AnDevCon - Tracking User Behavior Creatively
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This document discusses tracking user behavior within mobile applications using Google Analytics. It provides an overview of analytics and user tracking, and describes how Google Analytics can be implemented on Android applications. Key details include how Google Analytics collects and stores data on the device before transmitting it to Google's servers, and how common interaction types like pageviews, events, and ecommerce can be tracked. The document also discusses reporting features in Google Analytics like the Core Reporting API and different dimensions and metrics that can be queried.
![google_analytics_v2.db
Connection
™ Staging area for tracking data located on device
™ Next stop: Google Analytics servers
™ Command line access:
™ From platform-tools directory, open Android Debug
Bridge (adb)
™ adb -s emulator-5554 shell #example command
™ sqlite3 google_analytics[_v2].db
™ Begin issuing sqlite commands](https://image.slidesharecdn.com/trackinguserbehaviorcreatively-kiana-tennyson-130531085944-phpapp02/85/AnDevCon-Tracking-User-Behavior-Creatively-15-320.jpg){kind=tracking}
![The Query
™ Four required parameters:
™ ids (unique table id is “ga:[profile id]”)
™ start-date
™ end-date
™ metrics
™ Fifth strongly suggested parameter:
™ access_token – to get your full quota (OAuth 2.0)
™ Without access_token, miniscule quota for testing](https://image.slidesharecdn.com/trackinguserbehaviorcreatively-kiana-tennyson-130531085944-phpapp02/85/AnDevCon-Tracking-User-Behavior-Creatively-32-320.jpg){kind=tracking}
![What?
™ Know what your user is doing
™ By Individual – path tracking
™ By Demographic – event tracking, multi-channel funnels
™ Know what [else] they typically do
™ Most fundamental component of the User Story](https://image.slidesharecdn.com/trackinguserbehaviorcreatively-kiana-tennyson-130531085944-phpapp02/85/AnDevCon-Tracking-User-Behavior-Creatively-45-320.jpg){kind=tracking}
AnDevCon - Tracking User Behavior Creatively
- 1. Tracking User Behavior Creatively Kiana Tennyson AnDevCon V May 2013
- 2. Disclaimer: ™ IS a Feasibility Discussion ™ NOT an Ethics Discussion ™ NOT a Security Discussion ™ Don’t go to jail, get sued or end up defamed in Huffington Post.
- 3. What is Analytics? ™ Collection, analysis, reporting of internet data ™ Two categories – onsite and offsite ™ Two data collection methods ™ Log file analysis ™ Page tagging
- 4. What is User Tracking? ™ Logging characteristics about the the user and the user’s actions ™ More granular study than Web Analytics ™ Sticky subject! ™ Public apps… highest priority == user permission ™ Internal apps/corporate phones… different rules apply
- 5. Why do this? ™ Understand and optimize app usage ™ App assessment and improvement ™ Business drivers (cost effectiveness, profit increase) ™ Market research ™ Safety (parental controls, employee usage)
- 6. User Story ™ Web Analytics and User Tracking are meant to tell the story of our user(s)
- 7. Common Analytics Software SAAS ™ Google Analytics ™ Webtrends (paid) BYOH ™ Open Web Analytics ™ Piwik ™ SnowPlow ™ But…
- 8. Why not Analytics Sites? ™ No outsourcing ™ Extra needs/historical data ™ Company policy ™ Sensitive data
- 9. Open Web Analytics ™ Host your own database server J ™ Host your own analytics site ™ Open source; extend what you want ™ However: No Android client library… (contribute!) ™ Extras: ™ DomStream Tracking – tracks stream of mouse-oriented clicks (adapt to smartphone user interactions) ™ CrossDomain Tracking – tracks same visitor across different web domains
- 10. Google Analytics Platform Overview source: www.Google-Analytics.com
- 11. Google Analytics Workflow ™ Workflow (ga.js): 1. Browser requests page containing tracking code 2. _gaq array holding tracking commands created 3. GA source code is fetched and loaded 4. Commands on _gaq array executed, tracking obj built 5. Script element loaded to DOM 6. Tracking obj collects data (via gif request) 7. Gif request used for logging, data coll., post-processing
