What is Reddit's opinion of
Amplitude?
From 3.5 billion Reddit comments
➔ Amplitude website
By popularity on Reddit, this Service is:
37 reviews of this app found across Reddit:
Yes that’s right, by downloading the game and paying nothing not only am I not directly contributing to Bungie’s financial success, but my data on their server actually costs them money to maintain and store so if you want to get really technical, F2P presence actually costs them more money per individual than they make per individual. Luckily for us all, for better or worse, that cost is offset by the 10% of people who buy everything.
Here, this article should help you understand more clearly.
10 million events per month is the primary limitation. You also don't get all of the advanced analytics/collaboration features, but they're probably not too important early on. If you get traction and start needing more volume, you can also check out the scholarship program: https://amplitude.com/startups
Besides revenue, churn, ARR, etc. (because I cannot directly affect these metrics), the main metric for me is the usage (value) metric that will be different for different products.
For example, for my social media automation app, the metric is the number of posts people schedule in the app. The logic here is simple. I can affect this metric by improving experience or educating customers. And if this number increases, all the important metrics that I can't affect (MRR, churn, etc.) will also improve.
This metric of the product is called the "north star" metric. Check out this reading, it is really great and free: https://amplitude.com/north-star
🙌
https://amplitude.com/ It's analytics. a simple Google would have told you that.
Assuming thunkable adds it to your app unless you did it yourself. As for your app not targeting children no one here knows since you gave zero information.
Great site. However, it is hard to understand your value proposition. It is unclear who the target audience is and what use cases are you solving? Is it for product managers, developers or support teams?
It looks like it is targeting developers since some of the value prop is towards continuous delivery, security config etc. IMO, I don't see a strong use case for developers to use external config management. On the other hand, I believe that you should target Product Managers - Consumer PMs who run high number of experiments (e.g. weekly) and B2B PMs who manage high degree of configurations / customer due to the nature of B2B software . Their use cases require flexible configuration management and building it in-house is generally expensive. Few use cases that I can think about - A/B or multi-variate testing, control user flow (new user onboarding, feature intro, profile wizard etc), early access to feature, control access to features based on user profile/pricing tier etc. To solve these use cases, development teams will need to build/maintain massive config systems and thus opportunity cost is significantly high for PMs.
If you can highlight value/effort between build/buy, majority of Product Managers will influence their development teams to use an external configuration system. The best analog I can come up is how heap.io and amplitude.com sell their software. They sell to product managers but their product requires engineering teams to embed their code on webpages/apps (and also pass some additional attributes), so that product managers can use their analytics to under the user behavior.
Hope that helps.
Looks like amplitude is an analytics platform. If you temporarily whitelist the url (amplitude.com) and check their customer list (https://amplitude.com/customers), you might find out what's doing it.
​
No guarantees though.
I found the guides shared by amplitude quite useful, specially the user behavior and Behavioral Cohorting ones
I use amplitude.com to record events of interest and get some insights into how the app is being used. Most of the data I analyse today comes from Amplitude. But then there are some other metrics, like the distribution of app languages; the number of data points user has created; or the presence of tags and other grouping tools which a business has in use. It's more of a snapshot of things then a usage dynamics, if you know what I mean.
I think there's balance. Like estimating revenue on a single feature (especially without great product analytics) might be super hard, but guessing does still provide useful context for prioritisation.
I like a process where a team has a really good framework of product metrics (e.g. North Star Playbook) and then write their roadmap based on problem statements, hypothesis, and their expected impact on their metrics (and some of their metrics might lead to revenue directly or indirectly, e.g. you may have an problem space you want to work on, and you hypothesise that if you solve it, conversion will increase by 1%, and its fairly easy to follow that path to calculate estimated revenue, growth, # of new customers, other metrics etc.)
Every problem and hypothesis will be an educated guess, but the better your data is, and the better you are at testing ideas, the more educated you can be about estimates.
E.g. in the short term, you can test a hypothesis by implementing a really small MVP and releasing to a small cohort to test the concept, and if it moves the way you expect you may have validated the idea, if it is flat or moves backwards, you can deprioritise that idea knowing that you have validated the hypothesis (e.g. you expected 1% conversion resulting in $1mil in new revenue, it actually reduced conversion by 0.1% so reduced revenue by potentially $100k).
So yeah if you're expected to provide a revenue number, and then you're held to that, that's just poor product management. If you're expected to calculate estimated potential impact for your planned roadmap in order to make informed, data driven, product decisions that you can then validate, then thats just good practice.
