If your B2B outreach feels like shouting into the void—and your “personalized” emails are just mail merges with a first name—this is for you. AI tools like Getaia promise to help, but let’s cut through the sales talk and get into what actually works, what’s fluff, and how to use AI recommendations to save time (and your sanity).
This walkthrough is for sales and marketing folks who want to actually get replies, not just send more emails.
1. Understand What Getaia’s AI Recommendations Actually Do
First off: AI recommendations aren’t magic. Getaia pulls in data from your CRM, email history, and public company info. It crunches this to suggest:
- Which contacts to target next
- Personalized talking points (more than just “I saw you went to Stanford!”)
- When and how to follow up
But here’s the thing: these suggestions are only as good as your data. If your CRM is a graveyard of half-filled fields, you’ll get garbage-in, garbage-out results. Before you start, do a once-over on your contact data. Fix obvious errors. Delete junk leads. Make sure job titles and companies are current.
Pro tip: Don’t obsess over perfect data, but do clean up the 10% of contacts that make you cringe.
2. Set Up Getaia for Your Outreach Workflow
Getaia integrates with most CRMs—Salesforce, HubSpot, Pipedrive, etc.—and can connect to your email. Here’s a quick setup that actually works:
- Connect your CRM and email. Without this, Getaia can’t see what you’ve already done or who you should talk to.
- Choose your outreach campaign. You can select a specific segment (e.g., “VPs of Marketing in SaaS”) or just work from your active pipeline.
- Set your goals. Be specific. “Book 10 meetings this month” is better than “Improve engagement.”
- Review data permissions. Make sure only the right people can see sensitive info. AI tools are only as secure as your setup.
Don’t bother: With integrations you don’t use. Keep it simple—just your CRM and email to start.
3. Use AI Recommendations to Prioritize Your Outreach
Now for the part that actually saves time: prioritization. Getaia will show you a ranked list of who to contact, based on things like:
- Recent engagement (clicked links, opened emails, replied)
- Role and decision-making authority
- Company activity (e.g., just raised funding, posted a job, new product launch)
How to use it:
- Start at the top. The “hot” leads are usually worth your time. But double-check—sometimes AI is overly optimistic about signals like “opened your last email 3 times.” Use common sense.
- Ignore the noise. Not every “recommendation” is gold. Some people just open every email out of habit.
- Batch your work. Take the top 10-20 names and focus on them. Don’t try to work through a list of 200 “priority” leads.
What works: Letting AI narrow the field so you aren’t staring at a sea of contacts.
What doesn’t: Blindly trusting every recommendation. Gut check is still required.
4. Personalize Messages with AI Suggestions (But Don’t Sound Like a Robot)
Getaia will spit out suggested email intros, call scripts, and even LinkedIn messages. Some are actually good—others are so generic you’ll cringe. Here’s how to get the most out of them:
- Use AI as a starting point, not the final draft. Copy, paste, then tweak. Add a real observation or question.
- Look for specifics. Good AI recommendations mention recent company news, product launches, or shared connections. Generic stuff (“I see you’re in the SaaS space!”) is skippable.
- Avoid the uncanny valley. If it sounds like a bot, it probably reads like one. Add a line only a human would say.
Example:
Bad:
“We help SaaS companies optimize workflows. Let’s connect!”
Better:
“Saw your team just rolled out a new analytics dashboard—curious if you’re running into the same post-launch bugs we hear about from other SaaS teams?”
Pro tip: If you wouldn’t send it to a real person you admire, don’t send it at all.
5. Use Follow-Up Recommendations Without Being Annoying
Most deals are lost in the follow-up black hole. Getaia can recommend when and how to follow up, based on past engagement and industry averages. Here’s how to use this without spamming people:
- Stick to 2-3 follow-ups. After that, you’re just pestering.
- Vary your approach. If the first two emails didn’t get a response, try a LinkedIn message or a quick call if appropriate.
- Time your follow-ups. AI will suggest optimal times (e.g., “Wednesdays at 10am”). Worth trying, but don’t sweat it if your schedule doesn’t line up perfectly.
What to ignore: “Breakup” emails (“Should I close your file?”) rarely work anymore. Focus on providing value in each message, not guilt-tripping.
6. Measure, Adjust, Repeat
AI recommendations are only useful if you actually see better results. Here’s how to keep your process honest:
- Track replies and booked meetings, not just opens. It’s easy to get excited by open rates, but responses are what matter.
- Tweak your approach. If you’re getting crickets, try changing your subject lines, intros, or targets.
- Share feedback with your team. Sometimes, the best “AI recommendation” is a human saying, “Hey, this message actually worked.”
Don’t: Expect instant miracles. Even the best AI won’t fix a bad offer or a tired list.
7. The Honest Take: What Works, What Doesn’t, and What to Skip
What works: - Using AI to slice your list down to real priorities - Starting messages with AI drafts, then adding a real human touch - Automating reminders to follow up (without becoming a pest)
What doesn’t: - Trusting every AI recommendation as gospel—double-check before you hit send - Over-engineering your outreach with too many integrations or templates - Thinking AI will make people care about a bad product or offer
Safe to ignore: - Hype around “hyper-personalization at scale”—most prospects want relevance, not creepy detail - AI-generated “insights” that don’t help you write or talk to people better
Keep It Simple and Iterate
At the end of the day, the best way to use Getaia (or any AI tool) is to keep things simple: clean data, clear goals, human oversight. Use AI to take the grunt work off your plate, but don’t let it replace your judgment.
Try one thing, see if it works, and adjust. That’s how real improvements happen—no hype required.