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KEY HIGHLIGHTS

🎢 The first few steps in the analysis process of coming up with a trend

🛰 The key metrics to evaluate while drilling down on a trend – and how these differ by vertical. 

🤹‍♀️ Common pitfalls with statistics and how to avoid them

🎾 Why the ‘decline of app store spend’ narrative needs more nuance to be fully understood.

🪴 Attributing trends to their root cause: market movements vs. product movements

🐾 Deciding which trend to pursue

🥀 Learning through experience: the initial uptick doesn’t always translate to widespread consumer adoption.

KEY QUOTES

When the urge to investigate strikes

So when Elon Musk took over Twitter, we had a lot of questions from journalists, from clients and customers. What happened? Did people flock? Did they leave the app? Did they uninstall it?  And actually, the answer was no.

In the weeks after Elon Musk officially took over Twitter, we actually saw the number of active users increase. Now you might have opened the app and seen what was going on and decided I’m gonna delete this. Or you might have said, this is interesting, I wanna follow along. But things like that where there’s this natural shift, something happened, we want to investigate.

How the spend in gaming industry saw a trend

We started to see folks in Q3 of last year call in their earnings from gaming companies saying, “Hey, you know, the market’s changing. People are outside, they’re not gaming as much.” 

Then we ask, is that affecting mobile or is that more console related?

Are people really not spending? We’d go into the data and start looking at all the metrics that we’d want to map back. So that’s where it starts. Those are the three general areas that we end up always starting with a question, but it comes from different angles of what we’re trying to achieve.

How games vs. non-games evolved over the last year

This year we saw a decline of 2%. Now you might feel like it’s doom and gloom for the industry, but that is not true. The aggregate stat declined 2% year on year, to 167 billion dollars through the app stores. Now, where is that coming from? It’s actually when you split it between games and non-games, games declined 5%. non-games grew by 6%. 

So it’s a much more positive story for non-gaming. When you break that down by countries or even stores, it’s an even more compelling story.

Seasonality actually affects trends

So if I was analyzing the health and fitness space or even step trackers and looking only at 2022. There was a huge decline in downloads from the beginning of the year to the end of the year. The industry is bottoming out. This isn’t going anywhere, but really you need to look at January versus January, because when you extend that timeframe, if you don’t control for that seasonality, we actually don’t know if there was really strong growth.

For instance, this huge uptick in health and fitness apps is usually New Year’s resolution driven by people wanting to either lose weight or get in shape. Finance also seems to have a big boom generally in Q1, from either tax season or people wanting more financial fitness in a sense.

So if you don’t control for that seasonality, you could have some misleading stats.

Decreased disposable income affected game spend

As we have decreased disposable income, game spending has decreased. Non-gaming apps are the opposite. As disposable income decreases, non-gaming spending is increasing. So in that case inflation is affecting gaming or the cost of living and the rising prices are affecting consumers. It’s impacting our gaming spending, but not quite our non-gaming spend.

Analyzing data can help capture upcoming products/features

A really interesting example was in November and December of 2021, we started to see TikTok advertising more heavily on Spotify as a keyword for their iOS paid search. In markets like the UK and Australia, Australia tends to be that beta ground where you’re testing a bit with consumers before you roll it out. Then in March, we saw that TikTok announced a competitive version for artists and musicians to upload original music. So we had seen indications of this shift coming, and then we saw the rollout of a product and they had already been gathering momentum with advertising on similar user bases from Spotify.

Learnings from a wrong pick

I think we mistook more of an anomaly on one or two apps that we’re seeing some movement. And then some indications that big players were getting involved in consumer adoption. We were wrong. 

I think the lesson for us was, we should have looked a little bit more at a wider net as well and we equated a bit too much emphasis on a couple of small players that were growing.

FULL TRANSCRIPT

Shamanth

I’m excited to welcome Lexi Sydow to the Mobile User Acquisition Show. Lexi, welcome to the show.

Lexi

Hello. Thank you so much for having me.

