Welcome to the newest episode of our podcast! In this new interview, which was led by Mammoth Growth CEO Ryan Koonce, Mixpanel SVP Product Neil Rahilly talks about how useful Mixpanel is for event-based analytics. Neil makes a good point when he says that Google Analytics (GA) is better for looking at how well a website works and how much traffic it gets, while Mixpanel is better for looking at user behavior and asking more complicated questions. While GA can tell you what happened in different website sessions, it’s not meant to tell you who did what in those sessions, Ryan adds more information. Because GA wasn’t made to be a true cross-platform behavioral UX tool, you can’t ask questions about specific users or groups of users. Â.
Google shut down Universal Analytics (UA) on July 1, 2023, forcing growth marketers to switch to Google Analytics 4 (GA4). This gave Mixpanel the chance to create a very specific niche:
Mixpanel’s event-based analytics solution is right in the middle of GA and BI, so it can be used by everyone from growth marketers to product developers to quickly get useful information from their customer data. Â.
Neil concludes the conversation with a taste of Mixpanelâs AI tool, Spark. Mixpanel has done everything they can to make event-based analytics as easy to use as possible. Spark wants to lower any last barriers to entry even more. If you ask Spark a question about your customer data, it will make a chart for you that answers that question. You can see how it did it. Neil says that the next thing Mixpanela might use AI for could be a tool that checks for spikes, drops, or other strange patterns that could mean a data pipeline is broken.
00:05 Ryan Koonce: Hi, everyone. My name is Ryan Koonce and I’m one of the founders of Mammoth Growth. Today I’m happy to have Neil Rahilly with me, who is the SVP of Pat Mixpanel. Hey Neil, hows it going?.
â RK (00:19): Yeah, absolutely. I think one of the main things that people don’t understand is what analytics are. So maybe you can start by telling us how Mixpanel thinks about analytics now, and how that might be different from, say, a couple years ago. Then we can talk about where you’re going.
â NR (00:41): Cool. People can see what’s going on with their users and their business through analytics. They can also track their progress by creating metrics that show how well the product is doing in the business, get answers to their questions, and make smart choices. And really, you’re trying to get into this loop of setting goals for improvement, being able to measure them, and seeing a line move when you make progress. Then you ship changes, and you can really see what the effects of those changes were—what worked, what didn’t—and sometimes the things you thought would make things better made them worse. When you can see the real effects of the changes you’re making and make better decisions based on that information, you’re much more productive. You want everyone in your company to be able to serve themselves. Being able to do that so that they can work in that style.
â RK (02:04): We call that benchmark test and optimize. That’s why we have these loops. The idea is that you need the baseline data first, then figure out what you can do to make it better. Finally, measure it and do it. And so the thing is though is I know what we can do with Mixpanel. A question that comes up a lot in our talks is why not just do this with GA? Why shouldn’t businesses just use GA to do this? When I say “GA,” I mean Google Analytics.
â NR (02:32): Yeah. So I think Google Analytics is really made to help you figure out how well your website is doing and how the traffic you get from Google Ads ends up on your website. I believe that Google Analytics stops being useful when you want to look into more detailed aspects of how users are actually using your product and ask more complicated questions about how they go through certain workflows and how well they remember things. You cant go as deep. A real event-based analytics tool will give you a lot more freedom and help you answer a lot more questions in this area.
â RK (03:39): Well, you cant follow the user through the full journey in Google Analytics. So I think when we think about it, its not really a true cross-platform behavioral UX tool. It just tells you what happened in a session, not who did it in a session. And so I think when we think about, well, I dunno, maybe you chime in on this. I mean, sure, I can test with GA, but I can’t really test to a group of people or to specific users, for example. And I guess what do you guys think about that in terms of analytics, data market, and other analytics tools? For example, some people might say that building dashboards and Lookersa analytics are important. What’s the difference between GA on one end, Mixpanel in the middle, and Looker or Sigma Tableau on the other?
