#191: Drive | How To Measure Your Marketing Efforts with Pranav Piyush, Co-Founder & CEO of Paramark

This episode is from Drive 2024, our first-ever in-person event for B2B marketers in Burlington, Vermont. Pranav Piyush, Co-Founder & CEO of Paramark, hosted a session on one of B2B's biggest challenges: measurement and attribution.

Pranav covers:

• Why attribution models like first-touch and last-touch are outdated
• How to prove the incremental impact of marketing channels, including search, social, email, podcasts, billboards, and brand.
• How to present marketing's value to the CFO and CEO

Timestamps

• (00:00) - - Intro to Pranav
  
• (06:01) - - Marketing IS Measurable
  
• (06:44) - - What Does Attribution Mean?
  
• (09:59) - - Do Search Ads Drive Incremental Sales?
  
• (11:16) - - How To Find Cause From Search > Impression > Click > Conversion
  
• (13:09) - - Google’s Conversion Lift
  
• (14:36) - - Do Social Ads Drive Incremental Sales?
  
• (16:02) - - Tracking Demo Bookings vs. LinkedIn Impressions
  
• (18:17) - - Do Emails Drive Incremental Sales?
  
• (20:47) - - Do Podcasts Drive Incremental Sales?
  
• (23:59) - - Do Billboards Drive Incremental Sales?
  
• (26:23) - - How Do You Measure Brand?
  
• (31:18) - - Why You Should Experiment to Understand Attribution
  
• (33:28) - - The Long Term Impact of Brand Equity
  
• (35:13) - - How to Measure the Impact of Videos and LinkedIn
  
• (36:26) - - Impressions vs Results
  
• (39:36) - - Impressions vs Demos
  
• (43:33) - - Wrap Up

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Dave Gerhardt [00:00:12]:

Hey, it's me, Dave. So this is a special episode. This was a session that we recorded live at drive, our first ever in person event, which was early September in Burlington, Vermont. It was incredible. We had 200 people there. The NPS after the event was 88. We're going to do it again this year.

Dave Gerhardt [00:00:31]:

Don't worry. I know there's a lot of FOMO out there. For those of you that didn't make it, we're going to do it again September 2025. But we have all of the recordings right here for you on the Exit Five podcast. Now, this is just the audio if you want the full video and see the slides and everything that is available exclusively in our community. Not on YouTube, not on the Internet, nowhere else except inside of Exit Five in the community. Join 4400members exit5.com and you can see all the content. Okay, let's get into this session from.

Pranav Piyush [00:01:01]:

Drive.

Dave Gerhardt [00:01:05]:

Our next guy. So for a while before I did Exit Five podcast, I did this podcast where I interviewed CMOs. And at the end of the podcast, I asked every cmo, I said, if you could snap your fingers and have one marketing problem solved in your career, what would it be? Just shout out what you think they said. I'm sorry, what was that, sir? Did you hear that? They all said attribution.

Question [00:01:28]:

Right?

Dave Gerhardt [00:01:28]:

This is the thing that we've all been trying to solve for so long. Pranav has an awesome background. He ran marketing@build.com he was at Adobe, and now he's crazy enough to try to solve this problem himself. But I've learned a lot from him. I don't know how many people in the Exit Five community that are here. Yeah, he's done an awesome job just like being in there, answering helpful questions. And I think when we were putting together this event, we were like, we got to have him do this. He did a webinar with us earlier in the year and it was one of the most popular ones we've ever done.

Dave Gerhardt [00:01:54]:

So I'm super excited to see the live version of Helping us figure out measurement and attribution. Here's Pranav.

Pranav Piyush [00:02:13]:

There's a story behind that. There's a story behind that. So, I´m Pranav. It's impossible to follow the last speaker with the energy and the velocity and the speed and the passion. And that's why I'm actually here. There are probably many creative people in the crowd, so raise your hand if you primarily think of yourself as a creative professional. Raise Your hand. Okay, What I'm going to tell you is you all are Batman and measurement is Robin, not the other way around.

Pranav Piyush [00:02:49]:

So everything that I say for the next 30 minutes is not to put measurement and attribution and experimentation on some pedestal. It's not. It is a tool to help your creative excellence reach as many people in your audience as it can and influence growth, revenue, business outcomes. That's what matters. And what I'm here to tell you is that many people say, well, you know, it's impossible to measure everything. You're going to leave the next 30 minutes, and you're going to leave this room thinking the exact opposite. You're going to have the confidence to answer your CFO and your CEO, look them in the eye and say, yes, I can measure that. I'm going to show you how.

Pranav Piyush [00:03:34]:

How many of you have heard or seen this quote before? Right? Do you know who this guy is? John Wanamaker. All right, sorry. The Science of Getting Rich. Okay.