Shamanth

I have been looking at a lot of your posts on socials because this is the start of the year and there’s a lot that you’ve written that’s very forward-looking.

I thought it would be great to talk about how you come up with these insights, because what I’m reading and seeing from you is very interesting and insightful – and I’m also always curious about how you come up with these insights and trends. So I’m excited to dive into all of that today.

So what’s the typical starting point when you are performing the exercise of analyzing a trend or coming up with a trend? Where do you begin?

Lexi

It comes from a number of sources, but there’s always going to be a central hypothesis. We always have some questions and maybe we’re just proving or improving it. We’re neutral on what we find, but it’s more trying to figure out if this is happening in the market. There are a couple of ways that usually jumpstart the process sometimes. We do a lot of reports and analysis in the market, and so there’s a time bounded element.

For instance, we just released a few weeks ago, the State of Mobile 2023, where we are focusing on what happened in the previous year – what’s important for folks to know this year? How has the industry changed? What will people need to know to navigate that change? 

That one comes from a higher level of a place where we’re defining some of those key things that we are asked about or we think, from a year of being in this space and analyzing.

For instance, it could be that we have to talk about the cost of gas in the US and how that affected the rising fuel costs where we saw that bubble up in the market. So we’ll sit down and have a big brainstorming session and map out all of our questions and then bucket them by themes or by area.

Oftentimes an essential theme emerges and in this year’s report one of the central themes is how we’re reacting to having less disposable income as a society with inflation pressures, cost of living increasing, and still some lingering supply chain issues happening. So that was an essential theme that kept coming back.

In some areas and some categories, spend moved directly with  inflation and there was an inverse relationship of decreasing spend. 

We might also have a natural investigation. So, at Data AI we’ve got lots of top charts and trend lines. There are a couple of apps that are really climbing the chart.

Chick-fil-A in the US jumped up into the top apps overall. What did they do? It might be that they gave away a free chicken sandwich and had a huge advertising campaign so we could see it’s campaign driven. It’s not necessarily organic, it’s more of a paid play.

That would also include things like Twitter.

So when Elon Musk took over Twitter, we had a lot of questions from journalists, from clients and customers. What happened? Did people flock? Did they leave the app? Did they uninstall it?  And actually, the answer was no.

In the weeks after Elon Musk officially took over Twitter, we actually saw the number of active users increase. Now you might have opened the app and seen what was going on and decided I’m gonna delete this. Or you might have said, this is interesting, I wanna follow along. But things like that where there’s this natural shift, something happened, we want to investigate. 

So it’s from the two sides, one is looking at our data and seeing organically what changed. The other is externally in the news or from other folks, there’s a meaningful inflection point we might want to address. The last area is hunches or hypotheses, and this could be just a little bit more general like – has gaming really declined?

We started to see folks in Q3 of last year call in their earnings from gaming companies saying, “Hey, you know, the market’s changing. People are outside, they’re not gaming as much.” 

Then we ask, is that affecting mobile or is that more console related?

Are people really not spending?We’d go into the data and start looking at all the metrics that we’d want to map back. So that’s where it starts. Those are the three general areas that we end up always starting with a question, but it comes from different angles of what we’re trying to achieve.

Shamanth

So what’s happening in the world, what you’re seeing in the metrics and any hunches or intuitions that you are pursuing and all of those can provide interesting starting points in very different ways. To double-click on one of these directions, what are some of the key metrics you are looking at to really drill deep into whether this is even a thing. 

And how do these metrics perhaps differ by verticals or categories, if at all they do?

Lexi

There’s a little bit of the art and then there’s the science. The science is that, once you double click, you’ve got a bit more of a path.

I think a lot of the time it can depend on the trend. First you need to map the metric a little bit on that as well. And then there are some differences in category size or vertical. With the example of Twitter and people asking, what happened with Twitter?

Was there more interest? Were there more downloads? Were people using the app more and we would say, actually we think the more important metric here would be daily active users or weekly active users because we need to look at a short period of time right after the news. 