- 12. And on Android… ™ Same as conventional website tracking model ™ Web Property Id required ™ Four interaction types are tracked ™ EasyTracker library (v2) almost no dev effort L ™ Requires INTERNET and ACCESS_NETWORK_STATE permissions
- 13. GA for Android Workflow ™ Workflow: 1. tracker.trackEvent(…) called 2. event is put in localized SQLLite database on device as a “Hit” 3. At prescribed interval, dispatch occurs of collected data 4. tracker grabs “Hits” from local db 5. Sends them to NetworkDispatcher, which in turn posts an AsyncDispatchTask on a thread Handler 6. Handler sends hits over an HTTP connection via pipeLinedRequestor 7. When complete, callbacks are invoked, which sets a flag true indicating the dispatcher is reopened for business
- 15. google_analytics_v2.db Connection ™ Staging area for tracking data located on device ™ Next stop: Google Analytics servers ™ Command line access: ™ From platform-tools directory, open Android Debug Bridge (adb) ™ adb -s emulator-5554 shell #example command ™ sqlite3 google_analytics[_v2].db ™ Begin issuing sqlite commands
- 16. ™ sqlite> .tables #list all tables in the db ™ Most important table – events table ™ Columns: hit_id, hit_time, hit_url, hit_string ™ Data ™ 6! ™ |1350361553317! ™ |http://www.google-analytics.com/collect! ™ |v=1&ul=en- us&t=appview&sr=480x800&an=Kiana +ByProxy&a=0&tid=UA-35996923-1&aid=com.kt .kbp&cid=25c2e0bb07c4d6d&_u=.B&av=1.0&_v= ma1b3&cd=com.kt.kbp.flickr.FlickrActivity! google_analytics_v2.db The Table
- 17. Data Collection
- 18. Basic Interaction Types (Classic and Android) ™ Page View Tracking ™ Event Tracking ™ Ecommerce/Transaction Tracking ™ Custom Dimensions/Metrics ™ Timing, Social, Exception…
- 19. Pageview Tracking ™ Pageviews traditionally measure traffic volume to a site ™ Mobile apps don’t really contain web *pages* ™ App structure determines when a “page” is viewed ™ Multiple activity structure ™ Central activity, multiple fragments ™ Central activity, multiple layouts L ™ Any combo of the above ™ Simple line tracks a lot under the hood
- 20. public class TestPage extends Activity {! ! GoogleAnalyticsTracker tracker;! ! @Override! protected void onCreate(Bundle savedInstanceState) {! super.onCreate(savedInstanceState);! ! tracker = GoogleAnalyticsTracker.getInstance(); //singleton! tracker.startNewSession(“UA-XXXXX-YY”, this);! ! setContentView(R.layout.test_layout);! ! TextView helpLink = (TextView)findViewById(R.id.helpLink);! helpLink.setOnClickListener(new OnClickListener() {! ! @Override! public void onClick(View view) {! tracker.sendView(“/helpPage”);! Intent intent = new Intent(TestPage.this, HelpPage.class);! startActivity(intent);! }! }! }! }! Pageview Tracking
- 21. Event Tracking ™ Event tracking logs user interaction with the app ™ Button/link clicks, viewing a video, anything ™ Anything passed into GoogleAnalyticsTracker appears on the reporting interface (be consistent) ™ Category ™ Action ™ Label (opt) ™ Value (opt) ™ Category/Action pairs should be unique
- 22. public class VideoPage extends Activity {! ! GoogleAnalyticsTracker tracker;! ! @Override! protected void onCreate(Bundle savedInstanceState) {! super.onCreate(savedInstanceState);! ! tracker = GoogleAnalyticsTracker.getInstance(); //singleton! tracker.startNewSession(“UA-XXXXX-YY”, this);! ! setContentView(R.layout.test_layout);! ! TextView videoLink = (TextView)findViewById(R.id.videoLink);! videoLink.setOnClickListener(new OnClickListener() {! ! @Override! public void onClick(View view) {! tracker.sendEvent(“Videos”, “Play”, videoId, 0);! //initiate video playback! }! }! }! }! Event Tracking
- 23. Ecommerce Tracking ™ Track shopping carts and in-app purchases ™ Additional classes required to track transactions: ™ Transaction ™ Item ™ Process goes: 1. Create Transaction Object 2. Add Items to Transaction 3. Submit Transaction to Analytics Servers
