 Hi, everyone. Thank you so much for joining our webinar today with Product School. Today we're going to chat with you all about onboarding strategies to help you drive growth. And so if you're not familiar with onboarding strategies, by the end of today's call, you absolutely will be. And so as part of this session, we're going to help you understand how you can get a better, really understanding of your audiences across different channels and your audience's journey so that you can successfully onboard your clientele. We will walk you through some case studies of some of our own customers on how they've done this and some of the techniques and best practices they're using. We'll also share with you how AI and automation can make your job a little bit easier and also give you some better data and insights to be able to guide your onboarding journeys. And lastly, we'll talk to you about how to scale your onboarding strategy for retention, but also as your user base grows. And to give you a quick intro to me, my name is Megan and I head up the marketing at Mo Engage and I'm joined to you by my colleague, Vasil, who manages our strategy. And so with that, I will pass it over to Vasil and he will kick off the presentation today. Thank you, Megan. Really appreciate it. Hello, everyone. So just a very high level overview of who Mo Engage is. Mo Engage is a smart engagement platform. We use insights to really understand the user journey of customers and we help over 1200 customers and brands around the world. We use a massive amount of engagement on a daily basis. As you can see, we have customers all through the globe. We have offices as well in I think now 11 countries or something like that and a whole bunch of more partners. So we help startups as well as big large enterprise unicorns have meaningful relationship with our customers. So maybe we can kind of go into the next slide. There you go. Our offices. So what we are trying to do is really use insight engagement insights to understand what is happening with a customer in their user journey. So everything, all the data that we collect help us guide our customers how they engage with their users. So everything from onboarding, engagement, optimization to growth. And you can do this when you have the right data and when you have the right strategy. So let's talk about onboarding a little bit more and why is this so important to should be so important to you and it's so important in today's world. 74% of potential customers switch to other applications in onboarding process, if it's not right. So no user like a complicated onboarding process. So if you have too many fields, if you don't have the right integrations to switch to quickly onboard them in the app. If there is email that somebody needs to click on to confirm and they never get it. All of this is part of onboarding and the onboarding is so important today because you're spending a lot of money on acquisition. And the first thing that you need to do is to activate an onboard a customer. So this is why it is, you know, very this is probably the most important step of a user journey in the end of the day. Next. So in today's world, and I put some statistics here from Gartner, for example, everything is going on the cost of gas, the cost of food, the cost of technology. And is all of this is happening, you need to be able to understand better how to manage this cost. And if you can really manage the onboarding better, then, you know, all the money that you've invested in acquisition are not going to go away. So what this is here talking about is, you know, for example, Gartner asked a lot of marketers, you know, what do they believe is going to be a big impact on their markets and on their operations. And 75%, for example, said that they believe the increased costs would have a negative impact on their business. We're seeing that we're going into a recession. And this is why, in today's world, there's going to be so more important that you take onboarding activation so seriously. Because these customers that you're trying to get also, you don't want to lose them at the first point of engagement. You really want to get them from day one and give them some value, make sure that they see how easy it is to get on your platform and take care of them. Next slide. So let's go through kind of what is the onboarding process, you know, what really is going on there, right? So to understand the onboarding and to really optimize it, you need to take a lot of data. Now, we take data that is coming from email, from the web browser, from CDPs, from surveys, from the apps, from your TV. This user properties, behavior data and everything else goes into basically a user profile. We create this view of the customer that is 360 view of the customer. Sometimes some people call it single view of the customer to really understand at the beginning, where is this customer coming from? What is today like? Who are they? Once you know this, you can then better carve and create that user journey, which starts with the onboarding process. Next slide. So this is what a simple user profile kind of collects, you know, and has in sight, right? We know who that person is, we know whether they're male, female, when they became a customer. How are they using the system? If there is some loyalty level, what kind of how loyal is that customer? Sarah, in this case, what is the LTV customer, right? A lot of KPIs are very important. So the more data you collect, it's not just to use the data, but to really convert this data into insights. And when you convert this to insights, you can then better understand how to help a customer. Is this customer a happy