We don’t want to go a full month. It would take us a while to wait for that. If it was in the middle of the month, it might not be as clear of a line, but daily active users or weekly would probably be a great place to look. The active users is important because Twitter’s been around for so long, we’ve seen it’s been downloaded. We count downloads as the first time someone installs it. So if you uninstall an app and then reinstall it, that doesn’t count as a new download for us. So we’d say, active users are going to be better because Twitter’s been around for a while. 

If you’re looking at an app like Gas, it was really big from the social media standpoint and was just acquired by Discord. But when it popped up on the scene, people wondered what this new app was. Then you see that sometimes the app isn’t necessarily new, it’s just getting attraction for the first time.

But for us, this is a demand metric. We want to see downloads. Downloads is usually the first indicator, usage follows. After usage, you’ll see app store consumer spend. 

The other side is for instance, with gaming and the example I gave before, if we’re looking at the game sector, we want to know, are people still spending on games? Is it that they’re not using them as much? There are two types of spending. There would be direct app store spending where it’s through in-app purchases, and then monetizing through advertising.

So if we want to evaluate direct consumer spending through the app store, then we need to look at in-app purchases and how that trends over time. But we also need to make sure we look at metrics that align with advertising. So we need to look at active users, time spent, sessions on aggregate and then also on the per person basis, and see how that changes over time as well.

In this example if monetization is through advertising, then the more important metrics from the ones that we have internally would be time spent and your audience size, which would be your active users. 

With specific categories, it’s different. For social, one of the key metrics that we want to look at is engagement because historically those apps tend to monetize through advertising. So, how big is the audience? How much time are they spending? And then going deeper and saying, that’s interesting, the rank of that at least doesn’t change as much. 

If you’re trying to evaluate multiple social apps on time spent in social, number one is YouTube, and it’s been number one for a long time. If you want to count YouTube as social or in that realm. Number two is Facebook. Number three is WhatsApp.

So those don’t change as much, but what does change and where you start to see some really interesting trends emerge is in per-user metrics. 

For instance, the average person is spending almost 27 hours a month on TikTok. When you look at Facebook, it’s closer to 15, and then you can look at the growth changes, and they’re inversely related this past year in the US where one’s up about 5% and Facebook’s down. That gives you a really strong indication of that engagement depth for folks. So for social, historically, that’s where we would look. 

But TikTok has disrupted a lot of that by adding in in-app purchases. So those are when you’re sort of tipping content creators that are live streaming. Now I think we would have to add in, so let’s look at the monetization strategy through the app store, because it’s not just advertising any longer.

In a couple of other verticals like gaming due to different monetization mechanics, we’d look at time spent as a general rule of thumb to see how much time is being spent gaming, we will look at downloads, especially for new games.

The average revenue per user is another one, or revenue per download event to see the efficacy of recent months’ consumer spend through the app stores. For retail, we would look more at downloads, due to new players, but then also time spent and then sessions, we look at sessions as digital foot traffic.

 We would bucket potentially by different types of apps so you can compare, what are the average sessions per user of mobile-first retailers versus those guys, we would call them bricks and clicks internally, but like brick and mortar players like Walmart for instance, that have gone mobile and we’re seeing the differences in the trend lines there.

For finance, one of the key metrics we look at is downloads that are still very important, especially for FinTech as well as banking. But a lot of the big banks have such large existing user bases, you’re just organically porting people over to a mobile app. as well as acquiring new users too.

For finance, we’ll look at average sessions per user as well and often on a weekly basis. That’s been an interesting one because we equate it to a brand new behavior for a lot of banks. So we’ll see that a lot of people in mobile banking access their bank accounts at least one time a day. So that basically is like you walking into a branch one time a day, talking to a teller or withdrawing money or checking your bank account.That is a completely new behavior that didn’t exist before mobile. We probably didn’t go into a bank every day and often they weren’t open every day.

So that’s another interesting one that we look at specifically to finance and within mobile banking and it’s important. It’s that brand touchpoint and it’s how people have changed the consumption of their personal finance habits.

