79: New Discovery Metrics
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Welcome to Under the Radar,
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a show about independent iOS app development.
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I'm Marco Armet.
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- And I'm David Smith.
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Under the Radar is never longer than 30 minutes,
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so let's get started.
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So today I am delighted to report that we are once again
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going to be diving into the world of App Store Analytics,
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not just because I love spreadsheets,
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but because Apple gave us a little pre-WDC present.
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Specifically, they now break down in more detail
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the source data that we get in App Store Analytics,
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which is one of the things that I think I've most longed for
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in analytics for years.
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Like I remember, I think in my second or third WWDC,
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going to the iTunes Connect Lab
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and asking if there's something we could ever get,
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and then asking the next year, and asking the next year,
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you know, and having very polite, you know, like,
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well, that's the file of radar, which I've done,
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and eventually it finally came, so hooray!
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Yeah, this is one thing I didn't,
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I never expected them to do this for us,
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because, you know, really, for most ways
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in which Apple would give us, like, you know,
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data on where our sales are coming from,
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most of those are both competitively useful
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for other app stores, like Google and Amazon, whatever,
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so Apple wouldn't want to share that.
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And also, it's things that Apple
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tends not to be very good about,
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like, you know, just general analytics and tracking,
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you know, letting people track more about the behavior
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of their store, it's the kind of thing
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that Apple would not only want to keep private
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most of the time, but generally also wouldn't be
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even very good at providing,
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even if they wanted to, historically.
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You know, it's the kind of service
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they don't usually do well.
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So it's very nice to see it, and, you know,
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there's one slightly skeptical angle to this,
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which is like, well, maybe this is,
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they're trying to drive people to invest more
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into search ads because it shows how important search is
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for a lot of apps, but overall,
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I think they just did this not for that reason,
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but just because it's something that a lot of app makers
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really need as we take this business
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more seriously over time.
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You know, like, this is such a big part of technology now,
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this whole app business, that it's important
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that people are able to get some kind of insight
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into where people come from for their apps
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just so they can know things like
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is it worth investing in search ads,
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how important are various parts of the app store experience,
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how important is being featured, stuff like that.
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And before we had zero insight into that.
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Now we have not a lot, but some.
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- Yeah, and it's, I mean, getting access
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to this kind of data, and we'll dive into it in a minute
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for what the actual new data points we got are,
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but it's like, I think at its core,
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giving developers this kind of data,
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it just helps us make informed decisions
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rather than just wildly speculating and guessing
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and having to do these weird, like,
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second order approximations of what we think
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might be the case, and any time that we can have,
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make informed decisions about this type of marketing
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or this type of, you know, these things
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that drive downloads of our app,
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which is ultimately what most of the app store analytics,
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you know, most of, at least from my perspective,
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what I'm really looking at is, you know,
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what is causing people to download my app,
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and is there something that I'm doing wrong
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that I could do better, or something that I'm doing right
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that I can do more of to make that happen.
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And if I have no data, then I'm just guessing.
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And I mean, I will get into it probably
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in the second half of the show,
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but there's already been some really interesting
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and useful tidbits that I've been able
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to pull out of this data that, you know,
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is now going to be, as I make my next updates to my apps,
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like, I can tweak and change the way, you know,
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the other app store pages work to try and enhance for this,
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because now I have actual information that I'm basing on,
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which is just tremendously useful.
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- Yeah, I mean, like one of the big questions
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when you're trying to figure out how to market your app,
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or how to advertise for your app,
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are things like, should I buy ads on websites,
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or in podcasts, or like, outside of the app store?
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And there's been bits and pieces of ways
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that we can track that different, like,
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you know, affiliate campaigns first,
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and then more recently they added, like,
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the whole, the app store analytics campaigns,
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so you can track inbound links.
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But we, but all we could tell from that
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is that these things provide a small percentage
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of our total downloads, and there was always
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this giant black hole of, well, we know that, like,
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you know, five or 10% or whatever it is for your app,
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you know, that's coming from web referrals,
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and we have some ways to track those,
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but where's the other 90%?
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You know, like, it's just the app store,
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and now we have a very slight way to break that down,
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which is nice.