So I think that when you bring up SQL BI on the other side, you have, it’s kind of the opposite or a different set of problems there. Ultimately SQL gives you almost unlimited ability to transform and query the data on. But.
a NR (04:53): Right? Well, that’s what I mean by saying that it’s hard and takes a lot of time, then it costs a lot and moves slowly. Because of this, a lot of the time people either have to wait a long time or don’t get an answer. And in many businesses, there is an analysis team that has to create and set up dashboards, queries, and BI for the product and marketing teams to use. So, when we go into companies, we often hear that the data science team is overworked because they have so many questions that they can’t answer them all. The product and marketing teams are also full. And actually most of the time they hate doing it. It shouldn’t take a data scientist to tell you how many people signed up for this new feature; people should be able to find out on their own.
a (05:55): So, on the one hand, you have SQL BI, which can theoretically go to any depth, but it’s very slow, very expensive, and you need experts to use it. On the other hand, you have Google Analytics, which is kind of a solution for ads and web traffic but not quite, so you’re stuck between two apps. GA is easy to use, but you cant get the answers that you need. You can get the answers with BI SQL, but most people find it too hard to use and too slow. That’s why Mixpanel, which is what we do, is a kind of “sweet spot” place where everyone can use it. Its pretty simple to use. It only takes a minute to set up a funnel report with any number of funnels, retention, and other things. At the same time, you can find out a lot more about it. So we think of it as fast, easy, but powerful analytics for everyone.
â RK (07:04): Yeah, thats great. You kind of touched on this, but as companies make accurate, consistent, reliable, and easy to access data a must (and many still have a long way to go), who do you think should own the data in an organization today?
â NR (07:25): Well, that depends a lot on what size of company and stage youre at. For startups just adding some tracking with something like Mixpanel, its pretty easy. They can easily add that to what they do as part of their work as the engineering team, who are also building the product. The team works pretty closely together. That way, everyone in the company, even if it’s a small one, knows what’s going on, can use the data, and can ask the person next to them if they have any questions. As businesses get bigger, they collect more data, have more teams working on more things, and more people using that data who don’t always know all the background. I think it makes more sense to have a central data team whose job it is to organize the company’s data in a way that everyone can trust and understand. And where that point is, I cant say for sure, but probably somewhere around a couple hundred employees.
RK (08:50): I think that the data teams have trouble understanding that you can identify users, track events, and have time series data in the warehouse and get to it in another place without having to write mountains and mountains of Python and SQL. This is because they were trained on traditional data warehouses and Python and SQL. So, one change I see in the industry is that the data team still has control over the data and maybe even the governance of the data, but other people are joining to help with change management and make sure that the right questions are asked. Really, it’s crazy how many times executives ask for things that don’t really matter, mostly because they can’t get their hands on anything.
â (09:42): And so anythings better than nothing, even if its not the right thing. So the data team isn’t always the best group to change the subject and ask, “Okay, so why are we trying to do this? How do we sort through this huge spaghetti mess that you guys are throwing at me?” It’s interesting that this is changing quickly, and the data teams are happy about it because, to answer your question, data scientists don’t want to do data engineering. They might be able to do data science once we get everything in order.
â NR (10:13): Yeah, yeah, exactly. Theyre freed up to work on higher leverage, more interesting data problems. In that case, I think one of the most important things is that the data team will probably put the data in a data warehouse like Snowflake, BigQuery, or the cloud data warehouse. Sorry, Ryan, I had to plug my own service. So, what kind of analytics tool like Mixpanel do you need? In the past, event-based analytics tools like Mixpanel didn’t need to be connected to a data warehouse at all if you had BI. You track data directly to them. And so what we actually just released is the ability to connect Mixpanel to your data warehouse. And so the data team can really prepare the data there. It can come from all over the company, from support tickets to financial data to product usage data. Anything that’s being put into that data warehouse, they can get it from. To control and join the data, they use dbt or whatever they use. In that case, it can be put into a program like Mixpanel so that people can use it on their own to find answers.
a RK (11:41): I wasn’t going to talk about that, but I’m glad you did because reverse ETL is a hot topic right now. What we find is that some people think it’s the end of everything and that they don’t need to do anything else to get the data. So I think it’s important to make it clear that you can’t send time series data back to Mixpanel if you didn’t have it to begin with because you didn’t get it from an SDK or some other method. So maybe talk about that for a short time because I think people forget that you can’t get some things in the warehouse anywhere else.
â NR (12:18): Yeah, yeah, yeah. So I think you can use a CDP Segment or track a tool like a Mixpanel. Either way, you’ll definitely record some things in your application database, since it obviously picks up a lot of information about what users are doing. If your users table is stable and so are your signups, you don’t need to change that data. In fact, you should use that application data because it’s in a transactional database and is part of your application stack. Your engineering team and your application depend on it being correct. And so its a really, really high quality dataset.
RK (13:12): Signups, sales, or anything else that comes to mind as the thing that we would connect the API to in a normal setup.