So those would be some of the metrics. It really depends on each industry, and also depends on the app itself. So if you have a specific question, sometimes you’re gonna wanna look at usage data or things like active users, time spent, time per user, because that app has been around for a long time and so we really just want to see how long term it’s trending with its retention and engagement.

Shamanth

I imagine the metrics you’re looking at are also a function of the hypothesis you are trying to prove or disprove. Like you mentioned, on TikTok, if you’re evaluating the monetization effectiveness, then that’s when you look at the monetization metrics.

But if you’re trying to answer the question about whether TikTok overtakes YouTube or Facebook, you would look at very different metrics. Like you said, I think that’s where the art of it comes in as much as the science of everything you’re doing. So with statistics, it’s also easy to get some completely wrong conclusions, and I think there’s a book called, “How to lie with statistics.” 

I know people who lie about statistics because it’s just easy to be misled with these. So what are some of the common pitfalls with statistics, especially when you are looking at aggregates across verticals or written verticals, how do you avoid some of these defaults?

Lexi

It’s a great question. I think being in the data space and I think when you start to look at data with that type of lens I feel like you become a more informed reader of the news as well as advertisements.

You pay a little bit more attention to some of the studies referenced as well. So one of the things that we like to do in analyzing data is starting macro and going micro, and I think this is where for a lot of people – the nuance can be lost. In your point about aggregate stats, a common pitfall might be to stop at the macro.

For instance, a great example is one of the headlines of our state of the mobile report was that for the first time ever, consumer spending dropped on the app stores. We’ve never seen that. It’s been increasing for a variety of reasons. But mobile taking over the share of wallets, consumers migrate their behavior, in-app subscriptions, gaming, and mobile gaming becoming extremely popular,he movement of PC and core console titles to mobile, and every year we’ve seen this growth. 

This year we saw a decline of 2%. Now you might feel like it’s doom and gloom for the industry, but that is not true. The aggregate stat declined 2% year on year, to 167 billion dollars through the app stores. Now, where is that coming from? It’s actually when you split it between games and non-games, games declined 5%. non-games grew by 6%. 

So it’s a much more positive story for non-gaming. When you break that down by countries or even stores, it’s an even more compelling story.

So for non-gaming apps, we would look at iOS first, Google Play versus third-party android. In China for instance, Google Play non-gaming app store spending actually grew 24% year on year. So there’s very strong growth happening. A lot of that’s coming from big markets like Brazil and Mexico. But also in other markets where we’re just seeing growth among a lot of it coming from video streaming, from social TikTok being a big disruptive force, from dating apps, from photo editing.

There’s a lot of growth driving TikTok and the category it sits in the app stores is driving a lot of that growth. So nearly 80% growth year on year in consumer spending. There’s a lot of these disruptive forces happening, and the biggest way to avoid some of these pitfalls, you start at the macro, but you need to go deeper in each layer.

When we do those kinds of aggregate stats, we’d start with the macro, then we’d go into categories, and then we have App IQ and Game IQ at Data AI where we’ve got a robust taxonomy. We can go into shopping and then we can go into whether it’s reseller apps or direct or e-commerce directly. Is it buy now and pay later? Is it a coupons-and-rewards app? Where’s the growth coming from? You can go beyond that. Is it a specific title? Is it just TikTok driving the growth of this one sector? Or did the whole sector move together? I think that’s where you can uncover the good stuff.

Live streaming is booming and maybe it’s mostly just TikTok. Maybe that is the one big disruptive force. So I think that really helps when you have to keep going a little bit deeper and then splitting it by country. 

In gaming for instance, we saw the decline in gaming was 5% year on year in 2022 but there were countries that did buck that trend. A lot of countries moved in that direction. But China, Taiwan, Hong Kong, Brazil and Mexico, all actually saw growth in spending on games. So you need to tell both sides of the story that it’s not every country.

There are some big pockets of growth. And then some of the other common pitfalls I see are,  seasonality, whether you’re controlling or not controlling for it. 

