About Lee Jacobson

Lee is a video game and entertainment executive and is currently the CEO of Apmetrix Inc., a global provider of next generation multi channel analytics for video game, mobile, digital media and virtual reality companies. His experience spans over 25 years with some of the most well know companies in gaming including Virgin Entertainment, Midway Games and Atari.

Bad Data

Apmetrix Blog - September 15th, 2016 | By: Lee Jacobson | Marketing

Bad Data

This months blog post focuses on the importance of understanding what data is useful and what is not.  Single channel metrics are no longer enough to understand your customers, and if you’re not careful and using the proper tools you may be making decisions with bad data.
bad-data
Data-driven is one of those flashy terms that corporations like to throw around during press conferences. You hear statements such as, “Our new data-driven culture will lead to a 12% increase in net profit.” When sentences like that get thrown around, one has to wonder if the speaker is the victim of bad data. While using big data to support business decisions is the new norm, and a survival requirement for doing business online, the way the term data-driven is used misses the boat in many ways.

For one, it implies that all decisions made before the age of big data were not driven by quantitative or qualitative information. This is obviously and patently untrue. Good businesses have always used data as a tool. More importantly, the term imbues data itself with mystical powers to transform a mediocre or failing business into a success. This misunderstands the nature of data, the limits of data, the reasons businesses succeed and the inevitability of bad data.

Even if you’re doing everything right, asking the important questions, focusing in on the relevant areas, none of this guarantees that the analytics are going to point in the right direction. The results are only as sound as the data you analyze. While most businesses assume that there will outlier data that needs to be ignored, fewer ever stop to wonder if there might be a more systemic problem with their data. Is there a flaw in how the data is collected? Is there information that we don’t have that might make this result look more or less cheery?

Take this as a hypothetical. A small software company gets a sudden influx of orders from New Zealand, where they’ve never sold anything before. The payments all clear and the software company executives think they’ve somehow opened up a new market. They begin marketing their software widely in Auckland, where most of the orders came from. Seems straightforward, right?

What the software company doesn’t realize is that all those orders came from employees of Company Q. For internal reasons, Company Q had employees purchase the software and reimbursed them for the costs afterward. What looked like dozens of discrete customers was really nothing more than a bulk license order from one customer. It was also an order with little chance of being repeated. The software company is likely wasting its marketing budget due to bad data, or at least incomplete data.

If the software company had been aware of the context, or asked the right questions during the purchasing process, it would have viewed the sales opportunities in New Zealand much less optimistically. Data-driven decisions can be good decisions, but they depend on the quality and completeness of the data itself. Assuming that becoming “data-driven” cures all problems is shortsighted and unrealistic.

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Apmetrix Blog - September 15th, 2016 | By: Lee Jacobson | Marketing

Bad Data

This months blog post focuses on the importance of understanding what data is useful and what is not.  Single channel metrics are no longer enough to understand your customers, and if you’re not careful and using the proper tools you may be making decisions with bad data.
bad-data
Data-driven is one of those flashy terms that corporations like to throw around during press conferences. You hear statements such as, “Our new data-driven culture will lead to a 12% increase in net profit.” When sentences like that get thrown around, one has to wonder if the speaker is the victim of bad data. While using big data to support business decisions is the new norm, and a survival requirement for doing business online, the way the term data-driven is used misses the boat in many ways.

For one, it implies that all decisions made before the age of big data were not driven by quantitative or qualitative information. This is obviously and patently untrue. Good businesses have always used data as a tool. More importantly, the term imbues data itself with mystical powers to transform a mediocre or failing business into a success. This misunderstands the nature of data, the limits of data, the reasons businesses succeed and the inevitability of bad data.

Even if you’re doing everything right, asking the important questions, focusing in on the relevant areas, none of this guarantees that the analytics are going to point in the right direction. The results are only as sound as the data you analyze. While most businesses assume that there will outlier data that needs to be ignored, fewer ever stop to wonder if there might be a more systemic problem with their data. Is there a flaw in how the data is collected? Is there information that we don’t have that might make this result look more or less cheery?

Take this as a hypothetical. A small software company gets a sudden influx of orders from New Zealand, where they’ve never sold anything before. The payments all clear and the software company executives think they’ve somehow opened up a new market. They begin marketing their software widely in Auckland, where most of the orders came from. Seems straightforward, right?

What the software company doesn’t realize is that all those orders came from employees of Company Q. For internal reasons, Company Q had employees purchase the software and reimbursed them for the costs afterward. What looked like dozens of discrete customers was really nothing more than a bulk license order from one customer. It was also an order with little chance of being repeated. The software company is likely wasting its marketing budget due to bad data, or at least incomplete data.

If the software company had been aware of the context, or asked the right questions during the purchasing process, it would have viewed the sales opportunities in New Zealand much less optimistically. Data-driven decisions can be good decisions, but they depend on the quality and completeness of the data itself. Assuming that becoming “data-driven” cures all problems is shortsighted and unrealistic.

