Humans of Martech

What’s up folks, today we’re joined by Bobby Tichy, he’s Co-Founder and Chief Solutions Officer at Stitch. Bobby’s a highly respected Martech veteran having spent over a decade working in technical roles for some of the biggest names in martech:He spent a combined 6.5 years working on the Professional services teams at arguably 2 of the most well known companies in martech, Salesforce and Marketo where he was able to lead and support countless implementation projects for some of the biggest brands in the world.At Salesforce he focused on Marketing Cloud technical and functional architecture. At Marketo he focused on project and program management.In 2016, he left the in-house world and jumped to the agency side of martech working at Lev (a premier Salesforce consultancy) for 6+ years where he focused on Marketing and Enterprise architecture solutions. He also co-founded the In the Clouds Podcast, a show about Salesforce Marketing Cloud.Last year, after Lev was acquired by Cognizant, he co-founded Stitch leading their solutions team. Stitch is a new martech consultancy that specializes in Segment and Braze tech stacks.Bobby’s an expert in all things marketing technology architecture, customer data platforms, customer journeys and Dachshund dogs as the proud dog dad of 3. Bobby, welcome to the show, pumped to chat today.In-house vs agencyI’d love to start by getting your take on agency vs in-house, pros and cons and maybe get the inside scoop on going from SF to arch-nemesis Marketo a few years ago?I think the, the easiest way to think about agency versus in-house is when I was at Salesforce and Marketo, you’re really just focused on the specific problem as it relates to the technology. So that might be implementing, you know, Salesforce, Marketing Cloud or implementing Marketo for a particular customer. But when we’re on the consulting side or the consultancy side, you’re really more focused on that customer. So what problem are we trying to solve? It’s much more about business problems and outcomes than it is technology problems and outcomes.That’s probably the best way to think about it. Or at least the the biggest delineation that I’ve seen over the years, which the consulting side is so much more fun and so much more complex. It has each has its own challenges.On the SF to Marketo switch, I think I I was so naive at that point I had no clue that it was like moving to their arch nemesis. Now it would be like going from Braze to Iterable or you know something along those lines. And it was interesting because I even remember at the time, once I got to Marketo, there were all these kind of rumblings. You never know if they were founded or not. But you know when Exact Target got acquired by Salesforce, was it, you know, who are the other bidders? And I don’t know if you ever listened to the Acquired Podcast, but there’s an episode of Acquired on Exact Target and Scott Dorsey goes through like that whole process. Which is pretty neat. And then he mentions the SEC filings, they actually have to disclose, they don’t disclose the actual companies, but you can kind of deduce who the other bidders were. It’s kind of neat to go through.But anyway when I got to Marketo, there was like all this conversation about Salesforce because the Salesforce and Marketo integration (at the time) was market leading as far as market automation platforms were concerned and the Exact Target and Salesforce integration was not all that great at the time. Now obviously that’s totally flipped, but at the time it was interesting because I remember my first two projects on Marketo and Salesforce, I would kind of throw Exact Target under the bus a little bit with the horrible integration they had with Salesforce even though they were part of the same company. But I I had no idea to your point kind of like the political elements of my switch at the time.Switching platform expertise, from SFMC to Marketo to BrazeSo you went from SFMC to Marketo before going back to a SFMC focused agency but now you’ve left both platforms and at Stitch you guys focus on Segment + Braze. Did you play around with Braze before joining?(At Lev) we had a couple of large enterprise media entertainment customers that were leveraging both Salesforce Marketing Cloud and Braze and so they would use SFMC for journey orchestration and e-mail and then Braze for mobile because it’s the mobile capabilities were so much better. The UI is a little bit better too, especially for marketers. And so that was our first introduction to that platform and then as as we were leaving Lev and trying to figure out what we were going to do next.Everyone that we talked to, people from Movable Inc, people from Salesforce, you know sales leaders there and other people in the Martech ecosystem, all of them were saying like Braze was really where a lot of the marketers were going because it combined a lot of what we all loved about Martech, which was the advanced use cases, the power of the data. But combined all that with better usability, more real time, better mobile capability. So it just seemed like a perfect marriage of what we had experience in, but then also what was up and coming?How would you differentiate the companies that use Braze versus Marketo or SFMC?These are broad strokes, so they’re not specific or like universal comments. But I think the number one thing that we’ve seen for folks who are using Braze is those teams are typically more innovative and fast moving where they’re relying on marketers to build out campaigns and be in the tool every day and where they they understand. I think the other area of that too is they have the best understanding of their data. So what’s really awesome about Braze is this, this real time or event based architecture but also the the ability to to layer in some of those things.One thing that we always came up against whether it was at Marketo or Salesforce Marketing Cloud was we don’t want to bring in all of our PII into the platform. And so you started to see like Movable Inc does a really good job of this, of being able to combine multiple different data sets and then just put to like push out a piece of content or copy that is personalized. But Movable Inc doesn’t require that PII, It’s just based on these integrations that are happening in real time and with Braze we can do something very similar right where I can call out to my Snowflake instance at the time of an e-mail send and I don’t have to bring that PII into the platform, but I can still populate the PII and the e-mail. So these things that are are really fast-paced and moving.I think the area where Marketo is great is on the B2B side. We always saw a lot of customers migrate off of Marketo to whether it was SFMC or Braze because they’re trying to use it for B2C campaigns or for high volume campaigns.Implementating Marketo at TeslaThe one example I always like to use, and this is years ago, but I was on the team that was implementing Tesla at Marketo back in I think it was 2015 and they were launching their Model 3 and it took Marketo about 8 hours to send about 2,000,000 emails. And so obviously I’m sure that’s changed, you know being seven years ago, but at the time was a big deal. It took forever, right? And especially coming from Exact Target, which was this unbelievable sending engine. I couldn’t believe it took that long. So suffice to say that was a bit of an e...