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One thing, though, that I've noticed,
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and we're gonna get into this in a little bit,
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but one thing I've noticed is that, you know,
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the reason I'm giving such, like, vague numbers here
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is that as we got this ability over the, you know,
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last week when this rolled out,
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and I started seeing developers posting
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their pie graph breakdowns of, like, you know,
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this percent came from app store browse,
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this percent from search, this percent from app refer,
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this percent from web referrers.
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Everyone had extremely different percentages,
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and especially as you go down between the various metrics
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that we're gonna get into of things like, you know,
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how many times did you see it versus download it
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versus pay for it, the numbers vary wildly
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between different apps, and some of that you can kind of
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explain by things like paid versus free,
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but a lot of that is just, it seems like every app
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has extremely different numbers.
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There's only a few kind of general, you know,
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patterns we can derive from these,
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from the limited numbers that we've seen,
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but I don't know, but have you found the same thing?
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Like, every set of numbers I see is completely different
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from every other one.
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- Sure, and I mean, I even have, so I have, you know,
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a several handfuls worth of apps myself,
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and going through app to app, I mean, even among, like,
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the plus plus health apps that I have, you know,
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which are ostensibly fairly similar,
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there's wide variations between
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where people are coming from, and I think,
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like, that is a useful thing to point out, too,
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that what's so great about this is, say Apple published a,
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you know, I think we've had this a little bit
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every now and then where they'll say,
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most people come from search, I think is what they said
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when they were starting the search ads system.
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They're like, you know, the majority of app downloads
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come from search, I think.
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It sounds familiar anyway, but like,
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if they make a blanket statement like that,
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or you hear someone else's data,
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it isn't actually potentially very useful to you,
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because your app may, you know,
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they may respond very differently.
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You know, some of my apps are being heavily,
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you know, most of their downloads are coming
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from web traffic, from Google searches.
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Others are from browse, or from search,
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or from, you know, app referrals from other apps, like,
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knowing the actual breakdown is way more important
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than knowing what the average is for the app store at large,
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because every app is very unique,
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and I mean, none of my apps have at all similar
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distributions, which I think is telling.
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It's telling that, you know, the app is unique,
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and the reason people are downloading it is somewhat unique,
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and so you need to, there's not gonna be a one-size-fits-all
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solution for the marketing side of this.
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So, specifically, it's probably worth diving into
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what the actual things we're talking about are.
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So, the big, the key new area that we got,
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so if you go into iTunes Connect,
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and you go to the analytics area,
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there's now an area called, under sources,
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that now breaks down your, all kinds,
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all the different metrics, all the,
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and so you get things like impressions,
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which is the number of times that your app was viewed
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in the app store, you know, in all kinds of variations,
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it can be on the featured page, categories,
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top chart, search, like, overall impressions.
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- And it's just like, at times that your app, like,
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breezed by somebody, too, like,
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if they're scrolling through a list,
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and your app breezed through that list,
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like, that counts as an impression,
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not necessarily, they clicked on it, that's something else.
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- Yeah, if they click on it, then you get to the next one,
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which is the product page views,
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which is the number of times that your actual
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full product page was loaded.
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This is in the app store, or in another app
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that's using the StoreKit APIs,
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like the SK products view controller,
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I think is what they're talking about there.
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- And then app units, or, which we can probably
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sort of summarize as downloads,
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but it's important to note that this is only
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first time downloads of the app.
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- Yeah, it's new people downloading the app.
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- Yeah, so if you, if someone downloaded your app,
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installed it, and then deleted it,
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and then a couple months later went and installed it again,
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with a little, from the little, like,
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cloud with a down arrow icon in the app store,
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they wouldn't count as a new unit,
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even though they were downloading it.
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But the key thing now is that we can take that data,
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so those are the three main ones that I look at,
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impressions, page views, and downloads.
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And I can break those down now by,
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for the four different ways that people can get to there.
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So they can be browsing, so if someone is viewing your app
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or tapping to download or whatever,
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from, like, their starting point was a featured list,
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a category list, or a top chart in the app store,
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essentially those first three tabs
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going along the bottom of the app store app.
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- It's basically any part of the app store
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that isn't search.
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- Yes, yeah, and so if they were just browsing around,
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there was no explicit user intent
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that they were putting out
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and then the app store was responding to.
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And then there's search, which is the fourth tab
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in the app store app,
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where someone is searching for something
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and then going through a list
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and, you know, tapping to download from there.