- 24. public class PurchasePage extends Activity {! . . . ! ! public void onPurchaseConfirmed(Purchase purchase) {! ! Transaction transaction = ! new TransactionBuilder(purchase.getId(), ! purchase.getTotal());! ! transaction.setStoreName(Constants.STORE_NAME);! transaction.setShippingCost(purchase.getShippingCost());! transaction.setTotalTax(purchase.getTotalTax());! ! for(LineItem lineItem : purchase.getLineItems() {! !tracker.addItem(new ItemBuilder(! !purchase.getId(),! lineItem.getProductId,! lineItem.getCost(),! lineItem.getQuantity())! .build()); ! }! tracker.sendTransaction(transaction);! }! }! Ecommerce Tracking Step 1 Step 2 Step 3
- 25. Custom Dim/Metrics ™ Upgrade from Custom Variables ™ Three scopes (visitor, session, page) ™ Page-scoped vars overlaps Event Tracking functionality ™ 20 slots (can get weird… so keep a chart) ™ setCustomVar method ™ Defaults to Page scope ™ Does NOT send data like others, simply sets a variable
- 26. What Else to Track? ™ Track user’s touch order on the layout ™ OWA domstream tracking ™ Track user’s touch location on the screen ™ Set up clickable regions in layouts, perform event tracking onClick() ™ Track a user’s navigation session through your app
- 27. Reporting
- 28. External Data Integration ™ Compare brick and mortar shops with mobile traffic vicinity ™ Compare app activity to desktop site activity ™ Correlate high/low volume usage with external user statistics ™ Customize dashboards that include GA data
- 29. GA Reporting Framework Account Property Profile Report Profile Report Property Profile Report Report Property – website, blog, app Profile – A version of the property (Android, iOS, Blackberry) Query the profile tables via the Core Reporting API using the profile id
- 30. App Report Categories ™ Acquisitions ™ How your app is found/downloaded/installed ™ Users (who, where, when) ™ Info about people using your app and their devices ™ Engagement (what) ™ Ways people use your app ™ Outcomes (why) ™ Track targeted objectives with goals, ecommerce
- 31. Core Reporting API ™ Ability to export analytics data ™ Java, Obj-C, Ruby, among other client libraries ™ Data returned in JSON format ™ Paginated and compressed responses available ™ Daily limits to how much data returned
- 32. The Query ™ Four required parameters: ™ ids (unique table id is “ga:[profile id]”) ™ start-date ™ end-date ™ metrics ™ Fifth strongly suggested parameter: ™ access_token – to get your full quota (OAuth 2.0) ™ Without access_token, miniscule quota for testing
- 33. https://www.googleapis.com/analytics/v2.4/data ?ids=12345 &dimensions=ga:customVarValue5 &metrics=ga:visits &filters=ga:daysSinceLastVisit%3E%3D5 &start-date=2013-05-01 &end-date=2013-05-30 &max-results=50 (Where customVarValue5 == salesRepId) Select visits, customVarValue5 from 12345 where daysSinceLastVisit <= 5 and startDate => ‘2013-05-01’ and endDate <= ‘2013-05-30’ group by customVarValue5 limit 0, 50 Sample Query
- 34. Compared to SQL Additionally: Can sort by Metrics *and* Dimensions J Cannot query across profile-ids L GA Query Metrics Dim. Profile ID Filters SQL QuerySelect Col. Group By From (Table) Where
- 35. Dimensions/Metrics ™ Max 7 dimensions (per query) ™ Max 10 metrics (per query) ™ At least one metric is required ™ Not all combos are valid/make sense ™ What’s the difference? ™ Metric – a measurement of user activity ™ Dimension – groups metrics across commonalities
- 36. Metrics ™ Common ones ™ visitors ™ timeOnSite ™ organicSearches ™ adClicks ™ goal(N)Completions ™ Interesting ones ™ serverConnectionTime ™ domainLookupTime ™ redirectionTime ™ exceptions ™ uniqueSocialInteractions
- 37. Dimensions ™ Common ones ™ visitorType ™ campaign ™ city/metro/region ™ searchUsed ™ language ™ Interesting ones ™ customVarName(N) ™ mobileDeviceModel ™ hostname ™ nthMonth/Week/Day
- 38. Output ™ JSON response format ™ Client Libraries available ™ Java, Python, Objective-C, Javascript ™ Just use your favorite Json Parser Library
- 39. User Story
- 40. Who? ™ Know your user ™ By Individual – Corporate app that needs to track representative use in the field ™ By Demographic – Publically downloaded game catering to young males aged 9-13 ™ Know what you can store about them ™ Google Analytics policy expressly forbids: ™ (S)PII storage ™ Storing correlational data in 3rd party systems