What’s up everyone,If you haven’t checked out our previous 3 episodes in our AI series you might want to before this episode, we give you a lot of context around some of the events that have happened and will shape the conversation today.So basicallyHow fast could AI change or replace marketing jobs?How marketers can stay informed and become AI fluentExploring new paths to future-proof your marketing career in the age of AIToday we’re diving into specific tools… there’s a lot of noise out there right now.What tools you should play around withIn TMW #107 | ChatGPT and the artificial marketer, Juan Mendoza explains that“...generative AI tools are already everywhere. From text generation to video and audio production, to image creation, there’s a thriving industry of technologies taking small slices out of our creative talents, packaging them up, and selling them as a SaaS product on a recurring revenue model. If you’re wanting to stay relevant five years from now in the marketing technology industry, you’re probably going to have to learn some of these platforms. In 2010 we used to say: “there’s an app for that”. In 2023, we will be saying: “there’s an AI for that.””OutlineHere are some of the topics for this third AI episode:Key AI technology definitions and how to differentiate real AI tools vs all the noise out thereDeep dive into toolsContent marketing toolsEmail and marketing automation toolsPredictive analytics toolsText to presentation and pitch deck tools3D animation tools for product marketersSales and outreach toolsText to website creator toolsAd and social creative toolsAutoGPT and AI agentsAnd a bunch of other tools like conversational search engines, 1-1 convos with celebrities and an even longer list of honorable mentions Here’s today’s main takeaway:The key to future proofing your marketing career with the ever changing AI landscape is to stay curious, get your hands dirty and experiment fearlessly: Fill out some forms, spin up free trials, get on wait lists, and give new AI tools a chance. It's only by actually getting your hands dirty that you'll discover which tools truly work for you and which are just part of the ever growing sea of gimmicky AI tools.Definition of tech termsI’ll be using some of these terms throughout my analysis of some of these tools so here’s a primer explaining the three most common AI technologies used for marketing applications: MLMachine Learning): ML is a way to teach computers to learn by themselves, without having to be programmed for every task. They learn from examples and data patterns to make predictions or decisions. Applications include segmentation, predictive analytics and propensity models. NLPNatural Language Processing: NLP is a subset of ML and focuses on enabling computers to understand, interpret, and generate human language. Includes sentiment analysis, machine translation, named entity recognition, text summarization, and more. NLP techniques usually helps computers understand and communicate with humans using everyday language. GNNGraph Neural Network: GNN also a subset of ML is a type of neural network that aims to handle graph-structured data, data organized like a network or web of connected points. Applications include analyzing relationships between different things like users in a social network or users in your database or recommending additional products based on past purchase history. Real AI vs noisePart of the reason AI gets a really bad rep, especially in martech, is that anything that’s built on if statements or simple Javascript logic gets called AI. There’s still plenty of AI startups that shout about their proprietary AI when it’s probably just a few decision trees and a few interns running spreadsheets.Now though, you have an even bigger bucket of noise that’s essentially “slight tweak on Chat-GPT”. Developing AI that was comparable to human performance was a challenging feat prior to GPT's arrival. To achieve this level of sophistication, a company would have had to:make a substantial investment, amounting to millions of dollarsdeveloping its own algorithmsperforming extensive data cleanupBut it’s so easy now because GPT is so good out of the box. Allen Cheng puts it simply. Starting a new AI venture can be achieved by simply assembling a few elements: a product developed on GPT-4's user-friendly APIa website, and a marketing campaign. This is why we’re seeing hundreds of AI tolls pop up every week.A lot of these GPT-based products are pretty much indistinguishable from one another. Maybe a handful  have a significant advantage over others but most are gimmicky. And over the next few months, every tool is going to be integrating ChatGPT features inside their products in the hopes of making it stickier.The threat of GPT-nThe part that I find trickiest and the most discouraging about building anything on top of GPT is that any progress you make on fine tuning GPT-4 will totally be wiped out by GPT-5 or GPT-n… Kind of like we talked about in a previous episode with all the tools GPT’s plugins killed. So let’s cut through the noise and dive into legit AI tools, the ones you should be playing with and experimenting. Content marketing toolsCopy.ai and Jasperhttps://copy.ai/ https://jasper.ai/ AI text generators are very common these days, the two most popular tools, especially for marketers are Copy.ai and Jasper. Both allow you to bypass the initial stage of writing where you face a blank page. The promise of these tools is that they help you in generating ideas, saving time on brainstorming and drafting, and ensuring a consistent production flow, freeing you to focus on higher-level strategic tasks, original research, and connecting with your audience.I’ve played around with both Jasper and Copy.ai before ChatGPT came out… and they were super unique. But both Copy.ai and Jasper are built on top of GPT, they essentially rent usage of the platform. So they built a pretty nice UI on top of GPT… but now that ChatGPT came out, I’m sure they’ve seen a drop in usage. Plus GPT-4 is 3 times more expensive.They still offer marketing specific value though and can get you up to speed faster than using CGPT in the form of templates, prompts and workflows. Both are super powerful, you could make a case that Jasper outshin...

What’s up folks. This is part 3 of our deep dive into AI impacts on marketing jobs.I want to start off by apologizing that this episode might be a bit rusty, I’m attempting to record this while fully sleep deprived thanks to a 1 week old newborn at home haha Our daughter arrived nice and early and, yeah it’s been a wild change in sleeping patterns haha.In our first episode we introduced the topic and covered how fast AI could replace marketing jobs and what the transition might look like. In episode 2 we covered ways marketers can stay up to date with the latest advancements in AI.  Next up, 3. Practical changes and new areas marketers can invest in (today)4. Find the top AI marketing tools and filter out the noiseHere’s today’s main takeaway: AI is already disrupting martech but in 5-10 years our jobs are likely going to look very different. Now is the time to figure out if you need to make changes to your current area of speciality in order to future proof your career. Ask yourself if you should double down on additional areas like data and API services, getting closer to product and customers or starting to learn about ethics and data privacy.Today we’ll help you reflect on different options to investigate as you navigate through this future landscape and what job titles of the future might be in store for marketers.Here’s a quick outline of some of the new marketing areas to potentially focus on that might future proof your career if AI becomes as big as some are predictingOutlineAI tech implementation, find ways to use AI and automate tasksData and API services, exposing data from your business to let AI assistants leverage themGetting closer to product and customers, deeply understanding customers is always going to be something hard for AI to replicateCopywriting, generative AI is great at creating the familiar but can’t yet create the newEthics, privacy and responsibility, AI is really bad at displaying the POVs of underrepresented groupsAnd a look into the future at emerging tech, trying to guess some future job