Ask HN: What's your startup's analytics setup?

I have a love-hate relationship with data. Data is great for helping drive product, messaging, engagement, etc. However, most data ends up as noise. It's noise because it isn't actionable.

Ash Maurya wrote this great article on actionable metrics: http://www.ashmaurya.com/2010/07/3-rules-to-actionable-metri...

In the end I think it depends on how you want to use the data.

Here are a few things that I find useful:

- calculating your ROI on customers by correlating marketing efforts with key metrics. Google Analytics is good for this as you can basically identify the customer origin with a marketing campaign and how they convert for key metrics.

- full funnel perspective and cohort charts for AARRR metrics (http://500hats.typepad.com/500blogs/2007/09/startup-metrics....). KISS Metrics and Mixpanel are great for this, but I still haven't found anything that does the Cohort diagrams that well.

- experimenting with messaging using A/B testing tools like Visual Web Optimizer (http://visualwebsiteoptimizer.com/) which has it's own analytics.

- retention email marketing is great with Customer.io (http://customer.io/) but I have fairly limited experience with that.

Other tools include Statsmix (which I think is under-represented); it is pretty good for collecting custom event data.

Once you have the money for it, tools like Pardot are great for marketing overall. We just implemented this so I still don't have much experience with it personally. It's a full marketing automation tool and has other competitors with higher price tags.

By the way, Ash (and the rest of the the Spark59 team) are working to build a system to provide pirate metrics dashboard with cohorting, lifecycle email campaigns, and measuring impact of a/b test by creating cohorts for each group and reporting results in the context of AARRR.

http://usercycle.com/

Geckoboard is another dashboard that seems pretty good and has better pricing Statsmix.

Google analytics is great for basic web stuff (getting origin of requests and so forth). KISSMetric is phenomenal as well. If you do email marketing, I think SendGrid might be a good option to measure email engagement metric, on top of not having to maintain an email service.

If ever you feel like doing more data crunching on your own, I recommend getting started with Splunk. The company i work for uses it extensively. Splunk is phenomenal but tricky to use properly (I'll explain). I think the reason it works so well for us is because every action taken by either the server or user-facing devices is carefully logged. As a result, we're able to pull insightful user metrics in highly customizable way that any other service out there just can't get you. Here's the downside of Splunk: since it's so hands-on, there's little initial guidance as to what you should be looking at, and thus the hardest part of Splunk is knowing how to ask the right question. Beyond that, it definitely has its quirks. For example, I wish it was easier to export data to do more in depth data analysis with matlab and the likes (they have a so-so api). I also question the accuracy of their indexing at times (rumors has it around the office that there are log lines that don't get properly fetched...). In any case, if you are serious about analytics (and can afford it in the long run), Splunk is a strong candidate. It will force you to think long and hard about what exactly you are trying to measure.

edit: grammar.

I also like to use Splunk for all sort of logs, from nginx to python process logging. Sample of reading nginx log: http://cl.ly/image/1G2D0v3i1b1K/Image%202012-10-27%20at%2010...

We looked at Splunk and liked the architecture, but it doesn't really have customer-focused analytics in its DNA, and it's not open source - which is why we released SnowPlow (https://github.com/snowplow/snowplow)

This is great! The other day I was wondering if anyone had tried to build an open-source Splunk equivalent. I'll look into your guys' stuff. thanks for the ref!

Thanks mukaiji! Any questions you have, just drop me a mail - alex@snowplowanalytics.com

Isn't splunk just used for server performance monitoring or is it a general analytics tool?

At a previous job at a hosting company we used splunk, but we used it for monitoring a couple thousand virtual and physical services. Does it have uses beyond that?

Splunk is good for log processing of all sorts, including event logs. We log app events in a custom format, drain to syslog, and ingest into Splunk. It works great with the exception that some Splunk queries (through the API) can be quite slow for use in online user-facing analytic dashboards, and it's not particularly cheap.

Splunk is a great tool for any sort of logs, and that includes user events and so forth. Basically, if you log it, Splunk will index it, and then you can find ways to search it, correlate it, reverse-analyze it... the whole nine-yards. However, as another user mentioned below, "Log every single action, decision, call, message, visit, and fault in detail. Log it with structure." If you don't do that, Splunk won't be that useful. I can think of a few example at work where missing details in log lines quickly deflates my Splunk enthusiasm. So, log everything and carefully, all the time. Then Splunk becomes your friend.