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Then we have app referrals,
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and so this is where somebody is clicking on a link
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in an app that is then opening them in the app store,
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or any app that uses those store-cared APIs
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to launch the app.
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And this includes many of Apple's apps as well,
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so things like messages count in this,
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but it doesn't include Safari
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because the last type that we get broken out
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is web referrals,
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which are where a customer taps a link from a website
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and that then takes them to the app store.
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And this would be inside of Safari on iOS,
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but it's important to point out that non-Safari browsers,
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things like Chrome, would be attributed as app referrals
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rather than web referrals.
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Web referrals only includes Safari itself.
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- And in fact, Google Chrome is my top app referral.
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- There you go.
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Yeah, and so that,
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by breaking it down that way,
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essentially we can now take all of the metrics,
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I mean, I think there's seven or eight different metrics
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that are available in the app store analytics area,
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beyond just impressions, page views, and downloads.
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You can get into active sessions, paying customers,
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you can get, there's a whole bunch of deeper dive
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kind of things, but for the most part,
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you can take a look at those top three
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and you can look and see where your customers
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are coming from, and you can see,
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for some of my apps, it's like the vast majority
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of my downloads are coming from search.
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So something like search ads maybe makes sense,
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or focusing on app store optimization
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or focusing on the way that I peer in searches
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makes a lot of sense.
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If browse, and some of them come up mostly in browse,
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like that's a different thing,
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or some of them come up in web traffic,
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like one of my apps comes up is really high hit in Google
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for if you search for that app name,
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and so that actually drives a fair bit of traffic.
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And I can segment all these other metrics about that,
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and you can, the interesting thing is,
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now that you have the segmentation,
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you can, in some ways, like customize your thinking
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for each of those four little, like, I don't know,
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there's these four different distinct types of users
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that are coming into your app,
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because their experience is very different.
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If someone is browsing the app store,
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they are sort of, by their nature,
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they're not specifically looking for your app,
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or an app that is exactly like yours.
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I mean, maybe if they're going to the categories,
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and then they go to like,
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you know, some of those top charts,
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category, health and fitness,
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like maybe that's how they would go about
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looking for a step counter, like maybe.
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But more likely than not, they would just go to search,
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and they would search for step counter or pedometer,
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in my case, and, but if someone's browsing,
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like they have a slightly different perspective
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than someone who's searching,
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and I mean, this bears itself through in,
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you know, in a lot of my analytics,
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where I see, you know, for example, my conversion rate,
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you know, so from someone having an impression of the app
00:12:53
◼
►
to actually downloading it is three times higher
00:12:56
◼
►
on search impressions rather than on browse impressions,
00:12:59
◼
►
which makes sense, like if someone types in step counter
00:13:02
◼
►
in the search, then they're far more likely probably
00:13:06
◼
►
to download a step counter than someone
00:13:08
◼
►
who's just wildly browsing in the app store,
00:13:09
◼
►
and happens to, you know, my app happens to cross their path.
00:13:13
◼
►
But it's good to know, and it's good to know
00:13:14
◼
►
that it's about three times, which is honestly
00:13:16
◼
►
a little bit lower than I would have thought it would be,
00:13:19
◼
►
the difference, like, and this is where I love
00:13:20
◼
►
having the data for it, it's like, my gu--
00:13:22
◼
►
I would have guessed that it would have been,
00:13:24
◼
►
the conversion rate for search would have been way higher
00:13:26
◼
►
than for browse, but turns out maybe not.
00:13:30
◼
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That is crazy magic to me as an old school computer user
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- So the other kind of really cool thing
00:16:07
◼
►
that I've been doing, so as you imagine,
00:16:09
◼
►
and this is something I'd honestly recommend
00:16:10
◼
►
that everyone do if you have an app
00:16:12
◼
►
that you have access to this data,
00:16:13
◼
►
is you should take the data, export as much as you can
00:16:16
◼
►
into Excel or Numbers, whatever your preferred
00:16:20
◼
►
spreadsheet of choice is.
00:16:22
◼
►
- Are there others?
00:16:24
◼
►
I guess Google Sheets.
00:16:26
◼
►
- Google Sheets, Lotus one, two, three.
00:16:29
◼
►
- Is that still a thing?
