Also, I understand that Amazon includes 'System Events' in their free tier. Even with this included, at an average of 15 custom events + 5 system events, you can have 5MM sessions a month for FREE. This is more than enough for bootstrapped companies/projects to start and grow with.

I'm not sure who the customers for these analytics companies are (small projects that grow with them vs big projects that join them) but if it is the latter, well Amazon is def. the better choice. Although they do not offer any complex funnels/segmentation, I am sure this and other features will be added in the future.

Thinking about Peter Thiel's monopoly vs competition eating profits (Zero to One, awesome book!), I wonder if and how players in this space will be able to differentiate themselves enough to really have a competitive advantage over one another.

This is far more of a competitor to Google Analytics instead of us. Google Analytics gives away their product for free - by that measure this is expensive!

Though biased, I wanted to point out a few things since this isn't as amazing as one might think -- it comes with several gotchas (and please correct me if I am wrong):

- Systems events will take up a LARGE portion of this free tier and the paid tiers. Start and End events are going to put reasonably sized apps into the billions.

- If you manage to get rid of said system events, big parts of the dashboard are likely to be rendered useless like DAU, MAU, retention, etc.

- You cannot deeply segment any of this information so you will have a lot of questions remaining even just the next day

- It will be difficult to offer funnel analysis (which doesn't exist) that is retroactive at that scale. That means you will get the same kind of funnel that people hate with Google Analytics' goals.

- Generally speaking: complexity of analysis will mean higher prices

While Mixpanel pricing may seem expensive by comparison, the products are not comparable. You get what you pay for in the level of sophisticated analysis.

Given that, over time it is our plan to lower prices relative to the rate that hardware and infrastructure becomes less expensive. We think that's fair. And if we can improve our technology to become more efficient we most certainly want to make our software and products more accessible.

We are very open to your thoughts so please be harsh and candid (as I know HN can be). We deeply care about our startup customers who made and pushed us into who we are today.

Then I switched solutions for a while, looking for a good combination that'd give me Facebook attribution data plus user behavior. So far, I haven't found my ideas combination and in a way, Amazon doesn't change that.

I find that solutions like segment.io are great in the way that you can install their SDK just once, and have that proxy the events to all other SDKs. For now that's what I chose to do, to avoid week-long delays for approval publishing our apps in the app store.

We instead started throwing all of our events into Google big query. You can steam events directly into a table or proxy then through your server to add more metadata. You can even use mixpanels great open source client libraries and point them at your servers.

Initially I was worried that we would miss mixpanels built in analysis and tools but we honestly preferred querying a database with SQL better. The tricky queries are the funnels but once you wrote the query once you can just save the template. The only thing we had to build was a chrome extension that could graph the results of an arbitrary query.

For non technical people, Mixpanel def seems like the best product.

With mParticle, data portability is a feature within an end to end data platform. So is segmentation with the ability to create any audience you can think of and send it to partners like Facebook, Twitter, Google DFP, AppNexus, ActionX, and many more. Think about seamlessly running an App Install campaign on Facebook to all users that crashed and did not return and then measure it with Kochava or MAT, all with just one client side integration.

Nearly every comment here reflects concerns around cost but cost also includes labor costs, switching and opportunity costs, as well as wasted user acquisition costs. The reality is that you don’t have to send all your data to every third party. You should be able to send a configurable sample of your data to a third party, but also very specifically include or exclude data to reduce costs and protect users privacy.

Disclosure: Co-Founder of mParticle

Attribution is a tough problem in itself, most companies either do attribution really well or user behavior really well, but not both. The best analytics setups I've seen are ones where you have a separate attribution platform that feeds data to a user behavior platform.

The only Startups that can afford your service at this point are the ones that have only paying users.

We collect millions of data points a month and save them on our servers. We do not use Mixpanel's SDK to collect these data points, but have written our own code for that. We save the raw data on our server, aggregate a bunch of similar events to 1 event and then push it to Mixpanel using their API. We heavily use event properties to send as few events to Mixpanel as possible.

This way we get most of the data into Mixpanel and can build funnels, etc. without any issue. There are some edge cases where we aggregated data is a limitation. But for those cases, we end up using the raw data that we store.

Not sure about your use case, but hope this helps.

What you described is a lot of work to build and maintain and very brittle. We've had quite a few customers switch to our platform from Mixpanel that were doing the same thing - aggregating data or sampling.

The problem with either is that you basically blow up your user-level data (e.g. John Smith doesn't have the right activity history), you will miss potentially important trends that are statistically significant that only appear over time, and you limit the type of analysis you do by "property stuffing", particularly around cohorts and retention.

I am really sorry that we messed up here.

Mixpanel is one of the few pieces of software I've been excited to pay for. Hate to see them get a bad rap.

