![What Clay Is aware of That You Do not [+ Video]](https://i1.wp.com/learn.g2.com/hubfs/G2CM_FI1171_Learn_Article_%5BIndustry_Insights_Alex_Lindahl%5D_V1a-2.png?w=1920&resize=1920,1036&ssl=1 "What Clay Is aware of That You Do not [+ Video]")
Your advertising technique could also be caught in 2025.
When you’re rigorously crafting segment-based campaigns, your opponents is likely to be deploying AI brokers that know precisely when your prospects are prepared to purchase — typically even earlier than they do.
“Advertising based mostly on segments is changing into outdated,” says Alex Lindahl, go-to-market (GTM) engineer at Clay. On this unique dialog, he challenges typical advertising knowledge and introduces a revolutionary method that is producing 45% reply charges on chilly outreach. He additionally reveals how AI orchestration is remodeling buyer engagement from a scheduled broadcast into an clever dialog.
As somebody deeply concerned in advancing these advertising frontiers, Alex can also be set to share his insights and hands-on methods throughout an upcoming workshop on the AI in Motion roadshow in Atlanta in June 2025.
This is not simply one other AI assume piece — it is a sensible roadmap for creating what Clay calls “Go-to-Market Alpha,” the aggressive edge that comes from continuous experimentation and adaptation.
This interview is a part of G2’s Q&A sequence. For extra content material like this, subscribe to G2 Tea, a publication with SaaS-y information and leisure.
To look at the total interview, take a look at the video under:
Contained in the trade with Alex Lindahl
Many entrepreneurs are drowning in knowledge however nonetheless combating actionable insights. In your expertise working with Clay’s purchasers, how does an AI-first method essentially change the best way entrepreneurs ought to take into consideration their buyer knowledge?
When fascinated by knowledge utilization, it is necessary to contemplate the various kinds of knowledge which can be on the market. We’ve got structured knowledge, present in databases, CRMs, and product utilization metrics. Then there’s unstructured knowledge scattered throughout the online within the type of weblog posts, job postings, monetary stories, and numerous different sources. So it is advisable acknowledge that every firm has a novel best buyer profile (ICP) and distinct personas that require particular knowledge units. So the secret is determining the place you’ll be able to supply that knowledge, each internally and externally.
With the appearance of AI, we will now deploy brokers to collect unstructured knowledge from across the internet, analyze it successfully, extract significant insights, and develop actionable suggestions. The true energy comes from bringing these two parts collectively and mixing numerous knowledge sources with AI capabilities to speed up understanding and resolution making.
Traditionally, knowledge utilization has largely been guide, typically restricted to primary segmentation for strategic choices. However right now, we will apply AI throughout completely different components of the GTM funnel and enterprise processes to dramatically enhance how we collect info, analyze patterns, and take motion based mostly on complete knowledge insights.
On condition that the hole between producing insights and truly implementing them is a continuing problem in advertising, what frameworks do you advocate for organizations to show AI-generated insights into concrete enterprise actions systematically? Are there particular instruments or processes that you have seen work significantly properly?
Yeah completely. We consider Clay as a system of motion. So inside Clay, you’ll be able to have completely different columns powered by AI or knowledge sources, and AI can analyze and construction this knowledge successfully. As an illustration, should you’re focusing on a VP of Advertising, AI can align the suitable case examine or weblog publish particularly for that individual. The hot button is making use of AI in a structured manner throughout completely different workflow sorts.
AI brokers additionally come into play right here. Traditionally, ICP personas, and advertising and gross sales performs have existed individually with out a cohesive timing aspect connecting them. What I am now calling “best buyer indicators” defines particular indicators that reveal potential enterprise alternatives or challenges the place your product can present worth. This method strikes us away from conventional segments towards signal-based engagement.
And so I got here up with this framework known as “DRIVE” that constructions this method.
D – Detect: Determine the sign and decide easy methods to detect it and the way regularly to seek for it.
R – Evaluation: Analyze what the sign implies. You’ll be able to leverage AI right here — for instance, if an organization is hiring DevOps engineers, AI may also help conclude that they are scaling their engineering workforce. This assessment helps decide whether or not the sign warrants motion.
I – Determine: Uncover challenges the corporate might face in reaching its targets. AI excels right here when educated by yourself knowledge, weblog posts, case research, and their outcomes.