customer? Is this customer not happy and potentially, you know, or a returning customer? And so based on this, you can kind of figure out what offers you want to give them, what user journey, how do you want to kind of move the user journey of that user throughout? Maybe you want to make it easier or you want to get more information. So by understanding the user, by understanding where they're coming from, how they're using the system, what actions are they taking inside, how long are they staying in the app, or they're not staying on the app, where they came from and all that, you can then really start generating a better user experience. Next. So let me give you here a specific example. Audio Mac is one of our customers and for them, the onboarding is the most important part. We've had a number of conversations with them and so what they want to do is make it as easy as possible. Once you log in, be able to find the music that you like and to be able to start listening to it very, very simply and very quickly. So understanding what kind of music you like and then having maybe pre-built a playlist of that specific music is going to really help these customers have a great experience. There's so many options out there today, guys, as you know, for music apps, for all kinds of apps. So any brand needs to take the first and most important part of onboarding, so important. So when you can understand if somebody's coming from a rap website or having met a website, you can then really tailor the journey and have the type of music that they're going to listen to expose to them right away rather than have a very generic user journey. So again, understanding the user, understanding what that really means, what are those insights is going to help you to convert those users quickly into a bank customer as well. So let's look at a sample flow of onboarding journey. Somebody has found the app and they're installing it. What that means is that they already were advertised or they found it one way or another, they installed the app. After a day, if there is nothing really going on, you can send them push notifications if they have already opted for this, right? Who are the trending artists? Maybe we know already a little bit about them, where they came from, maybe they indicated what type of music they like or they clicked on a couple of songs so you can kind of understand it. They like opera or they like rap or something else. And so based on this, you want to quickly engage them. The next day, you wait one more day and then you send them what are the top songs via push notifications. You wait a few more days and then you send another push notification to a global level. You wait a few more days and then you send notification around supporters. So supporter push is a very interesting option between Audio Mac, which allows you to kind of support other artists. And so they're creating not just an app for listening experience, but a community. So again, if you understand why people go to one app and they have a very kind of different purposes, some just kind of want to enjoy some user experience, some want to contribute, others want to support a bigger community and engage with others. This is a great way to, again, in this case, engage your customers, engage your users. And you don't want to do too many of those notifications the same day or wait too long. So the other very important part of this is this gets optimized through testing. So maybe this is not going to be a very good example for every app out there, but you need to test and figure out depending on the users, depending on the content, depending on the vertical test different things. Am I going to wait the day? Am I going to wait three days? Is this person still engaging? Maybe you don't need to do some of those things and you can bypass some of those stuff. So again, use different channels. Think about understanding the better the user. And for Audio Mac, this is one of the user journeys that really work great for them for onboarding. Next slide. So Audio Mac did that specific, for example, journey. And this is what they got. They really had some lift in their conversion rate. So 8.4% increase. It's pretty good, you know, results and KPI. Excuse me. You know, in week one, they were getting only 4%. In week two, they got 5.1%. Week three, 5.5, and so on and so on. So during this whole thing, session per user also increased almost 18%. And this numbers, if you're engaging with the user and you have 18% increase, that means that you're doing something right. Maybe you can do much better engagement, but 18% is not better at all. And the premium trial started converting at 18% as well, increase. So again, test different things. You always have to test, have a hypothesis, and try new things all the time. In this case, for Audio Mac, that worked very, very well. Next slide. So what are the factors here that, you know, influence the quality of this engagement? You know, we talk about to product people versus marketing people. The conversation was so different. But product design seems to be one of the most important things. And ease of use. So if you have an app and kind of like look at where the buttons, and you have a phone, for example, are the buttons down in the bottom where it's easy for you to access, especially on this bigger phones nowadays, or do you have buttons that are in the bottom? Then you have some buttons on the top. And I can give you a lot of examples for bad design where even me with my big hands, I have hard time, you know, switching between different options of an app or trying to find where is this and where is that. So optimizing the user experience