titles for marketersI have to admit, what spurred this whole AI series and what led to my diving into the rabbit hole was a genuine fear, or at least serious contemplation about whether I needed to focus on new marketing areas or pivot in some case.New marketing areas to focus onYeah it’s a totally valid question and probably something a lot of marketers are wondering. Phil you had a great episode previously (part 2) that covered how we can stay informed… let’s chat about what you can do practically about your current situation or at least start thinking about career transition strategies. Some of you listening or reading today are probably already in a really nice spot. Our podcast mission is to future proof the humans behind the tech and if you’re already working with marketing tech you’re in a really nice position to continue the shift towards additional AI and automation. We talked a bit about this in the first part of our series – but I think that AI developments represent that same type of shift that we’ve seen in the past. The change always seems bigger when you look back historically, but living through these developments are step functions not quantum leaps.Still – it bears repeating – the pace of change in AI is far faster than other emerging tech we’ve seen in the past. I think while the tech is moving blazingly fast, there is already considerable pressure to throttle development. One thing that is highlighted in that Goldman Sachs fear report about Millions of jobs being replaced by AI is that despite losing millions of jobs, AI may also mean new jobs and a productivity boom.The report cited that 60% of workers are in occupations that did not exist 80 years ago. Think about aht for a second. I think that all you have to do to see how fast things are going is to pay attention to the developments coming out of ChatGPT. I’ve used it a bit and it’s mind blowing what you can do with it. I asked it to design a workout plan for me based on my age and fitness factors. I specifically told it that I couldn’t be sore or too tired while I ramped up - I chase 4 young kids at home, after all. The plan it designed is solid.I think the bigger factor isn’t how to apply this tech, it’s how quickly will use cases become common place. It’s easy to think of an AI reading all your docs and chat logs and then operating as a support chatbot – but how fast are teams going to move on this type of work? What type of engineering is required by the existing team to get this in place? Why do we assume they’ll automatically lose their jobs? Is it possible the extra efficiency can free up time to be spent on higher order tasks? Have you met a support team that isn’t overrun with requests and also have big ideas on how to improve customer success? There’s a process to tech adoption, and I think it has as much to do with confidence in the tools, concerns around ethics/privacy, and actually figuring out how to implement this stuff.Every week there’s like hundreds of new AI tools coming out. We’ll talk in our next episode about some of those tools but obviously the first new marketing area to focus on is AI tech implementation.While the tech is new, the process of adoption is as old as time itself.AI tech implementationThis might actually not be that new in fact. Scott Brinker recently surveyed martech folks and the most popular task in this role is to research and recommend new tools. Some of those new tools are just going to be predominantly AI driven.https://twitter.com/chiefmartec/status/1647291680788283394?s=20 Most of the Twitter bros are in two buckets right now:AI is going to replace every jobAI won’t replace your job… BUT Someone who uses AI will replace your job if you fail to integrate it.I think it benefits a lot of people on social media to stoke fears to generate buzz – and while there’s some truth to that, sure, one could also make an argument that AI could unlock an economic golden age.The question isn’t about the technology – it’s about human nature.As an individual contributor, I think AI will feel like a super power. There is no doubt that there is an opportunity out there for tech savvy marketers to use AI to level up and accelerate their own work. I think it’s fair to say we’ll see general adoption and benefits as well. Let’s unpack this.Peep lays it out nicely here, a nice niche for marketers is Ops folks who continue to find ways to use AI to automate t...

What’s up folks. This is part 2 of our deep dive into AI impacts on marketing jobs.In our last episode we introduced the topic and covered how fast AI could replace marketing jobs and what the transition might look like. It's not like our jobs are gonna vanish overnight, but the shift is happening faster than many of us realize. AI's no longer just a loosely backed buzzword; it's doing things today that we used to think were impossible. So, as marketers, we've gotta take this tech seriously.Next up, 2. Staying informed and keeping up with changes (today)3. Practical ways marketers can adapt for the AI-driven economy4. Find the top AI marketing tools and filter out the noiseOutlineHere are some of the topics for this second episode:Staying informed, who to follow, courses to check outIn person events and networkingExploring new sources of incomeHere’s today’s main takeaway: The impact of AI on the job market is difficult to predict in 5 years let alone 10. The only way to future proof your career and position yourself to thrive in an increasingly AI-driven economy is by staying informed and developing new skills. We’re going to double down on some of these in today’s episode.Commentary/question on shiny object syndrome vs being an early adopter.As a marketer, it’s our job to stay modern - it’s true of any job, but marketing is on the next levelWe self propel change and create our own reasons to change things up. We suffer a bit from herd mentality as well – I think we tend to rush the new trend, be it TikTok or ChatGPT and choose saturation instead of considerationI don’t think the value of being an early adopter is being “first;” rather, it’s giving yourself time to immerse yourself and begin to master the topicTo learn a topic, you simply can’t read 5 blog posts and master it; I firmly believe you need to get hands-on experienceShiny object - Try to make a buck, dispose of poor performer, invest in top performers; easily distracted by next objectEarly adopter - thoughtful approach to seeing new technology as part of wider trend; has playbook or process for learning and evaluating new tech, How marketers can stay informed and become AI fluentStaying up-to-date on the latest developments in AI and AGI is probably the top thing you can do as a marketer. Understanding capabilities as they are released or even pre-released. This allows you to get a leg up on others and see the potential impact on your company, industry and even job market as a whole. My goals would be to understand how AI works, its potential, and limitations. Most marketers don’t have a great grasp on this at all. Invest in learning about AI, ML, deep learning, and related tech. Ultimately try to arm yourself with knowledge to position yourself as a marketing expert in leveraging AI tools to drive revenue.I think you and are very similar in our approach to this: learn from smart people, and then jump in and experiment and get hands-on experience. Phil, your research process is always fire: who are the smart people you’re learning from? People and blogs to followThere’s waaay smarter people that are tracking this stuff. Not all of these have a marketing lens but they often cover marketing aspects. These are my favorite folks to follow.We’ll have links to all of their twitter accounts and their newsletters or podcasts in our show notes. Ed Gilhttps://twitter.com/eladgil https://blog.eladgil.com/ Ed is an awesome follow on Twitter, he’s an investor and advisor in some of the most well known tech companies like Airbnb, Coinbase, Instacart, OpenDoor, Pinterest, Square, Stripe and others. He worked at Google and Twitter after his company Mixer Labs was acquired. Aside from AI he’s highly in touch with everything tech and startups. He doesn’t post super often but he has a solid blog and he’s the co-host of No Priors podcast that features long form chats with the leading engineers, researchers and