Dave Gerhardt [00:03:50]:

He had a department store in Philadelphia.

Pranav Piyush [00:03:52]:

He had a department store in Philadelphia in The, I think, 1900s. Okay. And old school. He was actually, allegedly, also the person who invented, apparently, advertising like this was the guy who figured out that I can put some ads in the newspaper and bring more people to my department store. So 1900s. And the guy's like, I can't tell you which half is working. We're sitting here in 2024. We still can't tell which half is working.

Pranav Piyush [00:04:22]:

Right? So this is a perennial problem. And again, I will tell you, it's no longer the case. We can measure which half is working. And I'll show you. You might also have seen this. This is a very related quote. How many of you have heard this or something like this before? Right? What you want to measure is not measurable. What you are measuring doesn't really matter.

Pranav Piyush [00:04:46]:

There's more truth to this than anything else, right? The whole conversation about MQLs and traffic and leads. If you're in B2B, you know, all of that is essential to the conversation we're going to have today. And this one's my favorite. I don't know who said it, but it was fun. So I put it in here. Okay. Now, the biggest thing I would say is I really think you need to focus on what are the right marketing metrics, because I do think we're way past the stage where marketing is not measurable.

Dave Gerhardt [00:05:14]:

Marketing is absolutely measurable.

Pranav Piyush [00:05:16]:

We've talked about this. We always have great conversations on LinkedIn.

Dave Gerhardt [00:05:20]:

You need to be able to Measure this stuff.

Pranav Piyush [00:05:23]:

Okay, do you know who this is? Bill? He was the ex CMO at Zendesk and Slack and before that an SVP at Salesforce. Before that a VP of marketing at ign. And I think he started at Fox. So he's seen consumer, he's seen business, he's been a cmo. Look at what he's saying. Oh, it's all measurable. So what does he know that we all didn't know? And frankly, I didn't know this till like five years ago. Okay, the villain.

Pranav Piyush [00:05:57]:

So in this mission possible, we're going to talk about the villain. That is attribution. I hate that word. The real meaning of that word is cause and effect. Cause and effect. That is literally the meaning of that word. If you don't have cause and effect, it is not attribution, my friends. Okay, so just keep that concept in your head.

Pranav Piyush [00:06:19]:

Anytime somebody talks about attribution, what they're really asking is, hey, this thing that you did, did it cause the business outcome of sales or growth or whatever? Nothing else matters. Why do I call that the enemy or the villain? Because in the pursuit of attribution, we've invented all this stuff. First touch, last touch, multi touch. That has nothing to do with cause and effect. It's just all bullshit. And I'm not afraid to say it. So what? The real question that your CFO is asking, that your board is asking, that your CEO is asking, is how much incremental growth are you driving from your sales and marketing efforts? You don't see any mention of attribution in that question. They don't care.

Pranav Piyush [00:07:06]:

Attribution is the means to that end. And so when you think about incrementality, which is unfortunately not even a real world, but it's out there, you have to start thinking from what is the organic demand in the market for your business? What is the word of mouth that is being driven just because your customers love you? Hopefully your customers love you. How much brand equity have you built up? The longer that you have been in business, the bigger the brand equity that you have just because you've been there, right? Coca Cola. You don't need to be reminded of Coca Cola because of an ad. You know of Coca Cola because it's existed for 100 years or maybe more, then you have marketing and sales. Now if you think about that layer cake, that is the question that you're trying to answer. Your sales, your pipeline, your leads, your opportunities, every month, every quarter, how many of them are organic demand, word of mouth built up brand Equity, and then how much is coming from marketing and from sales. When you reframe your conversation in this way and you go back to your CFO or your CEO and show them this, they're gonna love you.

Pranav Piyush [00:08:16]:

I can guarantee that. You may not know the answer to how to quantify that just yet, but for the first time, you're gonna have an intellectually honest conversation about what is driving growth for the business. That's what matters. So we're going to go on this journey, five different missions, and we're going to walk through real examples of how I would do this if I were in your shoes. We're going to talk about search, social, email, podcast, billboards. Billboards? Yes. You can measure billboards? Absolutely.

Dave Gerhardt [00:08:47]:

Did you see that guy with the truck out there?

Pranav Piyush [00:08:50]:

I did not, actually. All right, okay. Now, one thing before I even go on these missions, just because you can measure something doesn't mean you have to. That's not what I'm saying at all. And so that's an important distinction. I'm not going to measure the impact of coming to this event. That's dumb. Right.