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Stay up to date on the latest best practices and trends in entertainment analytics.



  • icon

    We're Tailored

    View data your way with our suite of powerful tools. Create your own custom reports with graphics, filters, colors, visualizations using our ‘drag and drop’ interface.

  • icon

    We're Contextual

    Our unique multi-channel analytics platform does way more than just show you how many times something happened, we show you why using advanced correlations.

  • icon

    We're Cross Platform

    View all your media, gaming, crash and marketing analytics in one place. View user behaviors across all your web, mobile, PC, game consoles and other devices..

  • icon

    We're Streamlined

    Save hundreds of man hours by automating all your data collection and focus on what really matters…your bottom line.

Augmented Reality – The Old Becomes New Again

Apmetrix Blog - July 7th, 2016 | By: Lee Jacobson | Marketing

Augmented Reality - The Old Becomes New Again

This months blog post focuses on another part of what seems to be an ever increasing amount of excitement concerning the VR movement, augmented reality.
vr-2
Several years ago, there was a lot of talk around augmented reality and what it would do for business. Yet, all that discussion never seemed to materialize into anything substantive. AR became yesterday’s buzzword and was apparently supplanted by beacons. While beacons are terribly useful, they aren’t nearly as slick in concept or offer the same potential benefits. If anything, they feel more like a middling step between the non-interactive consumer environments that were, and the augmented consumer environments that could be. So, was the idea always a dead end?

As it turns out, no. It was just a little premature. The necessary technology and infrastructure nominally existed, such as high-performance mobile devices, cloud computing and ordinary objects capable of networking, but they weren’t quite ready for mainstream deployment of AR. Consider new smash hit games like Pokemon GO which seemingly came out of nowhere to take the people (and many businesses who would in hind sight love to have been one of those “Pokestops”) by storm.  Mobile tech has made serious progress in the last 5 years in terms of processing power, such as multicore chips, without sacrificing precious battery life. Cloud computing has finally hit its stride in terms of mainstream acceptance, for which we probably all need to thank Apple and Amazon. Finally, people are less disturbed by the idea that their shirt or a can of soup can connect to a network.

While there is, no doubt, peer-reviewed sociological explanations for that last, it’s really been the missing piece from a business case. As consumer reliance on mobile devices to answer their questions has increased, and consumer ideas about qualifies as a valid networked object have broadened, the potential of AR has become a hot topic again. The smart device-dependent shopper is going to be much more interested now in getting that additional information AR can provide. Will the webcam on this quadcopter I’m looking at livestream to YouTube? Is the HD on this older video camera progressive or interlaced?

Yet, while delivering more on-the-spot information to customers is outstanding customer service, it isn’t necessarily valuable to the business. Throwing information out into the universe via AR without some mechanism for understanding the results is a lot like running a blog without ever checking the number of visitors. As with any other touchpoint with customers, you need to be able to derive actionable information from that interaction. What content draws the most views? Does that content correspond to purchases in that location? You need a system in place to run analytics on how customers interact with content you deliver. Without that, AR becomes just another black box operation that you dump time and money into without a way to measure your ROI.

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Apmetrix Blog - July 7th, 2016 | By: Lee Jacobson | Marketing

Augmented Reality - The Old Becomes New Again

This months blog post focuses on another part of what seems to be an ever increasing amount of excitement concerning the VR movement, augmented reality.
vr-2
Several years ago, there was a lot of talk around augmented reality and what it would do for business. Yet, all that discussion never seemed to materialize into anything substantive. AR became yesterday’s buzzword and was apparently supplanted by beacons. While beacons are terribly useful, they aren’t nearly as slick in concept or offer the same potential benefits. If anything, they feel more like a middling step between the non-interactive consumer environments that were, and the augmented consumer environments that could be. So, was the idea always a dead end?

As it turns out, no. It was just a little premature. The necessary technology and infrastructure nominally existed, such as high-performance mobile devices, cloud computing and ordinary objects capable of networking, but they weren’t quite ready for mainstream deployment of AR. Mobile tech has made serious progress in the last 5 years in terms of processing power, such as multicore chips, without sacrificing precious battery life. Cloud computing has finally hit its stride in terms of mainstream acceptance, for which we probably all need to thank Apple and Amazon. Finally, people are less disturbed by the idea that their shirt or a can of soup can connect to a network.

While there is, no doubt, peer-reviewed sociological explanations for that last, it’s really been the missing piece from a business case. As consumer reliance on mobile devices to answer their questions has increased, and consumer ideas about qualifies as a valid networked object have broadened, the potential of AR has become a hot topic again. The smart device-dependent shopper is going to be much more interested now in getting that additional information AR can provide. Will the webcam on this quadcopter I’m looking at livestream to YouTube? Is the HD on this older video camera progressive or interlaced?

