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Data-Driven Design. You’ve got the data, so, now what? - Aaron Huang - Kontagent
 

Data-Driven Design. You’ve got the data, so, now what? - Aaron Huang - Kontagent

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Now that you have the data, what's the plan? Using customer data to understand and optimize your social or mobile game can produce huge returns. But, there are also dangers of relying too heavily on ...

Now that you have the data, what's the plan? Using customer data to understand and optimize your social or mobile game can produce huge returns. But, there are also dangers of relying too heavily on data without the proper level of controls, data science and overall process. Fortunately, there are now tools, technology and talent available in the market that are enabling forces for studios who want to be more data-driven. This session will analyze what it takes to become a data-driven organization, and look at some lessons learned from our experience working with some of the top grossing social and mobile game studios.

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  • Why is data becoming more and more important? Big Box stores, believe it or not, have pioneered innovation in Big Data, around looking at data and creating and optimizing customer experiences. Today, that data is available like never before in social and mobile. The app ecosystem is exploding. But, you need to not only have the right infrastructure, but the right mindset. I’m going to walk through how to create that mindset today, and why it’s so important to lay the groundwork with your organization to use data from day 1 to drive decisions. (INTRO to 3 Panelists)
  • So – how prepared are you to create a data-driven culture?
  • No need to get too creative on these slides, maybe just a different background image on each of the following 6 slides. We can discuss.
  • You go in the direction your skis point, just like data. You need those metrics that you can focus and rally your business around to go in the right direction.
  • Skiers responsibility code To fully exploit the opportunity presented by big data, a value chain must be created that helps address the challenges of acquiring data, evaluating its value, distilling it, building models both manually and automatically, analyzing the data, creating applications, and changing business processes based on what is discovered. “Organizations have to figure out a way to increase analytical capacity, not just raw storage capacity.” - IBM's AnjulBhambhri
  • Kontagent wrote the ‘book’ on this topic…Best practices can be bubbled up through rigorous data science. Come ask me about getting a copy of this 
  • Make sure your entire organization agrees and rallies on one set of data and metrics. Your marketing team’s ARPU is the same ARPU your developers and executives see. Make sure anyone in your organization can ACCESS the data – if engineers have to extract all the data, you can get data that is stale or worse yet, you don’t get all the data you need in a world of priorities between core development and analyzing your data.
  • Case study that is relevant to the synchronicity slide… - Added a new screenshot - Deleted bullet points (will just speak to them) - Animate the boxes in, with one second delay in between each (no click required) - Obviously my design stinks, so please do your magic! thanksSpeaking points (magda, disregard)Was there a drop-off at some popular stage in the game?Was the virtual economy balance off-kilter?Was the game loading slowly?Which marketing channels were producing the less engaged users?How do we measure and optimize all of the relevant levers that affect retention?
  • Case study that is relevant to the synchronicity slide… - Added a new screenshot - Deleted bullet points (will just speak to them) - Animate the boxes in, with one second delay in between each (no click required) - Obviously my design stinks, so please do your magic! thanksSpeaking points (magda, disregard)Was there a drop-off at some popular stage in the game?Was the virtual economy balance off-kilter?Was the game loading slowly?Which marketing channels were producing the less engaged users?How do we measure and optimize all of the relevant levers that affect retention?
  • Case study that is relevant to the synchronicity slide… - Added a new screenshot - Deleted bullet points (will just speak to them) - Animate the boxes in, with one second delay in between each (no click required) - Obviously my design stinks, so please do your magic! thanksSpeaking points (magda, disregard)Was there a drop-off at some popular stage in the game?Was the virtual economy balance off-kilter?Was the game loading slowly?Which marketing channels were producing the less engaged users?How do we measure and optimize all of the relevant levers that affect retention?
  • Case study that is relevant to the synchronicity slide… - Added a new screenshot - Deleted bullet points (will just speak to them) - Animate the boxes in, with one second delay in between each (no click required) - Obviously my design stinks, so please do your magic! thanksSpeaking points (magda, disregard)Was there a drop-off at some popular stage in the game?Was the virtual economy balance off-kilter?Was the game loading slowly?Which marketing channels were producing the less engaged users?How do we measure and optimize all of the relevant levers that affect retention?
  • You don’t need to be a rockstar data ninja, but you do need the talent. Technical and data-driven marketers, developers, product managers and executives. You need to speak the language, and ensure you have the right interpreter to make sure you’re communicating effectively across your organization. You need an internal ‘change agent’ in house to bend the ear of executives to rally development resources and IT around the data. A true data scientist should go above and beyond stats and math to champion new sources of ideas from data.
  • It all depends on your business strategy, but a few key considerations  With companies getting leaner and time-to-market becoming faster, it’s making more and more sense for new companies in the app space to look to third party solutions to get out the door faster.Don’t look just at the sunk cost of building the maintaining the infrastructure and hiring the right people, but factor in the opportunity costs of employee churn and maintenance costs that fall outside core development.
  • If you’re looking at the wrong metric, or the wrong set of metrics, your strategy could be led astray. You need to ensure you’re looking at the right metrics at the right lifecycle of your app. We’ll talk about this more in a bit…
  • Make sure you can see the entire picture.
  • Needs better design.
  • You’ve built a game, but need to prove there is a market for it, and determine what your scaling potential is. This is step number one in the data-driven design cycle.Key Question  Am I trending in the right direction in comparable industry benchmarks to give this app a reasonable shot?How should I segment my marketing campaigns to get visibility into different groups of users?Which regions should I target / test? By Marketing Channel: Which user segmentsAre the most influential?Are the most engaged? Are the most avid? Are the highest monetizing? ARM metrics to focus on in this stage: - CAC - 1-day retention - 7-day retention - Avg. Session Length
  • OK, congratulations, you’ve proven you’ve got a game that can monetize, now it’s time to rev up acquisition efforts. Presumably you know what types of marketing you need to do to generate high quantity installs…but how about quality? Can you get people engaged? How well can you monetize? Here are some key questions to be asking at this stage:Who are my most engaged users? What is the behavior of my paying vs. non-paying users?What is the behavior of my new vs. returning users? What are the critical chokepoints in my app I need to unblock? What user cohorts are the most engaged and influential? How can I get more users deeper into the app where they will start monetizing?What game mechanics can I test to increase virality, engagement and retention?
  • This is the HARVEST stage…Your game is monetizing efficiently, you’ve figured out the “system” and you want to keep it going as long as possible. It’s been fairly well proven that every game has a shelf-life on Facebook and other social networks…it’s the good ones that demand high engagement and strong monetization that last the longest.Big questions and learnings in this stage include:What is the behavior of my paying vs. non-paying users?What is the LTV of my users by different cohorts? When do my users start monetizing? How can I keep my paying users engaged and happy? How can I optimize my basket of virtual goods?How can I optimize the prices of my virtual goods? What is the behavior of my users over their entire lifetime? When is it time to start developing another game? What kind of game should I develop next?