I'm surprised no one has mentioned Piwik[1] so far...

For web-analytics it's almost on par with GA (at least back when i last used it) and you get to keep your data!

[1] http://piwik.org/

I use it too. I don't want any third party provider use for analytics.

If you happen to run a content-oriented website (e.g. a blog or blog network) then in my biased opinion, you should use Parse.ly Dash, which is built specifically for online content publishers. I'm the founder & CTO: http://parse.ly

No matter what site you run, though, you should use Graphite.

It's open source: http://graphite.wikidot.com/

It has a slew of client libraries so that you can instrument everything. See Etsy's tech post on this, "Measure Anything, Measure Everything": http://codeascraft.etsy.com/2011/02/15/measure-anything-meas...

Here's a concrete example of how we use it at Parse.ly: we instrument all of our API endpoints for each publisher (customer) that is using our API. We can put this instrumentation right in our code and thanks to pystatsd and UDP, it doesn't slow anything down.

This way, we can track which endpoints are being used and be alerted about spikes and go-lives from big sites. See this graph I generated from Graphite after toying around with the data to discover some of our top API users:

http://ubuntuone.com/0CRL8EsDuQjirYczUQCitg

And here is the Graphite expression I used to generate it:

    sortByMaxima(averageAbove(stats.api.prod.*.*, 0.01))

Don't pay for anything!

At least not now: While you may choose to put some money into a serious analytics package in the future (when you get millions of visitors per month and have specific measurement interests), there is absolutely no need to do that when you're small. It's just one more expense to think about.

If you don't know enough to choose one now (which is totally fine!) start with Google Analytics. It's free, it will do your sites, apps, and real-time stuff if you need it, your colleagues are likely to be familiar with it already, and it can cover A/B testing relatively easily.

When you find yourself saying things like "I wish Google Analytics had XYZ feature" or "GA isn't compatible with ABC thing we love" then you'll have a checklist for finding something more appropriate to your needs.

Otherwise, use the tools that come for free with services like Facebook and MailChimp! There are plenty of numbers in those while you're small.

Truly integrating multiple analytics package is — in my opinion — a solid opportunity for a start-up in itself, so if you're looking for a the one-stop-shop you probably won't find it. If you do, let us know! :)

I agree with the 'don't pay for anything early' sentiment, however I don't think it's good advice to recommend just Google Analytics. The data is wildly inaccurate and while provides some good stuff, it should not be your only form of data.

I'd recommend pairing this with the free mixpanel plan and/or getclicky so you have a few different sources to check each other.

Agreed. I keep these tabs open at all times: Mixpanel, Intercom, GA, Google Webmaster Tools. All great services and totally free for startup level usage.

Make sure that you setup dev/stage/prod keys/accounts for each too so that everything is kept separate and can be tested individually.

I'm a cofounder of rjmetrics. You probably won't be surprised to learn that we have all of our data from billing, product usage, google analytics, zendesk, hubspot, fogbugz, etc in our rjmetrics account. We give access to all of our employees and our board.

There are a lot of great tools out there, and we think ours is best at consolidating, analyzing, and acting on the data that ecommerce and saas companies have. We don't collect new data for you, which is the focus of a lot of the other tools mentioned on this thread.

My cofounder actually has a guest post on techcrunch today about the things to consider when buying or building an analytical system and trying to create a data driven company: http://techcrunch.com/2012/10/27/lessons-for-data-driven-bus...

Funny thing, I was talking to our CTO about RJMetrics and want to better understand options for going beyond what we do with Google Analytics today. Can you shoot me an email roger@room77.com?

It really depends on your business. Are you a b2b? b2c? media outlet? etc...

The question is, do you need Web Analytics to analyze your traffic (sources, exits, uniques, etc...), Customer Analytics to analyze your user base (unique customer identification, customer retention...), Mobile Analytics, Server Monitoring, Email Marketing Analytics etc...

Google Analytics can be the best free solution out there for general web analytics, it really covers everything you need to know about your "visitors" and it works really well with media outlets, blogs or websites where visitors don't identify themselves.