founders in AI. Ben Tossell (tuh-sell)https://twitter.com/bentossellhttps://bensbites.co/ Ben’s the Founder and CEO of Makerpad, one of the top sites to learn and work on no-code tools. He currently works at Zapier, focusing on AI after they acquired Makerpad last year. Before that he led Community at Product Hunt and later AngelList when they acquired Product Hunt in 2016. He runs one of the most popular AI newsletters called Ben’s Bites, it’s easily been my favorite daily way to stay up-to-date with the latest AI happenings. Sarah Guohttps://twitter.com/saranormous https://linktr.ee/nopriors Sarah’s a startup investor and the founder of Conviction, an early-stage VC firm specialized in AI startups. She made waves in SF during her time at Greylock, a top VC firm in the Valley, where she became their youngest general partner. She’s the other co-host of No Priors podcast alongside Ed Gil. She has an extensive network, and her close association with Andrew Ng (ing), the co-founder and leader of Google Brain, persuaded her that a "deep learning revolution was coming".Natasha Mascarenhashttps://twitter.com/nmasc_ https://pod.link/equity Natasha is a senior tech reporter at TechCrunch covering startups and AI and is the co-host of the Equity podcast. She wrote a super interesting article that summarized the discussions that took place during the Cerebral Valley Summit earlier this month. Ben Parrhttps://twitter.com/benparr https://benparr.substack.com/ Ben Parr is a seasoned tech industry analyst, he’s a journalist, author, investor, founder, and operator. Known for being Editor at Mashable and journalist at CNET, he’s also the co-founder of Octane AI, developing AI products for ecommerce.His long time column The Social Analyst covers the intersection of technology, particularly AI, and its effect on society. He’s highly entertaining on Twitter and doesn’t shy away from predictions and hot takes like recently when he pleaded that people stop saying GPT-4 can’t replace their jobs, he says “Yes, it can. It's only a matter of time”. So obviously on the AI enthusiast train. Shawn @swyx Wang

What’s up JT, good to chat again. When you aren’t podcasting or consulting, what are you reading or listening to these days?Yeah I’ve been BUSY. Bobiverse books, of course but also lots of Mario with my kids – haha, my downtime totally spent on guilty pleasures.Haha yeah you had a head start on Bobiverse but I overlapped you… that’s probably going to change soon for me… I don’t think I’ve announced this on the cast yet but my wife and I are on baby watch, first born arriving at any second now which s why we need to record a few episodes hahaI’ve actually been getting back into podcasts lately. Maybe I’ll plug a few of my favorites ahead of our next episodes. I’ve really been digging Making Sense of Martech lately. Juan Mendoza is the guy behind the podcast, he’s a friend of the show and he’s been doubling down on it, pumping out weekly episodes. If you want to go deep on some technical topics, in episode 37 he had the CEO of Hightouch Data on and he debates the merits of reverse ETL and they really unpack CDPs. Check it out.In the non marketing podcast world I’ve been taking a dive into the world of AI. No, not fluffy my top 10 ChatGPT prompts and buy my course type of content, way darker shit, like will marketing be replaced by AI in 10 or 20 years… sooner? My buddy Alex recommended The Ezra Klein Show. The episode is titled Freaked Out? We Really Can Prepare for A.I. On the show he has Kelsey Piper, a senior writer at Vox. She basically spends her time writing and being ahead of the curve covering advanced A.I.In that episode she says something like: “The AI community believes that we are 5-10 years away from systems that can do any job you can do remotely. Anything you can do on your computer.”Recently Goldman Sachs released a report saying AI could replace the equivalent of 300 million jobs. A day later Elon Musk, Andrew Yang, Wozniak and several other tech leaders wrote an open letter urging a pause in AI development, citing profound risks. So I went down a rabbit hole and it really prompted the next 4 episodesHow fast could AI change or replace marketing jobs?How marketers can stay informed and become AI fluentNavigating through AI in your marketing careerFind the top AI marketing tools and filter out the noiseSo basically1. How soon and how significantly will this impact my job2. How do I keep up with changes?3. Is it possible to adapt? How can I future-proof myself?4. How can I start right freaking now?!?Today we’re going to be starting with setting the scene and covering how fast shit is changing right now. Here are some of the topics for this first episode:AI isn’t new, especially for enterprise companies with lots of dataBut unlocking some of the potential for startups is going to be hugeWill all these advancements just make marketers better and more efficient?or will it actually push founders to go to market without a marketerMarketing will have massive changes because we primarily rely on the ability to understand and apply existing rules and processesWhat does ChatGPT have to say about all this?What if AI is one day actually able to replicate human creativity and emotional intelligence?We’ll talk about potential mass unemployment but the more likelihood of new job opportunitiesHow fast AI has disrupted other jobs alreadyHow AI might simply only ever replace the shitty parts of marketingHere’s today’s main takeaway: It's not like our jobs are gonna vanish overnight, but the shift is happening faster than many of us realize. AI's no longer just a loosely backed buzzword; it's doing things today that we used to think were impossible. So, as marketers, we've gotta take this tech seriously.Instead of asking if AI's gonna replace our roles in marketing, we should be talking about how quickly it could happen and what it'll look like if it does.A bunch of really smart marketers (and non marketers) out there are saying we need to hit the panic button. They're predicting that in just 5 to 10 years, we'll see a massive change affecting all sorts of remote jobs. Times are wild right now. So, fellow humans of martech, let's keep our eyes on the future and continuously evolve and adapt.JT I don’t want this episode to be fear mongering… I’d actually love to chat with people that are way smarter than us about AI and get both sides of the coin, those who believe AI could have a fundamental impact on marketing jobs and that AI is as important of a paradigm shift as the Internet was… people like Darmesh Shah, like Scott Brinker, and those who believe it will never completely happen and are still on the AI-skeptic side of things like Rand FishkinI think it's ok to be a bit uncertain or even afraid of what the future may hold with this new technology.As humans, we face an interesting dilemma -- we are capable of using and creating technology that don't fully comprehend ourselves. Our society is built on layers of abstractions -- you don't need to know how water purification or plumbing works to turn on your tap and get a glass o water.My deepest fear is not that we adopt and use these technologies -- it's that we do so without considering the cost.The only thing worse than being afraid is being unprepared.I think marketers can benefit immensely from a boom in AI tech -- that easily could extend to basically any other human discipline.Truth is that we have to deal with the facts on the ground.I think there are a lot of smart people to consider following to get different takes on the potential of impact. We'll load the show notes with links so you can check out our research.AI in marketing has been around for a whileWe’re not just waking up to AI for the first time lol we’ve obviously talked a lot about it on the cast and have been playing with AI and automation tools for a while right?ChatGPT is my big one – Really love it as a prompting tool to help me round out topics; I’ve used it for a personal coding project and I’m pretty stoked with what it can produce.But even before GPT, as marketing automation admins, we’ve actually been playing with ML features… maybe not considered AI for everyone but things like:Send time optimizationAutomated lead scoringSentiment analysis toolsAnd some cooler shit like propensity modelsIt’s worth s...

