
140: Jared DeLuca: Appcues’ Director of Ops on integrating demo bookings within your product and using AI to uncover incremental lifts from drip campaigns
10/08/24 • 58 min
What’s up everyone, today we have the pleasure of sitting down with Jared DeLuca, Director of Operations at Appcues.
Summary: Jared takes us inside the mad but amazing world of martech at Appcues – the top product adoption SaaS on the planet. We cover his transition from demand gen to ops, how he’s integrated demo bookings within the product using RevenueHero, the difference between ops and revops. We also cover a ton of ground on AI topics for marketers like machine learning lifecycle management, how to QA AI-driven messages and how to leverage AI to uncover incremental lifts in your campaigns.
About Jared
- Jared started his career with a few internships in PR before joining a Market Research firm
- That firm was later acquired by a UK based marketing data and analytics company where he worked his way up to Marketing Manager
- He then had a brief detour from SaaS at Keurig Dr Pepper in IoT Marketing Automation and Connected Panel Ops
- Finally Jared landed at Appcues, first in Demand Gen then Senior Martech and Ops Manager
- Today Jared is Director of Operations at Appcues
Moving from Demand Gen to Front-End Development
Jared’s shift from demand generation to front-end development was a mix of opportunity and curiosity. When his team’s operations lead left, he stepped in naturally. As the demand gen guy who relied heavily on those systems, Jared was the most logical choice. It wasn’t a calculated career move—it was about filling a gap. That’s how things go in startups, where you often find yourself doing a bit of everything.
His transition into front-end development had a different spark. Budgets were tight, and they didn’t have the luxury of hiring contractors. With years of HTML and CSS experience under his belt from working on emails and landing pages, Jared figured he could handle some of the coding work. AppCue supported the idea, allowing him to stretch into JavaScript. For small teams, having someone in-house with a broad skill set is invaluable, and Jared was more than willing to step up.
What made this shift special was Jared’s personal interest in coding. He enjoyed it. Coding wasn’t just a job; it was something fun to experiment with. One evening, while watching TV, he built a lead-gen magnet prototype in just an hour. It was born from a simple idea pitched by the content team, but Jared’s ability to quickly turn that into a working model showed the kind of spontaneous creativity that startups thrive on. The prototype may soon go live on their website.
Jared’s experience highlights the unpredictable nature of roles in smaller companies. You often find yourself taking on responsibilities you never planned for, and those unexpected opportunities can lead to new skills and career growth. For him, it wasn’t about following a clear path—it was about being adaptable and ready to learn.
Key takeaway: In a startup, being adaptable and willing to learn new skills can lead to unexpected career opportunities. It's less about having a perfect plan and more about being open to filling gaps when they appear.
How AI Tools Are Shaping HTML and CSS Learning
When asked if tools like ChatGPT make learning HTML and CSS easier today, Jared didn’t hesitate to agree. He pointed out how much simpler it is for anyone looking to pick up coding now compared to when he started. Back then, you had to figure things out manually, while now, AI tools can assist with the heavy lifting. However, there’s a caveat—knowing what to ask for is still crucial.
Jared challenged the idea that AI is replacing developers. Instead, he emphasized that understanding the underlying structure of HTML and CSS is still key. Tools like ChatGPT can help speed up the process, but without knowledge of where to apply that code, the benefits are limited. AI can’t tell you how to structure a website; it can only help fill in the blanks once you know what you need.
He highlighted that while AI can handle repetitive keystrokes, the real value comes when you already know what you're aiming for. It’s not about AI replacing junior developers—it’s about leveraging these tools to work more efficiently. If someone understands the basics of coding and web structure, AI can cut down the time it takes to implement those tasks significantly.
For Jared, the most significant takeaway is how much time he saves. What used to take him hours can now be done in minutes with AI. The difference is in the efficiency, not the replacement of skill. If you know what you're doing, ChatGPT and similar tools become an incredible resource for improving speed and output, but they don’t replace the need for foundational knowledge.
Key takeaway: AI tools can dramatically speed up coding tasks, but the real advantage comes when you already understand the basics of HTML and CSS. It’s not...
