Welcome to another episode of our mar-tech podcast Conversion Path. In this episode we are talking about our favorite tech and unveiling our go-to favorites for behavioral analytics, data, marketing and beyond.
Listen in to get a “peek behind the curtain” to learn about all of our favorite tech tools for mobile apps! We provide a round up of our go-to tech for marketing, behavioral analytics, customer data management, payment tracking and more.
Get insider tech tips for managing:
- Mobile app behavioral analytics
- Business intelligence
- AB testing
- Customer data
- Email/messaging tools
- Deep linking
- Payment tracking
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Conversion Path is a mar-tech podcast about data and growth for your online and mobile business by CRO firm Digital Dames. We gather every week to talk about how to amplify your product, service or message.
Resources mentioned in this episode
Visualization and Advanced Analytics
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Mobile App Tech Must-Haves (A Roundup Of Our Go-To Mar-Tech Tools)
J: Welcome to Conversion Path, a podcast about technology, data, and growth for your online and mobile business by Digital Dames. We gather here every week to talk about how to amplify your product, service, or message. I’m Jaclyn Hawtin.
M: I’m Mani O’Brien. In this episode, we are discussing our favorite technology and unveiling our go-to favorites for behavioral analytics, data, marketing, and beyond for your mobile app. We are very excited to share some of our favorite tools with you. Let’s kick it off with talking about analytics and behavioral analytics. To start, I will share with you our favorite tool called UXCam, which is a really awesome tool. We’ve talked a lot in previous episodes about user recordings and heat mapping analysis. Funnel analysis is another key component to gaining an understanding about how people are using your mobile app and UXCam is a great tool for that.
J: On the topic of user recording, that actually means your user’s screen is getting recorded as they’re using your app so you can see exactly what they’re doing on a video recording. A heat map is like a gradient filter, where you can see where the clicking is happening and where the red-hot spots are that are being interacted with a lot.
M: Great background. Thank you, Jaclyn. We’ve also talked a lot about AB testing. It’s important to present the information to people in different ways to get a sense of how they behave and find the right content to get them to behave the way you want them to. Some of our favorite tools include VWO. Other tools include Optimizely. A lot of tools now have some built in functionality for AB testing. For example, One Signal offers some components where you can present in-app messages and notifications in a really visual way to users. They do offer AB testing as well. Did I miss anything, Jaclyn, on the AB testing front?
J: I think you covered it. I would say on the topic of AB testing, if you can get into the mindset of doing ongoing AB testing, it will be very beneficial. We try to encourage organizations to do monthly experiments and do more if you can. You also have to allow enough time in between to collect enough data and remember that you’re not going to get a really successful result every single time. It’s probably going to take around six different approaches to land on something that makes a really big difference. So just some background there for setting expectations.
M: Great point. And on that topic, we should probably talk about behavioral analytics platforms. If you have an AB testing program, it’s not really going to serve you unless you have a good foundation for analytics. What are some of your go-to recommendations to that end, Jaclyn?
J: We usually recommend one of three platforms, either Mixpanel, Amplitude, or Indicative. They each have their own strengths. Mixpanel was developed as a tool specifically for mobile apps, so sometimes it’s a little bit easier to do the integration there than on other tools. They’re also consistently updating their platforms with new features and integrations. You have to do the research to make the best decision for your particular setup. These are behavioral analytics; they allow you to zone in on particular segments of your audience and get a really deep view of how they’re engaging with your app, which is very helpful.
M: We talked a lot about event tracking in previous episodes and how the data strategy, and a behavioral analytics tool is really at the core of presenting the data in a really visual manner across different teams so everyone can really get a sense of what’s working and what’s not in the app. Having great behavioral analytics tools is key to doing that.
J: This requires that you have your event strategies set up correctly and the events are being pulled in in order to be able to see this type of information.
M: What about business intelligence tools? What are your recommendations to that end?
J: There are a number of different tools you can use. Some people tend to want to use things that they have experience with, like Tableau or something like that. We like to recommend this tool called Mode. It’s more of a high-tech, contemporary platform. It allows you to do explanatory analysis of your whole data platform, your whole data warehouse, from a data scientist perspective. You can slice and dice the data in any way that you want to through SQL, Python, or R. It’s very powerful.
M: Powerful advanced analytics stuff. We can’t talk about analytics without at least touching on Google Analytics 4, which a lot of people might want if you are still using the Google Analytics platform.
M: Most people are familiar with Google Analytics; you’re tracking your users and new users’ sessions. You can get some marketing channel insights and event reporting as well.