00:16:30
◼
►
- I don't know, maybe it's a thing, or maybe VisiCalc.
00:16:32
◼
►
That's an oldie but a goodie.
00:16:34
◼
►
- The original.
00:16:35
◼
►
- So I do know, you take all this data in
00:16:38
◼
►
and then what I tend to do is I just start dividing numbers
00:16:41
◼
►
by each other, right?
00:16:43
◼
►
'Cause a lot of these things in absolute terms
00:16:46
◼
►
aren't particularly useful, like knowing the exact number
00:16:49
◼
►
of impressions you have, it's kinda nice I guess,
00:16:52
◼
►
but mostly what you need to know is the ratios
00:16:55
◼
►
between things because then you can really reason
00:16:57
◼
►
and compare between all the various types
00:17:00
◼
►
of traffic sources.
00:17:02
◼
►
And one of the things that I noticed that I think
00:17:05
◼
►
so far was the biggest insight that I think is actually
00:17:08
◼
►
like operative to me was that the majority
00:17:11
◼
►
of my app store downloads are coming from users
00:17:15
◼
►
who never actually view the full app store page
00:17:19
◼
►
for my apps.
00:17:20
◼
►
But the way I'm inferring that is that the app units number
00:17:25
◼
►
is higher than the page view number.
00:17:28
◼
►
So, but obviously still less than the impressions number.
00:17:32
◼
►
So in some ways, my naive thought for how the app store flow
00:17:37
◼
►
would work is that someone sees my app, they tap on it,
00:17:42
◼
►
they look at the page, and then they hit download.
00:17:45
◼
►
That is actually not, for the vast majority of the case,
00:17:48
◼
►
is not what I'm seeing.
00:17:49
◼
►
What I'm seeing is people are downloading straight
00:17:51
◼
►
from those top level lists.
00:17:55
◼
►
So from the top charts, from the search results,
00:17:58
◼
►
like in all of those, there is a download button
00:18:00
◼
►
right there, you don't have to tap through
00:18:02
◼
►
in order to view it.
00:18:04
◼
►
And so what's important about that is they're downloading it
00:18:09
◼
►
entirely based on the name, the icon, the star ranking,
00:18:12
◼
►
and the price.
00:18:13
◼
►
And in the case of search, they also get three,
00:18:18
◼
►
sorry, the first two screenshots as well.
00:18:22
◼
►
That is all they are ever seeing
00:18:24
◼
►
before they download the app.
00:18:26
◼
►
Which is kind of interesting to me.
00:18:29
◼
►
- It's, like seeing that number pulls out,
00:18:31
◼
►
it's like there's so many of these things
00:18:33
◼
►
that I think we've talked about,
00:18:33
◼
►
and I think a couple weeks ago we even had an episode
00:18:35
◼
►
where we were like diving into this kind of stuff,
00:18:37
◼
►
where it's important to have a good app store description,
00:18:41
◼
►
and your fourth and fifth screenshot are probably,
00:18:43
◼
►
you know, are somewhat, they're things you want to
00:18:46
◼
►
take advantage of and do well.
00:18:47
◼
►
But a very high percentage of people are just downloading
00:18:51
◼
►
based on just the name, icon, and star rating and price.
00:18:54
◼
►
And that's kind of crazy in some ways.
00:19:00
◼
►
I think in A, it means that you need to have
00:19:02
◼
►
a really good name, you need to have a really good icon,
00:19:05
◼
►
make sure your rating's high, and honestly,
00:19:07
◼
►
probably be free.
00:19:08
◼
►
Like, being free I'm sure drives this a lot.
00:19:10
◼
►
I haven't dug into deeply yet comparing free and paid,
00:19:14
◼
►
but I would expect that the ratio there is massively off.
00:19:18
◼
►
But if you're a free app, people will just, on impulse,
00:19:21
◼
►
they see it, get it, they're done.
00:19:23
◼
►
They don't even have to dive into it,
00:19:25
◼
►
which I think is really, you know,
00:19:28
◼
►
that it's a compelling thing to see.
00:19:32
◼
►
And especially interesting is when people are searching,
00:19:38
◼
►
they click through to the detail page even lower rate.
00:19:42
◼
►
I think it was 11% of my impressions turned into page views
00:19:47
◼
►
in search, whereas 45% of them turned into page views
00:19:53
◼
►
from browsing.
