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I have some questions related to top charts.Q1: Data.ai shows the overall top charts which includes games & apps too. but on google playstore we can only see top charts with respect to games & apps separately. My questions is how data.ai collects such type of overall data.Q2: How does data.ai shows the top charts data on analyzing which KPI, how does other app stores rank app under what KPI.
Five-Part User Acquisition Strategy Series | 10 Minute Tips & TricksOn-Demand Webinar Series
Hello data.ai Community,We recently wrapped up our five-part, 10 Minute Tips & Tricks series on UA Strategies. Each session is available to watch on-demand here in the Community, so check them out below! If you’re looking for quick, value-packed data.ai tips to enhance your user acquisition strategy, then this webinar series is for you. And the best part is that each video is roughly ten minutes long! Feel free to ask any questions in the comment section per video. Part 1: Timeline TrendsIn order to get revenue, you need to get downloads, and in order to get downloads, you need to show why your app is worth downloading. This can be done via your app's icon, screenshots, and description. You want to make sure you control all of these for your app.But equally speaking, you want to be able to monitor how your competitors are controlling theirs. Because the moment those change, it can be an indicator of a much larger marketing campaign or product update that you want to get ahead of an
In my daily interactions with developers and publishers, one question that often comes up is: How can I quickly monitor what my competitors are doing? You may not be aware, but we have a very powerful feature on our platform that can perfectly address this issue. Let me introduce you to this feature. This feature is called Alerts and its entry point is very obvious, yet it is often overlooked by many. You can find its icon in the top right corner. Clicking on it will take you to the alerts creation interface, where you can monitor specific products or competitors, as well as noteworthy emerging products in the market. There is a lot of customization available here. For example, you can choose to receive an alert when a competitor's store icon changes, or when a specific publisher releases a new product or is in soft launch. Ultimately, these alerts will be sent to you in the form of emails or mobile push notifications (requires installation of the data.ai Pulse). If you want to make an
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, 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
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
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!
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
Have the SDK acccess and wondering what’s the best way to analyse the data? Here are 3 ways to run SDK analysis What are the top SDKs being used across different SDK types? Example - What are the top Ad Mediation SDKs based on app installsFrom Discover section, select the Top Apps → SDKsFrom the filters select the type of SDK followed Platform, Country, Category and Date Sort this by one of the 6 metrics available for your analysis Which apps have installed a specific SDK? Example - Which apps have installed the AdMob Mediation SDK into themEither from the Top SDKs report or by searching from the universal search bar on top select the specific SDK. From here, you can click on the SDK name hyperlink and then see the list of apps with the SDK and also filter this by country/category. The result will also show the Installed dates. Please note that the Top 1000 apps per country and/or per category & subcategory is what you can see here.Can I get the full list of apps that have a typ
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! We have another awesome customer story to share with you.This time, we’re highlighting Bigabid, a demand-side-platform (DSP) optimized for in-app advertising user acquisition and re-engagement. “We regularly leverage data.ai’s creative gallery to assess various approaches that are performing well across a wide variety of industries… As a result, we increased our creative production process by 20% in the last year.” - Yotam Galon, Director of Growth, Bigabid Key result:Efficiency Win: Increased creative production process by 20% in the last year with data.ai The world of programmatic advertising can be a little complicated for 'outsiders'. To make things simpler, Bigabid – a demand-side-platform (DSP) optimized for in-app advertising user acquisition and re-engagement – likes to describe itself as a type of investor.Here’s why: Clients (developers) give Bigabid money to invest. But instead of buying bonds or shares, Bigabid buys advertising slots. Like any in
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!
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
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
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.
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?
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 data.ai Community.We’re excited to share another amazing story about 3dot14! Who is 3dot14?3dot14 is a mobile first demand-side platform (DSP), helping marketers around the globe acquire high value users for their apps. Their machine learning technology enables them to drive user acquisition and retargeting at scale for clients, which includes the likes of Amazon, Gojek, Lazada, and Plarium Games. Key Results2x increase in leads per month since using data.ai Improved conversion rate by 50% with data.ai Intelligence Increased average revenue per advertiser by almost 60% When our team sat down with Afraz Naqvi, co-founder of 3dot14, he shared: "I created an alert that informs me whenever there is a spike in downloads in finance apps in India. We were able to onboard 50-70% more advertisers per month due to our proactiveness, which was a direct result of us setting up those alerts.” To watch the video, click here. ChallengesFrom the outset, 3dot14 utilized the free version of data.
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