Why Product Analytics Trumps Marketing Analytics 🚀

Hey, me again.

they gave me a mic and let me, share my screen.

So I figured, hey, let me just talk about something that I'm seeing in the market based, off of everything that we do over at Vision Lab.

So, this is a bonus, extra little razzle dazzle on top because I, have had the pleasure of hosting you all day long.

So, so my thought is why you really want product analytics and you don't want marketing analytics most of the time.

Right?

So here's kind of my, my hypothesis is that most people are asking for that.

Let's hop into it because this is going to go real quick.

I've got 10 minutes starting right now, and I want to show you exactly why this is the case.

So this works.

we've had one million, five million, fifty million, a hundred million and beyond.

we work with customers all over the board.

And so I wanted to show you how this can apply.

But first, let's take a step back.

I want you to take note of the X axis.

And really, think about that for a moment as we go through this because I want you to call out why it's wrong or right or just, just keep your eye there.

so back in the day, 2019, we had the always on marketing, right?

It was right before COVID It happened Covid where everything was working.

Increased demand, let's crank it.

Regardless of what the outcomes are.

We then had hypothesis marketing, where what's happening, is it harder, is it a bust, is it good, is it bad?

I think if this will work.

I think it won't.

We then had this, a period of stable marketing where some things are just not working.

Some things that are working, is it working, is it not working?

And it kind of worked always, regardless of what the data said or didn't say.

And then now we are entering into the squeeze where we have same volume, higher costs, higher competition, more things entering the market.

So everything is, eliciting like this internal pressure, right?

I got same budgets, less results, tighter margins, higher volumes, lower costs, higher costs.

You name it, you've had the problem.

So technical marketing, where are you?

Look at the X axis, 2010.

So back in the day we had UA.

Wow, this tracks stuff.

So that was the sentiment.

We had page views, we had, some events.

We had.

We had some things.

We had the urchin that turned into whatever else.

You get the idea.

I'm not going to give you a history lesson.

then we had more utilization, right?

People figured out you could put scroll events into the labels.

We could use hack E Commerce to track word counts, Simo and we could figure out all of those type of things.

We then had the trying to figure out the product.

So what and how are the questions that we're trying to answer like what's happening on the site?

How is it happening on the site?

What's happening with this?

how are we kind of moving through time and now we are back in that squeeze.

Whereas how do we make our data more profitable?

Should we even have a two person team?

Should we work with a contractor, should we work with an agency?

What is actually the outcome?

And then in the meantime we sprinkled in all the idea around consent and legal NGA4 and AI.

Where does that fit into things?

What does it do?

So this is where the technical marketing timeline that I would like to show you if you're like who the heck are you?

What are you talking about?

I want to just give you a quick context here of JJ Vision Labs just because I like to give this, we work across spectrums.

We serve as the data department.

So we have right now trailing 12 month revenue.

I pulled this like a few weeks ago.

We work with 29% of our revenue comes from software companies, 29% from info companies, 28% from e comm and then 15% other.

Those are like your high enterprise style companies where you're like what do you sell again?

Like we sell X, Y or Z.

And our notable ventures are that we work with several hotel chains.

And the most interesting is that we have two religions that we work with.

So that's what, that's just why I would like to say hey, here's why you should trust us.

So Vespas, that is what I like to say that we were given when we had UA rollout back in the day is we were given a Vespa and said hey kid, ride this around.

You don't need a license.

Go out, have fun.

Zippity doo dah zippity day.

And what we've proceeded to do over these past 15 years is strap on Nos offender.

A spoiler.

We've tried to figure out how do we hack this thing to oblivion with whatever rules that Google does give us.

We now have user id but we can't use emails so we can't have an identifier that's the same across all platforms like an email address like most product Linux tools.

But we can hack the absolute living daylights out of it.

And I'd like to say what might be better is that instead of hacking together this Vespa, we could say what if we just bought a really basic, or old or used or kind of halfway working, old sports car, right?

We could just say that.

Which one would you rather go 60 miles per hour or 100 kilometers or I guess 80, go mediumly fast on this Vespa or a sports car?

And here is kind of what I've put together as the majority of analytics.

From the technical marketing side.

This is what we're doing.

At the end of the day, you can slice it or dice it however your heart desires.

The this is what we're doing is we are building question based answers.

Hey, how many people saw our pricing page and clicked the footer link?

Those are the ad hoc ones, right?

You're like, oh my gosh, how do I even answer this?

What do I do?

How do I get there?

We then have the consistent reportings, right?

So those are like, hey, how many sessions are on the homepage?

You have all heard those questions, comments, ideas around that.

We then need to send data to platforms, right?

This is where consent starts to factor into things.

Where you've got Facebook, you've got, Google Analytics, you've got Google Ads, you've got the consent of sending that data to a destination in the way that it requires it to be sent.

And then you want to determine actions to take, right?

So what actions are actually, actually ultimately being taken and when it doesn't work, how do we facilitate the why did not work?

Right?

Why is our conversion rate at 0.5%?

And that's where you sprinkle in those session recordings, the event logs, the user, behavior maps, the heat maps, all that jazz.

If you do something else that's not on this list or more things, let me know, I want to know what they are.

what about product analytics that's kind of like already answering all those questions and all you've got to do is strap on some sort of marketing analytics, around where they came from.

And that gives you web analytics with the added benefit of not having to hack together an email address or consent management across multiple platforms and you even get some like CDP functionality out of the box.

And so there are a lot of ways to do this.

So I'm kind of going to pit these two together.

I'm sorry for anybody who's like a real die hard GA fan, I'm really sorry.

Really, really sorry.

We still use it every day, I promise.

We still do, but there's a new kid on the block.

And I really like it because it allows technical marketers to utilize it to the fullest extent of its ability and talk with data teams and product teams and all those things.