Pranav Piyush [00:09:12]:

And so you also have to have the confidence to be able to talk about this with your leadership and put it into perspective. Why are you asking about measurement in the first place? Okay, so let's talk about search. The unfortunate reality with search is that is the number one thing that you all probably do in your businesses, right? That's the first paid advertising that goes out. And the reality is it's arguable. Is that even marketing? Is that even advertising? And so how many of you have read the book by Byron Sharp, how Brands Grow? Anybody? Okay, Very few. Homework. Everybody should be buying that book. I got nothing to do with it, but it's a great book, and it'll reframe how you think about marketing.

Pranav Piyush [00:09:58]:

The concept that you learn from Byron is there's this idea of physical availability and mental availability. This idea is very simple. It basically says you have to be available in somebody's mind. You have to have a presence in their mind. You have to be thought of whenever a certain keyword or trigger or job comes up in their mind. And then you have to be physically available. When they go to the department store and buy something, it needs to be on the shelf. Google search is very much like that.

Pranav Piyush [00:10:29]:

Google search is physical availability on the Internet. When somebody has already done the search, they're landing on that Google page. And if you're not there, you're missing out on sales. But is there cause and effect behind that something inspired the search that led to the impression that led to the click that led to the conversion. It wasn't Google that inspired the search. It was something else. So the cause is something else. There is no attribution to look for in your Google search results.

Pranav Piyush [00:11:02]:

And that's the reality. Now here's a really scientific example of this. This is from 2011, a dozen years ago. This is ebay. And they turned off ebay, public company, I think it was like $50 billion back then in terms of valuation. They turned off all of their paid advertising on Google and on Microsoft. Guess what happened? Nothing. All of it just went to the organic channels.

Pranav Piyush [00:11:28]:

Literally. There are papers written on this. I think you'll have access to this. You'll just look up the. Yeah, there you go. Berkeley Haas data scientist who did this research in 2011. It's 2024 and we're still debating this shit. It's crazy.

Pranav Piyush [00:11:45]:

Okay, this is from Google's YouTube videos. The first screenshot says cookie based measurement continues to degrade. Hmm. So anytime you need to talk about attribution and cookies and Google Analytics or anything that you're implementing on your website, pixels, UTM codes. This is coming from the horse's mouth. Google itself is saying, hey, it's not working, so you better do something else. What is that something else? Conversion lift. How many of you have heard of that term conversion lift? Okay, homework.

Pranav Piyush [00:12:22]:

Everybody needs to go back Google conversion lift. Okay, and why am I telling you this? They productized this experiment to actually work across Google, across YouTube and it's available to you. Call your Google rep and tell them you want to run a conversion lift study on your branded search, on your non branded search. And you will have quantified answers on the incremental contribution of those keywords of those ads to your business outcomes. It's all available and I'm just shocked that 90% of the people hadn't heard about it. So, okay, second, social ads, do they drive incremental sales? And this is a particularly interesting question. Let's think about social ads. TikTok, LinkedIn, YouTube meta.

Pranav Piyush [00:13:10]:

The primary way in which you consume this content is not based on intent. You're not actively searching and clicking on things going into LinkedIn. You're there because you're bored. You're bored at your job and you open up your LinkedIn and you're like, entertain me, entertain me for the next like five minutes before I have to go jump on this like stupid, boring webinar. Sorry. All right, so there you go. Good Job well done. Well done.

Pranav Piyush [00:13:49]:

Okay, so social works the same way as tv. This might sound weird and bizarre to you all, but it does. It's literally just a different medium for the same thing. You don't click on a TV ad, you don't click on a Super bowl ad, you don't click on a radio ad, you don't click on a podcast ad. Yet all of those things influence your buying decisions. Same way for social. So guess what? Facebook has the same thing. It's called conversion Lift, and it's even available diy.

Pranav Piyush [00:14:23]:

You don't even have to call your Facebook rep. Log into your Facebook Ads account. Go to the Experiments tab. It's right there. How many of you have tried a Facebook conversion lift test before? Zero. And you're probably sitting here thinking, facebook doesn't work for B2B. Absolute nonsense. It does.

Pranav Piyush [00:14:42]:

It absolutely does. And you finally have the tools to prove the incremental contribution from Facebook to whatever goals you have for your business. Now, what about organic social? What about organic LinkedIn? We are all on organic LinkedIn. How do we show the impact of that? I was literally talking at lunch with somebody. I don't know if he's here listening in or not, but it's all possible. Facebook makes it. LinkedIn makes it a little bit harder because they don't make it easy for you to get your employees, your team members data out from LinkedIn. But you can do a personal export, get that data.

Pranav Piyush [00:15:15]:

And what I'm showing you here is pretty simple. The chart on the left shows you your demo bookings. Let's say that is the key metric that you're optimizing for, and you've had lots of investment in organic social. I want you to do something very simple. Create one spreadsheet that plots your demo bookings on a weekly basis for the last 52 weeks. Take your LinkedIn organic impressions from your profile or from your company page and just put them on a spreadsheet and map it out and see what happens. There's two possible things that are possible here, okay? One is, as you have grown your LinkedIn organic impressions, your demo bookings have also gone up. Voila.