What’s up everyone today we’re talking about marketing roadmaps. Rodmaps are usually more common with tech product teams and they are also very common in the project management world. It’s about giving your team the big picture and helping everyone align on project goals. Anyone who’s been in marketing knows that this is something super useful that can be applied to this practice as well.Key takeaway: While it doesn’t always have to be set in stone, a roadmap helps your team stay accountable to certain tasks and deliverables but it’s also a focus weapon that arms you with the ability to say no to new requests. You work on priorities and capacity, you share it with other departments for feedback and it becomes marching orders. DefinitionOkay so how would you define a roadmap?Definition: A team roadmap is a visual overview showing what projects and tasks will be worked on and when.It usually includes objectives, milestones/tasks, deliverables, resources, and a timeline.A roadmap can serve as a reliable reference guide to help keep the team on track and share with other stakeholders your key projects and objectives. So how do you bring this to life?So I like to do this quarterly. Usually I have a backlog list of projects. This is made up of ideas and things that have popped up over time that we want to get to eventually. From the backlog, you want to try and assign a priority. This exercise can be wildly complex but it can be a simple ICE exercise (Impact, confidence, effort).One keep component as you score projects is company goals and OKRs. Defining the business goals and objectives that the marketing team will work to support. This is usually trickled down in some capacity from management. It might include goals related to increasing brand awareness, generating leads, or improving customer satisfaction.Then you look at capacity, how many hours of work does your team have this quarter, subtract meeting time and PTO. One thing I like to do here is keep a buffer of 15% time for unexpected urgent tasks that pop up.Then you can decide what stays in the backlog and what gets prioritized for the upcoming quarter.There’s a bunch of different tools you can use for roadmapping, whether it’s Jira, Asana, Trello, Notion or others, they all boil down to very similar functions.Start with a list of core projectsBreak up the projects into sub tasks and milestonesAssign task owners and deadlinesDescribe each task and highlight dependenciesToolsWhat are the best tools to developing a timeline for the initiatives and activities, including key milestones and deliverables.There are many different tools that organizations can use to develop a timeline for their marketing initiatives and activities, including key milestones and deliverables. Some common examples include:Project management software, such as Notion, Asana, Trello, or Microsoft Project, which can be used to create a visual representation of the timeline, track progress, and manage resources.Collaboration tools, such as Slack, Google Hangouts, or Microsoft Teams, which can be used to communicate with team members, share information, and collaborate on tasks.Gantt charts, which are graphical representations of the tasks and dependencies within a project. Gantt charts can be used to visualize the timeline, identify potential conflicts or bottlenecks, and adjust the schedule as needed.Spreadsheet software, such as Microsoft Excel or Google Sheets, which can be used to create a tabular representation of the timeline, track progress, and perform calculations.Overall, the best tools for developing a timeline will depend on the specific needs and preferences of the organization. By using a combination of different tools, organizations can create a comprehensive and effective timeline that helps them plan and execute their marketing initiatives and activities.What’s your fav tool?Trello never fails. But I’ve become a big fan of Notion.Yes, Notion can be used for project management and roadmaps. It’s usually thought of as a company wiki or a place to write memos, but it’s so much more… and if it can also help you manage your projects… imagine combining all of that in one place.Many teams haveA company docs or wiki like ConfluenceThey have a project management tool like Asana or JiraAnd then they have a bunch of scattered docs in the form of google sheets, google docs, foldersThat usually includes a bunch of emails alsoBut imagine if you could have just 1 tool to rule all of these. At my startup we use Notion pretty heavily. Not every does this to a T, we do have some stragglers, but imagine a world whereCompany docs and memos are no longer emails or a various panoply of google docsProjects are managed in one spot and reference things in the same tool, no need for separate logins or extra credentialsAll in Notion.Notion is a versatile and customizable productivity tool.I use it personally but also at work, like I mentioned.But because of its versatility, Notion sometimes gets a bad rep when it comes to project management or roadmapping… I’m here to tell you it can all work in there.Notion has a database that enables you to have a variation of views on projects and items, it has templates, it has comments and tracking changes features, it can do anything Trello or Asana can and more.Identifying stakeholdersIt’s easy to assume you chatted with important folks before diving into projects but speaking from experience, forgetting a key stakeholder and realizing it too late can create major chaos.What's the best path to identify dependencies and stakeholders?Conducting a stakeholder analysis, which involves identifying and prioritizing the stakeholders who are relevant to the project or initiative, and assessing their interests, needs, and potential impact. This can help organizations understand who the key stakeholders are and what their priorities and expectations are, and can inform the development of the project or initiative.Creating a stakeholder map, which is a visual representation of the relationships between the stakeholders and the project or initiative. This can help organizations understand how the stakeholders are connected, and can identify potential areas of conflict, collaboration, or influence.Developing a stakeholder engagement plan, which outlines the strategies and tactics that will be used to engage and communicate with the stakeholders throughout the project or initiative. This can help organizations ensure that the stakeholders are involved and informed, and can provide feedback and support as needed.Overall, identifying dependencies and stakeholders is an important step in the project or initiative planning process, and can help organizations understand the potential impacts and risks, and develop strategies to manage them effectively. By using a structured and systematic approach, organizations can improve their chances of success and achieve their goals and objectives.Sharing your roadmapFinally, how do you share this roadmap?Some possible approaches include:Creating a visual representation of the roadmap, such as a timeline, mind map, or infographic, which can be used to illustrate the key initiatives, activities, and milestones in an engaging and easy-to-understand format.Using storytelling techniques to communicate the roadmap, such as narrating a journey or...