â NR (13:20): But then, yes, youve got this whole server side. Yes, you may not save that as a byproduct because it’s part of a much bigger set of things that people do with your product. You may not save any data as a byproduct of that. So, if you want to know what people did in your app, like swipe here, you have to keep track of that product usage and user behavior data. Youve got to track those events. To do that, you need to set up something like Segment or Mixpanel, gather the data, and then load it into your data warehouse. If you want it to be there with all the other data, of course.
â RK (14:04): And I want to emphasize the importance of identity resolution in that front end tracking. So if a user goes to a website and signs up or signs in, we can track them back to their anonymous visits. If they then use an app, we can track them to that app and follow them through the whole journey. Most companies arent capable of doing that just in the warehouse. Nothing is impossible, so I wouldn’t say it’s impossible. But the work that goes into doing something in one place is first Another is something that you have to key in on very frequently because square hole,.
a NR (14:44): Yes, we are on version three of our ID management infrastructure at Mixpanel. It is one of the hardest engineering problems we have ever had to solve. Two of those things might not seem important, but they are very hard to connect if you want to. This is especially true if you’re trying to link activity from different tools and platforms that people have logged out of with activity that people have logged in to.
RK (15:16): Let me put it this way: every two or three months, we get a client or potential client who says, “Oh, no, no problem.” We built our own identity resolution system. And Im just like, okay, well, I know why none of your data adds up now, â.
RK (15:33): Lets go. First, let’s look at that and make sure it works right, because I promise you that it doesn’t work as well as an off-the-shelf system would for that job. And theres too many edge cases that arent accounted for. â.
RK (15:52): I want to quickly change the subject to something that’s been on everyone’s mind lately. This big move to GA4 and how its supposed to be the greatest thing ever. We haven’t seen it do anything well yet, but what do you think about that? How are you talking about the difference in the market right now?
NR (16:15): Yeah, so one of the things that, so GA4’s data model is an event-based system. So Google was moving to an event-based analytics system and that I think its a good thing. It’s making people more aware of event-based analytics, which is great because it’s simple, powerful, and easy to use. Yet, GA4 itself doesn’t seem to be a very good product, according to most customer reviews we saw. Its full of all kinds of, â.
NR (17:13): Its not ready yet. And so I know the record goes on and I hold back and thats been great for us. Because it takes a lot of work to switch from the old GA to GA4, it has really pushed a lot of marketing teams back into the market to see what else is out there. â.
RK (17:42): Well, its just different. I mean, look, lets be real. The old GA isnt even a real tool for analytics. There are some good opportunities there, but if you really want to know what’s going on and check your data, you can’t do that in GA. You need to use something else. And so I think for a lot of people, its just a shock that this other opportunity exists. And thats why thats another reason its so difficult. Its like, go hold on a minute. Next time I measure something, I’ll have to think about it and make sure it’s right. Before, if it was wrong, you didn’t know. â.
NR (18:19): And so its been great for us. A lot of marketing teams have looked around and asked, “Okay, if we’re going to do a migration, if we’re going to move to this new, so what else is out there? We don’t like using GA4, and what it did for us was really speed things up.” We’ve always wanted to go beyond just the product development use case, but that’s where Mixpanel started and where we were mostly focused until about a year ago. But event-based analytics, very generic. An event is just any interaction that your user is having with the product or company. You can model not only what’s inside the product, but also what it’s like to see an ad and click on it. Those are just more events. The great thing about it is that it has a full event stream that lets you see the whole journey. â.
(19:23): Marketing teams needed some things, especially when it came to attribution and multi-touch attribution around just session, page view, and duration on page. We took some features they liked in GA and added them to Mixpanel, so now I think you can do pretty much everything you could do in GA. You can do a Mixpanel and then you can do much, much more. So all of that was done to give marketing teams in Mixpanel a really smooth transition. That’s been a big trend for us over the last few quarters: more and more marketing teams and businesses moving from GA. The last great thing about that is that your product team and your marketing team can now see the same numbers, a
NR (20:25): Historically. Yeah. Yeah. Big problems historically is you get these different departments have completely different views on the data. â.
RK (20:33): I only have a few minutes left with you, so I want to make sure I ask you about AI since it’s being talked about a lot. Wheres AI going with analytics? Are all my data analysts going to be out of jobs soon? â.