What’s up everyone, today we have the pleasure of sitting down with Jared DeLuca, Director of Operations at Appcues.
Summary: Jared takes us inside the mad but amazing world of martech at Appcues – the top product adoption SaaS on the planet. We cover his transition from demand gen to ops, how he’s integrated demo bookings within the product using RevenueHero, the difference between ops and revops. We also cover a ton of ground on AI topics for marketers like machine learning lifecycle management, how to QA AI-driven messages and how to leverage AI to uncover incremental lifts in your campaigns.
About Jared
- Jared started his career with a few internships in PR before joining a Market Research firm
- That firm was later acquired by a UK based marketing data and analytics company where he worked his way up to Marketing Manager
- He then had a brief detour from SaaS at Keurig Dr Pepper in IoT Marketing Automation and Connected Panel Ops
- Finally Jared landed at Appcues, first in Demand Gen then Senior Martech and Ops Manager
- Today Jared is Director of Operations at Appcues
Moving from Demand Gen to Front-End Development
Jared’s shift from demand generation to front-end development was a mix of opportunity and curiosity. When his team’s operations lead left, he stepped in naturally. As the demand gen guy who relied heavily on those systems, Jared was the most logical choice. It wasn’t a calculated career move—it was about filling a gap. That’s how things go in startups, where you often find yourself doing a bit of everything.
His transition into front-end development had a different spark. Budgets were tight, and they didn’t have the luxury of hiring contractors. With years of HTML and CSS experience under his belt from working on emails and landing pages, Jared figured he could handle some of the coding work. AppCue supported the idea, allowing him to stretch into JavaScript. For small teams, having someone in-house with a broad skill set is invaluable, and Jared was more than willing to step up.
What made this shift special was Jared’s personal interest in coding. He enjoyed it. Coding wasn’t just a job; it was something fun to experiment with. One evening, while watching TV, he built a lead-gen magnet prototype in just an hour. It was born from a simple idea pitched by the content team, but Jared’s ability to quickly turn that into a working model showed the kind of spontaneous creativity that startups thrive on. The prototype may soon go live on their website.
Jared’s experience highlights the unpredictable nature of roles in smaller companies. You often find yourself taking on responsibilities you never planned for, and those unexpected opportunities can lead to new skills and career growth. For him, it wasn’t about following a clear path—it was about being adaptable and ready to learn.
Key takeaway: In a startup, being adaptable and willing to learn new skills can lead to unexpected career opportunities. It's less about having a perfect plan and more about being open to filling gaps when they appear.
How AI Tools Are Shaping HTML and CSS Learning
When asked if tools like ChatGPT make learning HTML and CSS easier today, Jared didn’t hesitate to agree. He pointed out how much simpler it is for anyone looking to pick up coding now compared to when he started. Back then, you had to figure things out manually, while now, AI tools can assist with the heavy lifting. However, there’s a caveat—knowing what to ask for is still crucial.
Jared challenged the idea that AI is replacing developers. Instead, he emphasized that understanding the underlying structure of HTML and CSS is still key. Tools like ChatGPT can help speed up the process, but without knowledge of where to apply that code, the benefits are limited. AI can’t tell you how to structure a website; it can only help fill in the blanks once you know what you need.
He highlighted that while AI can handle repetitive keystrokes, the real value comes when you already know what you're aiming for. It’s not about AI replacing junior developers—it’s about leveraging these tools to work more efficiently. If someone understands the basics of coding and web structure, AI can cut down the time it takes to implement those tasks significantly.
For Jared, the most significant takeaway is how much time he saves. What used to take him hours can now be done in minutes with AI. The difference is in the efficiency, not the replacement of skill. If you know what you're doing, ChatGPT and similar tools become an incredible resource for improving speed and output, but they don’t replace the need for foundational knowledge.
Key takeaway: AI tools can dramatically speed up coding tasks, but the real advantage comes when you already understand the basics of HTML and CSS. It’s not...