What’s up everyone? Today is a bit of a follow-up on the previous episode about building dashboards, check that one out first if you haven’t already.Today we’re taking this a step further and talking about data models and the limits of building dashboards.Here’s a typical stance on dashboard design:It is best to focus on the ideal scenario, and worry about the practicalities of implementation later, Or “let the ops team worry about that” as they call it. Haha yeah… This approach may seem appealing at first, as it allows designers to imagine and create without constraints. However, as a marketing operations person, I’m not a fan of this.Here’s today’s main takeaway: I believe that understanding how a dashboard is powered, and having a sense of what is possible and what is not, is a crucial differentiator.Too often, I have seen dashboard projects built in a vacuum, disconnected from the reality of the data and the systems that support them. In these cases, valuable time and resources are wasted building an idealistic dashboard that cannot be implemented or used effectively.Today we’re going to be breaking down how you can level up your knowledge about data models or the capabilities and limitations of the data and the systems that support the dashboard, and designing solutions that are feasible and effective. By understanding these constraints, designers and marketers can create dashboards that are not only beautiful and engaging, but also practical and useful.I feel like this topic could get hairy pretty fast, so let's break down some definitions for the listeners. Da hell is a data model, let’s start there.What’s a data model?Data modeling is a way to organize and structure data from different sources in a consistent and useful way. It helps to make data more accessible and organized, so it can be easily analyzed and interpreted.Gimme a non marketing example, how would you explain this to your mom?Example: A simple example of a data model is a phone directory. The data model for a phone directory would include information such as the names and contact information of individuals, as well as the relationships between them (e.g. family members, colleagues, friends). By organizing this information in a consistent and structured way, the phone directory can be used to easily look up and contact individuals. This data model helps to make the information more accessible and useful.Okay what about a marketing example, that was too simple.I’ll go with my bread and butter, Email marketing example: One example of a data model for email marketing might include information about the email campaigns that have been sent to different segments of your audience. This data model might include details such as the subject lines, Type of content, Subject line keywordsMain call-to-action You would also have the results of the campaignsopen rates, click-through rates, conversion ratesBy organizing and structuring this information in a consistent and meaningful way, the data model can help the email marketing team track the performance of their campaigns and to identify areas for improvement. For example, the data model might show that certain subject lines or content types don’t generate as many opens as some emails but they perform better at driving clicks and conversions, and the email marketing team can use this information to optimize their future campaigns. So why should marketers care about this? It’s to prevent shiny object syndrome and understanding where the numbers are coming from but also give you the ability to customize your dashboard.Exactly. A data model is the first step in allowing you to have a dynamic/interactive dashboard. Describe an interactive dashboard in simple termsDescribe an interactive dashboard in simple terms for the listeners. It’s being able to interact with the charts and elements to analyze different parts of your dashboard, for example; filtering certain elements and changing date ranges. This is what sets them apart from reports. For me, I see it as a personal assistant of sorts. An interactive dashboard allows you to easily filter, slice, and drill down into the data, revealing insights and patterns that might otherwise be hidden. Unlike a static dashboard or report, which shows the same view for everyone, an interactive dashboard lets different users explore the data in their own unique ways.What’s a simple example that most folks would understand?Imagine a sales manager who needs to understand the performance of her team across different regions and product lines. With a static dashboard or report, she would see the same view for everyone, with no ability to filter or drill down into the data. But with an interactive dashboard, she can easily select the regions, the individual reps and product lines that she is interested in, and see the data that is most relevant to her. She can even save her custom views, and share them with her team, so they can all see the data in the way that is most useful to them.Basically, a dynamic dashboard allows you to go from metric reporting to data exploration and analysis. In episode 64 we talked about GA4 so I have a GA example here.Example:Consider the following scenario: your marketing team has built a Google Analytics (GA) dashboard that shows monthly traffic data. The dashboard is static, which means that it updates every month, but it does not allow you to filter or drill down into the data. When you log in to the dashboard, you see the same view as everyone else, with no ability to customize or explore the data in your own way.Now imagine that, instead of a static GA dashboard, your marketing team has built a dynamic lifecycle dashboard that is powered by a data model. This dashboard allows you to filter the metrics by user attributes or campaign events, so you can see the data that is most relevant to you. For example, if you want to see how your email campaigns are performing, you can easily filter the metrics by channel. Or, if you want to see the impact of in-app messages, you can filter the metrics by that attribute. And, because the dashboard is dynamic and interactive, you can explore and analyze the data in your own way, without being limited by the pre-defined views of a static dashboard.Yeah. So where does the data model fits into this? Well the data model is what allows you to have a dynamic dashboard, especially when it comes to combining data from different sources. So data source > data model > dashboard? Is that the hierarchy? Yeah I think that’s fair.Understanding your data modelSo here’s a practical example:Let’s say we have two main data sources:New signup events from you...

What’s up everyone, today we’re taking a dive into the world of dashboard building.Startups may not always have the luxury of having a dedicated data analyst on staff, which means marketers may need to get more hands-on with data. Yeah I haven’t had the data analyst luxury in my career very often! In episode 38, we discussed marketing reporting and how you can use key reports to help highlight impact and find new opportunities. But we’re not talking about reports here right?That’s right, dashboards aren’t reports. They are living breathing snapshots of key areas you want to keep an eye on in your business.Yeah I think a lot of people don’t make that distinction and just assume reports = dashboards = chart. Where should marketers be starting? With charts?Scatter plots, bar charts, pie charts, maps, funnels, box plots… There’s a bunch of different chart types and visualizations at your disposal when you're designing your dashboard, but this isn’t where you should start.Here’s today’s main takeaway: When designing a dashboard, it's important to focus on the decisions you want to make, rather than just the metrics you want to track. Before building your dashboard, consider your audience and bring together the right people to answer key questions. This will help you create a prototype of your first version.Dashboard projects are close to both of our hearts. Both having worked for Klipfolio (a dashboard SaaS for startups and SMBs), we’ve spent a fair amount of time researching and writing about the internal dashboard building process.There’s obviously a critical collaboration piece to this that would be an initial starting point for anyone taking on a dashboard project. Yeah one thing we always said about building good dashboards is that it takes a village.So Phil, you’ve actually led the charge in this area at a few startups. What are some of the questions you should be asking as a marketer to get started?Questions before buildingThe first questions to tackle as a team are: What metrics would you look at on a regular basis to measure performance and determine areas for growth? What metrics do you care about the most?So ultimately, this depends entirely on your team goals and the top priority metrics we’ve selected as a group. These goals further inform how to prioritize views and metrics in our dashboard. What does this group of stakeholders look like when you’re starting to build things?Stakeholder groups:Main viewers: Who will be digesting or regularly looking at the dashboardMarketing Ops/Data Ops: What resources to you have to help you build the dashboardDesigner and point person: Who’s scoping out the dashboard and driving project management as well as designing the end dashboardAdmittedly, in startup land, you’ll likely be wearing all three hats. I know I have. But in bigger teams, you’re working with a lot more moving pieces. Yeah I’ve gotten a taste of both of these. Small teams and bigger teams. There’s advantages to both. But I think regardless, it’s important to get a lay of the land first.Yeah it might be helpful to walk through an example. You’ve been pretty deep in lifecycle marketing in your career. Maybe give us a real life example wearing a lifecycle hat. So Phil, you’re Director of lifecycle and you’re tasked with building out a lifecycle dashboard.Here’s a list of example questions to ask yourself and stakeholders Yeah I like the lifecycle example actually. It’s broad enough to touch most parts of marketing so I can  use it as goal posts as we unpack some of this stuff.Your goal with these questions is to figure out what metrics we care about the most, getting a benchmark and establishing a goal for each of these metrics and how they have been trending over time.Current segment/vertical data we get on signups, are there specific segments we know we want to grow?Current lead scoring on signup events, are we scoring leads based on email and domain and any other data we might