And you kind of have a unified conversation as opposed to one team looking at ga, another one looking at the sales data.

And you're really trying to unify everything under one roof.

There are others, right?

There's a mixed panel and there's amplitude and there's segment and there's.

They all do different things, but you get the idea.

I'm going to talk about post hog because I think it's really helpful.

It's really cool and I like their pricing model.

So I want you to ask yourself, are you souping up a Vespa or should you just buy a sports car?

And the Vespa being web analytics and the sports car being product analytics?

Again, totally up to you.

I'm not trying to convince you one way or the other.

I'm just trying to poise another side of the conversation.

FPS I had to look up the word souping because that felt like it was spelled wrong because it sounds like you're eating soup, but like it is the correct way of spelling like the soup up to make it a lot better type of thing.

So that was a funny little, tidbit there.

So here is a structure I want you to run through is imagine you have ads.

They're running to a landing page.

They have a lead magnet on them, little PDF download that we all love.

Then the thank you page is a book, a call, and then you want to qualify those calls, make sure that they are coming from actual, websites.

Then we have an invoice that is sent and then purchased, maybe a couple days later.

How are you going to send this back to Facebook?

Let's just say Facebook for the example.

Or to Google Ads or wherever my Google Analytics.

Doesn't matter.

How are you going to do this?

These all become really big problems, right?

You could say maybe I can hack the book to call.

If I use calendly, I could have a JavaScript listener on the thank you page that will send in a data layer event to GTM and we'll use the same session ID because the cookie will work there.

Or what if we use a webhook to server side tag manager.

We store the cookie there and then we could send it back to Google Ads or Facebook Ads.

From there we'll store the click ID in the session storage, local storage.

Maybe we'll send that back.

But then we have to have the qualified lead.

That happens in the CRM.

That will take a couple days and there's nothing associated with the page view.

How right becomes complicated.

There's a lot of ways to do it.

I've seen people do it.

You need to include like their click id, right?

You have to figure out, is it working?

Right?

A lot of platforms just say it is and like now you're like, okay, am I seeing the log?

Do I have a log?

And then a volume like 21 events a week.

It's kind of what we see as like a minimum of like that downstream event.

So do we need to include PII or not?

Oh my goodness.

Do we have consent to do this?

So these become problems, right?

These are their.

And there's a lot of ways to do this, right?

There's, this is one, one case scenario if you're on Shopify, right?

There's a few of the little data, the elevars we have in high level.

There's the hello conversions, there's the stapes.

we then have, the idea of using automations.

We then have HubSpot, Salesforce, most others, right?

You then have the DIY approach.

And then lastly I propose Post Hog, right?

Where you can have this idea of using product analytics to help facilitate marketing actions.

And Post Hog is like a fairly new tool, right?

They just lose a lot of money.

New kid on the block, more technical, than probably any other tool out there.

So you definitely need to be a technical marketer.

But it works, it does what it needs to do.

You can send web data, you can send calendar data, you can send serum data, product data, offline data, you name it.

And everyone's screaming at their screen like, this is a cdp.

I know what it is.

I know, like, yes, there's CDP functionality.

Every tool on planet earth is trying to like have those same functionality without calling it a cdp.

looking at you, those other tools that came after GA when consent was a big deal.

So again, those are all things.

So I just wanted to do that.

Here's some examples, right?

Imagine you have booked calls, attended calls, qualified calls, invoice and purchased.

How do you send those data to GA?

4, how do you send that to Facebook?

How do you even visualize that data?

It becomes very, very complex to do that and it just becomes a problem.

So again, this is how I would like to make you think is like, am I souping something up or can I use a different tool that can help facilitate this?

And so the question I get often Asked the most is where the data flows from or to.

And the way I like to think of it is like this.

You have web data that's deployed via GTM and then you have product data that's deployed via direct integrations right from server to server, from, hey, we know that this is happening in our application because we have the actual application.

We then use Post Hog.

You could use any tool.

I'm just giving you an idea of product analytics that unifies those two things together.

Using usually an email address, you can use IDs, et cetera.

And then you just send that data when it occurs, whether that's coming from the product side or the website onwards to add platforms, reporting automations, warehouses.

And then you can have your own reporting either in posthog or in another tool.

That's it.

And so you're probably over here thinking, I can do this.

I can use my server side tagging and I can divide this by the square root of 37 and we can have a general visualization that works.

and you're waiting on your ideal plan.

You're like, okay, I got this guys.

Here's our plan for Q4.

We're going to implement this.

where I think that you're, what you're doing is you are trying to use your super, super great mathematical skills, right?

Everyone's really, really skilled.

And if you're here at Measure Summit, you are skilled.

But are you sweeping up a Vespa or should you just buy a sports car?

And that is the question I'd like you to kind of leave today with is like, hey, do you just think about it?

Are you, should you be using a product analytics tool, in addition to or in conjunction with or in replace of a marketing analytics tool?

And how do you do that?

If you're like, hey, I wanted to take a little look at the Post Hoggy stuff.

Go to visionlabs.com academy posthog.

I talk about it a lot.

our team implements everything alongside GA4 and PostDog, and other tools.

Right?

There's so many of them out there.

Everyone's got a tool.

But I just wanted to put this out there.

I'm pretty sure no one else here is talking about this at Measure Summit.

So I want to put this into your noggin.

Go take a look at it.

Take a gander around.

When you're talking about product marketing data, what do you do with it?

And look at that list.

So that is where we are, folks.

My name is JJ Reynolds at Vision Labs.

It's been a pleasure hosting day one, and I will see you guys around the interwebs.

If you have any questions at all, visionlabs.com contact and my name is JJ Reynolds.

Like Ryan Reynolds, just better looking, you know, nothing big.