Yet, while delivering more on-the-spot information to customers is outstanding customer service, it isn’t necessarily valuable to the business. Throwing information out into the universe via AR without some mechanism for understanding the results is a lot like running a blog without ever checking the number of visitors. As with any other touchpoint with customers, you need to be able to derive actionable information from that interaction. What content draws the most views? Does that content correspond to purchases in that location? You need a system in place to run analytics on how customers interact with content you deliver. Without that, AR becomes just another black box operation that you dump time and money into without a way to measure your ROI.

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Stay up to date on the latest best practices and trends in entertainment analytics.



  • icon

    We're Tailored

    View data your way with our suite of powerful tools. Create your own custom reports with graphics, filters, colors, visualizations using our ‘drag and drop’ interface.

  • icon

    We're Contextual

    Our unique multi-channel analytics platform does way more than just show you how many times something happened, we show you why using advanced correlations.

  • icon

    We're Cross Platform

    View all your media, gaming, crash and marketing analytics in one place. View user behaviors across all your web, mobile, PC, game consoles and other devices..

  • icon

    We're Streamlined

    Save hundreds of man hours by automating all your data collection and focus on what really matters…your bottom line.

It’s A Brave, New Virtual World

Apmetrix Blog - June 1st, 2016 | By: Lee Jacobson | Marketing

It’s A Brave, New (Virtual) World

This months blog post focuses on what no doubt will change our perception of what’s real in the future…virtual reality/augmented reality.
vr-2
For a very long time, virtual reality was the pipe dream of science fiction literature, movies and television shows. Here’s looking at you, Star Trek’s Holodeck. While we haven’t even come close to the 5-senses verisimilitude of that device, VR is becoming a reality. Google is in the game, and so is Microsoft. Sony has dumped piles of money into getting VR ready for its Playstation 4 platform. Facebook famously bought up the crowdfunded Oculus Rift. Rumor even has it that Apple is secretly building something VR, but such rumors always surround Apple. So, what does all this virtual investment mean for analytics?

It means that things are changing. If you’ve been paying attention to the social sentiment around VR, you know that customers are extremely excited about VR, whether it’s the Rift, Vive or Sony devices. VR headsets are going to create environments where your customers interact with virtual products. While you can plan on the big companies keeping most of the data they collect to themselves, customers will talk about their experiences on social media channels. You should be listening. What you may discover is that your business makes, or could easily could make, a real world analog to some imaginary product in a VR environment.

You also better believe that once these VR platforms get established, there will be opportunities to place ads, develop content, and engineer apps that work directly with those virtual environments. After all, Facebook doesn’t develop all those games people play on the website. Modding has become so ingrained in gaming communities it’s practically a rite of passage. However proprietary the technology is at first, advancements always become a collective effort of the companies, third-party content providers and the user base. As that happens with VR, you’ll be in a position to gather information from inside the environments, much as you currently get data via APIs from big companies.

However, just as the explosion of social media sites (and who wants to bet someone is already working on a VR-only social media site) created an explosion in data available to businesses, VR will do the same. Each unique device, and the games/experiences built around them, will generate data sets that you’ll have to be able to translate into actionable information. You need to be prepared with a scalable analytics program that will help you to streamline that process, but also one that will stay on top of integrating these new data sources as they become available.

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Stay up to date on the latest best practices and trends in entertainment analytics.



Apmetrix Blog - June 1st, 2016 | By: Lee Jacobson | Marketing

It’s A Brave, New (Virtual) World

This months blog post focuses on what no doubt will change our perception of what’s real in the future…virtual reality/augmented reality.
vr-2
For a very long time, virtual reality was the pipe dream of science fiction literature, movies and television shows. Here’s looking at you, Star Trek’s Holodeck. While we haven’t even come close to the 5-senses verisimilitude of that device, VR is becoming a reality. Google is in the game, and so is Microsoft. Sony has dumped piles of money into getting VR ready for its Playstation 4 platform. Facebook famously bought up the crowdfunded Oculus Rift. Rumor even has it that Apple is secretly building something VR, but such rumors always surround Apple. So, what does all this virtual investment mean for analytics?

It means that things are changing. If you’ve been paying attention to the social sentiment around VR, you know that customers are extremely excited about VR, whether it’s the Rift, Vive or Sony devices. VR headsets are going to create environments where your customers interact with virtual products. While you can plan on the big companies keeping most of the data they collect to themselves, customers will talk about their experiences on social media channels. You should be listening. What you may discover is that your business makes, or could easily could make, a real world analog to some imaginary product in a VR environment.

You also better believe that once these VR platforms get established, there will be opportunities to place ads, develop content, and engineer apps that work directly with those virtual environments. After all, Facebook doesn’t develop all those games people play on the website. Modding has become so ingrained in gaming communities it’s practically a rite of passage. However proprietary the technology is at first, advancements always become a collective effort of the companies, third-party content providers and the user base. As that happens with VR, you’ll be in a position to gather information from inside the environments, much as you currently get data via APIs from big companies.