00:19:54
◼
►
So in the search area, those first two screenshots
00:19:59
◼
►
are very important because 90% of people
00:20:03
◼
►
aren't actually going any farther
00:20:05
◼
►
than that initial search list.
00:20:08
◼
►
So that's like the first insight that I pulled out
00:20:12
◼
►
of my data that I'm like, "Huh, that is really interesting."
00:20:15
◼
►
I mean, I think it makes me definitely emphasize
00:20:18
◼
►
a little bit the importance of preserving
00:20:22
◼
►
and maintaining my star rating in a way that I,
00:20:25
◼
►
well, I knew it was important.
00:20:26
◼
►
It's like, wow, that is probably very important
00:20:28
◼
►
because I can't really change the name at this point.
00:20:32
◼
►
The icon is pretty set, so really all I can change
00:20:35
◼
►
is making sure that I have a good star rating.
00:20:37
◼
►
And if I don't, and that ratio starts to go down,
00:20:42
◼
►
that's problematic in a significant way.
00:20:45
◼
►
- Yeah, I mean, I think many of us have suspected
00:20:49
◼
►
for a long time that not a lot of people read
00:20:52
◼
►
the description and stuff like that
00:20:53
◼
►
and viewed the whole page, but I don't think we ever had
00:20:56
◼
►
anything to really back that up until now.
00:20:58
◼
►
And now it's very clear what you're saying.
00:21:00
◼
►
It's like, yeah, search matters a lot,
00:21:02
◼
►
and everything else matters a little bit.
00:21:05
◼
►
But really, you need to optimize your app
00:21:07
◼
►
for visibility in search rankings.
00:21:11
◼
►
And seeing these numbers, on one hand,
00:21:14
◼
►
it's like, oh, thanks, Apple,
00:21:15
◼
►
for finally providing this information.
00:21:16
◼
►
On the other hand, it's like, oh, man,
00:21:18
◼
►
what a shame that App Store search is so mediocre.
00:21:21
◼
►
Like, it really, this really shows quite how much
00:21:24
◼
►
of an effect on the ecosystem search has.
00:21:27
◼
►
And it is really unfortunate that the actual
00:21:31
◼
►
relevance ranking of App Store search continues
00:21:35
◼
►
to be so, so mediocre.
00:21:38
◼
►
But that's the world we're living in, I guess,
00:21:41
◼
►
so might as well work within it.
00:21:42
◼
►
And one way to work within it is search ads.
00:21:45
◼
►
And this has been, they launched back in, what,
00:21:48
◼
►
October or something like that?
00:21:50
◼
►
- Something like that.
00:21:51
◼
►
I think it was in beta over the summer,
00:21:52
◼
►
and then in the fall it went live.
00:21:55
◼
►
- Yeah, I've been doing search ads every week,
00:21:57
◼
►
and we should do a whole episode about following up
00:22:00
◼
►
on doing them well.
00:22:02
◼
►
But basically, this shows me how many downloads
00:22:06
◼
►
of my app come from search total,
00:22:08
◼
►
and I can correlate that with my search ads numbers,
00:22:11
◼
►
'cause when you do search ads,
00:22:12
◼
►
it gives you lots of useful reports of things like
00:22:14
◼
►
how many clicks you're getting,
00:22:15
◼
►
and through what type of queries,
00:22:18
◼
►
and what it considers relevant to you, and everything.
00:22:20
◼
►
And so I'm getting about 12% of my search downloads
00:22:25
◼
►
are coming from search ads.
00:22:28
◼
►
I can now see that.
00:22:30
◼
►
And because my app gets so much from search,
00:22:33
◼
►
about 10% of all my installs are coming from search ads.
00:22:36
◼
►
So that's worth knowing.
00:22:38
◼
►
But again, these new metrics that we got
00:22:42
◼
►
really strongly illustrate quite how important
00:22:46
◼
►
App Store search is for a lot of apps.
00:22:49
◼
►
And again, I will say, as we said at the beginning,
00:22:52
◼
►
this does vary a lot for different apps,
00:22:54
◼
►
but one thing I've seen pretty consistently
00:22:57
◼
►
among most of the people's little donut charts
00:23:00
◼
►
that we've been passing around is that
00:23:03
◼
►
search is pretty important for most apps.