Woopra Customer Analytics (http://www.woopra.com) can be a great solution for you if your visitors identify themselves on your website. Woopra creates a profile for every single visitor on your website and aggregates visits across multiple devices (multiple cookies) under one profile when customers identify themselves. Which reduces the noise dramatically when you're doing reports on unique customers. Most people access your service across multiple devices (home, work, iPad, iPhone etc...) and you don't want to count every visitor multiple times in your reports.

Woopra also allows you to leverage your customer data for sales, marketing and support purposes as it builds a complete behavioral profile in real-time as they engage with your website.

My personal favorite Woopra feature is the ability to get push notifications whenever any visitor or identified customer fits in a certain category and/or commits one or more specific actions.

The other question you need to ask yourself is "Who's going to be using the product?". Products & Services are designed differently for Developers / Product Management, Marketers, Sales, Support...

To summarize: Web Analytics is a very generic term now and you're going to have to decide what fits better with your business:

A/B Testing: - Optimizely (Commercial)

Customer Analytics (SaaS): - Woopra (Commercial & Free) - KISSMetrics (Commercial)

Mobile Analytics: - MixPanel (Commercial & Free) - Flurry (Free)

News & Media Website Analytics: - Google Analytics (Free) - Chartbeat (Commercial) - Clicky (Free & Commercial)

Email Marketing Analytics: - Marketo (Commercial) - HubSpot (Commercial)

Server Monitoring: - WebMon (Commercial - recently launched) - NewRelic (Commercial)

(Disclosure: I'm founder & CEO of Woopra)

Disclosure: I'm founder/CTO of HubSpot.

I agree with you completely. It all depends on the type and stage of business. If all that's needed is analytics, HubSpot is likely overkill.

One quick piece of advice to the OP: Be careful not to spend too much energy analyzing the analytics tool choices. Most startups are better off making a quick decision, and getting back to working on the product.

Yup, in fact getting back to working on the product was my motivation for asking this question. There is a lot of work to do on the product and the last place I want to be spending time is on picking and choosing analytics solutions.

Andrew, our startup (credii.com) is trying to solve the exact problem you have - finding the right software for a particular use case - based on facts and social signal. While we are still not public yet, I believe we can help (and also learn from your experience). Can I shoot you an email ?

Yup. Fire away.

People should pick analytics according to what they want to solve. Is it some combination of monitoring or insight, pure insight? Are those insights the result of just aggregates, or is it user behaviour driven and requires cohorts and funnels, etc?

One of the questions that should be asked before you hear the answers people give is "What is your medium and what problem were you trying to solve?".

You can imagine that Stripe does a lot of business via their API and would want insight into usage and potential problem areas. Part of this may be solved by log file crunching, but part of the API may be considered to be a funnel if multiple calls are present... what solution did they use since they could not use one of the many JavaScript drop-ins?

Email marketing and push notifications have their own problems too... how are they getting their insight? Did they all use personalised tracking links, what was the best for this use-case?

The problem with "There are a lot of solutions to pick from" stems from everyone's problem being subtly different.

For the most part web analytics in a general sense is a solved thing (Google Analytics), but as soon as you start asking company/product specific questions about the behaviour of your users you may want to consider Mixpanel, rolling your own, etc.

I think most people's answer will add more noise to your decision rather than reduce it. I don't know how to start a poll on HN but it might just be simply to get a show of hands, determine the most used tools, and then go and take a close look at just the Top 3 or 5.

> I'm especially interested in hearing from the YC startups, since I figure there maybe a set of analytics tools that are suggested to you guys by the YC partners based on the collective experience of past YC classes.

I would think that YC companies and alumni actually try and help each other such that YC companies probably use another YC company product more out of shared benefit than a perfect match.

I would guess that part of the reason they would use Mixpanel is for this reason.

I work on web analytics for several startups here is the general trend.

Google Analytics is the most basic one they start with because its free and easily extendable.

Kissmetrics or Mixpanel for extended time period analysis (cohort, churn, clv).

Mailchimp and Visual Website Optimizer offer one click integration with GA. Mailchimp can be integrated with KM too so that helps tying the data together initially.

Usually once they setup KM/MP they use it for day to day and keep GA as backup. But alot of times you'd find yourself going back to GA to measure impact of an action that you werent tracking in KM.

We actually ended up rolling our own, but that's because the specifics of our model required us to be able to track things that a) no other analytics platform was going to be able to handle; and b) we wanted to retain our own data. So I'd just add that the proper solution is highly dependent on the company's model and what the company plans on doing with the info.