So if I was analyzing the health and fitness space or even step trackers and looking only at 2022. There was a huge decline in downloads from the beginning of the year to the end of the year. The industry is bottoming out. This isn’t going anywhere, but really you need to look at January versus January, because when you extend that timeframe, if you don’t control for that seasonality, we actually don’t know if there was really strong growth.

For instance, this huge uptick in health and fitness apps is usually New Year’s resolution driven by people wanting to either lose weight or get in shape. Finance also seems to have a big boom generally in Q1, from either tax season or people wanting more financial fitness in a sense.

So if you don’t control for that seasonality, you could have some misleading stats.

So that’s a very important one. A couple of other things are market share, was it market movement, or was it just one app, or was it just one country. The US is responsible for over 50% of all spending in the year on health and fitness apps.

So if the US market had a big shift, it would affect the global numbers. So it might not be a global trend, it might be a US trend, but because they occupy more than half of all spending, then it’s driven by the US. That’s the same for our example of TikTok, and then the last one I’d call out is I see a lot of interest in these day-over-day metrics.

There was a spike from yesterday and that could be very volatile as a space, and it could be your trend line’s been going down, but then one day had an uptick. But when you look at the whole quarter over quarter or year over year, you actually see a decline still. So I think being very careful in providing context is important.

Yes, there was a spike, but in the grand scheme of things, the average daily download for that time of the year compared to last year is still down 20%. So I think that context is really important even though day over day is great because you might see spikes from campaigns. 

Shamanth

What I’m hearing you say really is to understand the full context and get down to the root cause  and really understand what it is that the data is trying to explain. Sometimes even when I’ve looked at different kinds of analysis, if an app I’m working with gets featured on a national television show, they get a huge spike and you don’t want to look at the average that includes that.

Or one day their entire backend is down and their numbers look terrible, you don’t want to look at the average, including that time period. So I think just as you said, it’s important to really understand what is driving and contributing to your aggregate metrics to contextualize a lot of this.

To jump off from that, how do you think about attributing some of these trends to the causes? For instance, you might say, this vertical has gone down, shopping has gone down. How much is it because of the COVID hangover? Or if gaming is down, how much of it is because of ATT?

How do you think about correlating something whose root cause you have arrived at through analysis in the manner that you described? 

Lexi

That part is very fun, you feel like a detective, going through those motions.

For your example of ATT, one way we’ve looked at that is, has there been an impact specifically isolated to iOS right now? Because on Google, we don’t have the same changes at this time. So we can compare them and if they’re both behaving in a similar way still, we’d probably say, we haven’t quite seen the impact.

So in that way, we’re sort of using Google Play as a control to see how that might play out.  A couple of ways we look at it, we look at what are the external variables of the app performance or the market performance that could be causing this change.

Inflation for instance, is a big one where we’re looking to see, was there an impact? In our State of Mobile, we have actually a slide where we correlated the disposable income with App Store spending, split by games and non-games. We see that in the US, games move with disposable income.

So

as we have decreased disposable income, game spending has decreased. Non-gaming apps are the opposite. As disposable income decreases, non-gaming spending is increasing. So in that case inflation is affecting gaming or the cost of living and the rising prices are affecting consumers. It’s impacting our gaming spending, but not quite our non-gaming spend.

So that’s one way that we try to isolate. 

We also looked at the impact of the rising cost of fuel. We got the per dollar aggregate for the country, it does vary by city in the US for instance, but the average dollar fuel price, over time by week in the US and we correlated that directly with downloads of electric vehicle charging, map apps looking for chargers of electric vehicles.

We saw a very similar curve appear where, as prices of gas got high, interest in electric vehicle charging apps or maps to find those places grew. Then we can substantiate that with market measures around sales of electric vehicles in the US. So, Kia, Hyundai and Ford all had big years of growth in electric vehicle sales.

We feel pretty confident given the indicators of the market and our data correlating well with this effect, that the price of fuel alongside some interest in sustainability and increase in electric vehicle interest over the years drives this point.

Then outside of that, we look at the product. We can try to see if the app has a change. If we’re looking at a specific app, did the app update a feature? Did they have a version update? Are there new things called out in their screenshots, their descriptions? Their app reviews is a great place as well that we use to find what changed.