V – Worth: Align your resolution’s worth to the precise state of affairs the corporate is experiencing.
E – Execute: Take applicable motion based mostly on the sign.
The best implementation includes always-on indicators continually monitoring outlined account lists. This lets you goal particular accounts exactly when related indicators emerge, indicating well timed alternatives for engagement.
Remodel your AI advertising technique.
Be a part of trade leaders at G2’s free AI in Motion Roadshow for actionable insights and confirmed methods to reimagine your funnel. Register now
Many entrepreneurs are experiencing “immediate fatigue” from frequently refining their AI directions. What frameworks or approaches do you advocate for creating extra sustainable, reusable immediate methods?
I personally discover immediate engineering extremely enjoyable and highly effective. Particularly as a non-technical individual, as a result of now principally everybody’s changing into an engineer. You should use platforms like Lovable to even immediate your technique to creating an utility. However within the GTM world, there are tons of prompts which you can create, tons of prompts which you can motion.
So, how do you go from simply taking a immediate and refining it over time?
There are a number of approaches to create repeatability along with your prompts. One technique is creating a customized GPT by embedding your refined immediate right into a specialised mannequin, enriching it with contextual supplies and studying sources. This creates a reusable software that persistently generates advertising property or gives aggressive evaluation with out requiring you to recreate the immediate every time.
One other implementation technique includes AI brokers. At Clay, we make the most of an AI agent that executes customized prompts for analysis functions. As an illustration, you may direct the agent to find out whether or not a selected firm has a buying cart on its web site. The agent will go to the location, analyze it, and return with a definitive reply or related clarification.
The true energy comes from making use of this functionality throughout a number of accounts — whether or not tons of, 1000’s, and even tons of of 1000’s — permitting you to scale your immediate’s performance effectively.
The third method integrates these prompts instantly into operational workflows. Take into account a easy instance: When an inbound lead arrives, you may apply a immediate to categorize the individual’s title based mostly on seniority or job operate. A subsequent layer may then advocate essentially the most applicable case examine to ship them. This creates a sequence the place AI interventions result in progressively higher knowledge or motion outputs.
The method requires some preliminary funding in creating, refining, and testing your prompts. Nonetheless, as soon as optimized, you’ll be able to deploy them via customized GPTs, AI brokers, or workflow integrations the place they will operate constantly inside their designated context. This eliminates the tedious cycle of repeatedly copying and pasting prompts into ChatGPT, which rapidly turns into exhausting.
Your “Construct the Prompts & Motion the Insights” session within the “AI in Motion Roadshow” guarantees to assist entrepreneurs rethink their present method. What transformation do you sometimes see in entrepreneurs’ considering from the start to the tip of this workshop?
I believe what lots of people are realizing is that advertising based mostly on segments is changing into outdated. The brand new method is utilizing indicators to align the suitable advertising or gross sales play to your ICP or persona. So, we’re seeing a shift in considering — indicators at the moment are taking priority over segments.
Quite than creating typical campaigns the place you may ship one message this week and a distinct one two weeks later with maybe a couple of variations, we’re now focusing extra on listening to the market, accounts, or people. This permits us to use actions or ship advertising messages exactly once they’re more than likely to resonate with the recipient. That is one of many key insights individuals sometimes take away from our workshop.
One other realization is that immediate engineering, whereas sounding complicated or intimidating, is definitely fairly accessible. You solely want to know some fundamentals to enhance your prompts over time. You’ll be able to start with a primary immediate and easily ask AI easy methods to improve it or what parts is likely to be lacking. This back-and-forth dialogue with the AI helps refine your immediate based mostly on its suggestions, and you’ll incorporate these options and even have the AI rewrite the immediate completely for you.
You simply must ask the suitable questions and take into consideration what the output is that you really want, so you’ll be able to articulate that clearly to AI. And maybe essentially the most important takeaway is discovering how simply you’ll be able to create a customized GPT, apply your refined immediate, and use it persistently to make that immediate repeatable.
This additionally accompanies the broader notion that everybody is basically changing into an engineer right now. You’ll be able to create purposes, construct merchandise, present AI directions, and develop AI brokers — capabilities that weren’t beforehand accessible to non-technical individuals.
It is thrilling that people with out technical backgrounds can now carry out extra technical features by leveraging AI, making your entire course of not simply productive however pleasurable as properly.