be collecting?What’s the current activation rates of signups after the first email, what’s our deliverability rate on the first email to signups?Are there specific lifecycle status labels that we are currently using, ie Content lead/subscriber > Signup > Active/published site > Upgraded. Do we currently have micro stages/do we care about this detail, ie in between signup and active we might have, installed theme, created a page and created a menu.Do we currently have the ability to attribute multi touch events for email engagements? Meaning, if a signup opens a pricing email on day 4 and they click the plans link and they buy 2 hours later, is that email getting $%?With all of this information on hand, or at least identifying areas of focus and priority metrics, you can then start scoping out the first prototype of the dashboard, intentionally with too much information, with the hopes of cutting things out in following iterations. Exactly. Next we can talk about metrics that flow in from those questions. What metrics you should consider for the first prototypeThe critical piece of this phase is to spend time understanding the most important things to monitor and give ourselves time to explore different ideas before rolling out a finished dashboard.Here are the core areas of a lifecycle dashboard, with a focus on conversion rates, starting at signups (explicitly did not scope content lead > signup):Signups, signups by segment, signups by lead scoreConfirmations, signups > confirmation %, deliverabilityActive (published a site)Behaviors (installed a theme, >2 pages, menu)Email metrics, engagement score, top emails, ab testsConversions to plans, signups > conversions %, % in first 30 days, % after 30 daysUpgrades, plan breakdownRevenue impactYeah that’s a lot obviously, depends how long you want your dashboard to be but we’re still in the prototype phase here so more is better and you can always remove stuff later or create a second dashboard.The main takeaway of this episode though as we said is that When designing a dashboard, it's important to focus on the decisions you want to make, rather than just the metrics you want to track.So how do we do that?Focus on the decisions you want to makeSomething we want to keep in mind as we narrow the list of important metrics are the decisions we want to be able to make. The goal of our example dashboard is to monitor the lifecycle marketing performance and identify growth opportunities. That means answering questions like:Are we improving sign up engagement and conversions over time? Are specific segments or campaigns driving better conversion rates than others?Should we double down or kill this experiment/emailSo ultimately, the focus of the dashboard should be on Signups > activated(published site) rates and Signups > upgrade conversion rates in the first x days and the viewers should be able to see the impact across the funnel over time. So now that you have a better idea of all the metrics you want to start with, one of the next steps you can start thinking about is chart types, how you’d like to ideally display your data.Choosing chart typesScatter plots, bar charts, pie charts, maps, funnels, box plots… There’s a bunch of different chart types and visualization...

Universal Analytics is sunsetting in July 2023, and its replacement, Google Analytics 4, isn’t exactly getting a warm reception. For digital marketers, SEOs, analysts, and basically anyone else who got used to GA3 over the past decade, it’s a bitter pill to swallow.Ok, I’ll confess: I’ve been a bit further behind on Google Analytics 4 than I wanted. Like many marketers, I struggle to balance martech innovation against the reality of my day-to-day life. I admit I had been procrastinating on learning GA4, but no more.I’ve spent the last few months going as deep as I can on GA4 and, by extension Google Tag Manager. I’m not going to sit here and tell you that GA4 is Google’s gift to digital marketing – I think it’s still an immature platform.I am going to tell you GA4 is getting a much worse rap that it deserves precisely because so many marketers have been deep in GA3/UA for so long. Changing habits is tough, and GA4 makes it more challenging because of a new interface, not too mention a completely different approach to web analytics. No big deal - you can learn all this in a Sunday afternoon, right?Yeah, that’s going to be tough.Today I’m going to give a procrastinator’s guide to GA4. If you’re expecting me to complain about GA3, this episode isn’t for you. We’ll mourn the loss of GA3, briefly, but then move on to making the most of this situation. I don’t think GA4 is all bad – actually, GA4 is pretty slick and I think if it weren’t for the contrast to its predecessor, many folks would be pretty happy with GA4. – – – Alright JT, it’s great to be back behind the mic. We’re starting off with a fun one here. I’ll admit I’ve been out of touch with top of funnel reporting and analytics for the last couple years so I’m excited to learn about GA4. There’s rightfully been a lot of noise since its release in October 2020… maybe we can start there actually, the Google decision. Google has basically said that they are making the switch from Universal Analytics (UA) to Google Analytics 4 (GA4) in order to provide users with “more advanced tracking for digital marketers” But aside from new features like automated events, cross-device reporting and BQ support, there’s a lot more behind the decision to make the switch.Why is Google making the switch from UA to GA4?Needs attribution: Lawsuits in EU where UA used as evidencePrivacy regulationsEnd of 3rd party cookies, rise of first party cookiesSingle-page applicationsEvent-based measurementSo October 14, 2020: This was the date when Google officially announced GA4 and began rolling it out to users. What dates should marketers be aware about when it comes to the “forced switch from UA?”What are the important dates and why are they importantJuly 1, 2023, data collection stops. 6 months later, you won’t be able to access your dataYou’ve got 6 months to move to GA4 or another web analytics solution or you’ll be flying blind… You need a solution for your historic data (excel, bigquery, or API)Sounds like it’s time to put down that Netflix remote, grab a cup of coffee, and dive into the exciting world of GA4!It seems like such a big hurdle… JT, how can marketers start to learn GA4?How do I learn GA4There’s going to be a few layers to learning GA4. Let’s break it out into 2 roles:Web Developer, implementationDigital marketer or web analystFor web developers or implementers, GA4 can be installed directly on your website by inserting the code directly onto each page. This isn’t new. I think what is new is that GA4 is much more closely tied with Google Tag Manager. It is absolutely the recommended way to install and configure GA4. There’s a whole episode or series about Google Tag Manager we could do, but the short of it is that GTM gives you a huge toolset to do tons of cool stuff: event tracking, sending additional data through dataLayer, and modifying your implementation without having to directly modify your website.If you’re not already using GTM, GA4 should push you to start using it.For digital marketers and analysts, the task is about getting used to the new interface, migrating configuration settings from GA3, and making a habit of pulling reports from GA4. The big hurdle here is matching up the data from both tools – because I’ve never actually seen both tools give the same number.I think this is what people are most unprepared for: the new reporting paradigm and definitions. Things like users have modified definitions, in no small part because GA4 is better at tracking individual users and corrects known errors in GA3. However, whenever a disparity in the numbers arise, much hand-wringing and gnashing of teeth ensues…So getting it installed and playing around with new features is one of the first things folks should be doing. Data history and collection is important.These new features are more powerful and are said to help you better understand and optimize your digital marketing efforts… JT, what are some of the new features that excite you the most compared to UA vs GA4?What is different between GA3 & GA4Bounce rate, conversion tracking, user definitions;Event-based approach, more akin to product analytics tools, and, frankly, this is better for modern web (problem: vast majority of sites aren’t on modern tech)User InterfaceData collection and real-time dataData retentionSo gone are the days of needing to manually set up event tracking codes for specific things like we had to do in GTM? No, still more than enough in GTM. Enhanced Measurement gives us some events out of the box that seem to mostly work for some websites. Events are much better in GA4 – can send custom parametersOne thing a lot of folks mention is improved cross-device reporting, have you dived into this? How is Google associating traffic from multiple devices to unique users?I’m more of a Redshift guy than Big Query these days but I do feel like the switch to GA4 is also pushing many users to adopting Big Query right? GA4 includes native support for BigQuery integration, which allows you to connect your GA4 data with other data sources in Google BigQuery.JT what do you like the most about GA4 so far? Is it the Conversion Probability report or the Customer Lifetime Value report? Or just the new UI and design? What does Jon like about GA4?It might seem like putting lipstick on a pig, but I kind of like GA4. Maybe I’m just coping a bit or being obstinately positive, but change is the name of martech. This isn’t the first time I’ve had to switch tools against my will, and it won’t be the last.Everything is a tool, and GA4 is no different. Events are customizable and don’t have to send same parameters/fields as UA. You can send anything which is powerful when looking at custom data.Conversion events are much more accurate (citation)Reports are much more customizable and better lookingMachine learning to surface insightsSome of the coolest ML insights come in the form of predicting the likelihood that a user will convert on your website or app. This is based on their behavior and other factors. So theoretically, your business can better identify high-potential users and tailor your marketing efforts accordingly.Do you know what this looks like practically? Can you push segments of these users to BQ then Hubspot and send custom emails or better yet, to your product and surface different offerings?So like we said, there are many wa...