Previous Episode

139: Ron Jacobson: Why multi-touch attribution excels in credit distribution but fails in causality
What’s up everyone, today I have the pleasure of sitting down with Ron Jacobson, Co-founder and CEO of Rockerbox
Summary: Multi-touch attribution doesn’t tell you what really caused a conversion or revenue, it’s a credit distribution system. It’s still a useful guidepost in understanding where your efforts are making an impact. Incrementality testing, on the other hand, digs deeper—helping you pinpoint what’s really driving results by answering, "What would’ve happened without this campaign?" But to get there, it’s not about finding the perfect model, it’s about asking the right questions. Don’t get stuck in the basics like Google Analytics. True measurement demands first-party data and statistical modeling, especially as third-party cookies fade. For startups, the goal is momentum—nail one channel before diving into complex measurement. Build success first, then refine with tools like MTA or MMM to truly understand what drives growth.
About Ron
- Ron started his career as a software engineer before transitioning to product management at AppNexus where he ran the platform analytics team and later the real time platform product team
- He then took the entrepreneurial plunge Co-founding Rockerbox, first as a programmatic advertising platform then a multi touch attribution platform
- And today they’ve added a suite of marketing measurement tools that also leverage marketing mix modeling.
Rethinking the Role of Multi-Touch Attribution
Multi-touch attribution (MTA) often sparks debate around its effectiveness in driving marketing decisions. While many recognize it as a flawed tool, few fully grasp the extent to which it misses a crucial element: causality. When asked whether MTA should be seen as a credit distribution mechanism rather than a way to measure causality, Ron agrees wholeheartedly, explaining that this is exactly how his team has framed the discussion for years.
Ron emphasizes that MTA’s purpose isn’t to assign cause-and-effect between marketing touchpoints and revenue generation. Instead, it's a retrospective tool designed to distribute credit across various touchpoints in a customer’s journey. He argues that marketing teams need to shift their focus from chasing causality to understanding how customers interact with marketing efforts. This approach helps marketers assess what channels or strategies might be working, even if the exact causal impact remains elusive.
A specific example Ron highlights is when clients test new channels like OTT, CTV, or linear TV. Frequently, these clients aren’t sure if the new channel is even making an impact. The issue, he notes, isn’t necessarily that the marketing is ineffective—it’s that the data simply doesn’t reflect customer engagement due to gaps in tools like Google Analytics. While causality is still out of reach, MTA can at least show that the new channel is on the customer’s path to purchase, providing some reassurance that the efforts are not entirely in vain.
Ron points out that this shift in perspective helps marketing teams function more effectively. Rather than getting bogged down by the impossibility of determining exact causality, teams can use MTA to answer more immediate, practical questions: What are the touchpoints that seem to drive the most engagement? Where should we focus next? It’s not about perfectly predicting outcomes, but about gathering insights that improve day-to-day operations.
Key takeaway: MTA isn’t designed to establish causality, but rather to help distribute credit among touchpoints. When marketers focus on how customers engage with their efforts rather than trying to measure cause-and-effect, MTA becomes a valuable tool in refining strategy.
Understanding the Value of Path to Conversion
When diving into the value of the path to conversion, we often struggle with the fact that it doesn’t fully address causality. Just because a customer clicks on a Google link and converts doesn’t necessarily mean that click caused the purchase. It’s possible the customer had already been influenced by a social ad or an email from days prior. Understanding the motivations behind these actions remains elusive.
Ron’s take on this is refreshingly straightforward. He suggests ignoring the model entirely when pitching multi-touch attribution (MTA). Instead, focus on the question: What can you learn from understanding the customer’s path to conversion? By treating MTA as an alternative lens to last-click or first-touch attribution, Ron emphasizes that it provides more context but doesn’t necessarily give a definitive answer to causality. He argues that last-touch attribution, for example, isn’t the best method for understanding the full customer journey.
The real value of analyzing the path to conversion, according to Ron, comes from the variety of questions you can answer. Questions like time to conversion, comparing paths for...
Next Episode

141: Rutger Katz: Cutting through the fluff of Lean methodology and recognizing when process gets in the way of efficiency
What’s up everyone, today we have the pleasure of sitting down with Rutger Katz, GTM Operations Consultant.