Did a bug occur and people can’t log into their banking app and all of a sudden they’re flooded with one-star reviews?  People tend to do that. They’ll give that feedback on the app stores. So that can help determine a change, if there was a decline in usage of an app or an uptick in downloads.

We also look at, did they run a campaign or host an event? So if Pokemon Go Fest happens and they have different events that correlate, Genshin Impact has monthly events that they do, so we can see from social media app reviews and sometimes it’s called out in the App Store description of the app.

We can see when there are these changes because there’s a specific concerted effort by the app publisher. We can look at advertising to see if that helped grow downloads. So was it in-app install ads? Were there paid search ads like a concerted shift in their strategy for paid search ads, or did they just start paid search ads, and now we see a natural uptick in the percentage of downloads that are paid versus organic? Did a competitor run advertising on paid search?

A really interesting example was in November and December of 2021, we started to see TikTok advertising more heavily on Spotify as a keyword for their iOS paid search. In markets like the UK and Australia, Australia tends to be that beta ground where you’re testing a bit with consumers before you roll it out. Then in March, we saw that TikTok announced a competitive version for artists and musicians to upload original music. So we had seen indications of this shift coming, and then we saw the rollout of a product and they had already been gathering momentum with advertising on similar user bases from Spotify.

We try to look at it from those directions depending on if it’s a market movement or a specific app. Sometimes if the app is big enough, this specific change they make might shift their whole category. Genshin Impact is a leader in its category. If they did something different as a company, then it would likely shift some of the momentum of the category. That can also be a really strong indicator. We try to align dates as much as possible, and we’re making the best alignment we can.

Shamanth

As you said, it’s not always an exact science. The point is to put these pieces together, to really understand what story  all of this data is telling. That’s where a lot of the insights come from. You touched on some of this earlier but I’m curious if you can speak to this: how do you decide which stories are worth pursuing or which questions are worth answering?  

Lexi

From the data side, an easy starting point is what is surging or what is growing?

There’s an app called Bed, Bath and Beyond. I believe they skyrocketed up the charts last year, at about Q3, and it was before Black Friday and Cyber Monday. We though what happened there? What was this big shift?

We looked into it and we saw they just launched their mobile native loyalty program. They used QR codes in the store and you could get a free item if you joined their loyalty program. So we saw this massive growth from downloads and user acquisition, from this big concerted effort of launching a new feature.

First and foremost we saw that we needed to look at this because an app grew just ahead of Black Friday in the US. We saw Shein, which is a brand new app that had just been released, was basically topping the charts above Amazon and Walmart.

It was a new app from China, focused on discounts. Black Friday is a big emphasis, so the first place we tend to look is what’s happening in the data, what specific movement, especially if we’re looking at really timely trends. This week compared to last week, for instance. 

Other questions we often ask are coming from people in the industry. People asking us questions, our customers on LinkedIn or Twitter saying, “Hey, I have seen this, I’ve felt this when I’m looking at my app, is this true for the market?”

Then we get the itch and investigate the market. Is it isolated to one country? Is it a unique trend in a specific area? The news and media are a big one with journalists and what they’re reporting on. I think mobile tends to be a leading indicator in a lot of ways.

It’s often the first thing people reach for nowadays, for any sector. So when we start to see changes in the market that are being reported in the news, that’s often a prompt for us and say, okay, is this happening in our data? Can we see it? What’s the shift? Are people downloading new browsers? Are they using Duck Duck Go or is Chrome still dominant? Things like that. 

Sometimes it’s sort of the questions that we’re looking at if we have a hunch around, for instance, there’s been an uptick in anti-waste, anti-food waste apps.

So we’ve seen a few players in a few markets in Europe, and then as well in the US pop up and we look at that and say, okay, is this a trend or is this one app doing well? We try to see if it is just in a market that’s a bit more, either culturally or even policy-wise, more forward-focused on sustainability and green measures.