As a side note, I would highly suggest NOT building a custom analytics platform as a startup unless your model simply won't work without it.

    > As a side note, I would highly suggest NOT
    > building a custom analytics platform as a
    > startup unless your model simply won't work
    > without it.

Seconded. I work at a place that has gone down this path and there are a lot of pitfalls.

If you go with something like Mixpanel, then that software does what it does. If somebody wants to measure something that Mixpanel can't, they either have to go without or make a really good case for getting their desired figures some other way at huge cost.

Not so with in-house solutions. Because it's possible to constantly measure more things by investing programmer time, that's what happens. Be it product, marketing or finance, somebody always has another bright idea or another "I absolutely cannot do my job any more without this" measuring need.

Because this pressure to add features comes from within, rather than from outsiders, it's hard to resist. People will push you to ship "just this one thing" outside of the normal release cycle because it's always "so urgent". This happens to me several times every sprint because of our internal analytics software, and it's an enormous time sink when every "just this one quick thing" needs to be pushed through the QA and release process one by one.

Also, people are happier to put their faith into external products. If RJMetrics reports a higher-than-expected number of occurrences of event P, you assume RJMetrics is working correctly and the first question is "What bug in our system is causing too many of these events to happen?". If the internal analytics system says the same thing, it's an analytics bug until proven otherwise. As the maintainer of the analytics system, this gives me de facto responsibility for identifying and triaging the whole team's bugs.

As an obligatory plug: when we show SnowPlow (https://github.com/snowplow/snowplow) to startups who've rolled their own analytics setup, they often say "I wish this had existed when we decided to roll our own"...

One thing that's cool about KISS metrics is that they have an export feature which actually exports all your data to S3 buckets on a daily basis. Great for those that are worried about data retention.

If you need to analyze things that live in your database (users, transactions, actions on your site), I recommend RJMetrics.

I work for Shutterstock, a company that is now large enough to have gone through several phases of data maturity (we recently became a publicly traded company, which requires a high standard of data integrity and auditability).

We use a variety of tools to look at data: Google Analytics for traffic, a home grown BI and A/B testing framework, Great Plains for financials, our own open source toolkits for client side event tracking and data visualization (http://bits.shutterstock.com/?p=277 | http://code.shutterstock.com/), and RJMetrics to track and explore KPIs for our smaller business units that don't have dedicated analyst teams.

RJMetrics makes it incredibly easy to explore and visualize data without having to spend dev time pulling different views. They also have native support for things like cohort analysis and customer lifetime value (which saves a TON of time in Excel). In addition to the dashboards they provide (that a non-technical person can change and improve) they also have regular automated emails that help you and the team feel the rhythm of your business.

Basically: unless you are ready to devote a team of BI analysts to your product, RJMetrics gets you 95% of what you need with 5% of the effort of rolling something on your own. You'd be crazy to try and replicate this kind of functionality at an early stage of your business.

We measure web traffic with Google Analytics. Free, industry standard, works.

We measure app metrics and server/service health with Librato Metrics. A local statsd instance collects UDP packets from all over our infrastructure then consolidates and dumps them out to Librato every 60 seconds. We track thousands of data points every minute and it keeps up without issue. Librato offers great and flexible visualization of your data without breaking the bank - highly recommended.

Co-Founder/CTO at Librato here, just wanted to say thanks for the kind words, and include a link ;-): http://librato.com

We use Google Analytics, KissMetrics, New Relic, Pardot, Tracelytics.

I always go back to Google Analytics to check whether something else is broken, its just the de facto standard against which everything else is compared.

We recently rolled out KissMetrics for customer tracking and have been very impressed with it so far. The biggest difference of course is the base unit for KM is an action someone took, rather than just a pageview.

Being able to tie back those actions down to one user is also great when you are starting out to see the typical path someone takes before performing some action. Google Analytics only shows funnels in aggregate as all data is anonymous.

The general hierarchy of tools typically goes Google Analytics, then KissMetrics/Mixpanel, then Pardot/Marketo/Intercom.

Careful though when loading up all these scripts, at OpenSesame we are very tool happy and it became a problem for page load times. http://bit.ly/RABRJv

Log every single action, decision, call, message, visit, and fault in detail. Log it with structure. Log it in JSON.