I got my MBA from a top 25 US school and it got me hired for my first pm gig in a smallish (~700 employees) IT security company but didn't do much to prepare me for the first few years which was acting as a product owner working with engineers to decide what to build/fix next. After five years I left pm for more data centric roles focusing on tools to help product folks make better decisions. I recently returned as a sr. pm at a new small security company and find that my industry experience is my most valuable asset. My boss is VP product and doesn't have an MBA. You have to go up to CPO to get to someone with an MBA. You don't need to be technical to be a successful pm but it depends on the company. For Amazon you need to be able to master the STAR interview method and be a case study wiz. For this b-school will be a big help. If you can take courses on product management that would be helpful but may not find those at most programs. Were I to start over now I consider the one-year mspm program at Carnegie Mellon instead of an MBA. FYI: Also, knowledge of tools like Pendo or Amplitude would be useful to actually employ a data driven way to decide what to build next.
No it's wrong because there's no scientific reasoning behind it. It's just correlation. Things can correlate without that being the CAUSE.
​
https://amplitude.com/blog/causation-correlation
​
There is no scientific proof that masturbation has any effects on your physical health whatsoever. There are only studies showing correlations in data. There are correlations in data ALL OVER THE WORLD that have nothing to do with eachother.
Yes, when enough different studies show correlation between two data points, you can often assume causation.
> Once you find a correlation, you can test for causation by running experiments that “control the other variables and measure the difference.”
https://amplitude.com/blog/causation-correlation
Therefore, differently conducted studies allow us to form strong evidence for causation. I mean, this should be obvious unless you think causation can never exist.
You really aren't as smart as you think you are. Not even close.
lmao... I didn't attack you personally, I made an observation. I already removed the one word you could have taken as an insult.
Then again, I'm speaking to a person who is unable to understand the difference between correlation and causation, so I didn't expect anything else. Either way, for the sake of everybody who has to converse with you in the future, I hope you read this.
> Shame on you, I hope you're at least a teenager because such behavior is not adult by any means
Again, coming from somebody who doesn't know what correlation and causation mean, truly ironic.
Founder of Amplitude here. We spend a lot of time thinking about what it means to be great at product analytics. Our product aside, we have a pretty deep repository of content on the topic: https://amplitude.com/content-library
Bitclout is tracking user actions, device IDs, time stamps and wallet public key data via POST to amp.bitclout.com which is a proxy to enable sending analytics to vendor Amplitude via Ajax sub-requests.
What does everyone think about Amplitude? https://amplitude.com/
Basically as a software engineer, I do not have a law school degree or anything that, and thus do not have the requisite knowledge to be working in business operations, product design, or anything management related. I feel thankful that I get to work on this type of product as a software engineer. Of course promotions to management are possible if one chooses to go back to school for an advanced degree in a field like computer science, math, physics, or even business.
Here's an explanation about why correlation doesn't equal causation https://amplitude.com/blog/2017/01/19/causation-correlation
Here's why you suddenly see all these meaningful coincidences now that you're looking for them https://www.psychologytoday.com/us/blog/finding-purpose/201810/why-we-should-not-be-impressed-eerie-coincidences
I encourage you to study up on the law of large numbers, cognitive biases, and the prominence of rare events. Seeing the world through the lens of superstition might be comforting, but it's a dishonest way to live.
They'll typically assess for whether you can pick the right metrics for a hypothetical product. The key is picking a north star and contermetrics to make sure you get the full picture (e.g., north star = checkout conversion; counter = return rate). You'll want to describe how you would get to the best proxy for measuring success, and what you would monitor to confirm that side effects are minimized. Might also help to consider what metrics you'd like in a dashboard for this product.
Happy to hear that. I would say there are two pieces of it:
- We have people who really care about the quality of the product and what we're putting in front of customers, so they go above and beyond in these types of things. This is hard to replicate with process, it's all about culture.
- We have a team specifically focused on adoption/usability/collaboration in the product because we've proven that it has high impact on the business. We did analysis on how the number of end users sharing content affects our ability to grow customers and revenue. You can read more here: https://amplitude.com/blog/evolving-the-product-north-star-metric
usage data = analytics, we use amplitude in our mobile apps
If you want to read about their data security you can check it here https://help.amplitude.com/hc/en-us/articles/206533238-Data-Security-Privacy
> Men get assaulted more because they worry less.
You are using the rhetorical technique of confusing correlation versus causation. If you are a professional then you should already know the difference.
Men get assaulted more AND men worry less. These things are correlated. They are two true statements based upon crime data and mountains of psychological study data.
There is nothing you can point to that would demonstrate a causal link (i.e. "men worry less, therefore they get assaulted more).