of the design and app, whether this is a mobile, whether this is on a website, is one of the most important things. Again, how do you find this out? You look at insights, you look at the user journey. If you are seeing that users are dropping off, especially during the onboarding process, you need to understand why. You need to look at deeper into the data and see where is that drop-off happening. What type of users there is a drop-off? Is it with a specific operating system? Is it with a specific device? Is it with a whether you're looking on the web versus on the mobile? And so on and so on. But ease of use and simplicity is what makes, you know, what keeps coming back as the key ingredient to success. Then you need to kind of get, for example, let me look at here some numbers. For example, if you look at the different type of apps and verticals that you can be doing this, right? What kind of numbers you're going to get for this? Whether this is for business and finance, utilities, or educational. As you can see here on the slide, we have different numbers that are representing different KPIs about which apps are getting more, you know, better engagement versus others. But the type of channel here that influence the use, you know, is it that lifestyle? Is it utility? Again, all of this really matters and also different times. Right now, I bet you there is a lot of apps that are interesting to users around finance. And in this economic times, how do I save money? You know, what do I do because I'm most stressed out with my work? And mental apps have been going through the roof, especially during COVID. So it depends on, it depends on the vertical, it depends on a lot of things like that. Messaging strategy, that's another very big one. You know, from how often do you engage somebody? Are you bombarding them with messages on different channels, trying to get somebody to click and figure out which channel they want to be? Is it too much? Is it one a day, one a week? Is it five a week? You can overdo it. And also what is important to a specific user? If you can figure out what's important to one user versus another and you send them information, they're either going to ignore it, it's going to go into spam, they're going to flag it to the spam, and that's not going to help you. Here about speed innovation, this is an interesting one in updates. There are pluses and minuses when it comes to innovation, whether you have an app or a website. If you look at Meta and Facebook, they're constantly making changes to their app. Instagram, they just change and start testing the app without, for example, a shopping button. Sometimes you can do this easily if you're doing just some kind of a mobile testing, but sometimes people go and load the new app and you upload, and then you have to download it and then things break, and so it gets very complicated. So you have to think about what are the benefits versus the impact of having different changes that you can do on the site, on your mobile app and stuff, and do you want to do just some testing or do you want to do a full-blown change and update to your website with new features and new things? Try to do mobile testing, try to do website testing for a specific segment of the users and analyze that data for the user journey. Let's go to the next. So Empiricus is another happy customer of ours. They're a super app for the stock market. They're like a community of sorts as well in Brazil. They have almost half a million subscribers and they have lots of good content that brings people going back to it all the time. Now, what they did is they were using, for example, again, a user journey analytics and insights to understand what is happening with their customers, where is the drop-off? Once you install the app, what is going on? What works? What doesn't? And how long does it take for a user to go from installation to subscription in a user journey? And then they started doing a lot of testing and that really helped them optimize the user journey experience specifically at the onboarding activation point. Next slide. So this is like a very specific example with kind of their user graph. And so they looked at what is the problem? You know, you create a hypothesis and you see the onboarding funnel is too narrow, right? And hers, the engagement retention, the onboarding and everything else. So the idea here was to change the flow. So the user directly has contact with the right code. Again, how do you do this? You need to understand a little bit about the user. And then you want to put that information to them faster. You know, where you don't want to have, you know, five clicks, whether that's on the website or on mobile to try to find the right content. And many times, even if you search it and how is that being displayed and so on and so on. So by understanding the flows and trying to shorten the steps and the time it takes for a person once they install and get on the side to finding the content, they were able to reduce the drop-off by 45%. They changed the whole bunch of things and, for example, the content engagement increased over 100%. The app sessions increased by 20%, which means that people stayed longer on the app and on the website to read content because it was easier to find it and it was giving them value right away. 45% is really good. Now, how do you scale the onboarding strategy for one customer to millions? And that's not an easy one. We call it user personalization and how do you do this at scale, right? How do you do this is, again, you use the system to do it for you. Hopefully you have the right system in place that allows you to automate processes for each user