Pranav Piyush [00:15:56]:

What is that? That's called a correlation. This is how you understand the relationship between two metrics. Now, there's a weak correlation, right? Because on the left, you're seeing this, like, hockey stick chart on the impressions and barely any movement on your demos. Now look at the chart on the right. What does that show? Every time your impressions go up, your demos go up. Every time Your impressions go down, your demos go down. That's showing you a stronger correlation between your impressions and your demos. You take this back to your finance team, they will love you.

Pranav Piyush [00:16:28]:

Because now you're talking about quantified ways of linking things that you thought were not measurable, but they actually are down to financial metrics that they can put in their projections. Okay, this is Meta. This is from Meta's website again. 91% of people who could buy your product don't click on your ads. News alert from like this morning, I think, or yesterday. Facebook is literally starting to strip out UTM codes from their ads. How many of you heard that? You saw that, right? Somebody saw that. I'm not bullshitting.

Pranav Piyush [00:17:00]:

Okay, good. They're actively moving the discussion away from utms and click IDs and all the click based attribution because people do not click on their ads. They influence in a different way. So you need a different way to measure the impact of your Facebook ads. I wouldn't be surprised if LinkedIn does the same in the next 12 months. I wouldn't be surprised. By the way, Apple already did this five years ago. If you open up your Apple mail and you click on a link, the UTM codes don't pass through to your website.

Pranav Piyush [00:17:30]:

Five years ago. So old news. Okay. Do emails drive incremental sales? This one's the funnest one. How many of you think that if you stop doing all email tomorrow, just all email, you just stop doing it? Would it impact any of your business metrics for the next couple of months? What do you think? Any brave ones? When I talk about this? Yeah. What do you think?

Dave Gerhardt [00:17:56]:

I think absolutely.

Pranav Piyush [00:17:58]:

All right, by how much? For me, 10%. How did you come up with that number?

Dave Gerhardt [00:18:06]:

Based on self reported attribution where people set my newsletter is what made them reach out.

Pranav Piyush [00:18:10]:

Amazing. Okay, so that's great. You have a quantified answer.

Dave Gerhardt [00:18:15]:

Real small though. I'm not like an enterprise brand where it's messy and complicated.

Pranav Piyush [00:18:20]:

Okay, there we go. Now I'm going to give flowers to a company called Customer IO. I don't work for them, but they're great. The reason I talk about this is they've actually made incrementality testing a native part of their email platform. And how does it work? It's very simple. Whoever that you're going to send your email to, whether that's a nurture campaign, whether that's a one off newsletter, whether that's a welcome onboarding series, whatever it is, you can create a holdout group the concept of a holdout group is essentially saying we're going to take 10% of your audience that you would have sent this email to. We're not going to send the email. And then we're going to look at conversions not from that email, but from your first party data in your database, in your CRM for the demos, for the trials, for the sales that happened or did not happen.

Pranav Piyush [00:19:14]:

This allows you to do a true comparison of whether sending that email actually moved the needle for your conversion metrics or not. Now this is very different from I think Brendan Brendan's example, smaller base and you can get some self reported attribution to get you some directional answers. But when you're doing 100,000 emails and you're starting to see that unsubscribe rate go up and up every month, now you have a way, a tool to test which of your emails are actually working versus not no debates. Okay? Do podcasts drive sales? I can keep going, right? Like you give me any channel and we can talk about how you can prove the incrementality of that channel. There's two examples that I like to hit here. Any of your direct podcasts, I saw a bunch of hands go up. You have your own direct podcast production and there's a way to measure the impact of podcasts to your business metrics. The second is advertising.

Pranav Piyush [00:20:10]:

If you're doing something like podcast advertising through Spotify, they give you all of the data that you need that feeds into that same type of correlational analysis, your listens and your demos. So here's a very simple example. If your podcast listens are going up into the right and your weekly demo bookings are going up into the right, that's a good sign. That's what this chart is showing you. If you saw the alternative, where those dots were all over the map, right, in all four quadrants of the map, then you know that your podcast listens and your demo bookings have nothing to do with each other. That's randomness. So it'll take you five minutes to get this data, put it in a spreadsheet, plot it again, it's all measurable. Okay, last one.

Pranav Piyush [00:21:00]:

Billboards. What do you do with billboards? There's this really interesting company, Statsig. How many of you have heard of Statsig? How many of you have seen their billboards? All right, this is a fun one. So again, I don't work for Statsig. They might even be considered a competitor. What I do, and that's fine. They had a good billboard. Ab testing Saves VC money.