NR (20:50): No, I don’t think so. Now that we’ve started, I think there are a lot of places in analytics where these kinds of new large language models could be useful. In the beginning, we let people ask questions using natural language and then made reports and dashboards for them based on
NR (21:13): Yeah, this is called Spark. So thats our AI. And thats really great. These tools are still hard for new people to use, but the cool thing about adding them to an analytics product is that you don’t just give them the answer; they don’t know how you got there. They get the answer in the form of a chart that they can then interact with and look at all the data behind it. And so you can really trust and understand where that answer came from. And you can sort of learn by doing, right? You can learn by example. You had a question, it builds a chart and youre like, oh, okay. Thats how I would answer a question with this chart. It’s a great way to help users get started and save them time, but you still need the analytics tool running in the background. I think its going to help a lot on the data governance side as well. That’s why it’s important to be able to look for things that don’t seem to belong or sudden changes in levels that could mean a pipeline is broken. Thats probably the next space were going to apply AI. â.
RK (22:35): I think we’re in the first inning now. I can’t wait to see where everyone goes with it. â.
RK (22:44): All right. Well listen, were at time, so thank you so much for hopping on today. To sum up, my name is Ryan Koonce and I’m the co-founder of Mammoth Growth. My name is Neil Rahilly and I’m the SVP of product at Mixpanel. Thanks everybody. â.
Getting hired at a top digital marketing agency like Mammoth Marketing is no easy feat. With their innovative strategies and data-driven approach, Mammoth has helped countless brands expand their online presence
To join this talented team, you’ll need to showcase both your hard and soft skills during the interview process. This means not just demonstrating your marketing capabilities, but also your leadership abilities, analytical thinking, and creative problem-solving.
In this article I’ll cover the 20 most common Mammoth Marketing interview questions – from brainteasers to behavioral prompts – and provide tips to help you craft winning responses. With preparation and practice you’ll be ready to nail the interview and launch your career at one of the premier marketing agencies around.
Overview of Mammoth Marketing’s Hiring Process
The interview process at Mammoth Marketing is quick and competitive, with multiple rounds designed to assess candidates’ abilities from different angles.
Here’s a quick rundown of what to expect:
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Phone Screen: 30-45 minute call with a recruiter to evaluate basic qualifications.
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Video Interview: Pre-recorded responses to 5-10 questions testing communication skills.
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In-Person Interview: 4-6 rounds of interviews, including case studies, technical assessments, and behavioral interviews.
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Final Interview: Discussion of compensation, expectations, and final pitch to executives.
With an emphasis on skills-based assessments and collaboration, the process moves rapidly and requires demonstrating marketing competencies on the spot. Advanced preparation is key to shining throughout the various rounds.
The Top 20 Mammoth Marketing Interview Questions
Let’s get into the 20 most frequently asked questions during interviews at Mammoth:
1. How would you design and execute a marketing campaign for a new product launch?
As a strategic planning question, this tests your ability to conceptualize an entire campaign aligned with the product’s attributes and the company’s goals.
Tips:
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Demonstrate understanding of campaign strategy – market research, budgeting, messaging, channels, and measurement.
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Emphasize aligning with product USPs and target consumer insights.
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Provide specific tactics across digital and traditional channels tailored for the product.
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Highlight project management and analytical skills to execute within budgets and optimize based on data.
Example response:
“First, I would dig deep into understanding the new product by reviewing market research and identifying its unique value proposition. From there, I’d define campaign objectives like increasing brand awareness by 15% and acquiring 5,000 new customers in 6 months.
My approach would focus on a multi-channel digital strategy targeted at our core buyer personas. This includes search ads to capture demand for related keywords, an influencer program with relevant creators, and social media promotions optimized for engagement and conversions.
All messaging would align with the product’s key differentiators identified through our research. I’d manage the budget dynamically across channels, ensuring optimal ROI. And I’d measure success through sales, website traffic, social engagement, and brand lift surveys – adjusting creative, offers and targeting accordingly.”
2. Describe your experience with data analysis and how you’ve used it to inform marketing strategies.
With its data-driven approach, Mammoth wants to see that you can translate analytics into strategic insights.
Tips:
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Provide specific examples of analyzing data to improve campaigns – tools used, metrics, insights gained.
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Quantify the impact of your insights on marketing performance with hard numbers.
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Demonstrate you are constantly optimizing based on data.
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Emphasize using a mix of quantitative web/sales data and qualitative user research.
Example response:
“Performing in-depth analysis of website analytics has been crucial for optimizing my marketing strategies. For example, by segmenting newsletters based on user engagement data in Mailchimp, I uncovered differing interests between new and returning subscribers. I tailored content accordingly, which increased CTRs by 32%.
I’m also experienced with Google Analytics, leveraging funnel reports to identify high drop-off pages. This informed site redesigns that boosted conversion rates by 19% for one client.
