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Whom the Gods Would Destroy, They First Give Real-time Analytics

186 points by chrisdinn 14y ago

ChuckMcM 14y ago
Nice post. Ops guys though, like to see the bushes rustling right away so that we can reboot that switch before all hell breaks loose :-) The central theme is a good one though, tactics or strategies have an innate timeline associated with them, and deciding on tactics or strategies with data that doesn't have a similar timeline leads to poor decisions. The coin flip example in the article is a great one. Ideally one could say "What is the shortest interval of coin flips I can measure to 'accurately' determine a fair coin?" And realize that accuracy asymptotically approaches 100%. One of the things that separate experienced people from inexperienced ones are having lived through a number of these 'collect-analyze-decide' cycles and getting a feel for how much data is enough.
- btilly 14y ago
  One of the things that separate experienced people from inexperienced ones are having lived through a number of these 'collect-analyze-decide' cycles and getting a feel for how much data is enough. If you're going off of "feel" instead of statistics then you're doing it wrong. Period.
  - Tyr42 14y ago
    You can build a mathematical intuition. This is a valid thing. You just know how to dig down and prove you are right if asked, so it's ok to leave out details.
  - ChuckMcM 14y ago
    Of course you are, my comment was that when you are presented with a decision and the data that was collected and analyzed that went into it, if you've seen a few of these you are much better at catching problems. If you are the one doing the collecting and analyzing and you just think it feels like enough data but you can't actually reason to that point, then yes, you are doing it wrong.
  - Karunamon 14y ago
    >If you're going off of "feel" instead of statistics then you're doing it wrong. Period. I disagree, at least to a point. Take an experienced Operations/monitoring guy who's been around the block more than once, then sit him in front of the monitoring utilities for a new company developing a new service. Then, take a total newbie and put him in the same place. Train them both to equal skill on your tools and operations. Who do you think will make the most proper calls? Why? At this point, those statistics and that documentation do not exist yet. What constitutes a "false positive" vs a "drop everything and spin up more VMs and get on the load balancer" can be more of an art than a science, especially when you're first starting out. As hokey as this sounds, certain systems have a "personality" that varies between installations and companies, that nothing short of day to day use will educate one in.
    - btilly 14y ago
      For operations, I agree. A lot of the numbers you have don't have a rigorous statistical interpretation - for instance is a load average of 20 fine or a problem? Depends if you're looking at the Oracle database. But the original article was talking about A/B testing, and that is the context that I was thinking about. There you both can and should use statistics.
  - cftm 14y ago
    There's a lot of intuition and experience that is required to be a talented statistician; once the test has begun things are pretty much locked down (ie, if you know the math there is only one "right" answer from the data). The intuition and experience side of things comes with how the test itself is setup. Are things properly controlled, are you collecting the right data for what you're testing, is the data distributed properly for the test statistic you're using...the list goes on and on and on and on and on. There are plenty of places that require intuition and these are the places that errors are often introduced. Statistics is an art.
  - frozenport 14y ago
    I always thought statistics existed to give you the "feel". Statistics of more statistics is nonsense!
  - danenania 14y ago
    It's possible (though deceptively difficult) to train one's statistical intuitions to be pretty accurate, or at least accurate enough to give them a positive EV. I was a professional poker player for several years, and this is what becoming a strong player is all about.
- ajdecon 14y ago
  > Nice post. Ops guys though, like to see the bushes rustling right away so that we can reboot that switch before all hell breaks loose :-) I don't think you're disagreeing with the article. He shows a real-time dashboard of ops stats, and then says: > It's important to divorce the concepts of operational metrics and product analytics. Real-time ops statistics help solve ops crises, but product analytics can afford a little more consideration.
  - ProblemFactory 14y ago
    > It's important to divorce the concepts of operational metrics and product analytics. I don't think operational and product analytics are different in principle. In both cases, the best speed for analytics matches the speed of taking action on the results. In ops, there are people whose very job is to respond to a server crash in 2 minutes. In product design, there are no actions taken within minutes of seeing the change in data - so faster analytics just wastes time on refresh-procrastination, and encourages needlessly hasty decisions.
