Outbound is Dead. Long Live Outbound.
Over the past few years, I’ve heard a lot of chatter in marketing communities about how outbound is dying.
- “Gmail is routing all our emails to the junk folder.”
- “Superhuman is recategorizing messages into folders no one ever looks at.”
- “Apple is blocking all our calls because we’re not in the address book.”
- “All my LinkedIn messages go into a black hole – aka the ‘Other’ filter.”
- “FedEx couldn’t deliver the direct mail we sent because the buyer never goes to the office.”
Apparently, however, no one told the startup community that outbound was dying, because they have been raising hundreds of millions of dollars to build new AI-native prospecting tools. And for good reason. We need outbound! You can’t wait on buyers to find you via inbound.
Hope is not a strategy. While inbound delivers more qualified buyers that are in an active purchasing cycle, many of them are in the later stages having already completed 80% of the research they need to make a decision. Inbound is also less precise, often delivering leads that don’t fit your ideal customer profile. At most companies a healthy mix of inbound and outbound, account-based marketing is the best recipe for success with pipeline development.
To be fair, there is certainly some truth to the claims that the traditional approaches to outbound is slowly dying off, but in its place there is a new generation of AI-native tools emerging. And these tools can scale outreach to levels never before imaginable!
VibeGTM Baby!
You have no doubt heard of tools like Clay, Smartlead.ai, and Instantly that are all the rage in Rev Ops Slack communities. These…buzzwords like GTM engineer, revenue orchestration platforms, and my personal favorite – VibeGTM, that have been introduced.
In this article, we will explore 10 new AI technologies that go-to-market teams should be considering to supercharge their outbound motions. We’ll review in them in the context of how outbound teams use them in a campaign lifecycle:
- Research – Finding companies that match your ideal customer profile and then lookup contact information like email and phone number for key decision makers at those accounts.
- Scoring – Prioritizing which accounts to focus on for the next month or quarter by analyzing buyer intent data, news announcements, and recent marketing engagement captured in your CRM.
- Personalization – Creating targeted messaging for each individual buyer by conducting deep research on their social media profile, company strategy, and broader industry trends.
- Outreach – Securing meetings with prospects by scaling high volumes of cold email, voicemail drops, and LinkedIn requests. They monitor for replies and can generate automated responses to common questions.
You can deploy these new AI capabilities in three different ways:
1) AI SDRs
Vendors such as Artisan, AiSDR, or 11x bundle all of these capabilities into different agents that can run either autonomously or in copilot mode with human supervision.
2) Revenue Orchestration
Platforms such as Clay, UnityGTM, and Cargo.ai offer DIY models. You’ll need to hire GTM engineers with advanced scripting, prompting, and coding skills to build your own workflows.
3) Best of Breed
If you aren’t ready for either of the models above, you can deploy new AI tools as standalone applications layered on top of your existing stack.
Research
The first step in the campaign process is to identify the right list of accounts to target and then find the right people to target at each.
1) Agentic Search
Historically, GTM teams have used “sales intelligence” tools like ZoomInfo and Apollo to build account lists. These tools are great, but they are limited in scope to the information in their databases, which typically includes firmographics such as employee count, revenue, headquarters locations, and technographics such as the company’s CRM, ERP, and HCM systems.
But what if your ideal customer profile is more complex? What if you need to find retailers that offer free returns, financial institutions with crypto products, or startups that allow you to bring your dog to work? You won’t find those types of attributes searchable in a sales intelligence database, but you can find them with “agentic search.”
Platforms like Exa.ai and Landbase let you search the web and any other public data source to find companies matching almost any criteria you can think of. Sales intelligence databases are great, but they only track 1% of the available data about companies and people. Agentic search unlocks the other 99% by allowing you to search company websites, news releases, job listings, online reviews, patent filings, earnings reports, academic research, government datasets, and YouTube transcripts.
Suppose your ICP is an industrial company with complex go-to-market motions. You could write a prompt asking Agentic Search to search all known aerospace, automotive, and heavy industry companies that sell through a mix of direct sales, online channels, and multi-tier distribution networks. Agentic search will crawl millions of websites to find those with matching GTM strategies and return the list.
2) Data Enrichment Waterfalls
Historically, most companies have relied on a single sales intelligence vendor to support all of their sales and marketing campaigns, but one of the big challenges with this approach is that no single database has 100% of the records. You might go looking for a CTO’s email and phone number at one of your target accounts only to find that those fields are empty.