- 41. PII and SPII (Sensitive) Personally Identifiable Information ™ Full Name ™ SSN ™ Driver’s License # ™ License Plate # ™ Birthplace ™ Credit card numbers ™ Digital Identity (gray area) ™ Date of Birth ™ IP Address (sometimes)
- 42. GA – Answering “Who” ™ All tracking calls intrinsically collect visitor information ™ Decide what to query for ™ ga:visitors ™ ga:visitorType (new or returning) ™ ga:source (indirectly related to user) ™ ga:userActivityUserHandle
- 43. User Tracking – “Who” ™ Secure.ANDROID_ID (Has limitations) ™ TelephonyManager ™ getSimSerialNumber() ™ getDeviceId() ™ Build.Serial (Good for tablets) ™ Company-assigned ID ™ The following could be logged to represent a user:
- 44. User Story
- 45. What? ™ Know what your user is doing ™ By Individual – path tracking ™ By Demographic – event tracking, multi-channel funnels ™ Know what [else] they typically do ™ Most fundamental component of the User Story
- 46. GA – Answering “What” ™ Data Collection – Event Tracking ™ Reporting – Engagement Report type ™ Querying for: ™ ga:pageViews, ga:timeOnPage ™ MultiChannel Funnels ™ Reports created from sequences of interactions leading to conversion or transaction
- 47. User Tracking – “What” ™ Logging app usage via Singletons or local db inserts ™ Strategy determined by UI ™ Multiple Activity Structure – activity lifecycle drawbacks ™ Single Activity/Multi Fragment – lifecycle benefits
- 48. User Story
- 49. When? ™ When is your user in your app? ™ Time of day, week, month, season ™ Focus marketing efforts ™ Just before app is needed ™ To drive higher usage rates during low swings ™ Push new features/content during or before high usage times
- 50. GA – Answering “When” ™ No metrics correlating time and user activity ™ Dimensions to query for actions around specified times do exist (ga:timeOnSite, ga:visitLength, ga:timeOnPage()) ™ Answer “when are users most likely to …?” ™ Use a page level custom variable ™ tracker.setCustomVar(s, “Time ItemPurchase”, ! ! !dateTime.toString(), 3) !
- 51. User Tracking – “When’’ ™ Log system time when user makes important action ™ Time zone issues – log in UTC ™ Log start/end of session ™ Depending on UI structure, determine “session times” ™ Submit data group when session is complete, or at end of dispatch period
- 52. User Story
- 53. Where? ™ Where does your user most utilize your app? ™ What states/cities/etc is your app most popular? ™ Concentrate marketing efforts in less popular areas ™ Proximity awards ™ Field reps in region/expanding regions ™ Apps with parental control features
- 54. GA – Answering “Where” ™ No metrics to correlate geolocation to activity ™ Dimensions exist; collected from IP Address during HTTP Requests ™ ga:continent down to ga:latitude/longitude, etc
- 55. User Tracking – “Where’’ ™ Log location with android.location package ™ Locations don’t come on demand ™ Request updates from Context.Location_Service ™ Define a LocationListener ready to receive/handle updates ™ Choose best algorithm for selecting location ™ Trade-off between killing user’s battery and accuracy ™ Once location received, hold on until ready to send with other tracking data
- 56. User Story
- 57. Why? ™ When users convert and complete goals, it is easy to answer “Why” ™ When users are NOT participating in goal conversion/ completion, ™ Focus research on pageViews ™ Focus on events occurring on the higher rated pageViews
- 58. GA – Answering “Why” ™ Subjective question; no concrete method to answer “Why” a user uses your app ™ Align app goals with with user’s actions ™ Accept your app’s purpose to the user to fully realize its potential
- 59. User Tracking – “Why’’ ™ Too subjective for User Tracking
- 60. Wrap Up ™ Mobile devices are quickly becoming one of the most commonly used personal computers ™ Understand the boundaries of user privacy ™ Protect our users; they keep us “in business” J
- 61. Questions?