One of my team members and I will be at CTIA next week. If anyone is going and would like to meet, please let me know.
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I am very proud to announce I will be speaking at MIT’s CDOIQ (Chief Data Officer and Information Quality) Symposium in July about how data affects your LTV projections, and ways to improve the quality of your metrics. It’s going to be a great conference and I would love to meet up with anyone who will be there.
Given the importance of analytics to social and mobile game companies (just see all my posts about LTV, performance marketing, virality, monetization, etc.), having the best business intelligence (BI) team is of central importance. Finding that talent, however, is not easy. I have been very lucky to work with some of the best BI talent throughout my career; they have made me look much smarter than I am. Not everyone will be as lucky as I have been. A recent article in the MIT Sloan Management Review provides great advice on predicting the performance of potential analysts.
The article points out that the ideal analyst does not exist; the job description is looking for a “unicorn.” You should not be hiring for a laundry list of skills (e.g., “I need someone with R, SWRVE and Mixpanel expertise”) because the game industry is evolving so quickly most of those skills will soon be outdated. Instead, you should look for the curiosity to keep learning, rather than the skills themselves.
The research discussed in the MIT article points to several traits that are crucial to finding great analysts:
- They have a cognitive “attitude” and will search for deeper knowledge about everything.
- They are driven to be creative and will want to create not only solutions, but also elegant solutions.
- They have a strong desire to “do things the right way,” and will encourage others to do the same.
- They have an extremely high sense of quality, standards, and detail orientation, often evaluating others by these same traits.
- They tend to be somewhat restrained and reticent in showing emotions, and may be less verbal at team or organizational meetings unless asked for input or if the topic is one of high importance from their perspective.
- They may take calculated, educated risks, but only after a thoughtful analysis of facts, data, and potential outcomes. They persuade others on the team by careful attention to detail, and through facts, data, and logic—not emotion.
Overall, when looking for members of your BI team, focus on their curiosity and creativity (also a good idea when hiring for any position); not their resume or existing skillset. Finally, do not put too much emphasis on the interview process. Analytic professionals are analytic by definition, and thus may not be charismatic or present well in an interview even though they have the traits you need. Moreover, an interview is only one small piece of data in the picture of a candidate; do not put too much emphasis on this single data point and look at the body of work.
Although identifying and leveraging influencers is one of the fundamental strategies in social media marketing, a recent article in the Harvard Business Review (“What Would Ashton Do – And Does it Matter” by Sinan Aral) shows it is not as simple as many think. For those not familiar with the term “Influencer,” it refers to someone who has significant influence with either a niche or the mass market due to social media presence. It could be someone with two million Twitter followers or somebody whose blog is read by virtually every doctor (and thus influences the medical community). There are third-party services, such as Klout, that create scores that attempt to show how much leverage somebody has in social media.
In social media marketing, the tactics often revolve around identifying influencers and getting them to promote your game or product. The belief is that if some of these influencers are promoting your game or product, you will hit a threshold at which everyone is talking about it (and playing it). Thus, every marketer’s top goal is to get Ashton Kutcher, who has 13.7 million twitter followers, to tweet about them.
One of the questions I am most often asked is how to raise capital in North Carolina (or some other place that does not have many venture capitalists [VCs]) or whether the company should just give up and move. Until recently, the only advice I could give was “Keep plugging away and once you get traction you will be more attractive to non-local investors.” But given the success—some would say dominance—of game companies outside the San Francisco area, I have a more positive outlook. A recent blog post by Mark Suster also does a great job of providing tactical advice on how to raise money if you are not located in a major VC area.
Suster’s suggestions
Suster, a serial entrepreneur who is now a partner at GRP Partners, provides a lot of practical suggestions that improve your chances of raising capital. Suster points out that yes, it is easier to raise money if you are in a major VC center (San Francisco, New York, LA or Boston), and if you do not have a strong tie to the local area it would be easier to raise capital if you relocate. That said, he pointed out that some great companies have raised large sums outside these regions and provided some very useful tips for doing so. Continue Reading…
Below is a presentation that I gave yesterday on lifetime value (LTV) to the portfolio companies of YetiZen. It covers the importance of LTV, key variables (monetization, virality and retention) and how to affect them, importance outside gaming, cohort analysis and the predictive nature of LTV. Other than the final section on uncertainty, which echoes my blog post on Tuesday, the presentation is largely consistent with the one posted earlier that I gave at Groundwork Labs a few months ago. Here is the one from last night:
The key to using customer lifetime value (LTV) effectively is the understanding that it is a prediction, not a value. In my previous eight posts on LTV, I stressed the importance of LTV to the success of your game and company and the key components in determining LTV. After reading Nate Silver’s The Signal and the Noise, I realized that it is crucial to understand that LTV is a prediction and suffers the same risk as other predictions (e.g., elections, weather, sports scores).
The Uncertainty Principle
Many people mistakenly believe (and I may have inadvertently implied this in a previous post), that LTV is an exact function of virality, monetization and retention. It implies you put those variables into a formula and get out a number that shows precisely how much a player is worth. That would be the case if you did it with historical information after five years and then calculated how much that player had been worth to you. However, you are calculating how much the player will be worth, which is inherently different because you are predicting their future value.
The uncertainty principle, a key tenet of quantum mechanics (as popularized by Stephen Hawking), postulates that perfect predictions are impossible if the universe itself is random. Since you cannot have a perfect prediction, your LTV cannot be a distinctly quantified value. You are predicting future events (how much the player will monetize, how viral they will be and how long they will stay in your game) based on the available data. Your LTV model is a simplification of the world the player is in; you are looking at several variables but you cannot look at everything (e.g., chance of war, plague, everyone switching to Blackberry devices). In effect, your LTV calculation is very similar to a sportscaster’s estimate of how many home runs Albert Pujols will hit or a weatherman’s prediction on the likelihood of a hurricane to hit Cape Hatteras. Continue Reading…
I've spent the last two years learning everything I can about "growth hacking." I co-run the Growth Hackers Conference with Erin Turner, led efforts to build Udemy's user base, and consulted/advised companies like Lyft, Wedding Party, TenderTree and Sokikom. Over that time, I've worked with some amazing marketers. Recently, we've been discussing a new "formula" for growth hacking that has helped us achieve extraordinary results.
Great article about the importance of thinking about your customer when growing your product.
I recently read a column by Robert Eckert, the former CEO of Mattel who engineered its turnaround, and he highlighted two words that were crucial to his success leading the company. Although not as cool or trendy as some of the other topics I have discussed in this blog, looking at my own successes I realize these two words are as important or more important than many of the strategies I evangelize. Those words are Thank You. Continue Reading…
A recent Harvard Business review post by John Coleman about “old-school” business practices worth bringing back highlighted several traditional office habits that still improve productivity.While I love posting about the cool new trends (growth vs marketing , lifetime value-driven ad spending, etc.) that can have a huge impact on your business, I agree with Coleman that you shouldn’t abandon everything from business pre-2005. The four suggestions from Coleman’s post that I most agree with (he had five but I was not sold on one of them) are:
- Make meetings distraction free. This to me is the most important practice Coleman highlights, and it’s not necessarily “old school.” Meetings are not as productive if half (or even one) attendee is looking at their phone or playing with their laptop. Getting rid of these distractions make meetings more focused and productive. Although those using their devices may be doing something productive, if they have something more important to do they should not be in the meeting in the first place. (This brings to mind another good practice: make sure everyone in a meeting needs to be there.) Continue Reading…