Alex Lindahl
GTM Engineer at Clay
Your workshop covers “AI orchestrations.” May you clarify how this idea particularly applies to advertising workflows and supply an instance of how this has improved marketing campaign efficiency?
So, lots of the orchestrating of AI brokers may be completed via a number of approaches. In Clay, it is fairly easy — you arrange a column that applies your AI agent directions repeatedly throughout an account listing. Alternatively, you may deploy an ambient agent that displays for particular indicators or implement a chat agent that engages with clients to qualify leads.
Considered one of my favourite examples includes configuring a customized sign to trace sure key phrases on LinkedIn. When these key phrases seem in posts, each the content material and poster are robotically imported into Clay. The system then makes use of AI to investigate the individual’s title, persona, and message content material. Primarily based on this evaluation — significantly specializing in persona and title — it determines whether or not to proceed with message creation or take no motion.
The following part includes AI analyzing the publish and finishing a easy template like, “I simply noticed your publish on [blank].” with AI filling in that clean house. This creates a customized snippet which you can incorporate into your outreach. From there, an automation can set off both a connection request, a LinkedIn message, or an e-mail to that particular person.
For this explicit marketing campaign, I really noticed a exceptional 45% reply fee, which is completely insane by trade requirements. This success stems from incorporating timing parts and just-in-time messaging through the use of the detected sign to find out the optimum second for outreach. After all, we’re leveraging AI to filter prospects and guarantee we’re connecting with the suitable seniority ranges.
As you’ll be able to see, this method considerably boosts the general marketing campaign effectiveness as a result of it is extra personalised, well timed, and essentially extra related to what that individual is considering or experiencing in that particular second.
For individuals who acknowledge the potential of an AI-first method however work in conventional organizations, what sensible recommendation would you give to somebody who desires to champion these strategies inside their workforce however faces institutional inertia or skepticism from management?
I’d say first develop some stage of consolation and data round AI itself. Take a activity you consider may very well be automated and experiment with instruments like ChatGPT or a customized GPT to streamline it. This preliminary step focuses on enhancing your individual productiveness whereas gaining helpful prompting expertise and understanding what’s doable and what is not.
By this course of, you may naturally change into extra environment friendly and develop shortcuts for particular duties, resembling changing name transcripts into follow-up emails. This hands-on expertise builds your basis in immediate engineering.
Subsequent, establish a challenge inside your workforce the place you’ll be able to create a immediate that is going to assist speed up that challenge and transfer it ahead. And thru that, you are going to begin to expose your teammates to prompting and AI, and so they’ll most likely be fairly stunned. As soon as you have established this foothold, decide easy methods to combine AI into your workforce’s common operations — their each day or weekly workflows. This gradual enlargement demonstrates worth at more and more broader ranges: first private productiveness, then challenge acceleration, and eventually, team-wide implementation.
These progressive successes present the proof wanted to construct a compelling enterprise case. Now you can make knowledgeable suggestions based mostly on demonstrated outcomes: “We have efficiently utilized this at particular person, challenge, and workforce ranges. Let’s scale this method to different departments to attain related return-on-investment (ROI), productiveness positive aspects, and efficiencies.”
If readers may take away only one perception from this text, what would you need them to recollect?
I’d say an important takeaways are actually two issues. First, have enjoyable with AI as a result of AI exploration may be genuinely pleasurable. Second, experiment with your individual use circumstances and inside your organization’s GTM technique.
At Clay, we have developed this idea of “Go-to-Market Alpha,” which is basically discovering methods to do issues otherwise to achieve aggressive benefits. You’ll be able to’t uncover these benefits with out experimenting. Some experiments will not present ROI, however via this course of, you may uncover approaches that work remarkably properly.
The outdated playbooks aren’t working as a result of we have stopped experimenting. We have to frequently experiment to seek out that new playbook, that new wedge, that new ‘Go-to-Market Alpha’.
Alex Lindahl
GTM Engineer at Clay
So hold experimenting each personally and along with your workforce and firm. You will begin to uncover completely different pockets of “alpha” — aggressive benefits that profit each you and your group.
Should you loved this insightful dialog, subscribe to G2 Tea for the newest tech and advertising thought management.
Observe Alex Lindahl on LinkedIn to study extra about sign based mostly advertising.
Edited by Supanna Das