josh2600 14y ago
This is a really interesting post. While I agree with the basic premise that Real-time analytics are rarely helpful, here are a couple places where they could be very useful: * Conferences - Being able to see live user analytics on a conference site, since it is ephemeral, would be great. * Pop-up Sites - Again, the short nature of the site means seeing a blocking action or a broken link early is tremendously valuable. Basically there are a couple circumstances where real-time analytics might make sense, but they're generally short duration engagements. Getting analytics info for a site which is no longer being hammered is useless unless it's a long term project.
- josephlord 14y ago
  What action will the conference take based on any immediate information or do you mean the information will go on the site? Broken links etc. is probably in the operational category although a validator is a better solution for that issue. Logging errors and maybe tracking accesses to ensure every page is being reached can be done by realtime operational stats and doesn't contradict this article.
  - josh2600 14y ago
    So think of conferences where there's a site up for one day. If one wants users to clickthru to a particular page, but they're all going elsewhere, that's something that's only actionable on the day of the event (as changing it 12 or 24 hours later does one little good). I see your point about not contradicting the article, but I think there are instances where evaluating the performance of a website in real time (for time-sensitive events) could have a real impact. I don't think we're disagreeing so much as talking about the same point from different angles.
physcab 14y ago
I like this rant. Seldom do I see the need for a real-time system and sometimes I think engineers and program managers gravitate towards the concept to better answer questions of "why" a problem happens. But analytics problems most of the time can't be solved in real time. You have to put on your thinking cap, take a step back, do some background research, and be patient. And as an analyst it is bad for your credibility to jump to conclusions. Unlike engineering, it better to be slow and right on your first try than "move fast and break things".
sardonicbryan 14y ago
So I built and use a realtime analytics dashboard that tracks revenue, projected revenue, revenue by hour for a portfolio of social games. I find it incredibly useful, but I will give a couple tips that address some of the issues in the article: 1) You have to provide context for everything. Current real time revenue is presented right next to the 14 day average revenue up to that point in time, and also how many standard deviations the delta between the two is. Ie: Current revenue is $100 at 10am, vs. 14 day average of $90, which is 0.2 standard deviations of revenue at that time. 2) Hourly revenue is presented the same way, right next to the 14 day average revenue for that hour and the SD delta. 3) Look at it a lot. I've been looking at this sheet regularly for over a year now, and I have a really good feel/instinct for what a normal revenue swing is, and an even better feel for the impact of different features/content/events/promotions on our revenue. 4) This approach also works better when the impact of your releases is high. A big release typically spikes revenue 2-3 SD above baseline, and causes an immediate and highly visible effect. So while I'm not strictly testing for statistical significance, it's one of those things where it's pretty obvious. 5) It also works better if you use it in conjunction with other metrics. We validate insights/intuitions gained from looking at realtime data against weekly cohorted metrics for the last several months of cohorts.
- ProblemFactory 14y ago
  While this sounds very cool, and my inner geek would love this dashboard on the wall of the office - is it actually useful or is it a distraction? What actions or decisions would you make within minutes of seeing the results? If product changes take days or weeks, daily analytics is just as useful, and stops people wasting time on looking at the data more than once per day.
  - rossjudson 14y ago
    This is precisely the right point. We look at an analytic display to determine if action should be taken, and what those actions should be. The vast majority of "big data" is noise, more than effectively summarized with basic statistics.
  - sardonicbryan 14y ago
SparrowOS 14y ago