or type of user, right? So automatically, for example, figure out what is the best time to engage, what is the best channel to engage, what is the best message and on the best device for specific user. The system can automatically figure this one out for the user. This really is the best moment in user journey at the end of the day. There isn't really a best time. It's where is in the time of the journey, in the moment of the journey. Somebody, for example, is looking for a loan and you know that because they're searching through different websites and maybe the best channel for them is going to be SMS because they reply right away or they didn't put stuff in it. So figure out what is happening out there. Be aware of what are the external forces that they're happening. Interest rates are going up. There is recession. People really want to kind of jump in and cause that loan. Figure and use this in your journeys. You can't just build a journey and just leave it. You need to have multiple journeys test which one works for the what type of user and use the data to better figure this one out. And then the system can automatically do this for you and all your customers based on the segmentation that they have. Thanks, Vasco. And I was just going to add something on when it comes to the different tools. So obviously AI can be really helpful when you're trying to scale, right? And so there are several other tools out there. And this one in particular, we call RFM analysis and it stands for Recency Frequency and Monetary. And as a product manager, you want to create the ultimate experience for your customers. You want to make sure that you're offering them an experience that's meaningful, right? And so when it comes to this, go ahead, Vasco. No, no, I was just going to say, whichever tool you're using, whichever tool for analyzing you using, the most important thing though is going to be having good data. Make sure that you have good, hopefully first party data because it's a junking junk out. If you don't have good data, your analysis with whatever advanced AI or RFM tool you're going to have are not going to be as accurate. Sorry, Megan. No, no, it's so true. I'm going to go back to what Basil you had mentioned earlier around being able to make sure you're integrating data from different sources and you're creating that unified profile. And when it comes to tools like this, this is a way for you to easily dynamically segment your customer base so you can understand, okay, which of my users are the most loyal? Who are repeat buyers of us? Or who are hibernating users? I always try to think about the retail example because I'm someone who generally shops around Black Friday with certain brands, but I don't shop the rest of the time of the year. So I would be considered a hibernating customer. So how can you create an experience that's very relevant for me, but also that's separate from maybe your loyal customers where you're thinking about, okay, what kind of loyalty programs can I offer or what kind of content or products matter most to them. And so using a tool like this will help you scale and how does it work? Why does it work? It's really because you're able to quickly identify who are your champion users? Who are the users who are most promising, the ones that maybe have some potential? You might also see some that are at risk. So maybe you've seen a customer hasn't gotten from you recently and they were prior a loyal customer. Or maybe you've seen that a customer has recently uninstalled a mobile app that you're using to engage with them. Those are all signals that as a product manager, you're able to pick up on so that you can try to change that path of the user and still offer them the most relevant experience. And when it comes to understanding what that profitable path is, we talked a little bit about user path analysis earlier. This is kind of breaking down what does a typical journey look like for your customers. And as you know, you have a lot of different customers. You have your at-risk customers, your loyal customers. You have your hibernating customers and so forth. And everyone may be on their own path. And so when you're thinking about how do I create that user journey and how do I create that flow, just know that decisions can be made with intelligence and AI so that you can create and predict what that next path looks like. Because you may go into it thinking, okay, I think all of my users are going to follow one path, but that may not be the case at all. You want to make sure that you're looking for what a path of reality would look like for each individual. And I want to just talk to you a little bit about how AI helps here. We're going to walk through another customer example. But really AI is meant to tell you what is the best channel for each individual at the right time. So you may have someone that you're on-boarding that could be maybe a premium user, and they would essentially fall into a different path than someone who could just be a one-time purchaser. And so AI will tell you which of those journey segments are driving those key metrics, leverage control groups to understand what's the best path at that right time and trying to let the machine figure out that journey for your customers based on previous behaviors or based on their preferences, going back to what Vasco said about the data, making sure that it's based off of data so that you're not making those guesses, but you're able to actually follow reality based off of what those conversion points look like. And so when you think about intelligent path optimizer, this is a product that we have here and we'll walk you through an example