Use automate.io, and zapier.com to streamline a bunch of stuff too if you are pulling from multiple source. For example - I need to grab data from Intercom, Infusionsoft, ManyChat, FB Lead Forms all the time. Way easier if I automate tasks.
As mentioned below, sampling can happen, but it's pretty clear when it does. Here is a good article from Moz about it as well: https://moz.com/blog/sampling-in-google-analytics
There are cases where the GA tag won't fire or track properly, but we're talking specific cases like cookie-blocking browsers, VPNs, etc. I tell my clients that there is usually a small percentage of error to account for in GA.
As far as where to learn, there are tons of great resources. Going through Google's own training is a good start to get familiar with functionality. Once you're there, I would direct you to Lunametrics.com, Annielytics.com, and the book Analytics 2.0 by Avinash Kaushik for a good base. There are literally tons of articles (we marketers like to yell) around the web.
I've dabbled in Tableau and Qlik a little, but not PowerBI. They're great tools but take some heavy lifting to set up and get running.
I found this free course on Udacity was really helpful on getting better at A/B testing. It was created by Google employees, and it is very detailed. https://www.udacity.com/course/ab-testing--ud257
Then it's not spam. If you go to t.umblr.com is redirects you to https://www.tumblr.com, which is a known site.
If you visit a tumblr page, any referral links to another site are masked with t.umblr.com, so there must be a page linking to your site.
I just learned and tested all this with a little research.
Try one of thse: https://moz.com/blog/how-to-stop-spam-bots-from-ruining-your-analytics-referral-data https://www.distilled.net/resources/quick-fix-for-referral-spam-in-google-analytics/
Helped me out with the same problem.
Apologies for this, but a little bit more digging and I found exactly what I was looking for: https://www.google.com/analytics/web/importing#importing//%3F_.objectId%3DZxnJCS1rRuiJ1Zu-SMmHQg%26_.selectedProfile%3D
There are two basic challenges in data analysis: deciding what to measure (your metrics and dimensions, your KPIs) and deciding how to show it for greatest effect.
You're at step 1. There are lots of options. You could work out how much money the company loses by having agents mismatched with their service level, and track that quantity over time. You could work out what the peak of high-level call-ins is and work out how much money would be wasted if those agents were waiting for calls instead of servicing lower-tier tickets. You could calculate the saving based on comparing the two systems over time. These are really business questions, not data questions. Find out what people in your business need to know, and then come up with a strategy to give it to them.
As for choosing the right way to show it, here is what I've said on this topic before:
> Start by reading the great books on the topic: The Visual Display of Quantitative Information, Envisioning Information and Visual Explanations by Edward Tufte and something that covers Bertin (his 1968 book Semiology of Graphics is dated but the ideas are sound. I like Information Visualisation by Colin Ware, which takes Bertin's ideas further). Then Now You See It by Steven Few and Visualise This by Nathan Yau. You don't have to agree with those people's opinions, but those books will give you tools to begin developing your own.
Hey OP, thanks for using referrerspamblocker. I have a few remarks. Referrerspamblocker has been recently optimised. If you run our tool for the second time it will use a lot less calls as it will only update the last added filter / add a new filter. If we keep hitting the 2000 API calls, we can request a higher API limit from Google (although you are right that this is not enough by far). Also check out our segments, which do not require you to install filters, but can still give you a cleaner view of you data.
Regarding including valid hostnames mentioned in some other comments. We recently published this post to research the advantages and disadvantages of this strategy, including the data of our clients. And actually we have found that this is a very risky way of dealing with spam, since there is a big risk in possibly deleting genuine traffic.
There are a few reasons, and yes there is monetary value from this. This is covered quite well in this article
>Semalt is an SEO product that’s designed to give on- and off-page analysis such as keyword usage and link metrics. Their products seem to be somewhat legit. However, their business practices are not.
You can send events to more accurately measure user timings on pages and set them as "interaction hits" in GTM to have this reflected in time on page measurement as well.
An example would be sending a timing event every 15 seconds, thus making your time on page more accurate, but rounded down to the nearest 15 second interval.
Regarding your 5 minute comment, though I think this is way too high a bar to set, you can set an adjusted bounce rate to count a bounce as any pageview under 5 minutes.
Justin Cutroni just posted something about doing hourly, and even minute, analytics exports: https://plus.google.com/+justincutroni/posts/5ysUFX8t41q
As this is from API, you can use one of the spreadsheet import tools like Supermetrics to pull it in from the GA API: http://supermetrics.com/
Here are some of the best Marketing Attribution tools:
- Adobe Analytics
- Bizible
- Roivenue
- Attribution Insights
- Attribution Data Cloud
- Singular
- DailyStory
- TrackMaven
OWOX BI Attribution is a good tool to evaluate both, the online and the offline campaign input into your revenue. You can find out which of your advertising campaigns were under or overvalued, in order to optimize your advertising spend and optimize your advertising strategy considering how your ads perform on different devices, at different stages of the funnel
Here's more info on the tool https://www.owox.com/products/bi/attribution/"
There are no heat map and automatically tracked links/buttons in Google Analytics, you need some other tool.