00:23:06
◼
►
- Yeah, and I think the thing with there is especially
00:23:09
◼
►
that search is important,
00:23:11
◼
►
like it's important in a way that you can control and change
00:23:17
◼
►
because if your app is ranking well,
00:23:20
◼
►
if you're high in the top charts
00:23:21
◼
►
and being featured all the time,
00:23:23
◼
►
like your browse side of things is going to go up,
00:23:28
◼
►
but that is not something that you have direct control over.
00:23:31
◼
►
And so in some ways, like for me, some of my apps,
00:23:36
◼
►
browse is more important than search,
00:23:39
◼
►
just the way the numbers come out.
00:23:41
◼
►
But the reality is when I look at that,
00:23:42
◼
►
I think it's like, well, okay,
00:23:44
◼
►
I wanna do cool things that Apple is going to feature.
00:23:47
◼
►
Like that's something that I can sort of control maybe.
00:23:50
◼
►
And I wanna have lots of downloads
00:23:51
◼
►
so that I can rank highly in the top charts.
00:23:55
◼
►
But none of those are really direct things,
00:23:56
◼
►
whereas search is the only area
00:23:59
◼
►
where we have much more direct control over.
00:24:02
◼
►
Still not complete control, but we choose keywords.
00:24:05
◼
►
We choose what are those first two screenshots are.
00:24:08
◼
►
We choose a lot of things that will impact our ability
00:24:12
◼
►
to convert well in search.
00:24:15
◼
►
And so even if your app has higher impressions
00:24:21
◼
►
on the browse side, search is still, I think,
00:24:23
◼
►
probably a more important area to focus on,
00:24:26
◼
►
just because it's an area that I think we can have
00:24:28
◼
►
the biggest impact on in terms of actually affecting change.
00:24:33
◼
►
- Yeah, and the other thing, though,
00:24:34
◼
►
like this does show you quite,
00:24:37
◼
►
it shows you in kind of broad relative terms,
00:24:41
◼
►
like maybe it isn't worth investing a ton of time
00:24:45
◼
►
into trying to get featured,
00:24:47
◼
►
because it looks like the value of getting featured,
00:24:50
◼
►
I mean, obviously it varies
00:24:51
◼
►
depending on what kind of feature you get,
00:24:53
◼
►
but the value of getting featured is not amazing in this.
00:24:56
◼
►
Although, I'll tell you what,
00:24:57
◼
►
one thing I would love so badly to have
00:25:00
◼
►
is one of those little badges in search results
00:25:03
◼
►
that says like Editor's Choice,
00:25:04
◼
►
or like Best of the Outfit, or Essentials,
00:25:06
◼
►
like all those, there's a couple of very high level features
00:25:10
◼
►
that if you get one of those ever,
00:25:12
◼
►
I think you get that badge in your search result forever.
00:25:15
◼
►
And that, obviously, now that we see
00:25:17
◼
►
the importance of search,
00:25:19
◼
►
and especially like how your little listing looks
00:25:21
◼
►
without clicking through to your product page,
00:25:24
◼
►
the value of that would be immense.
00:25:25
◼
►
And I so badly want one of those badges on mine.
00:25:28
◼
►
But otherwise, yeah, I think it's very clear.
00:25:31
◼
►
The other thing I wanted to mention
00:25:32
◼
►
before we run in too much out of time
00:25:34
◼
►
is that a lot of the metrics that we get in App Analytics,
00:25:38
◼
►
including many of these new ones
00:25:40
◼
►
for sources of people and stuff, are opt-in only.
00:25:44
◼
►
And what this means is basically that only people
00:25:48
◼
►
who selected Send Data to Apple on the setup screen
00:25:52
◼
►
during the OS installation,
00:25:54
◼
►
only those people's data is being counted here.
00:25:57
◼
►
And for my app, that's a very low percentage.
00:26:01
◼
►
And the impression I get from most of the developers
00:26:03
◼
►
I've talked to is that for their apps,
00:26:04
◼
►
it seems to be a pretty low percentage too.
00:26:06
◼
►
And now you can even see, you can compare your numbers here,
00:26:09
◼
►
and you can see like, yeah, this,
00:26:11
◼
►
it's showing me a graph of this metric
00:26:14
◼
►
that says it's representing people,
00:26:15
◼
►
but then it says opt-in only,
00:26:16
◼
►
a little small text next to it.
