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Twitter Recap: Jeff Ma on Succeeding in Marketing with Data Analytics

Posted on Mon, Feb 6, 2017 @ 17:02 PM by Daniel James

Check out this Twitter recap of Jeff Ma's keynote from Symposium Scottsdale 2017 on using data and analytics to succeed in marketing!

Twitter Recap: Jeff Ma on Succeeding with Data Analytics

Symposium Scottsdale 2017 featured keynote speaker Jeff Ma, famous member of the MIT Blackjack Team that inspired Bringing Down the House and 21. Ma spoke to a packed room about the importance of analytics - from how to succeed with your data to the challenges you'll run into. We'll be posting a full recap on Wednesday, but since we live tweeted the keynote we'd like to give you those tweets!


Embrace Failure

Properly applying data to your affiliate strategies can be highly beneficial - advertisers can gain insights on campaigns and effective publishers, and publishers can evaluate what's working and what isn't. However, one key trend in 2017 will be using attribution data to get a better insight into your customer's path to purchase. This was a reoccurring theme throughout Symposium, and rightfully so - it will be crucial going forward. 

Learning How to be Data Driven



When learning how to be data driven, your goal is to reduce the edge of what you're going up against. In Ma's example, he discusses reducing the casino/dealer's edge in a game of blackjack, but you may think about this "edge" differently - it could be potential customers, or it could be potential visitors. Your goal is to get them to convert on a purchase, and the "edge" is everything that would cause them not to do that. By understanding what makes a customer make a purchase and what deters them, you can become more strategic with your affiliate efforts.





Jeff explains here two types of biases that occur and can cause problems - emotional bias and omission bias. Emotional bias has to do with making a decision that is driven, in part, by an emotional investment or attachment you may have to that choice. The problem with emotional bias is that when you're looking at a set of data, and the numbers are telling you one thing but you want the solution to be something else because of whatever your reason, you're making a bad decision. The other bias Jeff mentions at this time, omission bias, stems from feeling that an action you might be taking is bad, but not nearly as bad as doing nothing, so you decide on inaction rather than taking action. This is risky because it might mean "playing it safe" may not bring you the results you're hoping for. Ma notes that this is a game of "risk and reward" and you have to weigh the risk against the potential positive outcome. Data will help you properly weigh that option. 

Gut Decisions, Bill Belichick, and Cognitive Bias





Ma now explains how gut decisions and cognitive bias disrupts the opportunity to use data effectively. The idea of "going with your gut" over "going with your data" is a common one, and we can sometimes do this in our everyday lives without realizing it. However, Jeff explains that this is a bad idea because your data is already showing you the best solution - you just need to trust in your data. The example of Bill Belichick, the head coach of the New England Patriots, is brought up - if Belichick tells his team to make a risky play and the team succeeds, Belichick is heralded as a great coach. If, however, the team fails, the play is considered a failure and Belichick's coaching choice is questioned. Jeff notes, however, that a coach like Belichick isn't making these decisions blindly - he's using data-driven game plans to confidently make the risky play call. Even if the play doesn't work, the risk is reduced because of the data leveraged behind the choice. Cognitive bias is another problem - the idea that we need to agree with those around us or appease them with our decision can be a problem in itself. Letting people dictate your decisions can be problematic because not only do they not have access to the data you have, they may not see the potential rewards that you see.



Loss aversion, according to Ma, is one of the biggest challenges that cognitive bias can bring. We love to win, and we hate to lose. When faced with a situation where we could win, lose, or walk away, we're more likely to walk away because the idea of losing is much worse - especially if you've already won a little and consider yourself ahead. The problem is, even if the data says the reward is higher than the risk, many people will still avoid taking the risk because they don't want to lose out. 

5 Steps to Succeeding with Analytics


Ma presents a straightforward look at the path to success with analytics - start with your data, analyze what your data is telling you, and implement strategies based on that data. However, this is easier said than done, and Ma reviews five steps to success.


 These five steps outline the ways to make better decisions using your data, as well as avoiding the mentioned pitfalls. Those five steps are:

  1. Don't favor inaction over action
  2. Don't fear losing
  3. Focus on the big picture with long term goals
  4. Process overall results
  5. Stick with it!

For a full analysis/write-up of the keynote, check back on Wednesday! 

Tags: Affiliate Marketing, Symposium Scottsdale, Data Analytics

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