For example, links tracking and form analytics are in Yandex Metrika by default. Also there are heat maps and View session recordings.
https://metrica.yandex.com/about
In Russia Yandex Metrika is using often in parallel with Google Analytics (or instead of) especially because of the unique features.
You should definitely take a look at Yandex.Metrica: https://metrica.yandex.com/about/
It's realtime, definitely we can handle this load (we have bigger clients) and it's totally free.
I'm from a product team so feel free to ask any questions here or on pm.
I guess it depends on what you're defining as a segment but have you looked in to using Google Data Studio to do this?
Would be a piece of cake to set up (and everyone loves cake) and you'll be able to put together as many charts as you need.
Here are some example reports to get a flavour of the sort of thing you could build
What are you hoping to achieve with more of a product focus? (As opposed to marketing focus?) In my experience, Adobe Analytics has much deeper capabilities than GA, supporting both product UX and marketing insights. But what you get out of it depends on your initial setup and your rollout and stack integration roadmap.
You're probably aware of this, but Adobe Analytics and Power BI have an integration: https://powerbi.microsoft.com/en-us/documentation/powerbi-content-pack-adobe-analytics/
From Moz Blog
How is Search Visibility calculated? Your Search Visibility score is calculated by:
Taking all of your rankings for all of your keywords. Applying an estimated click-through-rate (CTR) based on each ranking position. The CTR calculation ensures that higher ranking keywords are appropriately weighted in the score. Adding all of your CTRs and dividing by the number of keywords you're tracking in that Campaign, giving you a single metric of 0% -100%, calculated to 2 decimal points.
I'm currently going through some Udacity classes (free ones)
I'm working through statistics classes to get to the A/B testing class
They have a cool Data Analyst Nanodegree ... requires Python knowledge though
I've been digging around for classes as well but i don't have a sponsor. So far the Udacity classes have been the most convincing
There is a checkbox in the admin section where you can exclude Bot traffic / SPAM from your reports. If this doesnt help you have to create custom filters:
https://moz.com/blog/how-to-filter-junk-traffic-google-analytics
Most likely, it's because Moz updated their DA algorithm. They're calling it DA 2.0. https://moz.com/domain-authority-2.0
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While the other comments may be "accurate" - they certainly don't seem "helpful" or "polite." Domain Authority is absolutely a made-up metric, from a third-party company, that has no direct connection to Google, or its rankings. However, for many, it may a good internal benchmark, or as someone pointed out, perhaps good for competitor analysis. Like most things, it can be used in moderation and in combination with other reporting metrics.
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Legitimate traffic from Turkey is labeled tr in Turkish.
Are you sure the traffic is from organic search? If your organic search spiked, follow these steps to create a more robust filter for bot traffic:
https://moz.com/blog/how-to-filter-junk-traffic-google-analytics
Right.
So what I'm curious about is what you personally use these tools for, especially once you understand how off they can be compared to GA data.
Moz did a study testing GA numbers against the estimation tools and even though it was a small sample size (around 150 sites), the analysis is shocking.
https://moz.com/rand/traffic-prediction-accuracy-12-metrics-compete-alexa-similarweb/
Are you comfortable making big decisions based off these tools?
So are you comfortable basing big decisions off the standard of error you calculated from just your own site?
They use a few different methods to make their guesses. The main one is a user panel, which is a small group of people (largest I know of is SimilarWeb which has a reported panel of 1M) that opt-in to having their web activity tracked and then the estimation tools extrapolate their activity to the entire web.
So they look at what sites this panel visits and how often, and then use that data to try and guess how many visits other websites get.
Obviously GA is the way to go when you only want data on your own site, but there doesn't seem to be anything super accurate when it comes to checking out competitors.
Check this article out: https://moz.com/rand/traffic-prediction-accuracy-12-metrics-compete-alexa-similarweb/
They seem really off most of the time...
Don't worry about the late response. I'm more interested in learning from this experience then I am actually answering the question. You'll have a Reddit Gold on the way for your efforts, by the way.
I ran the modified code you supplied and this was the error. I did upload a test file yesterday which is in the same format as the larger file with millions of rows. It is here
I'm a contractor/at an agency, but I can tell you about one of the best implementations I've seen.