00:26:17
◼
►
And if you look at the absolute numbers on the graph,
00:26:20
◼
►
compared to the numbers in the ones that are not opt-in only,
00:26:22
◼
►
you can see it's a pretty small percentage.
00:26:24
◼
►
So I would say that any metric that says opt-in only
00:26:29
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is not incredibly useful,
00:26:31
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because it's such a small percentage,
00:26:33
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and it probably is not like a random sample.
00:26:36
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It's probably not completely representative of the whole.
00:26:39
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So those metrics I would not put a lot of weight in.
00:26:42
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But the ones that are not opt-in only,
00:26:43
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I think that's great to have.
00:26:45
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- Sure, I mean though, the reality is, it is what it is,
00:26:48
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and that's the best we have.
00:26:49
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So like, I definitely love diving
00:26:53
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into some of those opt-in only ones.
00:26:55
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And fair enough, it's a small,
00:26:57
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perhaps not random distribution,
00:26:59
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but at least it's something.
00:27:01
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You know, and getting insight into 20% of my users
00:27:05
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is better than getting insight into 0%.
00:27:08
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And I think too, it's, the biggest thing that I think of
00:27:13
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when I look through these numbers though,
00:27:14
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like is how massive of an opportunity, in theory,
00:27:19
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and you know, it's a very big in theory,
00:27:21
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a lot of my apps have,
00:27:24
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that I'm currently not taking advantage of.
00:27:26
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And by that I mean, like when I look at this,
00:27:29
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I can't help but look at the impression to download number.
00:27:33
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So essentially like my conversion rate from, you know,
00:27:36
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the number of times my app icon slid past someone's eyes
00:27:40
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to when they downloaded.
00:27:41
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And a lot of those are, you know, pretty low.
00:27:44
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I think for browse, for Panorama++, it's about 11%.
00:27:49
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For search, it's 28%, which is good.
00:27:52
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I'm not saying like that's not,
00:27:54
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it's not a terrible number.
00:27:55
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It's not, you know, fractions of a percent.
00:27:58
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But when I see that, I see it as a massive opportunity.
00:28:01
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And I think that's the thing that I probably would leave
00:28:04
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towards the end of the show,
00:28:05
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sort of for everybody to think about is
00:28:07
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using this kind of data,
00:28:10
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you have a tremendous opportunity to increase your,
00:28:13
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you know, your user base, your download numbers.
00:28:16
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Because, you know, if right now only one out of 10 people
00:28:20
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who are browsing around and see my app icon download,
00:28:23
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like if I can turn that into two out of 10,
00:28:27
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which is, you know, the actual numbers involved
00:28:29
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aren't actually that dramatic,
00:28:32
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like, or the increase isn't that dramatic,
00:28:34
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but the numbers involved would actually be very significant.
00:28:37
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And so it's a very big opportunity.
00:28:39
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I'm like, well, what if, you know,
00:28:40
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what do I have to do to make it to affect that number?
00:28:43
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And what I love is that I can, as I make changes, you know,
00:28:46
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so I'm actually going through and making a few tweaks
00:28:49
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to some of the, like I'm actually making a few,
00:28:52
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a tweak to the apps icon,
00:28:54
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and gonna be changing around a little bit
00:28:56
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the first two screenshots in some of my apps.
00:28:59
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And what I love is I can make those changes
00:29:00
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in the next update, and then now I can go into this area,
00:29:04
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and I can see, did that change anything, right?
00:29:06
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Like I can, it's not quite A/B testing,
00:29:09
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which would be, you know, lovely in its own way,
00:29:11
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►
but also terrifying.
00:29:12
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But I could also, but I could very least,
00:29:14
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I can make a change, I can measure its impact,
00:29:17
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and then, you know, iterate on that,
00:29:19
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and hopefully increase these numbers, you know,
00:29:23
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►
ever so slightly, and you know,
00:29:24
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these small changes in conversion rate
00:29:26
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►
can have a pretty significant impact
00:29:29
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►
ultimately to my bottom line, which is really cool.
00:29:32
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- Thanks for listening, everybody,
00:29:33
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and we'll talk to you next week.
00:29:36
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[BLANK_AUDIO]