However, just as the explosion of social media sites (and who wants to bet someone is already working on a VR-only social media site) created an explosion in data available to businesses, VR will do the same. Each unique device, and the games/experiences built around them, will generate data sets that you’ll have to be able to translate into actionable information. You need to be prepared with a scalable analytics program that will help you to streamline that process, but also one that will stay on top of integrating these new data sources as they become available.

Subscribe to our monthly newsletter!

Stay up to date on the latest best practices and trends in entertainment analytics.



  • icon

    We're Tailored

    View data your way with our suite of powerful tools. Create your own custom reports with graphics, filters, colors, visualizations using our ‘drag and drop’ interface.

  • icon

    We're Contextual

    Our unique multi-channel analytics platform does way more than just show you how many times something happened, we show you why using advanced correlations.

  • icon

    We're Cross Platform

    View all your media, gaming, crash and marketing analytics in one place. View user behaviors across all your web, mobile, PC, game consoles and other devices..

  • icon

    We're Streamlined

    Save hundreds of man hours by automating all your data collection and focus on what really matters…your bottom line.

Vote for Better Data

Apmetrix Blog - May 11th, 2016 | By: Courtney Escajeda | Marketing

Vote for Better Data

With election season squarely in our midst, it is important to consider the effect the changing political environment will have on your content’s performance.
elephant-and-donkey-2011-B
With election season squarely in our midst, it is important to consider the effect the changing political environment will have on your content’s performance. Will your fans continue to purchase every edition you release? Will they spring for the in-game purchases that make up an important part of your bottom line? Will they even be talking about you as much? These are all important questions to ask yourself as you face a shifting consumer market.

Historically, election years see much upheaval across many consumer markets. Sometimes the change is positive as some people see a ‘fresh’ political leader as a beacon for hope economically, socially, or whatever their particular concern might be. With increased political confidence, they begin to feel more confident financially and therefore are more active with their spending habits. On the other hand, the change can be similarly negative as people might view the newly elected leader as confirmation of the ‘country’s decline.’ As a result, they enter a ‘prepare for the worst’ state of mind and begin restricting their spending. Not only is this detrimental to your selling schedule (including new releases, in-app offers, etc.), it is especially concerning given that a decreased monetary flow between fan and brand means that they are less likely to engage with and promote your brand. If they aren’t experiencing the “latest and greatest” or buying that “$1 armor upgrade”, what will they have to talk about in the online forums that have increasingly become your brands PR lifeline?

While it is hard to predict exactly the projection of the consumer market during this election season, there are many different resources at your disposal to help protect your brand regardless the outcome. To begin with, it is very important to remain part of the conversation. With the public discourse consisting more and more of political/social/etc. issues throughout the year, it is important to make sure that you’re not left in the dust. Re-engaging your fans can be as simple as jumping in (or starting) social media conversations that are discussing your content. Not only do fans love when a favorite brand engages directly with them (thus getting them to talk more about you), but furthermore by adding to or directing the conversation you ensure it flows in a beneficial direction.

Similarly, by listening to what the general discourse is, you will get a better idea of the types of offers and push messaging language that might fare better amongst a generally concerned audience. Are people complaining about how a potential candidate will increase the average “cost of living”? You can offer them discounted or bundled in app offerings. Does your audience tweet about how “it doesn’t matter who is elected, no one listens to them anyways”? What better time to restructure your messaging to make it friendly and more personal (e.g. “We’ve listened to your feedback, that’s why we’ve added new gear options.”)

In general, highly targeted push notifications are an extremely useful way to get players reengaged and spending within your game. With all of the news stories and political updates coming out, your audience is likely to have their mobile device nearby giving you ample opportunity to reach out to them. Did a candidate just drop out causing a mass press frenzy? Your customer could have their phone in hand reading the news making it a perfect time to send them a nudge about new game features, upgrades, etc. It’s all about making sure your messaging is in the right place at the right time.

However you choose to stimulate your engagement and monetization strategies this election, it is critical that you stay diligent in doing so to ensure you don’t lose your fans’ attention. If you need help aggregating, correlating, and visualizing all of your data along the way, Apmetrix’s tailored solution makes it quick and easy. If only it was as easy to pick the best candidate….

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Apmetrix Blog - May 11th, 2016 | By: Courtney Escajeda | Marketing

Vote for Better Data

With election season squarely in our midst, it is important to consider the effect the changing political environment will have on your content’s performance.
ab-testing
In a previous post, “Actionable Analytics,” we discussed the difference between actionable analytics and vanity analytics. The core difference is that actionable analytics provide you with information you can use to do something to improve your business. Of course, the key problem is figuring out what constitutes an actionable analytic for your specific business. While understanding the nature of your business helps you to zero in on which analytics are crucial, testing provides the only viable way to determine this with certainty.