It’s not surprising that records are sometimes incomplete. There are hundreds of millions of businesses around the world and billions of employees who work there. Every day new businesses are formed while others are acquired or shut down. People switch jobs more frequently than ever and often don’t update their LinkedIn profile. Keeping an accurate, up-to-date record of each company and all of their employees’ job titles, email addresses, and phone number is an almost impossible task.
But a new group of AI-native vendors is rising to solve this challenge. These innovators have adopted a different model that operates on the premise that no single sales intelligence database will ever be perfect. A better strategy is to use multiple sources using a “data enrichment waterfall.” Platforms like Clay, FullEnrich, and Waterfall.io can search through dozens of sources to find them.
Here is how it works. Suppose your company sells payroll solutions to HR leaders. One of your target accounts issued a press release announcing a new VP of Human Resources. You need to find her email address and phone number. The data waterfall will first search source A for her contact details. If it doesn’t find the email and phone number in source A, it will check source B. If it doesn’t find a match in source B, it will query source C, then continue searching through additional sources D to Z until it finds a match.
3) AI Qualification and Scoring
If you are chasing a large TAM, you cannot pursue all your prospects at once. You need to prioritize which ones to focus on. Historically, sales teams have made these judgments by having BDRs or account executives perform the analysis. The challenge is that analysis is a time-consuming process that it is hard to find the time to do right.
AI-powered Qualification agents can search through list of accounts to identify those that are most likely to buy in the next few quarters. They can search through news feeds to find the compelling events that drive new purchasing cycles like market expansions, funding announcements, or leadership changes. They can analyze third party buyer intent data to identify the companies who have been researching your products in marketplaces, reviews sites, or media properties. They can also search first party data from your CRM and marketing applications to understand which prospects have been visiting your website, reading your content, and watching your podcasts.
Each account is assigned a score and stack ranked so that your GTM team knows which accounts to prioritize this quarter to maximize their chances of success. Many will also provide the rationale for why each account was selected. You can understand why AI selected the accounts and decide whether you want to follow its recommendation or override it.
Personalization
4) Hyper-Personalized Messaging
Decision makers are inundated with emails, phone calls, and LinkedIn messages from sales teams today. To stand out and get a response, you need to take a personalized approach. But taking the time to research each potential buyer at each target company is time-consuming. With conversion rates on outbound campaigns often below 1%, spending 15 minutes to develop a personalized message is hard to justify.
AI Personalization agents will search through your prospect’s LinkedIn profile, podcast interviews, and social media posts to grab the killer soundbites you need for the “show me that you know me” copy that converts. They will create a shortlist of the top keywords to include in your subject line to jack open rates. They can analyze recent news releases, earnings reports, and competitor announcements to create the pitch that nails the “what’s keeping you up at night” issue.
You can also use AI to translate the messages into multiple languages. If you are prospecting throughout Europe, you could generate email or InMails with personalized messaging in English, French, German, Dutch, Italian, and Spanish.
5) Multimedia Content at Scale
Personalization isn’t limited to just text. With agentic AI, you can mass-customize website pages, videos, images, and audio content for target accounts.
With Tofu, Prismic, and Webflow you can mass generate personalized, ABM-style landing pages with your prospect’s name, logo, and brand identity. You can include value statements targeted to their specific role and case studies of lookalike accounts from their industry.
HeyGen, SendSpark, and Captions allow you to send out thousands of personalized headshot videos. Thanks to the magic of AI-powered lip-sync and voice cloning technology you can produce hundreds of these from just a few minutes of baseline footage.
Tools like Arcade, Navattic, and Reprise allow you to mass-produce personalized product demonstration videos. Open with a greeting of the buyer by name and focus the features on those most relevant to their specific roles.
After the initial discovery call, you can send customized follow-up documents. Use AI to mass personalize Google Slides decks that reference the prospect’s name, job title, role, and company logo. Create custom Google Docs that reference the company’s mission statement or quotes from their executives.
Outreach
Once it’s time to engage the prospect, you can use AI to create high-volume, automated email sends, voicemail drops, and LinkedIn DMs that embed hyper-personalized messaging and mass-customized content in the campaigns.
6) Email Automation
AI-native platforms are helping GTM teams land in the inbox with models optimized for deliverability. For example, platforms like Smartlead.ai, Instantly, and Salesforge will rotate sending from thousands of mailboxes on hundreds of different domains to ensure. They use techniques like ESP (email service provider) matching to boost inbox placement. Recipients on Gmail are only sent messages from other Gmail accounts to ensure the message stays “on network.”