God says... 21:7 And they asked him, saying, Master, but when shall these things be? and what sign will there be when these things shall come to pass? 21:8 And he said, Take heed that ye be not deceived: for many shall come in my name, saying, I am Christ; and the time draweth near: go ye not therefore after them. 21:9 But when ye shall hear of wars and commotions, be not terrified: for these things must first come to pass; but the end is not by and by. 21:10 Then said he unto them, Nation shall rise against nation, and kingdom against kingdom: 21:11 And great earthquakes shall be in divers places, and famines, and pestilences; and fearful sights and great signs shall there be from heaven. 21:12 But before all these, they shall lay their hands on you, and persecute you, delivering you up to the synagogues, and into prisons, being brought before kings and rulers for my name's sake. ---- How's your seismograph?
btilly 14y ago
Gah, yet another article that links to Evan Miller's article on how to not run an A/B test. I really need to finish writing my article that explains why it is wrong, and how you can do better without such artificial restrictions. His math is right, but the logic misses a basic fact. In A/B testing nobody cares if you draw a conclusion when there is really no difference, because that is a bad decision that costs no money. What people properly should care about is drawing the wrong conclusion when there is a real difference. But if there is a significant difference, only for small samples sizes is there a realistic chance of drawing a wrong conclusion, and after that the only question is whether the bias has been strong enough to make the statistical conclusion right. He also is using 95% confidence as a cut-off. Don't do that. You don't need much more data to massively increase the confidence level, and so if the cost of collecting it is not prohibitive you absolutely should go ahead and do that. Particularly if you're tracking multiple statistics. If you test regularly those 5% chances of error add up fast.
- joshuacc 14y ago
  I would love to read your article when you finish the writing. It sounds very interesting!
- RyanZAG 14y ago
  No analysis of AB testing should ever miss this incredibly important fact about statistics. http://xkcd.com/882/ http://xkcd.com/882/ When you make confidence tests on a continuous process, you will hit this 1 day in 100 on average for 100 days of testing at 99%. If you're doing multiple AB tests per day, well... EDIT: And another important issue: if you are testing on Valentines day and the pink color/A test is beating out the orange color/B test, then this result may only happen on that one day per year. This applies to hot news topics and numerous other fads as well. Also make sure your tests really are independent - if you do A/B testing off of fixed IP address hashing and have a small user base, by random chance you may have your top customer always being in 'group A' and giving group A a higher than expected base average - an extra bonus click for every group A test may skew your statistical tests as they assume independence.
  - 14y ago
lmkg 14y ago
Full-time web analyst here. Total agreement. Information is as useful as your ability to act on it--no more, no less. Real-time analytics is something that sounds sexy and gets a lot of headlines (and probably sales), but it's not particularly useful, especially compared to the cost to implement. Most organizations aren't capable of executing quick decisions of any significance. In fact, quite a few business models wouldn't have much to gain even if they were capable of it. My experience is that there are three types of companies, with very little overlap: 1. Companies large enough to receive statistically significant amounts of data in under an hour. 2. Companies small enough to make decisions regarding significant site updates in under an hour. 3. Companies whose name is "Google." Fact of the matter is, any change to your site more significant than changing a hex value will require time overhead to think up, spec out, test, and apply. Except in the most pathological cases of cowboy coding, it will take at least a day for minor changes. Changing, say, the page flow of your registration process will take a week to a month. You won't be re-allocating your multi-million-dollar media budget more often than once a quarter, and you have to plan it several months in advance anyways because you need to sign purchase orders. In short, you can usually wait 'til tomorrow to get your data. Really, you can. Sure, you can probably stop an A/B test at the drop of a hat, but if it took you a week to build it, you ought to let it run longer than that. I have had one client who really did benefit from real-time-ish (same-day) data. It was a large celebrity news site. They could use data from what stories were popular in the morning to decide which drivel to shovel out that afternoon. This exception nonetheless proves the rule: Of the 6 "requirements" listed in the article, only 1.5 were needed in this particular case: hard yes on accessibility, and timeliness was relaxed from 5 minutes to 30. (Note that when I say analytics, I mean tools for making business decisions. Ops teams have use for real-time data collection, but the data they need is altogether different, and they are better served by specialized tools).
- RyanZAG 14y ago
