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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 address the second bucket by generating more pipeline and winning more business with a much leaner team.
So how does Gem AI work? 🤔
These are the 3 pillars Gem AI is built on:
- Identify
- Prioritize
- Action
In this blog we'll break down our pillared approach.
Gem AI Pillar #1 - Identify
Before you can start any sales playbook, you need to identify your ideal customer profile. In a perfect world, your company has a deep understanding of your ICP and buyer personas. In reality, many companies are missing a large chunk of their in market buyers.
In UserGems Signal Platform, you can use Gem AI to find 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.
If you’re an AI email hater, you’re not alone. 🙅
AI-generated messages have become a popular approach for many companies. Lots of messaging tools have hit the market. But most of them still suffer from 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.
If this is your approach, you’d be better off not sending an email.
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
Adding AI and machine learning capabilities into sales processes isn’t a passing trend — it's the future. More and more, we’re seeing companies that adapt to new ways of doing things come out ahead of their competition.
Start by focusing on identifying your best ICPs and buyer personas. Next, prioritize the leads most likely to convert. Finally, take action through personalized and relevant messaging.
Boost Your Pipeline With Signals 🚀