On the other hand it is demonstrably true that rapists and child molesters are at the very bottom of the food chain in prisons.
Men's need to protect women is so very ingrained in our biology that even the very worst of us, prisoners, will beat up and kill other men who commit those crimes.
> Most of my guy friends, myself included,
Oh shit, you are a dude ... sigh ... stop white knighting and go take a STEM class.
> When your thought is "if I go out I could get brutally assaulted/raped/killed"
Most women do not think this way
I mean this in a very empowering way and I hope you take it that way - it sounds like you are feeling a lot in general and sometimes when we are overwhelmed with feelings, we can try to find a reason or cause and randomly assign a person or event to it, when in reality, that person or event has nothing to do with it, we're just people really full of feelings.
When I was younger, I was a very full of feelings kind of person and I very mistakenly assigned causation through correlation to a lot of people and events. Feelings are odd things from a scientific perspective and are subject to shifts based hormonal imbalances, sleep, diet, and even weather. Getting older, the intensity of feeling cools and calms significantly.
Soul mates don't exist, it's a silly concept that sells books and movies. Real relationships take work, effort and a decided commitment to work through all the bs of each other and all the world will through at you to maintain intimacy and connection with another human being - that can only happen over the course of time. Knowing someone for two week, two months, even two years isn't so much in the span of a relationship. It's perfectly natural and normal for young women to be in love with the idea of love - it's a natural phase in your emotional development, but your far better off knowing it for what it is and seeing it for what it is than giving in to magical thinking about soul mates with an individual you barely knew who clearly gave off enormous red flags.
Many thanks! I've installed the Classy Shark 3xodus and it's very informative.
7 trackers were found, 4 of which are Google-related (typical since the app was installed from the Play Store, 1 from "AWS Kenesis", another one is "Amplitude" and the last one is "Branch". All trackers with a "shopfront" in other words.
Let's see if I'm OK with that..
I agree OKRs are quite a good way of stating these kinds of things, but everybody does this a bit differently, however the form you see in "Radical Focus" by Christina Wodtke is very outcome-focussed and at the right kind of level for the top of the business in my opionin.
Other references that are pretty good on this kind of thinking are "Escape the Build Trap" and The North Star framework (https://amplitude.com/north-star).
>That blue line is an exponential growth chart (bottom of article)
That does not show exponential growth. Take a look at Wikipedia, there's an actual exponential chart at the top.
> superimposed on the Chinese data to convey it is indeed, exponential.
Except it does not match the data at all. You might as well have put a graph of your dick next to it.
> It's unequivocally not linear growth.
Except it is.
>Did you even go to college? Numbskull.
Are you actually unable to write a comment that doesn't end with an insult?
Maybe the NFL app if you have that...
Seems relevant. https://amplitude.com/blog/2016/10/26/how-the-nfl-can-evolve-into-a-content-platform
Before my sources, here’s some basic facts.
Yes, daily active users have been rising. ~2.59 billion of them today.
But let’s look at the definition of daily active users: it can be problematic.
Out of these “active” users, daily or monthly, most have the account but are using it less and less. Consumer demand is falling, and they’re spending more time (which equals money) elsewhere. The way internet metrics data is measured is flawed in so many ways, beginning with the tracking of usage and how it plays into economics. The consumer’s wants change every second.
Facebook deletes 3 billion fake accounts. In the last year or so. I guess everyone forgets about that. That’s more than twice the amount of “active” users, in total.
The definition of an “active user” of social media needs to change for the sake of accuracy.
There’s obviously more at play here: corporate lobbying, skewed or misleading stat releases for economic purposes, etc. But that’s an entirely different topic.
I suggest you read “Everybody Lies” a book by Seth Stephen-Davidowitz. Follow it up with “Messing With the Enemy” by Clint Watts. Related and highly recommended.
Generally, it’s best to examine social media and its structures much more critically before engaging.
Yes but MAS and MAE don't really provide much a picture of the ecosystem. It is not common practice to lump everyone in a big group and say look at these numbers. While it serves a purpose it doesn't provide the level of insight into an ecosystem needed to see change over time or how/where gains can be made or where work needs to be improved. While the data is presented as a total of all apps and a total for X particular app different groupings of how individuals are counted would be beneficial.
​
For instance, cohort analysis specifically taking the total users of a given day called day 1 and seeing how many continue to be users at day 2 or day 3 or etc. Another aspect is how many users who download and app and join the ecosystem continue to be a part of the ecosystem at day 2. We've heard a lot about how such a metric doesn't matter but there are experts in this area who don't agree and retention is just as much a success metric for KIN since one of its goals is to increase user retention (yet no data on how this actually plays out) https://amplitude.com/blog/2015/11/24/cohorts-to-improve-your-retention?fbclid=IwAR3aUAxx0E_QtgltAgT6ahvpe_aqFoN3uNPxngJg472wfWDDjDmiKUmyiow
​
This is just one example of counting in a more informative way. There is nothing wrong with presenting totals but such breakdowns offer too little insight into important metrics for improvement, issues, and successes.