  "They could use data from what stories were popular in the morning to decide which drivel to shovel out that afternoon." This doesn't seem to be the same thing as a business decision to me - this is more of a process. It's the same thing as in a JIT supply line, such as ordering more car doors because the line ran quicker in the morning. What you've done in this case is set up a just-in-time celebrity-drivel creation process and are making standard operational decisions instead of business decisions. If you were deciding to change how the share functionality of the site worked because people were not using it in the morning, then this would be a business decision, and I have a feeling you would not make this decision on just a morning's worth of data.
lostnet 14y ago
And we shouldn't have calculators because we may forget the relationships between numbers? I use analytics to do significant A/A testing on every configuration the sites users are actually using to determine what will work for my A/B testing later... Should I maintain a separate realtime analytics or delay deployments by 24 hours when I would like a little more assurance? This is not a rhetorical question, whether I should keep maintaining separate tracking for the 20% of the time where google analytics is unfit is an open problem for me. Similarly, I would like to know if there is a sudden plummet in some demographic the second I start a test. It usually isn't significant, but the client panic will be. It is better to cancel the test and do a post-mortem before restarting.. A B test doesn't have to get its day in court. Giving delayed numbers for routine reports is perfectly valid, dressing up that pig is luddism.
- gfodor 14y ago
  Presumably anything along the lines of the "demographics drop" you mention would be in live operational metrics if it is something that is an effective metric for monitoring the health of the system.
toprxsavings 14y ago
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toprxsavings 14y ago
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car54whereareu 14y ago
"You just need to understand cause and effect," said Apollo. "He's right, mortal. This isn't what you would call rocket science," added Athena. "Okay, and my business will succeed if I can understand cause and effect?" "Yes," said Apollo. "Of course! Why are you wasting time? Go write some software", said Athena. So yeah, real-time A/B testing seems like a bad idea, but real-time analytics sounds fine. On the other hand, maybe the Gods gave you the idea of cause and effect to destroy you. I bet more than one story on hacker news today pretends to understand the causes for an effect.
creature 14y ago
I once interviewed for a lead webdev role at a small startup. They had 10-12 people, and a product that was doing OK. (I was thoroughly unconvinced by it, but that's another story). One of the things they talked about was their upcoming plan to build a real-time analytics system to track user behaviour. A big project! That I would get to spearhead! They'd budgeted 2-3 months and 6-8 people to implement it. We talked about their plans for a bit, before I asked (what I thought was) the obvious question: "So, what's the real-time system going to help you decide that the current system won't?" There is a long, uncomfortable pause as the two people look at each other, each hoping the other will answer. "Well... it's not so much the real-time element, per se..." one managed. "But we want more granular data about how people are using our app." "Okay. But you're currently doing analytics via HTTP callbacks, right? Why not just extend that to hit some new endpoints for your more granular data? You've already got infrastructure in place on the front and back end to support that." No answer. We moved on. I don't know if I actually saved them 1-2 man-years of work or if they plowed ahead anyway.
phyalow 14y ago
Splunk? - I cant help but think that is piece of software would address most concerns this article raises.
AnthonyMouse 14y ago
I agree with this in general, but there are exceptions. For example, it would be nice to know immediately if a new change has caused your conversion rate to drop precipitously for some reason, so that you can turn it back off and take a minute to see if you can figure out why before you lose a full day's worth of revenue.
- scottandjames 14y ago
  Agreed- seeing real-time changes are helpful to respond to drop-offs or spikes. Also, if you are aware of the general trend of Tuesdays being higher traffic/results than Saturdays (to take his Etsy example) and don't take those to heart around product decisions, then watching real-time numbers to respond to changes as they happen can help you hop on waves with supplemental content or messaging.
cftm 14y ago
Interesting post though I feel the author is somewhat missing the forest for the trees; the issue isn't about "real-time" the issue is that many people conducting A/B tests don't understand what the statistics are telling them nor do they understand when an adequate "sample" has been pulled. Real-time data isn't needed for A/B testing but this falls into the PEBKAC category.
frozenport 14y ago
Yes, Yes, and a Thousand Times, Yes!