They use a customized implementation of Snowplow to store everything digital related - websites, mobile apps, marketing apps. Additionally, on the same storage they dump data from the adserver, DMP, CRM and a few other databases (HR and some ERP systems). There are 3 (4) levels of aggregation:
1) The above data is stored on Amazon s3. It is processed via Amazon Data Pipelines. Aggregations here are kept to a bare minimum and the team is very careful not to bloat it.
2) Data is loaded to Redshift once a day where more aggregations are made, but the team is still very delibarate about it.
3) Dashboards and reporting is done via Tableau server. Analysts aggregate and model the data in whatever way they see fit. Since everyone is in their own room so to speak, they are not concerned with the bloat.
When the analyst wants fresher data or a very customized view, she downloads it to a local database or if she's gonna use it regularly/too large, she spins an Apache Spark instance (a few clicks on AWS), and uses R + Shiny to do the work. Spark is also how they put models in production for personalization and mark. automation.
Reporting is accessed via an intranet, which is a drupal site. The analysts use their own tools, obviously, mainly R and Tableau. Manager cats use Excel and Tableau.
This is deployed at a full service hotel chain with ~40 locations. The (this) analytics team is 8 people + 2 points of contact.
Here are suggestions I have gotten from other threads, in case anyone is interested and would like to add anything:
Agreed.
And you can also apply for freelancing jobs on Upwork.com on the side.
But the best strategy is definitely building a network of clients in the real world rather than online only.
I'd check into behavioral analytics which streams all sources from all social media platforms, CRMs, mobile..BA really is a one stop shop to source data from disparate sources, both structured and non structured..The company I work for published this wiki a while back and it's always being updated..It's a great source..
http://www.cooladata.com/wiki/pages/viewpage.action?pageId=1572895
Also, this post on Capterra covers what you're asking..I think:) It's a great source, cuz you can see what others are saying about the products mentioned..
UTM tagging your URL.
See the tool here to create your URL.
See the report for your tagged URLs here.
Make sure you filter by the correct source/medium that you tagged your URL with.
You can build it out in excel or google sheets if you have all the data sources to save money? When you say uploaded do you mean SQL?
There is a free trial version of Tableau if you want to test out. Also just google "excel dashboards", there are also cheap courses you can take in udemy that might help you build out what you want.
Here is a link to some free excel dashboard templates. https://exceldashboardschool.com/
Udacity had a scholarship program last year, intro to data science. It had 3 parts: one about descriptive statistics, one about SQL and the third one about python. I didn't like the python one at all, complained to my then software developer colleagues that it's impossible to learn. They recommended this course to get familiar with how programmers think: https://brilliant.org/courses/computer-science-fundamentals/
Udacity, Udemy, lynda,com, coursera - these all have courses on data analysis.
Do you have a particular area you'd like to explore with analytics? Maybe that could help you get started and help you get over your fear of numbers.
If you just want to dip your toes in it so to speak, you could try learning Google Analytics to see how you like actually working with data. It's easier to learn than most programs and it provides a lot of insights.
Go for Tableau. Tons of companies need help simply visualizing their data. I would even recommend getting certified (it's a nice talking point in an interview). You can find courses that teach you what you need to know on sites like Udemy.com for $10 - $20.
I've never used Looker or Data Studio, and haven't seen a lot of job postings asking for that requirement (at least here in the DFW area). Whatever you do, stay away from IBM Cognos.
Yes, it's possible.
There are different Attribution models, such as:
- First Click
- Last Click
- Last Non-Direct Click
- Data-Driven (GA360)
- Linear attribution model
- Time Decay attribution model
- Position Based attribution model
- Funnel Based Attribution model
You could try out OWOX BI Atrribution to measure the performance of any events, including offline ones, for your business. It's pretty easy to configure and it's more accurate. Here are more details about it https://www.owox.com/blog/articles/funnel-based-attribution-model/
I believe Analyzecore and OWOX have articles about how this works: http://analyzecore.com/2017/09/28/marketing-multi-channel-attribution-model-based-on-sales-funnel-with-r/ https://www.owox.com/blog/articles/funnel-based-attribution-model/
Did you heard about this attribution? https://www.owox.com/c/na - evaluate each step in the conversion process, not only the final one - include offline orders, calltracking - сalculate the probability and value between the steps of the funnel Watch how it works: https://www.youtube.com/watch?v=sId2AQ9_vzg&t=1029s
Yes it certainly has been happening for some time now. The difference here is that google has moved the Google Analytics reporting console from https://www.google.com/analytics/web/ to https://analytics.google.com/analytics/web/ instead. Basically I had to manually remove what was originally the GA tracker endpoint entry that was blocked in my hosts file as well as unblock the domain in uBlock Origin in order to see my reports. This seems to be a new thing that Google has done in the last 24 hours.
I have done the top channels and source/medium report for you. Just import this custom report:
https://www.google.com/analytics/web/template?uid=DRSQCSTqQoip3UFNfw54LA
(I won't see your data or anything - all sharing custom reports does is share the template.)