Yet, for reasons both practical and mysterious, businesses often shy away from performing tests with their readily available data. Some of the hesitancy presumably stems from a fear of resource drain. Essentially, “I can’t afford to have my employees running a/b split tests on Facebook ads because I need them doing things that contribute to the bottom line.” Without beating the dead horse too hard, dumping time, energy and money into any effort without a reasonable certainty it actually does contribute to the bottom line is suicidal for a business.

If you believe that driving traffic to your website from Facebook increases your ROI, test it. See if there is a correlation between boosting total visitors from Facebook and your total sales. If moving from 5,000 visitors from Facebook to 15,000 visitors a month doesn’t substantially boost your sales, driving traffic from Facebook isn’t profitable. Or, at the very least, you know you’re driving the wrong traffic from the social media giant. Without testing, you’re forced to guess about causation.

If your marketing people tell you that small changes in the language of online marketing content can improve sales performance of a given product, or even improve social sentiment, a blanket change to language is as dicey as doing nothing. With the existing language, you’re dealing with a known quantity and consumer response. With new language, anything could happen. Sales could spike or plummet or stay the same. The testing is where the pudding proves out or fails utterly.

While professional intuitions about customer reactions to a new product, new marketing language, and even new social media platforms shouldn’t be discounted, the technology to test it is available. Testing data is, in the long run, essential to the bottom line. Moreover, there is rapidly improving software that streamlines processing that data into something intelligible and testable. To give up those potential insights is to rob your business of the exact thing it needs to succeed: knowledge.

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Stay up to date on the latest best practices and trends in entertainment analytics.



  • icon

    We're Tailored

    View data your way with our suite of powerful tools. Create your own custom reports with graphics, filters, colors, visualizations using our ‘drag and drop’ interface.

  • icon

    We're Contextual

    Our unique multi-channel analytics platform does way more than just show you how many times something happened, we show you why using advanced correlations.

  • icon

    We're Cross Platform

    View all your media, gaming, crash and marketing analytics in one place. View user behaviors across all your web, mobile, PC, game consoles and other devices..

  • icon

    We're Streamlined

    Save hundreds of man hours by automating all your data collection and focus on what really matters…your bottom line.

Let There Be Tests

Apmetrix Blog - March 3rd, 2016 | By: Lee Jacobson | Marketing

Let There Be Tests!

This month we discuss the importance of multivariate testing and letting data drive your actionable strategy, not just intuition.
ab-testing
In a previous post, “Actionable Analytics,” we discussed the difference between actionable analytics and vanity analytics. The core difference is that actionable analytics provide you with information you can use to do something to improve your business. Of course, the key problem is figuring out what constitutes an actionable analytic for your specific business. While understanding the nature of your business helps you to zero in on which analytics are crucial, testing provides the only viable way to determine this with certainty.

Yet, for reasons both practical and mysterious, businesses often shy away from performing tests with their readily available data. Some of the hesitancy presumably stems from a fear of resource drain. Essentially, “I can’t afford to have my employees running a/b split tests on Facebook ads because I need them doing things that contribute to the bottom line.” Without beating the dead horse too hard, dumping time, energy and money into any effort without a reasonable certainty it actually does contribute to the bottom line is suicidal for a business.

If you believe that driving traffic to your website from Facebook increases your ROI, test it. See if there is a correlation between boosting total visitors from Facebook and your total sales. If moving from 5,000 visitors from Facebook to 15,000 visitors a month doesn’t substantially boost your sales, driving traffic from Facebook isn’t profitable. Or, at the very least, you know you’re driving the wrong traffic from the social media giant. Without testing, you’re forced to guess about causation.

If your marketing people tell you that small changes in the language of online marketing content can improve sales performance of a given product, or even improve social sentiment, a blanket change to language is as dicey as doing nothing. With the existing language, you’re dealing with a known quantity and consumer response. With new language, anything could happen. Sales could spike or plummet or stay the same. The testing is where the pudding proves out or fails utterly.

While professional intuitions about customer reactions to a new product, new marketing language, and even new social media platforms shouldn’t be discounted, the technology to test it is available. Testing data is, in the long run, essential to the bottom line. Moreover, there is rapidly improving software that streamlines processing that data into something intelligible and testable. To give up those potential insights is to rob your business of the exact thing it needs to succeed: knowledge.

Subscribe to our monthly newsletter!

Stay up to date on the latest best practices and trends in entertainment analytics.



Apmetrix Blog - March 3rd, 2016 | By: Lee Jacobson | Marketing

Let There Be Tests!

This month we discuss the importance of multivariate testing and letting data drive your actionable strategy, not just intuition.
ab-testing
In a previous post, “Actionable Analytics,” we discussed the difference between actionable analytics and vanity analytics. The core difference is that actionable analytics provide you with information you can use to do something to improve your business. Of course, the key problem is figuring out what constitutes an actionable analytic for your specific business. While understanding the nature of your business helps you to zero in on which analytics are crucial, testing provides the only viable way to determine this with certainty.