186 points by chrisdinn 14y ago

Nice post. Ops guys though, like to see the bushes rustling right away so that we can reboot that switch before all hell breaks loose :-) The central theme is a good one though, tactics or strategies have an innate timeline associated with them, and deciding on tactics or strategies with data that doesn't have a similar timeline leads to poor decisions. The coin flip example in the article is a great one. Ideally one could say "What is the shortest interval of coin flips I can measure to 'accurately' determine a fair coin?" And realize that accuracy asymptotically approaches 100%. One of the things that separate experienced people from inexperienced ones are having lived through a number of these 'collect-analyze-decide' cycles and getting a feel for how much data is enough.

btilly 14y ago
One of the things that separate experienced people from inexperienced ones are having lived through a number of these 'collect-analyze-decide' cycles and getting a feel for how much data is enough. If you're going off of "feel" instead of statistics then you're doing it wrong. Period.
- Tyr42 14y ago
  You can build a mathematical intuition. This is a valid thing. You just know how to dig down and prove you are right if asked, so it's ok to leave out details.
- ChuckMcM 14y ago
  Of course you are, my comment was that when you are presented with a decision and the data that was collected and analyzed that went into it, if you've seen a few of these you are much better at catching problems. If you are the one doing the collecting and analyzing and you just think it feels like enough data but you can't actually reason to that point, then yes, you are doing it wrong.
- Karunamon 14y ago
  >If you're going off of "feel" instead of statistics then you're doing it wrong. Period. I disagree, at least to a point. Take an experienced Operations/monitoring guy who's been around the block more than once, then sit him in front of the monitoring utilities for a new company developing a new service. Then, take a total newbie and put him in the same place. Train them both to equal skill on your tools and operations. Who do you think will make the most proper calls? Why? At this point, those statistics and that documentation do not exist yet. What constitutes a "false positive" vs a "drop everything and spin up more VMs and get on the load balancer" can be more of an art than a science, especially when you're first starting out. As hokey as this sounds, certain systems have a "personality" that varies between installations and companies, that nothing short of day to day use will educate one in.
  - btilly 14y ago
    For operations, I agree. A lot of the numbers you have don't have a rigorous statistical interpretation - for instance is a load average of 20 fine or a problem? Depends if you're looking at the Oracle database. But the original article was talking about A/B testing, and that is the context that I was thinking about. There you both can and should use statistics.
- cftm 14y ago
  There's a lot of intuition and experience that is required to be a talented statistician; once the test has begun things are pretty much locked down (ie, if you know the math there is only one "right" answer from the data). The intuition and experience side of things comes with how the test itself is setup. Are things properly controlled, are you collecting the right data for what you're testing, is the data distributed properly for the test statistic you're using...the list goes on and on and on and on and on. There are plenty of places that require intuition and these are the places that errors are often introduced. Statistics is an art.
- frozenport 14y ago
  I always thought statistics existed to give you the "feel". Statistics of more statistics is nonsense!
- danenania 14y ago
  It's possible (though deceptively difficult) to train one's statistical intuitions to be pretty accurate, or at least accurate enough to give them a positive EV. I was a professional poker player for several years, and this is what becoming a strong player is all about.
ajdecon 14y ago
> Nice post. Ops guys though, like to see the bushes rustling right away so that we can reboot that switch before all hell breaks loose :-) I don't think you're disagreeing with the article. He shows a real-time dashboard of ops stats, and then says: > It's important to divorce the concepts of operational metrics and product analytics. Real-time ops statistics help solve ops crises, but product analytics can afford a little more consideration.
- ProblemFactory 14y ago
  > It's important to divorce the concepts of operational metrics and product analytics. I don't think operational and product analytics are different in principle. In both cases, the best speed for analytics matches the speed of taking action on the results. In ops, there are people whose very job is to respond to a server crash in 2 minutes. In product design, there are no actions taken within minutes of seeing the change in data - so faster analytics just wastes time on refresh-procrastination, and encourages needlessly hasty decisions.