It seems like there may be certain start-ups being targeted that aren't a perfect fit for the pricing structure. If you are B2B SaaS the price is well worth it.

My startup builds products for news publications and we are quite happy with GA and using GA APIs to show the same on our dashboards. There are a couple of Bootstrap themes that do a really good job of displaying the same GA data in a dumbed-down, visually appealing layout. There are also some pretty good charting libraries which makes it easy to talk plot GA data on dashboards.

I may be wrong but it seems MixPanel is targeted toward startups who value conversions very strongly and are already spending boatloads on advertising, affiliates, etc.

I found that Per IP address analystic give me much deeper understanding of events flow. Geoip lookup also allows for me to gain inside to correlate engaged user level to the type of contents to organization name/type.

However, I read all three responses to your comment. One comment points to your high(er) price, one more says your price is unaffordable, the other one says the giants will "will douse the flames of your party." Imo this is a problem - not just for your company, but for every startup/small-company out there.

Amazon and Google can both afford to lose money on their analytics engine. In the old days, people may have described it as predatory pricing. However, that doesn't matter because the legal definition of "predatory pricing" is somewhat limited and consumers/customers mostly care about short-term matters like the price of the product today. Of course, MixPanel itself is a venture-funded company that can absorb some losses (so you're in a better position that what a bootstrapped company would be in). However, this just points to the challenges that small companies face in the market. Of course, I root for the little guy (and I myself started a company that has never sought funding and hasn't gone through the consulting/services path either). I also want giant companies to have a smaller market-share, so I wish you the best.

Could your COGS really be more than 10 - 20%? Usually margins on SaaS is 85%+ and money is spent mostly downstream on payroll for sales, marketing, support, and development.

So I'm a bit surprised to hear 'once infra costs come down we'll lower prices'. When, outside of 'have 1TB of S3 storage for free for your photos', is infra ever the driving cost?

So, in a way, you make an interesting point: it's quite difficult to reduce costs for your smallest customers since the cost of supporting them isn't generally infra related (unless you're a consumer startup?).

There are number of advantages to have lots of smaller customers, no matter how seemingly "unprofitable" on paper they are: marketing, product feedback, etc. Your mileage may vary though for each business and its timing in the market.

It's a hard technical problem but we feel like we've cracked it. Would love to hear about what you think look at what we're up to. Same sort of power as Mixpanel (more in some cases) as well as pricing that's more than 10x better: https://amplitude.com/pricing

What I'd like improved about Mixpanel:

* lower pricing (love the free tier, and until now I had just one client went beyond it and afforded to upgrade)

* be able to send notifications on events. I got sick of the excuse that "you've actually come across a really important characteristic of Mixpanel's data structure. People & Events both apply to users' distinct IDs, and sometimes appear to be working in tandem (e.g., people profile activity feeds), but the two sections of analytics actually live in two completely distinct data stores"

* do simple enhancements / bugfixes. I've sent suggestions to support, they said Yes, great, and nothing happened. Gave up. Examples: prefill notify me test email with current user's email address; fix properties in live view which are filled with custom links -- mixpanel will open those relative to report, instead of new window.

(I'm a founder at Heap.)

I like this approach. Is closer to what web developers are used to: We included analytics on every page, we don't need to create reports until we find a problem or something to optimize... and we still can do forensics.

2 side notes:

– Asked who did this in our app, he told me it was really easy to add mixpanel on "every event". But anyway, he would prefer that it was automatic... and not having to do it again on every view we include.

– As said on my previous comment, for this you need it to be cheap. If not, im creating a problem instead of a solution. At this scenario, mixpanel' people looks less exprensive than heap' sessions.

A question:

Does a "pay for the metrics you use" model makes sense?

Collect everything, what you pay is some sort of multiplier of (metrics used in reports or segments per user). It would be great, at least for this scenario.

I read in the first comment (from mixpanel founder) that the hard part is not collecting data but making them work as formulas.

That makes you able to not storing the data that has not been included on any report or segment for more than a month or something like that if you want to reduce costs.

My history is that I built a real-time analytic engine for reporting project/program progress within large multi-nationals.

We had this idea of a maturity scale to guide a client along a path and to show how our features differentiated us from competitors:

Level 1) A client is recording progress against key milestones

Level 2) A client is trending data against those key milestones and comparing against past data

Level 3) A client is using drill-downs to understand how to affect the trends and deliver milestones sooner against specific metrics from L2

Level 4) A client is defining and reporting exceptions (+/- %/n from expected)

Level 5) A client is defining and using event-driven reports from those exceptions

All clients were at L2 within days of being set up on the system. Few clients ever reached L3, and none ever reached L4 or L5.

The problem was, our price tag was derived from the cost of storing, reporting on, and executing workflow around L4 and L5... we were expensive. This was fine from the perspective of the sales process because everyone wants to reach L5 and so buys into it. But in reality it turned out that once clients had mastered L2, the incremental value received from the weight of extra process required to make L3+ valueable to them just never added up.