Summary: Rutger helps us cut through the fluff of Lean methodology in marketing and how to spot when process gets in the way of efficiency. His advice is to cut out the waste—whether in your process, your tech stack, or how you measure success. Focus on what drives conversions, keep your systems lean, and use simple structures to maintain speed without sacrificing alignment. We also tackle tech debt and how a top-layer AI interface could simplify the case for a composable martech stack.
About Rutger
- Rutger started his career in Neuroscience as a virtual reality developer at two different public research universities to study bodily illusions in VR
- As the VR industry was quite immature at the time he pivoted to martech consulting, where he would spend 12 years working with different technology consulting firms getting a breadth of experience across marketing operations, martech, customer data and go-to-market across a variety of clients including Unilever where he focused on social analytics
- And last year Rutger decided to go out on his own as a GTM Operations Consultant and recently launched NEON Triforce, a boutique consultancy focused on optimizing GTM for B2B scale-ups
- He also recently joined The Martech Weekly as Content Lead for EU & UK organizing their first event in London.
Lean Marketing in Practice
Lean marketing is all about eliminating waste and doubling down on what truly matters. Rutger emphasizes that no matter the size of the company, from a startup to an enterprise, inefficiencies always creep in. These processes—whether learned from someone else or ingrained as “the way things are done”—often aren’t optimal. Lean seeks to strip down these ingrained habits, perfecting the path to deliver value to customers.
Rutger highlights that lean marketing goes beyond just being "efficient." It is about understanding how every action connects back to the entire organization. The real challenge is aligning marketing efforts with revenue-driving KPIs, rather than fixating on vanity metrics like page views or social media follows. For Rutger, Lean is about cutting through those superficial measures to ensure that marketing impacts the business holistically.
What makes lean particularly valuable is that it doesn't stop at marketing. Rutger explains that Lean should apply to your entire go-to-market strategy. This means assessing not just how marketing operates but how it interlocks with sales, customer success, and even product development. It's about delivering maximum value to the customer while ensuring that the organization operates as efficiently as possible in providing that value.
Lean marketing is not a standalone function—it’s a way to optimize the whole organization. When done right, it leads to higher customer satisfaction, longer-term retention, and ultimately, a more streamlined business. For Rutger, this is where the real impact of Lean lies—not just in marketing efficiencies but in enhancing the customer experience across every touchpoint.
Key takeaway: Lean marketing is about focusing on what truly drives value. It's not just about marketing—it's about creating efficiency across your entire go-to-market approach, from sales to customer success, all while tying back to key business metrics.
Solving Inefficiencies in Sales and Marketing Alignment
When asked about real-world applications of lean methodologies, Rutger didn’t hesitate to dig into a common yet overlooked issue: the disconnect between sales and marketing. In his experience, CMOs often claim that everything is running smoothly. But when the conversation shifts towards collaboration with sales, the cracks begin to show. One CMO even mentioned that their sales team requested fewer leads, as they were overwhelmed by the volume. Others spoke of back-and-forth frustrations trying to sync efforts between both departments.
For Rutger, the root of inefficiency often comes at the handoff between marketing and sales. He explained that marketing teams frequently misinterpret sales-qualified leads (SQLs), sending what they define as SQLs but which sales deems unqualified. This misalignment creates friction, wasting time and resources on both sides. To fix this, Rutger advocates stepping back from just marketing processes and focusing on sales first. Understanding sales capacity and needs becomes essential to deliver the right leads at the right time.
A critical step in this process is optimizing for sales’ actual conversion capacity. Rutger highlights that if sales needs to convert 100 leads per month, with a 5% conversion rate, marketing needs to deliver 20 times that amount—2,000 SQLs. He stressed the importance of timely response, pointing out that conversion ra...
If you like this episode you’ll love
Episode Comments
Generate a badge
Get a badge for your website that links back to this episode
<a href="https://goodpods.com/podcasts/humans-of-martech-355655/140-jared-deluca-appcues-director-of-ops-on-integrating-demo-bookings-75820486"> <img src="https://storage.googleapis.com/goodpods-images-bucket/badges/generic-badge-1.svg" alt="listen to 140: jared deluca: appcues’ director of ops on integrating demo bookings within your product and using ai to uncover incremental lifts from drip campaigns on goodpods" style="width: 225px" /> </a>
Copy