josh2600 14y ago

This is a really interesting post. While I agree with the basic premise that Real-time analytics are rarely helpful, here are a couple places where they could be very useful: * Conferences - Being able to see live user analytics on a conference site, since it is ephemeral, would be great. * Pop-up Sites - Again, the short nature of the site means seeing a blocking action or a broken link early is tremendously valuable. Basically there are a couple circumstances where real-time analytics might make sense, but they're generally short duration engagements. Getting analytics info for a site which is no longer being hammered is useless unless it's a long term project.

josephlord 14y ago
What action will the conference take based on any immediate information or do you mean the information will go on the site? Broken links etc. is probably in the operational category although a validator is a better solution for that issue. Logging errors and maybe tracking accesses to ensure every page is being reached can be done by realtime operational stats and doesn't contradict this article.
- josh2600 14y ago
  So think of conferences where there's a site up for one day. If one wants users to clickthru to a particular page, but they're all going elsewhere, that's something that's only actionable on the day of the event (as changing it 12 or 24 hours later does one little good). I see your point about not contradicting the article, but I think there are instances where evaluating the performance of a website in real time (for time-sensitive events) could have a real impact. I don't think we're disagreeing so much as talking about the same point from different angles.

physcab 14y ago

I like this rant. Seldom do I see the need for a real-time system and sometimes I think engineers and program managers gravitate towards the concept to better answer questions of "why" a problem happens. But analytics problems most of the time can't be solved in real time. You have to put on your thinking cap, take a step back, do some background research, and be patient. And as an analyst it is bad for your credibility to jump to conclusions. Unlike engineering, it better to be slow and right on your first try than "move fast and break things".

sardonicbryan 14y ago

So I built and use a realtime analytics dashboard that tracks revenue, projected revenue, revenue by hour for a portfolio of social games. I find it incredibly useful, but I will give a couple tips that address some of the issues in the article: 1) You have to provide context for everything. Current real time revenue is presented right next to the 14 day average revenue up to that point in time, and also how many standard deviations the delta between the two is. Ie: Current revenue is $100 at 10am, vs. 14 day average of $90, which is 0.2 standard deviations of revenue at that time. 2) Hourly revenue is presented the same way, right next to the 14 day average revenue for that hour and the SD delta. 3) Look at it a lot. I've been looking at this sheet regularly for over a year now, and I have a really good feel/instinct for what a normal revenue swing is, and an even better feel for the impact of different features/content/events/promotions on our revenue. 4) This approach also works better when the impact of your releases is high. A big release typically spikes revenue 2-3 SD above baseline, and causes an immediate and highly visible effect. So while I'm not strictly testing for statistical significance, it's one of those things where it's pretty obvious. 5) It also works better if you use it in conjunction with other metrics. We validate insights/intuitions gained from looking at realtime data against weekly cohorted metrics for the last several months of cohorts.

ProblemFactory 14y ago
While this sounds very cool, and my inner geek would love this dashboard on the wall of the office - is it actually useful or is it a distraction? What actions or decisions would you make within minutes of seeing the results? If product changes take days or weeks, daily analytics is just as useful, and stops people wasting time on looking at the data more than once per day.
- rossjudson 14y ago
  This is precisely the right point. We look at an analytic display to determine if action should be taken, and what those actions should be. The vast majority of "big data" is noise, more than effectively summarized with basic statistics.
- sardonicbryan 14y ago

SparrowOS 14y ago

God says... 21:7 And they asked him, saying, Master, but when shall these things be? and what sign will there be when these things shall come to pass? 21:8 And he said, Take heed that ye be not deceived: for many shall come in my name, saying, I am Christ; and the time draweth near: go ye not therefore after them. 21:9 But when ye shall hear of wars and commotions, be not terrified: for these things must first come to pass; but the end is not by and by. 21:10 Then said he unto them, Nation shall rise against nation, and kingdom against kingdom: 21:11 And great earthquakes shall be in divers places, and famines, and pestilences; and fearful sights and great signs shall there be from heaven. 21:12 But before all these, they shall lay their hands on you, and persecute you, delivering you up to the synagogues, and into prisons, being brought before kings and rulers for my name's sake. ---- How's your seismograph?