One thing that you should consider is having some user analytics... Basically you will want to know:
- where people are coming from / how they find out about you
- what they do / use most
- who sticks around / comes back
- for those who don't, where they drop off
- how to find/encourage more of those who do
I have found Google Analytics or Amplitude as two good (free!) getting started choices.
Maybe you have something set up but at a quick look I didn't see anything.
Also if you need a primer on analytics, this seemed to cover the basics (and there's a deep deep rabbit hole you can go down so watch out and err on the side of just getting started!): https://www.slideshare.net/gosquared/analytics-101-for-startups
Good luck - and welcome to the hard part ;-)
What you need for product feature discovery are as follows. Pretty much any product analytics tool (Mixpanel, Amplitude, Countly etc) has those features:
​
- Custom user properties that hold a key-value and a method to modify it for each user profile.
- Funnels that show you how your users have been performing a specific set of actions
- Custom events with segmentation values that help you understand all feature usage (e.g click on a menu, test new functionality etc)
​
HTH
​
I've moved over to Amplitude from Mixpanel as my go-to for more actionable startup analytics than GA but they're still 3rd party...
I agree with u/paul345 that you'll likely spend way more time than you want/need to if you try the roll-your-own route though so make sure you have a really good reason if you do.
And then there's the point regarding how companies w less gender disparity in their leadership perform better. I'm usually cynical about such research because they prove nothing more than correlation.
Comparing companies throughout the board, once again, doesn't prove anything. Unless all the companies used in the research have the same business model, sells similar products, operate in the same markets etc your claim might bear some validity.
Say, if a research shows company A managed to equalise the gender ratio over X years, and in X years, profits were raised by Y%. Notwithstanding changes in market conditions and product launches, this research would certainly be valid.
Bottom line, to truly validate such a huge claim that more females -> better company, a sound model would be needed.
Otherwise, it's merely correlation, which can happen between the most far fetched things.
https://amplitude.com/blog/2017/01/19/causation-correlation/
In the past we've used Amplitude Analytics. Funnels are easy to create and your event data is processed very quickly. We used them on both Android and iOS. We also sent some events from our backend.
https://amplitude.com/ https://github.com/amplitude/Amplitude-Android
I think you massively overstate the economic importance of casual players.
"According to a study by Slice Intelligence, the population of Pokemon GO paying players peaked in size on July 15 and has been shrinking ever since. At the beginning of September, Pokemon GO had lost almost 80% of its paying players and its paying population was well below that of other mobile games.
Yet Pokemon GO was still generating over six times the in-game revenue of Candy Crush Saga—the second-most profitable game in the app store.
This indicates that most of the revenue—which comes from in-app purchases in the free-to-download game—is coming from a loyal player core.
Slice Intelligence also reports that 11% of users making in-app purchases were players who had made 10 or more in-app purchases in the previous year. In the mobile gaming app industry, these rare but valuable players are called whales, like the high-rollers in casinos who are lured to spend a lot of money."
https://amplitude.com/blog/2016/10/27/pokemon-go-lost-players-won-game/
If there wasn't a culture of accountability before, all you're doing is creating pin dancing metrics.
Nobody has a problem with analytics. Including the people making mischief with analytics. Meaning culture determines the analytics that keep it from having to change.
You Say You’re Data-Driven, We Call Bullshit sure you're data driven, I'm just asking whose hands are on the steering wheel.
Bullshit analytics that can lead you to disasters numbers don't lie. Which is why grifters embrace numbers.
I am using Keen.io to track starts of the application only. Using the Rest API interface so no SDK needed. For events such as activity launch or fragment adding I use Amplitude Also Rest API interface no sdk needed. I think both offer a SDK but I did not find this useful cause making request is basicly what my whole app does. And now I have full control. You can create a base class an just pass the simple class name. Also I track every request a user makes to the backend. It seems like double traffic but I will improve this. Like some sort of batch post to amplitude. But I build it easy to see what I need. I find it useful for instance I want to see how much time something is shared true shared intent when I implemented this feature. And it turns out that nobody uses it. So this way I don't need to improve there. But fetching data is used a lot so I will set my priority there. If there are more questions let me know. I don't track personal information about the user. I just want to know the usage I really don't care about the user specific.