Is there a counter-trend, that might be happening, but at the same time, we see fast fashion apps like Shein are still booming. So we could say, people are looking for sustainable options. But perhaps there was a bit of the trend being driven by cheaper options because in a lot of these apps you could swap food or get things from restaurants at a highly discounted price. So maybe there’s a confounding variable here and it’s actually more of a financial motivator than a sustainability motivator or the two trends are sort of equally working together.

So those are some of the questions we start with but a lot of it’s coming from the market, folks asking us directly and then our monitoring every day in the data and saying, this changed what happened here.

Shamath

Yeah, you’re casting a wide net to filter out and figure out what is worth pursuing.

Just to look at another dimension of a lot of what you’re doing, is there an example that you can think of, of a trend or analysis that you got wrong? Can you talk about what you learned from this or how getting this trend wrong informed your own methodology?

Lexi

Yes. One of the trends we got wrong was, with live commerce or video commerce apps. So what we tend to look at is China as a market that tends to be a first mover in mobile shopping globally and prior to the pandemic it was the US by a lot in terms of mobile uptick and usage of shopping apps.

It was still very desktop for e-commerce, but then very in-person still as well. We saw some indications of live streaming performing very well in China. People are selling goods through live streaming on specific big apps. We thought maybe this trend is going to pick up in the West  and that we will see it in the US.

We actually saw some indications of one or two very small apps. There was a small app that focused more on digital collectibles and collectible items. It was a live-stream shopping app.

We saw QVC, which is a major TV shopping network in the US. 

Those apps were doing okay, they were still very small, but the growth was strong. So you’re coming from a small base, which sometimes means it’s nascent, but it’s showing strong promise. Sometimes that means it’s actually got some growth, but it’s not going to get that meaningful momentum. 

We did see TikTok focusing on live streaming for shopping. We saw Amazon had invested in a feature and so we were pretty bullish thinking that it would pick up, but we were wrong.

I don’t think it really has. We saw a lot of abandonment of shopping features and shopping emphasis in some of these social apps and at the end of the day, I think we mistook trialing and some of the big players with consumer uptake. We just hadn’t seen that yet.

We got that one wrong. We thought we were seeing some initial small attraction but it sort of fizzled out.

Shamanth

So the initial uptick doesn’t always translate to widespread consumer adoption.

Lexi

I think we mistook more of an anomaly on one or two apps that we’re seeing some movement. And then some indications that big players were getting involved in consumer adoption. We were wrong. 

I think the lesson for us was, we should have looked a little bit more at a wider net as well and we equated a bit too much emphasis on a couple of small players that were growing.

Shamanth

I mean, just the fact that a lot of the analysis you do is so hard to get right and the fact that it is not an exact science at all is exactly what makes everything you do so fascinating to me.

A few people I know are able to zoom in and out to courses and macro behaviors in this manner. 

Lexi, this has been very fascinating, and this is perhaps also a good place for us to start to wrap up. But before we do that, could you tell folks how they can find out more about you and everything you do?

Lexi

Absolutely.  I’m most active on LinkedIn. I’m happy to chat with folks and love to have conversations about what’s happening in the market and what questions people have. So you can find me on LinkedIn. 

You can read all of our analysis and research that’s coming out on our blog data.ai/insights. We put all our reports and weekly blog posts where we’re analyzing big trends in the market. So I encourage you to check those out.

Shamanth

Excellent, this is perhaps a good place for us to wrap. 

Thank you so much for being on the show.

Lexi

Thank you for having me. It’s been so fun talking about this. 

A REQUEST BEFORE YOU GO

I have a very important favor to ask, which as those of you who know me know I don’t do often. If you get any pleasure or inspiration from this episode, could you PLEASE leave a review on your favorite podcasting platform – be it iTunes, Overcast, Spotify or wherever you get your podcast fix. This podcast is very much a labor of love – and each episode takes many many hours to put together. When you write a review, it will not only be a great deal of encouragement to us, but it will also support getting the word out about the Mobile User Acquisition Show.

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Thank you – and I look forward to seeing you with the next episode!