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To acquire players from the west, we are running ads on fb, instagram, google, putting out content on our game pages. Is there any specific better way that we are missing out on? Do you guys know any agency or a person who has expertise in UA specifically for western market in F2P casual mobile games?
What according to the community are the key metrics to track a new game when launched? If D1/D7 retention, engagement metrics are to be considered, can anybody suggest what are the industry benchmarks to stay at for these metrics for considering to continue working on the game? PS- Making this open ended irrespective of genre. Maybe the replier can help us understand what benchmark to consider for the respective metrics/ genre.
Hi to everyone,I used data.ai API (specifically portfolio/app-store end) to obtain data about all the ratings of an app for the last month but I can’t figure out how to calculate the rating for that period from raw data like this:I read online that Google is now weighing recent ratings more heavily than historical ratings, so using a simple formula like the following one will return incorrect rating:RATING NUM = MAX(0,[@[one_star_incremental]])+2*MAX(0,[@[two_star_incremental]])+3*MAX(0,[@[three_star_incremental]])+4*MAX([@[four_star_incremental]],0)+5*MAX([@[five_star_incremental]],0)RATING DEN=MAX(0,[@[one_star_incremental]])+MAX(0,[@[two_star_incremental]])+MAX(0,[@[three_star_incremental]])+MAX([@[four_star_incremental]],0)+MAX([@[five_star_incremental]],0)OVERALL RATING FOR LAST WEEK = sum(RATING NUM) / sum(RATING DEN) Can someone help figuring out what weights should I give to the most recent reviews?Thank you!
Hello to everyone,I am facing an issue while try to calculate the average ratings of an app using the following fields (returned by the API calls):one_star_incremental two_star_incremental three_star_incremental four_star_incremental five_star_incremental total_count_incrementalIn order to calculate the average ratings of an app for period X, i would use the following formula (for all the record in that period):sum(one_star_incremental+ 2* two_star_incremental+ 3* three_star_incremental+4*four_star_incremental + 5*five_star_incremental) / sum(total_count_incremental)This formula returns wrong data compared to the dashboard I created on data.ai portal. Can someone help me?Thank you!
I often find myself creating groups of apps to conduct analyses on, generally because I’m looking at a specific segment that’s not defined by Data.ai or because I have a specific type competitor I want to analyze. Often, I sift through long lists of apps through reports like the app explorer or top apps, and need to click each app I want to compare ( “Select objects to compare”) or add to a group individually. Is there a faster way to do this?For example, say I want to select 20+ consecutive apps in a list, my instinct would be to select the first app in the list, hold down shift, then select the last app in the list of consecutive apps, with the expectation that all the apps in between will be selected. This is not possible though, it simply selects the text in the list instead of the checkboxes.
What are the best ways to utilize data.ai in User Acquisition perspective? While data.ai offers wide range of mobile app data, here are few data points you can check to have better understanding of UA. Timeline Report - Check app version updates, app market asset status In any app’s detailed analysis page, go to info>timeline. From here, you can check an app’s detailed app updated records including icons, description, version update and many more. data.ai automatically show you the changes that have been made by colors:Red indicates content that are removed or modified. Green indicates newly added content. Having a higher app update frequency is one of the known key factors to boost ASO. Download channel - Breakdown total downloads into paid and organic Total download volume consist of paid downloads and organic downloads. If your contract includes the Download Channel report, you can get in-depth details on this. Go to Analyze > Market insights > Download channel or, in sin
disclaimer: I am the CPO of Trackingplan, a SAAS observability and data quality solution for digital analytics and marketing dataBased in your experience, I would like to know how you currently detect problems in your data and how much effort does it take to maintain a minimum of quality?- Do you have a dashboard to monitor them?- Do you carry out manual QA processes from time to time or per release?- Do you have automated tests?- etc…Thank you in advance
Hello data.ai Community, My name is Taylor Lundgren and I’m the Product Marketing Manager for Mobile Adtech & UA here at data.ai. We're so excited to announce the launch of the Mobile Monetization Guide! We invite you to join in on this special Community conversation dedicated to discussing the Mobile App Monetization guide's content and related topics. If you have any questions, thoughts, or need clarification on anything in the guide, please comment below and you’ll be able to engage with the guide’s creators and your peers to gain additional and valuable insights. Guide Details:We worked with a great partner in Google to produce this new guide which covers tips, tricks and best practices for mobile app monetization. This is a key resource to help you boost your revenue, optimize your monetization strategy or discover how to streamline your acquisition-to-purchase pipeline.We've broken the report down into a few sections : Market and Product Overview Global Market Data Monet
We’ve all looked at one of our competitors and saw a spike in downloads that line up with a known acquisition campaign, but is that a direct indicator of success? Or is it just “surface” success? Let’s take a look at how to understand that, in a matter of minutes, without having to spend lots of time looking at numbers. First - we’ll need a group of apps to compare. Head to the compare report, which lives in the left hand navigation pane and under “Compare”. At the top left, you’ll have a filter that allows you to either select a group that you’ve already created, or create a new one if you haven’t. Search for apps that you’d like to compare, and hit the + icon to add them to the group In the example below, I’ve just got one app selected. Here we can see a clear increase in their downloads since June. There’s obviously weekend spikes in here too, but the trend is increasing. This app is running an acquisition campaign. It looks like it’s succeeding, but how should we measure the suc