of how you can make this real. But it's really about allowing you to experiment because when you are starting to collect data on your users, you may not have all of the answers, right? You need to build off of previous data. You need to build off of previous actions that users are taking. And so what our intelligent path optimizer does is allow you to have some AB and multivariate testing so that you can essentially optimize paths in real time. Whether you're starting to see a trend that maybe path A outperforms path C or path C outperforms path B and path A, it will be able to optimize that journey for similar behaviors or similar profiles. And so when you're thinking about scale, this is I think the answer is how can I scale a unique path for each individual and it really comes down to that dynamic segmentation, that dynamic journey building in the moment. And so I'll walk you through an example with JibJab. And so JibJab, you may be familiar with, if you aren't, it is a media and entertainment company. They specialize in customized personalized videos for almost any kind of holiday or event. So whether you have a birthday or you have Hanukkah or Christmas or maybe it's just an everyday video, you can personalize your face within those videos. And so for JibJab, personalization is extremely important because that's the epitome of what their business is. But they were really looking at a customer journey strategy that helped them get more engagement but also increase their subscriptions. So fun fact with JibJab, they do absolutely no advertising to make revenue. Their revenue is driven specifically off of premium users. So you can start with a free account. They have some basic free videos, but their hope is to monetize those users so that they can become premium and have access to that premium content. And so what did they do? So they did a couple of things. And we'll walk through each of these on the next slide. Being able to identify a customer journey path. They built and experimented with multiple customer journeys and then creating a lasting impression with personalized notifications. And you can just see some of the results. So they had an uplifting conversion as well as a click-through rate with personalization. So understanding customer with user path analysis, so we talked a little bit about this already with Empyracus, but this is what a flow looks like for JibJab. So if you're using their mobile app, you also can of course consume content on the website. But this is just one journey for their app. And they wanted to essentially understand where do their users go before dropping off. And so the first is that the app is opened and they may share a video or a GIF. Then they may decide to do another video or a GIF. And then the last touch point is yet another video, content or drop-off. And finally it's to engaging with alternative content and then dropping off altogether. So there are multiple drop-off points throughout this journey. And that was allowing them to essentially use that data to craft what does a typical customer journey look like and how can I foster that engagement before they think about dropping off. And so they built and experimented with multiple customer journey paths. And so this is just an example of the different kinds of paths. And using our intelligent path optimizer, they were able to identify that path B was the most successful path in being able to prevent that drop-off. And lastly, what they did in terms of onboarding was really focusing on that personalization component because as I mentioned, personalized videos, that's the heart of their business. But if they're not offering content that's also personalized throughout that onboarding journey, they may be less likely to engage those users and retain them over time. And so they really focused on what are the personalized welcome messages that they could offer to their customers. Leveraging tools like push notifications to get them coming back to the tool or sharing new videos that they're promoting and making sure that customers are alerted of those videos as long as they are relevant to what that profile is. And so you can just see some examples to the right of what some of those push notifications look like as well as some of that relevant content maybe based on previous videos they've consumed with. And so some of the results, they saw 26% increase in click-through rate, as we mentioned in a 1.5 times conversion. But they also got an 82% increase in click-through rate and going back to that AI capability, they were really leveraging the best time to consent component because they want to make sure that they're sending these notifications and relevant content at the time that their users are engaging. And this was one of the areas where they were able to see the most lift by being able to offer the right path to the right person at that right time. And that is all we have today. I just wanted to thank you all for joining us and listening to some of these strategies and best practices we shared. Hopefully there's something you can take away to inform your own strategy. I also wanted to share that we will offer attendees a exclusive free limited trial of Mo Engage. That way you can try to test out some of these features yourself and hopefully see some initial boosts of improvement areas in your own onboarding experience. We have our emails listed here. We definitely want to hear from you. If you have a question, if you want additional insights or best practices, just send us an email we would love to meet you and learn more and answer any questions you might have in the future. Thank you so much for your time today. Thank you.