Pranav Piyush [00:21:17]:

Good tagline. We ab tested this billboard against that one. This one lost. So how do they test these billboards? They were being cheeky with the advertising here. But the reality is, the way you test billboards is by doing the same type of holdout testing with geographies. You buy a bunch of billboards in Burlington, you don't buy a bunch of billboards in New York. And you look at your demo bookings from Burlington versus from New York and you have undeniable evidence over a six week period of whether your billboards worked or did not. Now this gets a little bit more scientific.

Pranav Piyush [00:21:54]:

There's more data science. You probably want to have a marketing analyst do the math for you. It's more complicated. But hey, guess what? It's doable. You can do it. It's all measurable. So again, the spirit of this conversation, right we started with measurement is impossible. Don't talk to me about measurement.

Pranav Piyush [00:22:17]:

We got to be creative, we got to take big risks. All of that is true. But when your CFO and your CEO ask you, how do you measure the impact of that? You now have a clear answer. And I don't expect marketers to be able to do this yourself. Your answer is going to be, please help us find a marketing analyst who understands correlation and can run this analysis. Now, you can do some of this yourself. If you're curious, if you're technically savvy, come find me. I'll give you a whole bunch of toolkits to allow you to do that.

Pranav Piyush [00:22:48]:

The reason I threw this up. This gets a lot more complicated when you have search, social, emails, podcasts, billboards, all running at the same time. Now what? Right now, we're far away from home. A spreadsheet ain't going to cut it. But guess what? If you go talk to a Coca Cola to a png, to an Asana, to a doordash, to an Uber, to a Salesforce, to a plaid to a square. They are all doing this through data science. And all the concepts that I talked about are available to those brands and becoming increasingly available to even smaller brands. It's all possible.

Pranav Piyush [00:23:24]:

It's a question of do you have the will and the courage? And the last thing that I say is, do you fear finding out whether you're fudging up? If you're not, then you won't have any problem figuring out how to measure all this. Okay, last one. Bonus brand. This one gets me going. Oh, brand branding, brand marketing. Does anyone know what any of that means? The reality is the words Prevent us from doing justice to brand measurement. Brand by itself is nothing. Brand is Pranav.

Pranav Piyush [00:24:02]:

Pranav's name is the brand. Coca Cola's insignia is the brand. Exit Five is the brand. So how do you measure brand? That's like a dumb question. How do you measure Coca Cola? How do you measure Pranav? How do you measure Exit Five? That's a dumb question. So the question to ask is not how do you measure brand? The question is to ask, how do you measure the effectiveness of your brand campaigns? And here's the answer. If you measure the effectiveness of your brand campaigns through awareness, you're going to get fired. Why do I say that? Awareness does not pay bills.

Pranav Piyush [00:24:37]:

What pays bills is revenue. You have to be able to tie brand campaigns down to revenue. And guess what? Everything that we talked about, search, social, podcast, billboards, email, they are all you can constitute those to be brand campaigns. This is nothing different about measuring brand campaigns from anything else that you don't call brand campaigns. Okay, now here's a fun little tidbit. What people say versus what people do are completely different things. So Brendan talked about self reported attribution, right? Like, how did you hear about us? And they said something. Now the reality is this is a fun example.

Pranav Piyush [00:25:18]:

There's a company called, or an institute called the Pew Research Institute. How many of you have heard of that one? Okay, good. Yes. So you all know about that. They asked. They ran an online poll where they asked people, are you certified qualified to operate a nuclear submarine? 12% of the people said yes. The real answer to that question is zero percent, right? Close to like there's zero percent statistically, like zero point. Whatever, whatever, whatever.

Pranav Piyush [00:25:50]:

So what people say and what people do are completely different things. Okay? So think about that. When you say, hey, have you heard of this brand? Oh yeah, I have. Like means shit. Okay, What I'm saying is that has no reason to imply that they will buy from your brand. Remember that. And it all comes back to measuring the bottom line. Okay? You can do simple things.

Pranav Piyush [00:26:21]:

I threw this chart up. Credit to Dave, who was listening to.

Dave Gerhardt [00:26:24]:

His homework exercise Founder mode.

Pranav Piyush [00:26:29]:

There we go. And this is a lagging metric, right? So I don't want to paint this impression that, oh, this is how you should measure brand. No, we were just having a discussion about if I had to measure something, what would I measure? And my sort of reaction to him was, look at the volume of branded clicks on your Google search console and you just see, are people searching for your brand? If people are searching for your brand, you're probably doing something right now. I'm not going to ask you to take this to your CFO and go like, oh, look how awesome are we doing? But it's a good sanity check. If your branded clicks are flat over time, whatever you're doing on brand marketing ain't working. It's an easy barometer. All right, that was it.