Data-Driven Design. You’ve got the data, so, now what? - Aaron Huang - Kontagent Data-Driven Design. You’ve got the data, so, now what? - Aaron Huang - Kontagent Presentation Transcript

  • AARON HUANG, Head of Product Marketing
  • 0 6BEGINNER DATA-DRIVEN
  • Data-Driven Development:A Phase Based Approach Collect Build Beta Launch and Audien Testing Phase Maintai ce n Acquire X X X Engage X X X > Monetize (and mobile) X 6
  • CASE STUDY: ExecAlign Marketing, Product, Design & DevelopmentWhat is the Issue?Day 1 Retention isDropping Retention is trending down!
  • Product Mgmt/CASE STUDY: DeveloperAlign Marketing, Product, Design & DevelopmentWhere is the Issue?New incoming users from a new marketing sourceareNOT completing the tutorial at a rate comparable toexisting players. Tutorial completions: Tutorial completions: existing players new players
  • CASE STUDY: Product Mgmt/Align Marketing, Product, Design & Development DeveloperIsolate and optimize. 1. Funnel analysis and drop-off optimization on the tutorial. Increase tutorial completion rate for new Optimize Drop-off %’s players to increase retention
  • CASE STUDY: MarketerAlign Marketing, Product, Design & DevelopmentIsolate and optimize.2. Decrease or Eliminate spend onthe new marketing channel
  • CASE STUDY: Find the ‘Sweet Spot’ to maximizeA FALSE POSITIVE revenue and profit % Paying Users is Trending Up… But ARPU & ARPPU is trending down…!
  • 6
  • DATA-DRIVEN DEVELOPMENT:A Phase Based Approach X X X X X X X 6
  • DATA-DRIVEN DEVELOPMENT:A Phase Based Approach 6
  • DATA-DRIVEN DEVELOPMENT:A Phase Based Approach X X X X X X X 6
  • DATA-DRIVEN DEVELOPMENT:A Phase Based Approach 6
  • EXPERTISE:We Help You On Your Roadmap to Success X X X X X X X 6
  • DATA-DRIVEN DEVELOPMENT:A Phase Based Approach 6