Yet, for reasons both practical and mysterious, businesses often shy away from performing tests with their readily available data. Some of the hesitancy presumably stems from a fear of resource drain. Essentially, “I can’t afford to have my employees running a/b split tests on Facebook ads because I need them doing things that contribute to the bottom line.” Without beating the dead horse too hard, dumping time, energy and money into any effort without a reasonable certainty it actually does contribute to the bottom line is suicidal for a business.

If you believe that driving traffic to your website from Facebook increases your ROI, test it. See if there is a correlation between boosting total visitors from Facebook and your total sales. If moving from 5,000 visitors from Facebook to 15,000 visitors a month doesn’t substantially boost your sales, driving traffic from Facebook isn’t profitable. Or, at the very least, you know you’re driving the wrong traffic from the social media giant. Without testing, you’re forced to guess about causation.

If your marketing people tell you that small changes in the language of online marketing content can improve sales performance of a given product, or even improve social sentiment, a blanket change to language is as dicey as doing nothing. With the existing language, you’re dealing with a known quantity and consumer response. With new language, anything could happen. Sales could spike or plummet or stay the same. The testing is where the pudding proves out or fails utterly.

While professional intuitions about customer reactions to a new product, new marketing language, and even new social media platforms shouldn’t be discounted, the technology to test it is available. Testing data is, in the long run, essential to the bottom line. Moreover, there is rapidly improving software that streamlines processing that data into something intelligible and testable. To give up those potential insights is to rob your business of the exact thing it needs to succeed: knowledge.

Subscribe to our monthly newsletter!

Stay up to date on the latest best practices and trends in entertainment analytics.



  • icon

    We're Tailored

    View data your way with our suite of powerful tools. Create your own custom reports with graphics, filters, colors, visualizations using our ‘drag and drop’ interface.

  • icon

    We're Contextual

    Our unique multi-channel analytics platform does way more than just show you how many times something happened, we show you why using advanced correlations.

  • icon

    We're Cross Platform

    View all your media, gaming, crash and marketing analytics in one place. View user behaviors across all your web, mobile, PC, game consoles and other devices..

  • icon

    We're Streamlined

    Save hundreds of man hours by automating all your data collection and focus on what really matters…your bottom line.

Results Versus Relevance

Apmetrix Blog - February 1, 2016 | By: Lee Jacobson | Marketing

Results Versus Relevance

This month we discuss the complexities in understanding complex data with regards to what’s relevant, rather than just showing simple results.
results
Business is a results-oriented field. While a Michael Porter might come along every once in a while and knock it out of the park with a philosophical treatise like “On Competition,” most businesses are concerned with what happens in the trenches. Did it sell? Are we making a profit? One area where this mindset doesn’t always serve a business well is analytics. Like any data-heavy field that relies on statistics, it’s beyond easy to show analytics “results” that have almost no relevance. Yet, what the business needs more than anything from its analytics is relevance.

A deeper stumbling block that drives the results versus relevance issue is a rational career-preservation instinct. Everybody knows, or at least believes, that delivering bad news is a good way to get fired. When you’re in sales and you aren’t moving the product, it’s hard to hide that fact. When you’re in analytics, you can cherry pick results that seem to show progress for a given project or product. An easy way to do this is by dumbing down the analytics. Instead of talking about the emotional tenor of responses for the product, business or brand, the analytics person can talk about the volume of engagement.

“Our brand is seeing significant attention on Twitter. 15,000 mentions in the last 48 hours. Thousands of comments on our Facebook page.”

That is a result without relevance. It sounds impressive. It sounds good. By avoiding substance – 14806 of the mentions and all of the comments burned the brand in effigy – the analytics person avoids the Wrath of Boss, at least temporarily. Of course, the truth will come out eventually, but the analytics person lives in hope that the blame will be shifted to anyone else. This tendency is even more pronounced when the person doing the analytics is nominally part of the team in charge of the failure.

An assistant in the marketing department may be analyzing the numbers, but not be in a position of authority in terms of the project itself. That person is doubly motivated to either make sure they aren’t delivering the news or to massage the bejeezus out of it before they report to the higher ups. As a “marketing person” they’re as likely to be lumped into the failure as the people actually responsible. Default response, report “results” and avoid “relevance.”

As a business owner, you’re in a tricky position. You either need to understand the math and the analytics well enough to spot the BS, or you need to help create a work environment in which employees don’t equate bad news with career suicide. Relevance, however bad, always helps your business. Fluff results never do. In the end, a culture of fearless analytics honesty is less work than constantly rechecking the math.