Dave Gerhardt [00:27:12]:

Yeah, that was awesome. That was really good.

Pranav Piyush [00:27:19]:

All right.

Dave Gerhardt [00:27:20]:

I want to let people ask questions, but selfishly, I have a couple. First of all, the submarine slide. Did you already know that joke? Like, where did you find that?

Pranav Piyush [00:27:28]:

You know, my co founder is big into polls and politics, and he's, like, big into social stuff, and he's learned everything about marketing over the last, like, three years. So when he sees interesting stuff from outside of marketing, you know, that was it.

Dave Gerhardt [00:27:43]:

I like the stuff that you talk about with, like, correlating things like LinkedIn impressions to demos. One thing that I struggle with with that, though, is, like, oftentimes the answer then means like, oh, we should do more. And the issue is, like, you can't just necessarily, like, post more on LinkedIn and you will get more demos. Like, becomes like, how do we drive this? Right? And so it's like, maybe that's a separate discussion, but how do you figure out then what to go and do with that? It's not like when podcast impressions go up, demos go up, but it doesn't mean that if you then go put out a podcast episode every single day, you're going to see the same type of growth.

Pranav Piyush [00:28:19]:

Great question. The answer is pretty simple experimentation. Everything that you do in your marketing plan should be an experiment. There's a hypothesis, there's an expected lift, there's an investment. And guess what? Two out of your ten experiments are actually going to work. The remaining are going to fail. This is not Pranav saying this. You go look at leaders from Microsoft, Amazon, booking.com, uber, Airbnb.

Pranav Piyush [00:28:44]:

They are saying this. They've been doing it for decades, and the general benchmark is about 20% success rate. So everything, right? When you say, let's double the volume of podcasts, go test it and see if that happens or not. There's a concept of diminishing returns on any channel, on any strategy, right? You naturally hit a certain amount of diminishing returns, and that's what you're trying to find. And how do you break through that ceiling of diminishing returns? There's ways to do it, which is completely different. Creative.

Dave Gerhardt [00:29:15]:

Yeah, I guess it's like, if anything, it might push you to try new. Like, we roughly know this channel is working. Let's try new things within this channel.

Pranav Piyush [00:29:22]:

Precisely.

Question [00:29:24]:

Hey, that was awesome. I think I could speak on behalf of everyone. That was great. I have concerns about, I have concerns about the brand, the bonus mission.

Pranav Piyush [00:29:36]:

Yeah.

Question [00:29:36]:

Because I think part of the challenge is trying to measure brand in the same way that you're measuring things that are meant to be direct response that are meant to be performance and saying, my brand isn't performing enough for me. But maybe brand is about education and then awareness is the right metric and impressions as an outcome is the right thing to measure. Because the message that I'm saying on a brand level isn't meant to get you to do an activity, but we need that layer in order to get us to performance. And I also think if we're talking about these different channels as including brand or having brand in it, I even think of like, you know, trade shows. How do I measure the part of the booth, the brand part of the booth as driving some sort of outcome separate from whatever else I was doing? The amount of people that showed up to the booth. Those are things that get very messy to me.

Pranav Piyush [00:30:29]:

Yeah. There's a reason I'm here and I have a job. Right. Because it is messy for certain things. The reason I pulled up the slide is I had something in there that said brand equity. Right. Now that's a real thing. And what that means is this is the long term impact of your brand existing.

Pranav Piyush [00:30:47]:

And apart from, you know, when Elon Musk figures out how to put neuralink in all our brains, we're not going to know how that stuff works. There is no science that has been done or technology that has been invented to help you understand the long term impact of brand. Anybody selling you that is lying. I have looked at everything and it doesn't exist. There's a lot of dubious sort of research on that. Like I said about awareness, you can't pay your bills through awareness. So all I'm saying is you're measuring something that doesn't matter when you're measuring brand awareness. And I know this is a philosophical debate and I can't answer that over like a five minute Q& A, but we should talk now.

Pranav Piyush [00:31:27]:

Trade shows, that's easy. You should be tracking event attendance for every event. And you correlate your event attendance with your demos and your pipeline. Guess what? 90% of the companies that we work with don't even track event attendance. So when you don't have the data what are you going to do? Right. You're stuck in the same problem. So really be intellectually honest about what you mean when you say brand. Right.

Pranav Piyush [00:31:53]:

And some things are going to be measurable that are more shorter term. And if you're going to show up at the board and say it's brand and I can't show you any numbers, you're going to have a short shelf life. I'm not saying it doesn't exist. There's no such thing as a brand. There is, but the science literally doesn't exist to measure it other than this. Yeah.

Dave Gerhardt [00:32:14]:

All right, thanks. How about LinkedIn video? We talked a little bit about that during lunch. What would you suggest in terms of measuring impact of video and LinkedIn?