J: It’s nice to have, especially if you’re doing advertising on Google itself, it’s a good thing to have. Even though you have all of these other awesome tools that are doing very advanced analysis, it’s good to have this perspective as well.
J: When using Google Analytics 4 from a technical perspective, you need to make sure that you have Firebase integrated into your app so the data flows from the app into GA4. Firebase can be used for a bunch of different things. But at the minimum, it’s required for passing data into Google Analytics 4.
M: Absolutely. Moving on from analytics, Jaclyn, we’ve talked a lot about our favorite tools, customer data platforms, what’s your recommendations around CDPs?
J: For your actual data warehouse, we’d recommend either going with something on AWS or something on Google. So maybe Amazon Redshift data warehouse at AWS and Google BigQuery for the Google side; both are really powerful. You can easily connect a lot of different tools that are automatically pre-built into their system. In terms of using a data pipeline tool, we recommend Segment. Segment is easy to use. They have a good support system. There are a lot of resources and people you can reach out to if you need help with your integration.
M: Definitely market leaders there. Shifting gear over to in-app messaging and email marketing. Some of the tools that we recommend here include Braze, which is a really popular email marketing tool, especially for mobile app marketers. You can enable any variety of personalized marketing through emails and push notifications. They also allow for deep linking where you can link users directly to specific portions of your app. Another popular tool that we love for email marketing is Klaviyo; it’s really an incredible system.
One Signal is also pretty great for in-app notifications and in-app messaging and utm.io is my favorite go-to for documenting your tracking link strategies. Without getting too much into the weeds, obviously, you want to be able to track users when you send them push notifications, text messages, or emails and you want to get a sense of what they’re looking at inside of your app. Having a really strong tracking link strategy is important and so utm.io is a great go-to for that.
J: What about payment tracking?
M: We recommend Revenue Cat for this tool. It’s such a great resource for having a source of truth on your transaction history, so you can see in a single dashboard. You can see reporting on revenue coming in, how many people have left your app, you get churned data, you get a sense of your recurring revenue over the course of time with a breakdown of marketing channels. It’s a really powerful tool.
J: Does Revenue Cat calculate lifetime value of users?
M: It does. You do get a sense of lifetime value, because you kind of have a sense of drop offs. They keep a track of what’s going on, down to the user level. There’s not a lot of personalization within Revenue Cat, so it’s all anonymized. You can see on the top level, transaction history and revenue trends, etc.
J: They have a lot of third-party integrations as well.
M: They do. Revenue Cat has integrations into BigQuery, into Amplitude, and many others.They also have a lot of integrations with marketing platforms as well. You can pull in Apple Search Ads information, although the new ATT tracking limits the amount of analysis you can bring into Revenue Cat. Having your CDP is a nice additional layer of information.
J: One thing I just want to add about analytics, tracking, and analysis, and all of that, in general, from a data perspective, is be careful not to bog yourself down with too much information. A lot of times, you’ll get really excited at the beginning of the project and think, “Oh, well, we’re setting all of this up now, we should probably track everything. Because otherwise, we might miss some information, we won’t know if it’s important in the future.” You create so many event labels, you have so much information coming in, then when you go to analyze it, you’re like, “It’s just too much.” I think it’s better sometimes to just have a minimum viable product with your data. Have questions laid out, your business questions you want to solve, and then what are the exact top-level KPIs you want. Then what are the little variables of events under each one that are absolutely necessary to make those calculations and just leave it at that. You can add more events later if it’s necessary, but don’t bog yourself down.
M: I love that. Backing up a little bit, from a starting point, think about the funnel and what steps you want your customers to take within the app. Then try to pick one thing you’re going to measure their behavior on. For example, did they sign up for a free account? Then try to map that out. Data is hard. It’s the age of too much information with data.
J: Knowing what to track is kind of an art.
M: Cognitive overload on the horizon. That happens too, absolutely. Is there anything else you want to add, Jaclyn? Any other go-to tools that we’ve forgotten to mention?
J: That’s it for me today.
M: We would love to hear what you are using for your mobile app. Let us know if we’ve missed any. We’d love to hear from you. As always, you can find us on our website at digitaldames.io, across social media channels @digitaldames. Feel free to drop us a line anytime. We would love to hear about other topics that you are interested in learning about in data, technology, and marketing. Our email is [email protected]. With that, this concludes this month’s theme of Mobile App Marketing. We will see you next month. Thank you so much for listening.