It’s no secret that product marketers can sometimes struggle to get the alignment they need with product managers, and as a product manager myself I think that’s a problem - it needs to change.
When PMMs and PMs work together they can create not only better customer experiences but higher conversion rates to boot. In this article, I dive a little deeper into that as well as share some approaches to improving your conversion funnel without needing to change your product from my own experience doing just that.
My article today will be on how to improve your conversion funnel without changing your product. I do have a dirty secret. I'm not a product marketing person. I'm a product manager, even though I love working with product marketing people.
I also wanted to touch on why every product manager should care about marketing as well because I know they always don't
Why should product managers care about marketing?
When I left Zynga, I was making games and we would get five to seven million people playing any of our games.
We had marketers there, but all of that was done in the background. I didn't really have to do anything to get users. So when I joined Fever, as a VP of product, I was like, why do we need marketing?
Here are some things that product managers who are naive may think:
- Products should sell themselves, they don't need marketing to do that. That's very old school.
- People might talk about product-market fit - if you need marketing, you don't have product-market fit.
- Word of mouth, my product is really cool. You didn't see Facebook or Instagram needing marketing back in the day so why should my product need that as well?
- Lastly, virality - why do I need that? Our users will share our product, we don't need traditional marketing.
So this was a very naive picture and this was much earlier in my career before I got to really understand the benefit of marketing.
This is the company I mentioned before. Fever was a mobile-first event discovery app, we launched in 2012 and I joined in the latter end of 2012. We had a seed round of around 2 million bucks, a small team in New York, as well as Europe.
The engineering team was in Madrid, Spain - that's where I was for a while. When I joined, you can see from our conversion funnel, that even though these aren't the actual numbers, you see that the conversion rate is around 2% but every once in a while, it spikes to around 4%.
When I was there, one thing I was interested in understanding was, why our conversion rate increased every once in a while?
What was going on?
We had a couple of hypotheses. We said, was this a weekend effect? Because we're an event discovery app, so are more people just coming on the weekend? No, because you can see in the image they don't happen every weekend. They're happening on Tuesdays and other days.
Is it because we have a really popular venue? No. They were all different types of venues and they were happening all over the city, but mostly in a specific demographic or place, which we'll get to later on. Is it a popular event? No, it was like all types of events.
So there wasn't anything unique about the event or venue. Lastly, was it due to one of our PR campaigns? These are all different hypotheses that I tested and we looked at, and we couldn't figure out why.
The emoji was me back then.
What our analytics told us
When we looked at our analytics platform, we were using Mixpanel. I'm sure some of you are familiar with that. In the people's profiles, we saw that the ages of the users who were in the increased conversion peaks that we saw were between 17 and 22.
Pretty much all the venues were in the West Village, and their email domain ended in edu. Does anybody reading have any ideas of who they were?
They were NYU students. So basically, we had an event discovery app and our biggest consumers were NYU students.
Our marketing focus didn’t reflect our best users
But our marketing campaign didn't reflect that. So we were spending close to 300,000 bucks a month, acquiring users and the users we were acquiring were not the best users for us because mostly NYU students and other college students in Columbia and other places were the main people downloading and going to our events.
You see here the keywords we were buying were 'New York events', 'things to do in New York', our Facebook ads were location-based Manhattan, and in a pretty wide age range.
We basically were buying a lot of traffic, because it was cheap and because it converted well, without thinking about how well it converted. Because the click-through rate was high not think through how well it converted through the rest of our funnel.
How do we pivot?
We started to see that the way that students were finding our posts was via all these other Facebook pages. We saw that they would have an NYU student page, and then they would post a popular event that we had, and then all of them would go to that event.
Sponsored Facebook posts and self-generated content
So we started to buy sponsored ads, initially, and over time, we started to make our own pages that were just like their pages and we used those to get them to follow. And then instead of paying for sponsored posts, we were able to keep that person seeing all of our events whenever they went to Facebook, for example.
The second thing was we got influencers from college campuses. Again, this was 2014 so influencing was not nearly as big as it is today. But we got the coolest people on NYU or Columbia and got them to basically promote their friends about our event.
The last thing we did was just a typical referral program.