Pranav Piyush [00:32:26]:

Yeah, so I mean, LinkedIn, we talked a little bit about this. If you're doing everything on the company page, you will be able to get all the analytics about impressions, clicks, views, plays, all for your video content as well. If you're doing it on your own personal page, I do that and I export all of that personal data and put that into the same spreadsheet that I'm talking about for video, you want to look at plays and views, you will want to look at completion rate, not just the impressions. So there are nuances there for each ad format, for each video format, and for each type of strategy. And then going back to this, you also don't want to look at this just on a channel basis. Right. You want to do this at the strategy level. If I have five different types of content on LinkedIn, I've got podcasts, I've got long form, I've got memes, I want to be able to break that apart and find the independent correlation of each of those with your business outcomes.

Pranav Piyush [00:33:21]:

So that gets more. When you're doing that type of volume, it gets into more detail and it takes more work. That's why you have software. Hello.

Dave Gerhardt [00:33:27]:

That was great. I never thought I'd want to give a standing ovation to talk about. Wow, that was great. That was great. I loved it. So if you were talking about correlation between impressions and results, do you have examples where company leadership said, let's over index on impressions and the direction of marketing went completely wide and they were like, all right, let's just get more impressions at any cost.

Pranav Piyush [00:33:50]:

Well, there's a lot in that question. Think of it this way, right? All impressions are not the same. That's basically what you're asking about. And the point that you're making is the impressions that you have gotten over the historical time period that you're doing the correlation for either are working or not working. Right now, if you say, okay, it seems like it's working, we're going to double down on this. And now I've doubled the number of impressions. But guess what? I started generating memes that my business audience doesn't give a shit about. Then obviously that strategy is not going to work.

Pranav Piyush [00:34:24]:

This is why we were talking about experimentation is when you think about net new things, everything should be run as an experiment. And when you run experiments, you have a control. A control means an audience that you are not showing those impressions to and you're tracking whether that audience is converting at the same rate or a higher rate or a lower rate than your test group. So it's not an easy answer. But the answer is basically run a lot of experiments and that's the only true way of knowing causal sort of impact of your marketing efforts. Experiment, experiment, experiment every month.

Dave Gerhardt [00:34:59]:

Yeah, I think you may have just answered it, but I'm looking for a little bit more clarity on what has happened, let's say over the last like two or three or five years that has enabled the data science industry to answer this question for the first time.

Pranav Piyush [00:35:13]:

You're like a vc. This is awesome. I'm prepared, I'm prepared.

Dave Gerhardt [00:35:17]:

I'm a brand creative. We're going to talk later.

Pranav Piyush [00:35:19]:

There we go. No, it's a good question. So a few different things have happened. All the privacy changes have actually forced everybody to reevaluate whether a click based approach even works. It never worked. Flash news, but it's become in focus. It's come into focus that it's not working. Right? That's why you have Meta and Google saying actively, hey, it's not working, you got to do something else.

Pranav Piyush [00:35:43]:

That's one. The second is there's a whole bunch of machine learning stuff that has emerged. All of the stuff that I talked about, even Google and Meta have created open source solutions to do this. Nobody knows, right, because we're marketers and we're not in the dev docs, but those exist. So they have come onto the scene over the last five years. So privacy changes. The data science stuff, unfortunately, with all the ZURP stuff, right, all the free capital going up, the scrutiny has gone tighter. And so you have now finance and executive teams looking at everything and going, hey, something's not adding up, right? This team is saying 20% impact, this team is saying 40% impact, this team is saying 70% impact.

Pranav Piyush [00:36:23]:

You add it all up and you're talking about 150% of your sales, something doesn't add up. Right. So when you have all of those things come together, there's a massive sort of reawakening happening in marketing. So yeah, that's what's going on. Yeah.

Question [00:36:37]:

Hi, over here. Benjamin. Nice to meet you and really nice talk. I would like to ask you about because the correlation between impressions and demos, I can understand that From a smaller SaaS or like smaller software organization such as, I mean like, or okay, you publish ton on LinkedIn. I can imagine, Boom. You sell out your event in two days. It's a pretty easy correlation. I work with like SaaS that are like 5,000 people and we do thought leadership for dozens of their leaders that are publishing at the same time.

Question [00:37:11]:

So they're doing a good job, they're building brand. I'm just lost, I guess of like, do we say to each leader, okay, you stop posting this week for six weeks and therefore we'll see if this. Like, do you understand? Like it's.

Pranav Piyush [00:37:24]:

Yeah, yeah, yeah. It's a great question.

Question [00:37:25]:

Will we hire you or is that.