Season 1 featured our first 50 episodes, 20 of which were guest episodes. In today’s episode we’re going to recap our key takeaways from each guest episode in season 1.Our first guest episode featured Lauren Sanborn, Director of RevOps at CallRail. She recently moved over to DataRobot, an AI cloud platform for Data Scientists.  Aside from leaving us with several marketing and sales alignment tips, my favorite takeaway from Lauren was to not be so hard on yourself if you don’t know what you don’t want to do (for work). Her advice was to get out there and try different things so you can start to mark off what you don’t like. Eventually you’ll find something that you love.”Our next guest in episode 07 featured one of our most senior and perhaps most accomplished guest, Brian Leonard, former co-founder of TaskRabbit and now CEO of Grouparoo (recently acquired by Airbyte).Brian went pretty deep on the relationship with marketing and engineering and my favorite takeaway was that marketers and engineers shouldn’t think of themselves as doing completely different things inside a company. At the end of the day, both groups are there to move the needle on the business. So the best way to think of it is to come together to power the right stack.Instead of pitching to product, marketing needs this, pitch it as, the company needs this and this is how it will benefit everyone. For example, marketing attribution isn’t a marketing or a marketing ops thing. It’s a company thing.Next up was our boy Nick Donaldson in episode 10, fresh off a new consulting gig at Perkuto. Another marketer who’s moved on to another company, he’s now running Marketing Operations at Knak. Nick is wise beyond his years and my favorite takeaway from our chat with him was that the number 1 skill to succeed in marketing ops is curiosity. Early in your career Google and twitter are your best friends. There’s so many smart people that have been in your shoes and are nice enough to share those insights. Find them. Read them. Learn from them.So 10 episodes in and we already had a RevOps Director, a CEO and founder and a consultant. We also had a Professor. In episode 11 we were joined by friend of the show Jonathan Simon.This might have been controversial amongst his peers at the University but we’re happy to report he’s still in his current gig (lol). My favorite takeaway from our chat with Jonathan is that you don’t need a degree to have a successful and happy career in marketing anymore. More than anything, marketers need to be adaptable to changing tech and strive to be lifelong learners. He talked a lot about side hustles and starting something, in his course he actually gets all his students to start a blog and build something during their time there.Episode 17 featured Ottawa native Julie Beynon who leads analytics at Clearbit. Things got technical pretty fast but I think Julie did an awesome job introducing data warehousing and making it seem a lot less intimidating.My favorite takeaway was when she explained that a DWH doesn’t have row limits and isn’t limited by your laptop’s CPU. She loves a Google sheet as much as any data driven marketer, but at some point, startups need to upgrade from that clunkiness to a data warehouse solution.It’s been fun seeing the martech landscape shift from; APIs for everything and we integrate with all your tools to – we build on top of your data warehouse or we connect natively to Big Query.Keeping to the data theme, we had Steffen Heddebrandt in episode 19. Still almost a year later he’s trashing Google Analytics on LinkedIn (lol). He’s the co-founder of Dreamdata, an attribution solution for B2B startups and SMBs.Attribution still gets a bad rep, we heard Corey trash it in season 2, but Steffen has solved big pieces of this puzzle at his startup. My favorite takeaway from our convo was when he declared that when it comes to revenue attribution, GA is basically close to useless for B2B companies. Multi touch attribution software does sound like magic when you’ve tried to orchestrate it yourself, but give Dreamdata a spin if you’re still skeptical about it.Episode 25 featured Naomi Liu, Director of Global Marketing Ops at EFI. Naomi spends some of her time mentoring future marketing ops leaders and was hiring for an entry level marketer on her team at the time so we centered our conversation around how to ace your first marketing job.My favorite takeaway was when Naomi said that new marketers should be asking lots of questions. Be that annoying kid in the back seat asking all of the questions.Episode 27 featured friend of the show and local Ottawa social media maven Erin Blaskie. She recently made the switch from leading marketing at Fellow to go back to freelancing as a fractional CMO.My favorite takeaway was when we asked her how marketers should choose between the freelance route and working in house. She thinks everyone should try both. Throw out everyone else’s definition of success and make your own by trying different things. Big company, startup, agency, freelance, give them all a shot.In episode 37, we had another manager who was hiring on her team. Shannon McCluskey leads marketing ops at Clio and my favorite takeaway was when she described the role of marketing ops.We are not order takers, we’re active consultants designing our own destiny. Sometimes we need to evaluate solutions our partners haven’t thought of. We don’t always say yes to every request we’re given.Episode 39 featured co founder and CEO of Kank Peirce Ujainwalla. A well known face in the martech scene, we asked him to weigh in on the html vs text debate for emails.He said it’s important to do a mix of both. Text emails have that personal feel, but HTML is still super important for all your visual users and telling your brand story.Episode 41 featured another local Ottawa and social media expert and now head of marketing at Fellow – Manuela Barcenas. She’s also a productivity nut and my favorite takeaway was when she said that her biggest productivity superpower is knowing what to work on when you open your laptop in the morning. Time blocking and planning your week ahead of time by scheduling tasks and deep focus blocks.In episode 44, friend of the show Roxanne Pepin from Rewi...