App store categories can be fairly generic. App IQ helps break down apps into Genre / Subgenre to help identify top competitors without too much manual digging. Quickly uncover the top performing apps. In this example, we are looking at the “Weather” Subgenre for Q3 and it is highly competitive. After The Weather Channel, there are several apps fighting for download market share. An app like AccuWeather (which is sitting in the 3rd spot in terms of downloads) may want to look into what features The Weather Channel has that they do not, to potentially attract new users. Below is a visual of the Feature Comparison Report, where you can see side by side what your competitors have that you may not. AccuWeather currently does NOT have a feature that provides Allergy Insights - the top performer does. I wonder if that is important to users? Let’s find out! Advanced Reviews buckets customer reviews into “topics” so you can quickly identify specific areas to monitor over time. You can al
Want to keep track of which other apps or games are competing for your users’ time? And even further, quickly check which new and emerging apps and games your own users are now using?data.ai’s Top Apps Report sorted by Active Users and App Used helps answer these questions quickly. To reach this reportNavigate to our Top Apps Report Select App Store Categories Filter by Active Users Select either iPhone or Android phone Select Weekly or Monthly date Granularity Input your app or a competitor app into the “App Used” filter In the example above, we are analyzing Monopoly Go’s Android Users in the United States for the last three months, and we can see how many of their users are playing other games such as Roblox, Pokemon Go, and competitors like Coin Master, and how the usage in those apps are trending compared to the previous 3 month period. To quickly identify new apps or games and emerging competitors for your users time, sort the table by “Change % Period Over Period” and then
Hello and thank you for attending today's webinar title, "Game On: Elevate Your User Acquisition Strategy with 5 Quick Plays."We're excited to continue the conversation here in the Community. If you have any questions, please comment below and our panelists will reply for the rest of the day. If you have any insights you'd like to share, we welcome your thoughts as well.This webinar topics include:Increasing efficiency and cutting through the noise with data.ai's exclusive Mobile Performance Score: Learn about our cutting-edge tool that's redefining the way you measure mobile performance. Tactics to fight rising advertising costs and improve Customer Acquisition Costs: Gain insights that will supercharge your user acquisition efforts.Thank you for joining!
data.ai users commonly ask question about data.ai’s methodology.Today, I’ll go through data.ai’s methodology and explain it as easy as possible. Both “download” and “store revenue” estimations are based on the rank history in the app stores (App Store / Google Play Store). Download Ranks of “Among Us!” in US (iOS)Download estimation in US (iOS)In the same way, data.ai estimates “store revenue” based on the trend of rank history. data.ai has stored more than 1 million first-party data from all over the world. (From data.ai ConnectPlus)As you can see, “Among Us!” ranked 26th in Oct 2023 (US). With both the global first-party data and rank history of “Among Us!”, data.ai is able to estimate its volume of downloads on a daily basis. In essence, this is how data.ai estimates “download” and “store revenue”. Take Note: data.ai has never used first-party data directly for each app’s estimated data on the UI and has always followed SEC compliance.
Hello data.ai Community,Our Support team took some time to put together a little article that tackles a question they frequently receive. If you have any further questions on this topic, feel free to comment below. Sometimes customers will try to compare Active User data from the “Compare” report with the “Usage” report, or API 1.3 and they will see a discrepancy in the numbers presented. Reports: Compare app Usage Report This is expected for the following reason: Root Cause:The “Compare” report does not include Tablets. On the bottom of the report you can see this message displayed: “Usage metrics for ‘all supported devices’ do NOT include tablets:” Now if you check this data on the “Usage” report and segregate by device, you will see that we take Tablets into consideration: In short, we have 5142 AU coming from tablets (which is not considered on the “Compare” report). Lastly, the “API 1.3” numbers take Tablets into consideration (so it will match the “Usage” report, but not the
In today's fast-paced world, time is an invaluable resource, and optimizing your workflow can significantly impact your productivity. Here are some valuable tips and techniques to help you work more efficiently and save precious time when conducting analyses with data.ai: 1.) Save your Reports:Rather than repeatedly configuring filters for the reports you frequently access, make use of the "Favorites" feature. This convenient option allows you to save all your selected filters, such as app groups, metrics, and date ranges, for quick and easy retrieval.To add a report to your favorites, simply click on the star icon located in the top right corner of the page. All your saved reports can then be accessed effortlessly from the main dropdown menu on the left. 2.) Custom Dashboards:Custom Dashboards provide a tailored solution for generating personalized reports and insights centered around your key performance indicators (KPIs). Once you've set up your dashboard, updating the date range is
In data.ai’s Insider Tips report, we outline just how vital Total App Revenue is for your app in our five Insider Tips.Learn everything from optimizing your ad networks to strategizing for your genre by digging into your competitor’s successes. And discover how two leading brands (Voodoo and Badoo) implemented winning monetization strategies based on ad revenue and IAP.Total App Revenue empowers you to identify the revenue streams making up the $500 billion mobile economy.Check out the latest report to see how you can anticipate your competitor’s monetization plan (before they do) – and your app can be more profitable than ever.
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