Pranav Piyush [00:37:30]:

I didn't say that. I didn't say that. So the reality is again, if you have the fear of finding out whether you're fudging up, you're not going to do this. If you want to know the truth and if there's a reason to know the truth, you're going to want to do this. Now, what do you do? Right. Not everything is about stopping everything or pausing your activity. There are ways to design these experiments with a limited downside risk. That's what we do.

Pranav Piyush [00:37:59]:

And what does that limited downside risk mean? It essentially means either changing the velocity or the volume of posting. If you're talking about organic social. Right. Or it's increasing the velocity and the volume of posting. Right. That's upside rather than a downside risk. So that's a conversation you should have with your team on what is the hypothesis that you want to test. Maybe you're trying to make a case for we should hire 10 more content folks to make that case.

Pranav Piyush [00:38:28]:

I'm going to run an experiment for two months. We're going to bump up or six months we're going to bump up the volume and velocity and look at the metrics and then let's go make the case for that 10 person content team. So it's all about how you design those experiments. Yeah.

Question [00:38:43]:

How you doing, Pranav? Good to see you again. We were talking in my breakout session group earlier. I don't know If Adam's in here. But he had a great point about brand being something that you look at not as a correlation to a business outcome, but as a coefficient that impacts. Okay, you're not looking for brand to directly drive demos or something like that, but you're looking at brand to provide a 20% incrementality to everything else. It's not directly driving impact what makes sales easier. Maybe going back to Ari's question too, earlier, maybe that's something that helps. But to your point, from much of this, it's picking the right things to measure and then how you're looking at it in the big picture.

Pranav Piyush [00:39:17]:

I go back to the same thing that I talk about all the time. What is it? What do you mean by brand in that sentence? Right. Words are important, right? When we're talking about the math that we're doing here, what is the actual thing that you're referring to when you say the word brand? Right. Because if I say, let's measure Coca Cola, right? Coca Cola is the brand. Well, what does that mean? That means nothing, right? So the closest thing to that is brand equity. And if you go to a Nielsen or what's that firm? I'm forgetting the name of them. It's a big brand agency. Anyway, the point is they'll give you some fancy math about how to calculate brand equity, and they literally put that in your P&L, etc.

Pranav Piyush [00:39:53]:

Etc. I don't know that there's any legitimacy to those numbers because, again, what are you actually measuring? And the most interesting thing that I've seen for brand measurement is brand penetration, which is essentially saying, out of the 200 people here, how many of you use. Use HubSpot? How many of you use Salesforce? How many of you use Close? And that's the only real meaningful difference between those three brands is the actual share of the market, the actual penetration of the market. So if you want to measure brand, that's what I would measure is you versus your competition on the share of the market that you have. Yeah.

Question [00:40:34]:

Hey, I was wondering, how would this change? Or does it.

Pranav Piyush [00:40:38]:

If you have, like, an enterprise sales.

Question [00:40:42]:

Cycle that's like very long, 12 to.

Pranav Piyush [00:40:45]:

18 months, and you do see that just to get to a contact request.

Question [00:40:52]:

There'S multiple touch points leading up to that.

Pranav Piyush [00:40:55]:

So how do you really, you know.

Question [00:40:57]:

Measure and look at it from that perspective?

Pranav Piyush [00:41:00]:

Oh, my God. That's my favorite question. So, good one, good one. Okay. There's a lot in there. Yeah. Starting with how do you measure marketing? What is the metric that Marketing is held accountable to in that environment. Right? That's the most important question to answer before I talk about touchpoints.

Pranav Piyush [00:41:18]:

So if you're going to say, oh, it's revenue, we are team sport, sales and marketing together. Like, okay, why don't we just put marketing on the sales team then and let's just have them pick up the phones and talk to everybody. Right? Like team sport. It's not how it works. So you have to pick a metric that is truly in marketing's control. And that metric is not going to be revenue. It might not even be qualified pipe in an 18 month sales cycle. It might literally be the number of people who are raising their hand and saying, hey, I like what you're doing.

Pranav Piyush [00:41:53]:

I want to talk to you more about something. Is that a demo booking? Is it a trial? Is it a contact sales form, whatever that might be. And the first conversation I would have is, that's the metric to build your measurement around. Now guess what? You can build a separate model that goes from that hand raiser to closed one. The reason you have to build a separate model is now you have a lot more data and there's different factors. There's more about your product team, your sales team, your solutions engineering team, your customer success team, your pricing team. They influence the process way more than marketing does. To go from that hand raiser to that closed one, that's a different problem altogether.

Pranav Piyush [00:42:35]:

That's a different use case altogether. Again, you can apply the same data science principles to it, but it's a different question. So I don't know if I answer your question fully, but we should talk more about it if that's interesting.

Dave Gerhardt [00:42:46]:

Awesome. Give it up for Pranav. That was awesome.

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