Now go start playing with RecordStream: https://github.com/benbernard/RecordStream

You can perform any post-facto analysis you can dream up - tomorrow or three years from now.

Sounds interesting, care to give an example how you use it exactly? You dump everything to JSON and then simply run some RecordStream queries on the data? Or do you generate something visual?

If you're lucky enough to log straight to JSON, you can pipe straight into recs. Otherwise, recs-frommultire is a great way to get the stream started.

From there, I typically end up using recs-grep or recs-xform to filter or transform the raw data. This is when you can isolate the data of interest or exclude data you don't particularly want. You can also transform dates and times or change units of measure.

The actual analytics tend to be done with recs-collate. This lets you aggregate in almost any way you desire and get a ton of great stats out.

For presentation, reds-totable gives you a nice, quick glance at results, and recs-tognuplot gives you quick graphs. For additional fun and presentation, recs-tocsv is a good way to go.

A really, really, simple example: 1) cat your webserver log to recs-frommultire, defining an expression to pull our URLs, page lantencies, and response codes 2) pipe to recs-grep and filter out URLs that aren't of interest, like favico gets

2) pipe to recs-grep to select only 200s 3) pipe to recs-xform to translate dates into something like a utc millisecond 4) pipe to recs-collate to build a histogram of average latencies for each unique url 5) pipe to recs-totable for prettified output

The real power of the system lies in the ability to chain transforms. You can bucket out percentiles, dice by many dimensions, and collate along many axes. Best of all, since it's just shell commands, you can mix in perl or python for extra-complex steps.

Home-grown systems deserve a place in this discussion as well.

For my point I'll break up analytics into halves: (1) collection and storage of data (2) analysis and presentation

Splunk is an example of something that only does the second half, as collection and storage are done in your own application logs. The downside as noted here is that this requires much customization to teach splunk how to interpret your logs.

On the other hand systems like GA, Mixpanel, Omniture, etc. provide powerful analysis and presentation out of the box, but keep the data locked up in a proprietary format that's usually never available outside their systems.

My personal preference for start-ups is to follow both paths: (A) implement some closed system like GA/Mixpanel that will work immediately (B) simultaneously record all useful data yourself and implement analysis systems as is justified

edit - i guess you can't hack it to look like bullets with spacing

At SnowPlow we break home-grown analytics down into five stages:

     Track -> Collect -> ETL -> Store -> Analyse

SnowPlow straddles all five stages - and the data is in non-proprietary formats throughout.

Have a look at https://github.com/snowplow/snowplow if you want to find out more...

Nice, I've gotten close to building this exact data flow from scratch and it was not fun.

You're just missing step 6 ("-> Present"). I'd build some really simple jquery datatables template that will present the output of a hive query, if only to have some screenshots for non-technical people involved in the decision.

Thanks jparker, and you're totally right - we are still missing 6. -> Present :-) We will get round to it - it should be easier once we have connected Infobright as a storage option alongside Hive...

Mixpanel lets you easily export all of your data at any time, either as a raw data dump or filtered by date range, property or segment.

https://mixpanel.com/docs/api-documentation/data-export-api

It's easy to get analysis paralysis with analytics, because pretty much anything can be measured now. You'll need benchmark analytics like visits, pageviews, etc; then you'll want key performance indicator (KPI) metrics that change over time. The KPI stuff will vary depending on what you think is important for users to do. For instance, if you were an e-commerce store, then you'd want to look at cart abandon rates, conversion rates by category, traffic by category, conversion rates by traffic sources, week over week revenues, 30 day daily average, 90 day daily average. For cohort analysis and anything money related, I've found custom sql queries displayed on a reporting page isn't too hard to do, and it's great when your KPI's change or you want to add more into reporting later.

Mixpanel (web) and Mixpanel (iOS).

Our Product/Marketing Maven and iOS engineer are both obsessed with Mixpanel.

I know Mixpanel is super useful for measuring specific actions, flows and features within a webapp that you want to measure and promote, but does it have utility beyond this use case? How are you guys using it?

Were I working on a webapp at my current startup, it would certainly be my first choice as an analytics tool of the ones I'm familiar with. However, I'm not working on a webapp. Instead I'm working on a javascript library/framework that developers will integrate into their own products once it is released, I'm not sure whether mixpanel provides value to me except by proxy if/when our customers use mixpanel themselves and share some of their insights with me.