But the most interesting thing I thought about for this article was, how do we figure out who our users were?
How we did it
Because I think that's less known in terms of product marketing and marketing overall. You see here traffic- we all have our different sites for traffic: Facebook, Google, any domain.
That's the one thing that we all do because that's where we get our users from. We already had our traffic sources. Then we had analytics: Mixpanel, Localytics, Amplitude, Google Analytics is another one, where you can see events that your users are doing.
Earlier, I talked about how we were able to identify that these were NYU students by looking at the people's profile and understanding what emails they use and everything else. We were able to identify that these were NYU students. What we didn't do, at least early on, was we didn't have an attribution provider.
Because we are a mobile-only experience, from the time a person clicks on some piece of media, some piece of creative, to them installing your app, it's really hard to follow that person, especially back then.
Before we had an attribution platform, we were looking at click-through rates, we saw that a click may cost 85 cents or may cost $1.50, but we really couldn't understand how well that person did from:
- Clicking on an ad,
- to them going to the app store page,
- to them downloading the app,
- to them actually creating a profile,
- to them finding an event,
- and then actually paying for that event,
- and then doing that over and over again.
That whole piece was invisible to us.
The last piece I think has just started to get popular over the last four or five years - aggregator platforms - mparticle and Segment are two of the more popular ones.
What they allow you to do is basically you have your analytics platform, you have your attribution platform, and any number of tools that you want to use, but if there's any product marketers or marketing people reading, whenever you want to implement a new one, the product team is always not so keen because implementing any one of these things takes a lot of development resources and takes a lot of time to execute.
With the addition of aggregators, what they allow you to do is you integrate with the aggregator, and then if you want to switch out Amplitude for Mixpanel, or Mixpanel for Localytics, it becomes much easier.
That's something that I just started to see happen more often and now, instead of integrating directly with any sort of marketing tool, I basically see if that tool is integrated with an aggregator like Segment or mparticle, and then I basically integrate there. That way I can switch anyone out fairly easily and don't have to worry about all the additional time in case we ever want to switch that tool.
I think that's a really good thing that if you aren't familiar with you should certainly check out and then mention it to your product manager, and your development team, you guys can look really cool on their side.
Defining your marketing approach
Now I just want to talk about the different approaches that I've been through in my career as a product manager.
If you can get to that top part, which when I worked at Amazon, this is where we were at, then you're probably fairly optimized in terms of your campaigns.
Spray and pray
Spray and pray - I don't know if you’ve heard of that, but that's where Fever started off, where we were optimizing based off click-through rate, we were optimizing based off impressions and we would buy keywords.
But we really had no idea outside of just driving traffic to an app store page, how that traffic was performing.
The second phase is channel optimization. To get to channel optimization, you have to have an idea from your creative, to actually use your product for me, there's an app store page in between.
You have to have an idea of how well your creatives are actually converting not from just click-through but from your actual conversion funnel. Which percentage of your creative from Facebook is actually leading to a person downloading the app, signing in, and then optimally converting in whatever that subscription is or whatever the objective is for that.
Over time, you're able to optimize your keywords to say, "Okay, New York events is not a good keyword for us but we should be focusing on hungry college students". Then you would cut off the keyword campaign related to some generic events and you would focus more of your budget on campaigns that you think or see are converting well.
This is where I see a lot of companies at now.
Channel, content, and product optimization
The next phase is channel, content, and product optimization. This is a really cool place to be if you can build the infrastructure to get here. This is where you're not only optimizing your channel, but you're optimizing your product and you're optimizing your creativity.
It can be difficult to get all the way to do this but at least optimizing your product is not too difficult to do. What this includes in terms of having an attribution platform, having your analytics integrated within your app, and then you can basically say, and this is one thing I did at Amazon, where I worked at Audible which is an audiobook company.
Let's say that you have creative for Harry Potter, so the person clicked on something for Harry Potter, they didn't download the app, when they onboard, instead of seeing some sort of generic sign-in screen, we can show them creatively related to Harry Potter.
What does that mean? That means it's an end-to-end experience from that person actually clicking on creative to actually seeing that in the product. I found that to be incredibly powerful in terms of converting that person from not just clicking on an ad, but to actually signing up for their service and then getting them much closer to signing up for a subscription, which was the product that audible was.