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Apmetrix Blog - January 22, 2016 | By: Lee Jacobson | Marketing

Results Versus Relevance

This month we discuss the complexities in understanding complex data with regards to what’s relevant, rather than just showing simple results.
results
Business is a results-oriented field. While a Michael Porter might come along every once in a while and knock it out of the park with a philosophical treatise like “On Competition,” most businesses are concerned with what happens in the trenches. Did it sell? Are we making a profit? One area where this mindset doesn’t always serve a business well is analytics. Like any data-heavy field that relies on statistics, it’s beyond easy to show analytics “results” that have almost no relevance. Yet, what the business needs more than anything from its analytics is relevance.

A deeper stumbling block that drives the results versus relevance issue is a rational career-preservation instinct. Everybody knows, or at least believes, that delivering bad news is a good way to get fired. When you’re in sales and you aren’t moving the product, it’s hard to hide that fact. When you’re in analytics, you can cherry pick results that seem to show progress for a given project or product. An easy way to do this is by dumbing down the analytics. Instead of talking about the emotional tenor of responses for the product, business or brand, the analytics person can talk about the volume of engagement.

“Our brand is seeing significant attention on Twitter. 15,000 mentions in the last 48 hours. Thousands of comments on our Facebook page.”

That is a result without relevance. It sounds impressive. It sounds good. By avoiding substance – 14806 of the mentions and all of the comments burned the brand in effigy – the analytics person avoids the Wrath of Boss, at least temporarily. Of course, the truth will come out eventually, but the analytics person lives in hope that the blame will be shifted to anyone else. This tendency is even more pronounced when the person doing the analytics is nominally part of the team in charge of the failure.

An assistant in the marketing department may be analyzing the numbers, but not be in a position of authority in terms of the project itself. That person is doubly motivated to either make sure they aren’t delivering the news or to massage the bejeezus out of it before they report to the higher ups. As a “marketing person” they’re as likely to be lumped into the failure as the people actually responsible. Default response, report “results” and avoid “relevance.”

As a business owner, you’re in a tricky position. You either need to understand the math and the analytics well enough to spot the BS, or you need to help create a work environment in which employees don’t equate bad news with career suicide. Relevance, however bad, always helps your business. Fluff results never do. In the end, a culture of fearless analytics honesty is less work than constantly rechecking the math.

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All Your Data Are Belong to Us

For video game fans of the early nineties, and Internet meme lovers ever since, the phrase “all your bases are belong to us” is legendary. It first appeared in a game called Zero Wing and stands as a testament to mistranslation. For many businesses, big data and analytics is a classic case of “all your bases are belong to us.” You know the data is out there. You also know you should be able to do something with it, because just about every business magazine and marketing expert alive tells you so. Yet, when you get your hands on the data, it leaves you scratching your head.

Volume is a big part of the problem. With the ever-expanding set of opportunities to gather ever more data, it’s painfully easy to lose the financially valuable trees through the nigh infinite data forest. Culling useful knowledge from that vast expanse of information requires a combination of sufficient processor resources, a viable analytics 2.0 program and a sense of what benefits your business. Without that combination of factors, you run a real risk of mistranslating your data.

Now, with any luck, you’ve got a good sense of what matters to your business and your staff knows what information they need from big data. Any good IT person can get you set up with the right technological infrastructure to process all that data, or you can sign on with a cloud-based analytics service that processes it for you. Where things get tricky is the software.

Just because an analytics 2.0 program can show you the data you’re interested in, doesn’t mean that it’s going to show you that data by default. Even with vendor assisted customization, analytics programs often lack an intuitive interface that lets you easily move from a big-picture view to drilling down into a highly selective data set. The less intuitive the program, the less “all your data are belong to you.” The data becomes the software’s hostage and you’re left in the unenviable role of hostage negotiator with your business success on the line.

What’s worse is that un-intuitive programs are likely to lead you to misread the end results of any given analytics function. Maybe you were looking for overall social sentiment about your new product and all you’re getting is social sentiment from Instagram. If you don’t catch that error immediately, it can be disastrous. Regardless of social sentiment on Instagram, you wind up with an incomplete and undoubtedly skewed view of social sentiment regarding your new product. Since you can’t avoid sanely big data and analytics are the inevitable end result of big data, you need to stack the deck in your favor where you can: the software. When you go to make that investment, be sure the software is intuitive to use not only for you, but for your staff as well.

Here, There Be Pirates!

The image of pirates on the open seas wielding cutlasses and swilling rum has certainly got a boost in recent years courtesy of Disney. Yet, the modern pirate sails a very different ocean: the digital ocean of the Internet. These pirates don’t steal gold, but your intellectual property. As most app developers know, the turnaround time from app release to hacked versions going up on pirate boards runs about 72 hours. If you’re like most app developers, you can almost hear the money being deposited in a pirate’s bank account.

Almost as bad as the inevitable financial loss is the faulty data that you get from those hacked apps. A wealth of data from users that never bothered to become paying customers provides limited utility value. In the end, all it tells you is what appeals most to people that don’t pay. Working from that data just means that your next app, or the improved release of the current app, will be even more appealing to non-paying base. This isn’t what anyone would call an ideal situation.