btilly 14y ago

Gah, yet another article that links to Evan Miller's article on how to not run an A/B test. I really need to finish writing my article that explains why it is wrong, and how you can do better without such artificial restrictions. His math is right, but the logic misses a basic fact. In A/B testing nobody cares if you draw a conclusion when there is really no difference, because that is a bad decision that costs no money. What people properly should care about is drawing the wrong conclusion when there is a real difference. But if there is a significant difference, only for small samples sizes is there a realistic chance of drawing a wrong conclusion, and after that the only question is whether the bias has been strong enough to make the statistical conclusion right. He also is using 95% confidence as a cut-off. Don't do that. You don't need much more data to massively increase the confidence level, and so if the cost of collecting it is not prohibitive you absolutely should go ahead and do that. Particularly if you're tracking multiple statistics. If you test regularly those 5% chances of error add up fast.

joshuacc 14y ago
I would love to read your article when you finish the writing. It sounds very interesting!
RyanZAG 14y ago
No analysis of AB testing should ever miss this incredibly important fact about statistics. http://xkcd.com/882/ http://xkcd.com/882/ When you make confidence tests on a continuous process, you will hit this 1 day in 100 on average for 100 days of testing at 99%. If you're doing multiple AB tests per day, well... EDIT: And another important issue: if you are testing on Valentines day and the pink color/A test is beating out the orange color/B test, then this result may only happen on that one day per year. This applies to hot news topics and numerous other fads as well. Also make sure your tests really are independent - if you do A/B testing off of fixed IP address hashing and have a small user base, by random chance you may have your top customer always being in 'group A' and giving group A a higher than expected base average - an extra bonus click for every group A test may skew your statistical tests as they assume independence.
- 14y ago

lmkg 14y ago

Full-time web analyst here. Total agreement. Information is as useful as your ability to act on it--no more, no less. Real-time analytics is something that sounds sexy and gets a lot of headlines (and probably sales), but it's not particularly useful, especially compared to the cost to implement. Most organizations aren't capable of executing quick decisions of any significance. In fact, quite a few business models wouldn't have much to gain even if they were capable of it. My experience is that there are three types of companies, with very little overlap: 1. Companies large enough to receive statistically significant amounts of data in under an hour. 2. Companies small enough to make decisions regarding significant site updates in under an hour. 3. Companies whose name is "Google." Fact of the matter is, any change to your site more significant than changing a hex value will require time overhead to think up, spec out, test, and apply. Except in the most pathological cases of cowboy coding, it will take at least a day for minor changes. Changing, say, the page flow of your registration process will take a week to a month. You won't be re-allocating your multi-million-dollar media budget more often than once a quarter, and you have to plan it several months in advance anyways because you need to sign purchase orders. In short, you can usually wait 'til tomorrow to get your data. Really, you can. Sure, you can probably stop an A/B test at the drop of a hat, but if it took you a week to build it, you ought to let it run longer than that. I have had one client who really did benefit from real-time-ish (same-day) data. It was a large celebrity news site. They could use data from what stories were popular in the morning to decide which drivel to shovel out that afternoon. This exception nonetheless proves the rule: Of the 6 "requirements" listed in the article, only 1.5 were needed in this particular case: hard yes on accessibility, and timeliness was relaxed from 5 minutes to 30. (Note that when I say analytics, I mean tools for making business decisions. Ops teams have use for real-time data collection, but the data they need is altogether different, and they are better served by specialized tools).