These examples demonstrate how I continuously analyze KPIs across platforms to gain actionable insights that improve campaign ROI. I’m obsessed with testing and optimization guided by the data.”
3. Discuss a project where you had to manage cross-functional teams; what was your approach to ensuring collaboration?
Here they are evaluating your leadership skills in orchestrating aligned efforts across diverse teams and perspectives.
Tips:
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Discuss a specific project and the different teams/departments involved.
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Emphasize facilitation tactics – clear vision, open communication, defined roles, collaborative tools, and setting shared goals.
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Demonstrate ability to resolve conflicts and motivate teams toward aligned objectives.
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Share a quantifiable result showcasing how your collaborative approach drove success.
Example response:
“As the digital marketing lead for a recent product launch, I had to coordinate across sales, engineering, creative, and PR teams on a tight deadline.
From the start, I established regular status meetings and used Asana to assign tasks, set timelines, and track progress. This transparency kept all teams aligned as launch day approached.
When conflicts arose about launch messaging, I facilitated collaborative brainstorms leading to a consensus that satisfied all parties. This proactive communication was vital for rapid decision making as launch neared.
The seamless cross-functional collaboration resulted in a highly successful launch with sales exceeding targets by 35%.”
4. Can you give an example of a successful strategy you implemented to increase brand awareness?
This question tests your ability to execute effective awareness-building campaigns.
Tips:
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Detail a specific branding campaign you conceptualized and ran.
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Explain your rationale for the strategy and tactics chosen based on the brand’s goals and audience insights.
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Provide measurable results demonstrating your strategy’s success at increasing awareness.
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Quantify performance with metrics like impressions, engagement, recall lift, or traffic growth.
Example response:
“As an example, I led a branding campaign for ABC Company focused on cementing brand recall and visibility among college students in our region.
Leveraging survey data, I knew this demographic relied on streaming music and campus events for discovery.
So I executed an integrated partnership with a popular campus radio station, sponsoring a series of concerts on target campuses paired with concert promotions across the station’s streaming app.
This immersive branding campaign generated over 600,000 impressions on streaming platforms. And our brand recall lift survey showed a 24% increase among college students, proving the strategy’s effectiveness at driving awareness.”
5. Explain how you prioritize tasks when managing multiple deadlines.
Here they want to understand your approach to juggling competing priorities – an essential skill in the fast-paced marketing world.
Tips:
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Discuss your framework or system for task prioritization and time management.
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Provide real examples of successfully prioritizing amid tight deadlines.
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Demonstrate ability to focus on most critical tasks while multitasking.
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Emphasize adaptability when new urgent tasks arise.
Example response:
“When managing competing deadlines, I utilize the Eisenhower Matrix as an initial filtering tool, separating urgent/important tasks from ones that can wait.
For the urgent ones, I block time on my calendar dedicated solely to those projects, guarding against distractions. Daily stand-up meetings within my team ensure we’re aware of shifting timelines and can re-prioritize if new urgent tasks emerge.
A real example was balancing multiple client report deadlines while new requests appeared. I delegated smaller tasks to my team to handle new requests while I focused on the reports. We delivered high quality work across all projects within the deadlines through this structured yet agile approach.”
6. Tell me about a time when you had to adapt your communication style to effectively persuade or collaborate with someone.
They are assessing your emotional intelligence and flexibility in working with a diverse range of people.
Tips:
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Provide a detailed example demonstrating your ability to discern someone’s personality/communication style.
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Explain specifically how and why you adapted your communication approach to improve collaboration with them.
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Share the positive results of adapting your style – were you able to influence or align with them?
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Focus on examples relevant to marketing like working cross-functionally, pitching clients, etc.
Example response:
“When starting as the marketing lead on a software design team, I noticed right away that the engineering manager preferred direct, metrics-focused communication rather than broad context.
So in our discussions, I would clearly frame recommendations in terms of impact on KPIs like conversion rates or growth targets. And I prepared data-backed presentations focusing only on the most relevant statistics.
This aligned well with his analytical approach, making him more receptive to my input. It resulted in the engineering team implementing several of my recommendations that improved registration conversions by over 15%, demonstrating how adapting my communication style drove collaboration and results.”
7. How do you measure the success of a marketing initiative, and which metrics do you typically focus on?
Here they want to assess your proficiency with marketing metrics and proving ROI.
Alaskan Marketing Basics: An Interview with Tyler Williams // Mammoth Marketing
FAQ
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