars Gem AI is built on:
Identify
Prioritize
Action
Here's how each pillar works.
Gem AI Pillar #1 - Identify
Before you can start any sales playbook, you need to identify your ideal customer profile. Most companies miss a large portion of their in-market buyers because they lack precise ICP and buyer persona definitions.
In UserGems Signal Platform, Gem AI identifies your ICPs and buyer personas.
First, create a new buyer persona or ICP within UserGems. You can manually input variables like buyer titles, # of employees, country, industry, etc.
As you select variables, Gem AI offers AI Suggestions, similar to predictive text in search engines.
These suggestions stem from statistical analysis of UserGems’ customer data. Our algorithms incorporate dozens of different variables like average win rate frequency and how likely they are to convert.
This feature helps companies find their ICPs and best buyer personas. Refining your ICP and Buyer Persona is likely to bring in more relevant prospects, so the next step is to prioritize them.
Gem AI Pillar #2 - Prioritize
Gem AI prioritizes prospects using a signal-first approach.
We value each signal differently based on various factors. The value of most signals depends heavily on the prospects’ characteristics as well as the product you’re selling.
For example, a Gem with a more recent job change will be more valuable than a Gem who changed roles 3-6 months ago. But a Gem with a key buyer persona profile will rank more highly than another more recent job change Gem outside of your ICP.
Other characteristics that impact signal values include traits like:
Past relationships
New hires
Promotions
Recent company funding
Company news
Existing customer competitors
We trained UserGems' machine learning model using real sales data. The model considers context when prioritizing prospects. It also prioritizes prospects and companies based on customer-specific signal values, not just generic user values like industry and company size.
Gem AI can then provide customized recommendations, taking into consideration all buyer signals and prospect characteristics, as well as target company characteristics.
Once we’ve identified our target accounts and prioritized them, it’s time to do something with them in an efficient and customized way.
*Data Safety*
No sensitive company data is used in Gem AI models between UserGems customers. We’ve created a General Model that’s used to create company-specific custom models. Your sales data is only used to train your company-specific model, and your private data will never be used to train another company’s model.
Gem AI Pillar #3 - Action
We’ve all seen AI-generated emails by now, and many of us have strong impressions of them.
Most AI-generated emails fail for three reasons:
Companies now use AI-generated messages widely, and dozens of messaging tools exist. Most of them still exhibit three common problems:
No relevant context
Wrong or inaccurate content
Read like they were written by AI
If your emails aren’t relevant, the recipient is going to click delete. If the recipient thinks that AI wrote the email, they’re going to lose faith in your company. And, worst-case scenario, if the LLM hallucinated and included inaccurate content, you could lose a prospect because you (accidentally) lied to them.
This approach reduces email effectiveness to the point where sending no message would yield better results.
We have a better approach to AI email messaging at UserGems. We’ve been incredibly careful to make sure that our Gem AI-generated emails are relevant, personalized, and only sent to the best prospects to avoid being spammy.
How AI email messaging in UserGems works:
Gem AI combines signals and your company’s value prop to craft personalized messages.
This message is then inserted dynamically and directly into your Outreach or Salesloft cadences.
Managers and reps can edit the messages for tone and style and get snippet prompts from the UserGems App.
The system builds final messages based on prospect- or company-specific signals. This ensures content is relevant and information is accurate. Sales reps get maximum control over their messaging this way.
UserGems AI Signal Platform Capabilities
Our customers see measurable pipeline gains when they use AI to identify in-market buyers, prioritize by signal strength, and personalize outreach at scale.
Companies that act on buyer signals with coordinated, AI-powered outreach consistently outperform those relying on generic automation.
The three-pillar approach—identify your ICP, prioritize by signal, personalize with AI—turns buyer intent into pipeline faster than manual prospecting or generic automation.
Boost Your Pipeline With Signals 🚀