Optimize for the creative
Outside of optimizing within the product, which is already very cool. What you can also do is optimize for the creative. The way that it works is that as you are basically getting people to click on ads and feeding your attribution platform, and your attribution platform is feeding your analytic platform and your product, it's actually going both ways.
Because you have people doing things in your app, and then you're reporting that back to your attribution partner. You're seeing that "Okay, this creative got people to sign in to the app, this creative got people to actually sign up for a subscription". And what you're basically doing is getting an understanding of how your creative relates to your actual users.
Over time, what you can do is feed those events back to another partner, and then basically say, "Okay, this person looks similar to Yohanes, or this person is Yohanes, he hasn't used the app in a while, I want to show him something based off the last thing he used in the app, which is re-engagement campaigns".
But once you get a bit more sophisticated, you can say, "This person looks like Yohanes, and I'm going to show him creative that worked for Yohanes or I think may have worked for Yohanes". And that's when you basically have your creative optimized for lookalike audiences, or for that potential user. You have to have a lot of scale to do that.
But if you can, then over time, you see really big increases in conversion rates from just using traditional banner campaigns.
Dynamic onboarding vs. generic sign up
This is the example I talked about before, what's happening here is what the industry calls a deferred link. So it's a deep link and within that creative, there's actually an attribute associated with whatever thing the person is looking at.
In the example I gave, when a person clicks on a Harry Potter ad, we basically fingerprint that user and now there's something related to that Harry Potter ad in that user's device or somehow is related to that person's profile with an attribution platform.
Then, this person is not our install yet, but they go to the App Store, and once they go to the App Store, and download our app, once they launch the app for the first time, we then check to see if they have this attribute.
We say, "Oh, this is Yohanes, he liked our Harry Potter ad, let's show him our Harry Potter onboarding experience". Once you do that, this person can then make the connection that this was the creative or this is the ad I looked at, and oh, it's in the product and they gave me the first hour for free.
It's an end-to-end experience and if you compare that to the generic sign-in screen that we see most often, at least in the use cases that I've seen, that end-to-end experience converted much higher.
I can't give any specifics because I'm under NDA for every company I've worked at. But I've seen that this personalized flow works very well.
Personalized web push campaign vs. we miss you email
This next example is closer related to analytics. I'm not sure if there's only me but I think at least in my time working in product, I did a lot of 'We miss you' campaigns. A lot of times we do 'we miss you' campaigns because we don't have a really good idea of who our users are.
But if you have integrated an analytics platform, then you basically can do better than a generic, 'we miss you' campaign and you could have a push campaign, email campaign, and web notifications, related not to just some generic creative, but you can have it related to this user.
In this example, I did not work in this company, it's an airline app and the person was looking at a flight to Japan, and after the person hadn't used the app or opened the app within four or five days, instead of sending a generic, 'we miss you' campaign they send a personalized notification.
I've done personalized re-engagement many different times and it always converts better than a generic one size fits after 12 or 14 days. This is another example of working with product and marketing, where you can come up with a more personalized experience that converts much better.
Dynamic content optimization vs. generic banner ad
The last piece is the dynamic content optimization, which I touched on before. With this you basically have people going into your app and then feeding information back and then dynamically creating creativity based on whoever sees your screen.
You can see here that there are different creative depending on who the person is. If the person is somebody they think will like a big face, then you have that, and if it's someone who's more focused on price then you have that.
The interesting thing is that the creative is dynamically presented to the user in real-time. They see that this person is similar to Yohanes, here's the creative that we're going to show him all in real-time.
For these types of campaigns, I found that initially they convert about as well as traditional ads, but over time, and as you feed more and more information into that DCO engine, then it actually improves the conversion rate for your creative over time.
Compare that to a generic creative and it's very easy to see how powerful this could be. These are all different examples of how when product works with marketing you can see a much more personalized and improved experience.
Why should product managers care about marketing?
The question I proposed to myself about eight years ago - why should a product manager care about marketing? I now have an answer.
The reason why product managers should care about marketing is that when they work together, they create better customer experiences and also much higher conversion rates.