RyanZAG 14y ago
"They could use data from what stories were popular in the morning to decide which drivel to shovel out that afternoon." This doesn't seem to be the same thing as a business decision to me - this is more of a process. It's the same thing as in a JIT supply line, such as ordering more car doors because the line ran quicker in the morning. What you've done in this case is set up a just-in-time celebrity-drivel creation process and are making standard operational decisions instead of business decisions. If you were deciding to change how the share functionality of the site worked because people were not using it in the morning, then this would be a business decision, and I have a feeling you would not make this decision on just a morning's worth of data.

lostnet 14y ago

And we shouldn't have calculators because we may forget the relationships between numbers? I use analytics to do significant A/A testing on every configuration the sites users are actually using to determine what will work for my A/B testing later... Should I maintain a separate realtime analytics or delay deployments by 24 hours when I would like a little more assurance? This is not a rhetorical question, whether I should keep maintaining separate tracking for the 20% of the time where google analytics is unfit is an open problem for me. Similarly, I would like to know if there is a sudden plummet in some demographic the second I start a test. It usually isn't significant, but the client panic will be. It is better to cancel the test and do a post-mortem before restarting.. A B test doesn't have to get its day in court. Giving delayed numbers for routine reports is perfectly valid, dressing up that pig is luddism.

gfodor 14y ago
Presumably anything along the lines of the "demographics drop" you mention would be in live operational metrics if it is something that is an effective metric for monitoring the health of the system.

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toprxsavings 14y ago

car54whereareu 14y ago

"You just need to understand cause and effect," said Apollo. "He's right, mortal. This isn't what you would call rocket science," added Athena. "Okay, and my business will succeed if I can understand cause and effect?" "Yes," said Apollo. "Of course! Why are you wasting time? Go write some software", said Athena. So yeah, real-time A/B testing seems like a bad idea, but real-time analytics sounds fine. On the other hand, maybe the Gods gave you the idea of cause and effect to destroy you. I bet more than one story on hacker news today pretends to understand the causes for an effect.

creature 14y ago

I once interviewed for a lead webdev role at a small startup. They had 10-12 people, and a product that was doing OK. (I was thoroughly unconvinced by it, but that's another story). One of the things they talked about was their upcoming plan to build a real-time analytics system to track user behaviour. A big project! That I would get to spearhead! They'd budgeted 2-3 months and 6-8 people to implement it. We talked about their plans for a bit, before I asked (what I thought was) the obvious question: "So, what's the real-time system going to help you decide that the current system won't?" There is a long, uncomfortable pause as the two people look at each other, each hoping the other will answer. "Well... it's not so much the real-time element, per se..." one managed. "But we want more granular data about how people are using our app." "Okay. But you're currently doing analytics via HTTP callbacks, right? Why not just extend that to hit some new endpoints for your more granular data? You've already got infrastructure in place on the front and back end to support that." No answer. We moved on. I don't know if I actually saved them 1-2 man-years of work or if they plowed ahead anyway.

phyalow 14y ago

Splunk? - I cant help but think that is piece of software would address most concerns this article raises.

AnthonyMouse 14y ago

I agree with this in general, but there are exceptions. For example, it would be nice to know immediately if a new change has caused your conversion rate to drop precipitously for some reason, so that you can turn it back off and take a minute to see if you can figure out why before you lose a full day's worth of revenue.

scottandjames 14y ago
Agreed- seeing real-time changes are helpful to respond to drop-offs or spikes. Also, if you are aware of the general trend of Tuesdays being higher traffic/results than Saturdays (to take his Etsy example) and don't take those to heart around product decisions, then watching real-time numbers to respond to changes as they happen can help you hop on waves with supplemental content or messaging.

cftm 14y ago

Interesting post though I feel the author is somewhat missing the forest for the trees; the issue isn't about "real-time" the issue is that many people conducting A/B tests don't understand what the statistics are telling them nor do they understand when an adequate "sample" has been pulled. Real-time data isn't needed for A/B testing but this falls into the PEBKAC category.

frozenport 14y ago

Yes, Yes, and a Thousand Times, Yes!