With limited recourse, developers tend to accept these as the harsh realities of app development and hope that enough people will pay to make it financially feasible to continue. A better situation is one where your analytics suite tells you what data comes from legitimately purchased apps and what comes from pirates. In that situation, you can kill two birds with a single stone.

The identification and removal of fraudulent data means that your analytics are reflecting the actual users you care about, namely the ones that pay. While the features or elements these users prefer might be identical to those preferred by people using hacked apps, you won’t know for sure until you filter the data. If there is a preference variance between paying and non-paying users, you can slant your next release to favor your paying user base. That doesn’t mean the new version won’t get hacked, because it almost certainly will, but it incentivizes paying users to recommend the app to like-minded others.

Of course, that still leaves the financial loss of all the non-paying users. If your analytics suite can identify non-paying users, it provides you a golden opportunity to help recoup your losses. You don’t need to just lie down and take it! You can feed those non-paying customers ads. You get compensated by the advertiser and get to annoy non-paying users. Win-win.

Hyperlocal, Proximity Beacons and You

Are you taking proximity beacons seriously? If not, you should be, because Apple is taking them seriously and so is Google, via the Android OS. Proximity beacons, or what they can do, provide businesses the chance to interact with customers not just on the local level, but the hyperlocal level. In other words, you can communicate with customers inside the building, department or even aisle.

The profitability in achieving that kind of personalization is, frankly, mind-boggling. A substantial portion of the smartphone-owning public, a constantly increasing number, is willing to tell you where they are in exchange for more relevant marketing or deals. Although not proximity sensor driven, this is the same conceptual model Groupon employs by providing city specific deals in its emails.

Take a grocery store, for example. Few retail environments are so plagued by the problem of choice paralysis. There are countless brands competing or trying to compete for consumer attention and dollars. Without some compelling reason to do otherwise — such as conscious cost-cutting or a reason to believe another product will perform better — most consumers opt for their normal brands. This decision or non-decision lets them avoid the choice paralysis of trying to figure out, on the spot, which of the dozen or so choices might best serve their needs.

Enter proximity beacons and hyperlocal marketing. If you want to move a particular product or set of products, proximity beacons can help provide your customers with a reason to choose a specific product. Instead of waiting for customers to “discover” a product on the shelf, every customer with the appropriate software on their phone can receive a coupon for a product on entering the store. If you want to help move secondary products, messages or coupons can be delivered in the aisles. The previous tendency to grab the familiar is now offset by an opportunity for novelty at a reduced cost; two things that are likely to drive sales.

The trick, of course, is to keep track of the information. It’s not enough to simply send the messages. How many people are receiving the messages? How many people are using them? This is where a robust analytics 2.0 package, such as Apmetrix, becomes invaluable. Not only can it import the data and give you a real-time view of what’s happening in the store, but it can also help you track social sentiment about the deals on social media.

Don’t Let Context Pass You By

By: Lee Jacobson, CEO – Apmetrix

Context can help organize the sometimes chaotic world of data into coherence. Take the following statement as a case in point: One man punches another man in the face. In the world of analytics, this would simply be reported as an instance of pure data. On the other hand, this statement as written leaves us confused. Why did the man punch the other man? Should we be horrified? Disappointed? Thrilled? If this action happened between two patrons in a bar, it can mean one thing. If it happened in a mixed martial arts match, it would mean something very different. Under the old model of analytics, we would translate this scenario by counting how many times someone gets punched in the face. In other words, we would record the number of occurrences for that specific action. Unfortunately, without context this approach only multiplies the amount of data you don’t know what do with.

To carry this metaphor just a little bit further, the function of analytics 2.0 is to provide you the context you need to understand whether to cheer or help pull a couple of guys apart. Let’s look at a different example. Say for instance that your metrics show an unusually high rate of cart abandonment in the last day. This high rate of cart abandonment also corresponds with a big uptick in chatter about your business on social media. If you aren’t looking too closely at the social sentiment (i.e. the context) of the chatter, you might read this as a win. There is social engagement about my brand!

When you finally set aside the volume of chatter to investigate the emotional tenor, you discover that your potential customers are actually vehemently complaining. Maybe you’ve got a glitch in your cart programming and customers are being overcharged on shipping? Perhaps it won’t let anyone using Firefox complete their transactions? In situations like this, context would alert you to the problem, make your data coherent, and better position you to take action.

Of course, if you’ve had twenty-four hours of lag time between the problem occurring and starting to resolve it, the damage is already done. The Internet world moves quickly and the loss of customer trust is nearly as fast when things go wrong. For your analytics to mean anything, they need to happen in real-time and cue you to social sentiment. Apmetrix builds and expands its analytics solutions with these exact concerns in mind. Whether it’s mobile, digital media, gaming, television or any entertainment solution we offer, Apmetrix has a scalable solution for your business.