Actually you can use Mixpanel exactly for that. We're a B2B company and have exact same use case as yours. We provide some Javascript code that our customers add on their sites. We don't require our customers to have Mixpanel account and we also don't load our Mixpanel JS to our customers' site.

What we do is - we send requests to our server from our customers' site with key information that we want to track, and then we send those events to Mixpanel through server API (e.g. PHP) calls.

It works really well for us. We're measuring how our customers' customers are using our Javascript based widget, and are able to improve our performance, engagement, etc.

Hope this helps.

Sounds like you shouldn't use Mixpanel.

We're a consumer company: engagement, usability, etc all matter to us.

Lots of different analytics solutions suited for different scenarios mentioned in your list. Each one serves a different need even though there is some degree of overlap between them. You need to answer questions about your business to figure out which tools you should be using - Are you guys in the enterprise or consumer space? How do you market your startup's products? Do you use Email Marketing? Do you use Social Media to promote your startup or its products? What are the metrics you should be measuring to understand if your business is growing? Answer to these questions will determine which analytic solutions you should be using for your startup.

At Monetate, we rely a great deal on Google Analytics as well as a tool like Raven. With some TLC, Google Analytics can tell you a great deal. Here's a blog post that one of our marketing director's wrote recently that may be helpful: http://www.contentmarketinginstitute.com/2012/06/content-mar...

All of those products exist because they all have slightly different benefits and drawbacks. What cocktail of analytics products is right for you depends on your specific needs. In general I would say use google analytics (because it's free), and when you want to pull a report that google analytics can't give you, consider what other service(s) could.

Completely agree, which is why I asked the question. I wanted to hear more about the analytics cocktails of others and the startup they are working on to determine which ones may be useful to investigate further if their startup is analogous in someway to the one I'm working at now.

Have you seen the "What are the most popular services used by Y Combinator startups?" infographics? Mixpanel seems to be doing extremely well among YC startups.

http://blog.competemonkey.com/post/34661393079/what-are-the-...

I use google analytics as a historical record, but very rarely review it.

Mixpanel for event tracking, getclicky for real time site stats (only monitored when we have pr/marketing stuff going on).

StatsD and Graphite for user facing analytics (I run a marketplace for cranes/heavy machinery so advertisers need to review just their stuff).

I had the same problem, which is why I created Instahero: http://www.instahero.com/

You can extend it to cover any sort of reporting you need. Nothing else I've used could cover all the cases I needed.

I haven't used it myself, but the folks at Github have made Gauges (http://get.gaug.es)... It looks pretty powerful and intuitive and offers real-time analytics.

You need to be aware that every tool of this kind comes with at least 30K of javascript and at least one additional request.

Below is my current setup

Web site: KISSmetrics Google Analytics New Relic

Server: New relic

Mailing: MailChimp Google Analytics

> You need to be aware that every tool of this kind comes with at least 30K of javascript and at least one additional request.

Chartbeat's JS is only 3k gzipped (http://static.chartbeat.com/js/chartbeat.js). We work very hard to keep it as small as possible while providing as much utility as we can.

We've gotten a lot of mileage out of fnordmetric: https://github.com/paulasmuth/fnordmetric

How you measure analytics for your app instead? We are using mixpanel on our Phonegap app. What's your experience with analytics on native platforms?

We looked at a lot of solutions for tracking in iPhone apps. We tried Flurry (http://www.flurry.com/) for a while, but they wouldn't give us access to our raw event data. After more investigation, we decided to go with Mixpanel. Their web interface is great for answering quick questions and we can export all the raw event data whenever we need to more heavy analysis.

we use google analytics, mixpanel, calltrackingmetrics, and newrelic.

ChartIO?

Can you provide more details on how you use Chart.IO? Seems like it could be useful for aggregation of different sources, but that doesn't seem like something they promote as a feature they support. They mention Google Analytics, but not many different analytics tool beyond GA.

They can link with your cloud DB, mysql or other data sources. Useful for making dashboards.

I wouldn't consider Chart.io an applicable product for a startup, $185/month for a charting interface is way to expensive.

I'm using Hitsniffer: http://Hitsniffer.com for real-time analytics. I have been for a few years now. Highly recommended.

Google analytics I usually have automatically emailed to me every week. I should be more vigilant about utilizing it.