We sold ourselves as the only company offering L5 reporting, and whilst clients were aspirational they only ever had the need for L2 or L3 reporting. We were giving them L2 reporting for the price of an L5 system.

Reading the comments here, and I personally have not used Mixpanel for a while now, I suspect that you guys are on the same path we were: Selling the complexity and the capability of a Formula 1 car, when most people just want a Volvo.

It's not even the first time I've seen this cycle repeat itself. Even when I think of companies like Vignette (15 years ago) I recall they sold caching + personalisation, the price tag being determined by the personalisation but it turned out almost every client only needed the caching. I can't think of many clients who stayed with them after that epiphany had been had. Good enough is frequently good enough.

Which reminds me of this: http://archive.wired.com/gadgets/miscellaneous/magazine/17-0...

"When Cheap and Simple Is Just Fine" - and if the orgs do not have data scientists to make sense of the advanced reports you're offering, then those orgs may likely choose to go for something cheaper and simpler that is giving them high returns at the level they're operating at.

Amazon's main purpose in building an analytics tool is to drive spend to the Amazon App Store. If you can't measure the ROI of their app store, you can't devote more resources to it.

This applies to just about all the big tech companies and their respective distribution platforms: Google with AdWords, Facebook with mobile ads, and Apple with the iOS app store. Lots of dollars flow through these platforms, and Amazon/Facebook/Apple don't want their developers measuring those dollars with a hostile competitor's analytics offering. (Often, the hostile competitor they have in mind is Google.)

You'll notice this in the screenshots for Amazon's mobile analytics. On the Overview page, note the breakdown of "Lifetime Value Per User". There are separate figures for iOS users, Android users, and...Fire OS users. A line item for "Fire iOS users" would never be so prominent in Google or Apple's analytics (or even present).

Thus, Amazon et al. focus on making their own analytics tools good at measuring acquisition (prioritizing their own channels) and some high-level metrics. Digging into the data is much less of a priority. Even basic questions - "what's the conversion rate for my signup flow?", "what are the email addresses of my active users?", "what percent of my revenue comes from repeat visits?" - require you to use a different tool.

Bigger companies are aware of this feature gap and happy to pay the price premium. But startups are (appropriately) more price-sensitive, even though a solid investment in growth/analytics is arguably more important for startups.

I'd love to hear HN's feedback on how Heap (and other analytics companies) can structure their pricing to better accommodate small companies.

Amazon unlikely will be the best solution (e.g. I bet Mixpanel will be significantly better for at least next few years), but they may cover a lot of typical use cases. That will commoditize the user event analytics and put pressure on the other companies.

You know, Analytics + SNS + SES would make up a nice a little marketing automation solution and I wouldn't mind building my own reports in R or whatever.

However, there's no way to retrieve and reuse any data through the API. Seems like a major opportunity loss with AWS users as target audience.

Overall I agree with Suhail’s points regarding GA being the closest proxy for this service. You do get what you pay for when it comes to advanced analytics. If anything Amazon’s move shows that simple data collection around analytics is becoming commoditized. We tend to price based on MAU’s rather than events to help customers with predictability, but given that event data points are the basis of our (and pretty much all analytics company’s) cost model, that can present challenges.

The problem being highlighted in this thread is that the value derived from advanced analytics doesn’t justify the cost in the minds of a lot of startups. There are a variety of reasons for this: not enough users, deeper insights are “interesting” but not game-changing, complex to set up, hard to understand, requires lots of event tagging, etc.

Here’s one way to think about the value of more advanced analytics: they are primarily valuable for startups when they power the ability to take action on them (i.e. In the form of marketing campaigns). For example, if creating intricate and specific funnels and flows seems like overkill for your startup e-commerce app, would the value increase if you could send a push or in-app message to users who have dropped at a specific point in a funnel but have purchased before? I suspect that it would, but clearly the value fluctuates depending on the stage and context of your app.

i've headed analytics/targeting at a yc company in the past before mixpanel, flurry were in the market, and saw first-hand how portability/dumps of the data made a big difference as you grow - something that not all analytics saas companies provide.

disclosure: i work @helpshift and we have several customers who may have 100M+ data points/week but we dont price based on data points. we give the basic active, engagement and session metrics like amazon, and search/faq metrics within our sdk. slice-n-dice reports based on custom events are coming soon.

but our pricing is aligned around in-app customer support & active users. we dont track/charge for metadata, breadcrumbs and you can tie as much data to an issue/user (much like Parse out-of-box). most of our users have several sdk's and we're fine with that too.

that said, i see a lot of value in heap/keen/segment that make it less important where/how the data is and let you focus on what insight to surface