AI-native tools also have built-in email verification steps. Email addresses are automatically checked to confirm they have valid syntax (firstname.lastname@company.com) and aren’t spam traps. AI tools will flag high-risk recipients who are known to block senders or mark emails as spam.
AI can also monitor incoming replies and automatically generate replies. For example, you might configure AI to auto-generate answers to common questions. If the prospect replies at 3AM requesting more information, the agent can send marketing collateral. If they ask for a meeting, the agent can automatically send a Calendly link.
7) LinkedIn Automation
Tools like Heyreach, Aimfox, and LinkedHelper can bring the same levels of automation we are accustomed to with email to LinkedIn prospecting. You can warm up prospects with automated profile views and post likes. Once you are ready to connect, you can add the personalized AI-generated messages to your InMails. After the prospect accepts, you can send an automated message requesting an introductory meeting, a podcast interview, or an event invitation.
These tools also enable you to automate nurture campaigns. Suppose a prospect replies to your InMail saying they are interested, but timing is not good right now. You can set up an automated sequence that automatically engages at regular intervals. In two weeks, it will do a profile view. Four weeks later, it endorses them for a skill. Workflows can be set up to monitor new posts and automatically like them. These touches keep you visible to the prospect and keep them warm for follow-up.
8) Phone Automation
We didn’t need AI to automate phone calls. We’ve had robocalling for decades, but those were generic pre-recorded messages. I suspect in the not-too-distant future we will have AI calling agents that can carry on a live conversation with you autonomously. We have already seen 1Mind, Docket.io, and Saleo offering avatars that can demo software and engage in real-time conversations on a website.
In the meantime, there are other ways to use AI to optimize your cold calling efforts. AI can generate hyper-targeted call scripts with messaging specific to each buyer and account. Synthetic voicemail tools can automatically record personalized messages in your voice after just a few minutes of training.
AI can also help keep callers out of trouble and avoid wasting time on low-engagement accounts. For example, before a phone number is added to a calling sequence, it can be screened to ensure it is “callable” and not a Google Voice, SMS-only, fax, or modem line. AI can also analyze historical connection patterns for each phone number to recommend which contacts are most likely to answer and which are most likely to be forwarded to voicemail.
Three Ways to Adopt AI for Outbound
9) Revenue Orchestration Platforms
The first is a DIY approach, implementing a platform such as Clay, UnifyGTM, or Cargo.ai. These revenue orchestration tools offer many of the AI capabilities outlined, including data enrichment waterfalls, agentic search, and hyper-personalized messaging. They also offer email and LinkedIn outreach. They also offer integration with hundreds of sales automation tools to extend their capabilities.
You will need a GTM engineer to implement a revenue orchestration platform. GTM engineers bring a higher level of technical depth to marketing and sales teams with skills like scripting and programming. They need to manage complex integrations among the CRM, MAP, internal, and external data sources via APIs and webhooks. They also need expertise in writing advanced prompts that instruct AI tools to search for target accounts and write hyper-personalized messages to prospects.
It’s also worth noting that revenue orchestration platforms are not limited to outbound prospecting. Although that was the primary use case, these vendors are quickly expanding across the full go-to-market motion. For example, GTM engineers use Clay to generate pre-call discovery briefs for AEs, including account profiles and dossiers on the meeting attendees. These tools can be used to mass-create QBR decks for customer success teams, pulling in data from internal systems such as call transcripts, trouble tickets, and billing records. Clay is even being used to improve Service Desk processes. It can auto-classify new tickets as hard, medium, or easy and extract patterns to prioritize product roadmap features.
10) AI SDRs with Human Oversight
Another option is to use AI SDRs. New startups such as Artisan, AiSDR, and 11x have introduced specialized agents that can perform many of the complex outbound prospecting tasks humans have traditionally undertaken, but in a much faster timeframe. AI SDRs can operate autonomously (think full self-driving mode) or with a human-in-the-loop to review and approve key steps in the process.
Research agents can identify your list of ICP accounts and find the best contacts at each company. Qualification agents can analyze buyer intent data, news signals, and marketing engagement to score and rank each account. Personalization agents can use firmographic, technographic, and psychographic data to draft targeted messages for each prospect. Outreach agents execute multi-touch campaigns via email and LinkedIn and monitor for responses.
The term “AI SDR” is certainly ominous to business development teams, but so far we have not seen these new technologies replace humans. Instead, they are being used to augment human teams and increase their productivity.
This article was originally published on my LinkedIn newsletter – Growth Trajectory.