Then I'd advise clicking edit on the custom report to see how it is done. The main difficulty I have is knowing what things are called as names for each thing changes over the years. "Default channel grouping" is your channels these days.
Once you have it down, you can import this into hundreds of properties.
You may want to check out https://www.google.com/analytics/partners
It's a list of agencies that are certified directly by Google to do exactly the type of work you're describing.
While I agree that you should look into GTM, it does have a decent learning curve and isn't a one-click fix.
definition on GA: Unique Pageviews is the number of visits during the specified page was viewed at least once.
So if user A clicked on Page 1, Page 2 and Page 3...Unique Pageviews would show 3...when in fact it's one person...
You need to create a custom report with pageviews, unique pageviews and users...you'll see different numbers for all 3 metrics. Try this custom report template: https://www.google.com/analytics/web/template?uid=PtEJ4hthQZCmLkFbFD75vg
Same! We self-hosted Metabase on AWS for the last 3 years to get analytics from Redshift. Actually, it's pretty easy and cheap to self-host if you have someone on your team responsible for infra/DevOps. Btw, Metabase (like many others) has just released "a migration guide".
For those of you still in the middle of searching for a new home for your analytics and dashboards, I saw this Product Evaluation matrix on the Chartio community that may help you at selecting the next product/vendor.
It is only possible to capture users going backwards in the funnel when using the Goal Flow report. In the Funnel Visualization you would see the backward move as an exit.
You must have used the right regex, but it is always good to test them with some URLs we might doubt if they will trigger or not. I usually test every regex code here: http://regexpal.com/
Can I ask what language you're using and how you're setting it up?
I'm not aware of a solution that pulls directly from the stores -- perhaps someone else is.
In my company we use a service called Appfigures (free for up to 5 apps, quite affordable beyond that), which can pull the data from the app stores and then provide them through an API. Power BI has a connector for Appfigures which makes it easy to get the data out, and alternatively it's not too difficult to do it manually in Excel using Power Query.
If you're using the GTM data layer, you should be able to use something like this: http://www.codeproject.com/Articles/28363/How-to-convert-IP-address-to-country-name
to look at the IP and lookup the country. You'd then set your rules for the tag to only fire when that daya layer value was set to whatever you needed it to be.
Have you tried Google's Data Studio?
I haven't fully dove into it yet but it seems it can be a granular as you can be within Google Analytics. There's a couple real examples you can test if you scroll down a bit and they can be used as starting templates.
Most companies will use some form of single authentication. Basically, once you are logged in as your unix or windows user, that will be used across all the other applications. I have been accustom to single sign on at most companies. So when I go to drop box or workday I am automatically authenticated.
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I think Auth0 is one.
https://auth0.com/blog/what-is-and-how-does-single-sign-on-work/
You can also use Google Page Speed Insights to grab page speeds for your or any one else's sight. They also have an API you can use if you need to pull lots of page speeds. https://developers.google.com/speed/pagespeed/insights/
I prefer parse hub https://www.parsehub.com
It let's you use an input table. For instance if you want to find competitor store location based on zip code, and have to enter in a zip code to a field and search for stores, you provide parse hub a list of zip codes and it will enter a zip, scrape the results, and repeat until it have all zip codes covered.
I'm in progress of implementing a Kibana dashboard to show near real time graphs of products in a sequencing queue and has been fairly easy to setup.
It's part of the Elasticsearch stack aka "ELK Stack".
The questions is extremely vague.. Is it a native app or a wrap? What type of integration are you looking for and can implement?
As a safe bet, take a look at Firebase - it might just be what you're after.
Make sure you haven't fucked up the regular expression for the IP.
Use this tool. Enter some IPs in the text below, yours included, and enter the reg expression you used to check if it highlights all the IPs or just yours.
Do you have a high level understanding of what segment is and how it works? If so, this is simply as easy as adding GTM as a destination in Segment. https://segment.com/docs/destinations/google-tag-manager/
A tracking plan is as you said, like a reference. For example: https://segment.com/academy/intro/how-to-create-a-tracking-plan/
Are you using spreadsheets for planning in your team? I'd love to hear your experience.
I'd look at Tableau Blueprint https://www.tableau.com/learn/data-culture
Creating a analytics function is really about changing the culture. Organisations need to value data as critical element to everyday's business decisions.
The biggest challenge you will face is not a technological one, but rather how to engage their people and manage change.
Here buddy: https://www.tableau.com/solutions/topic/google-analytics https://www.tableau.com/solutions/workbook/facebook-connector
Hope you find it useful!
edit ps.-you can track Adwords in your GA account and then get that info into Tableau.
https://www.amazon.co.uk/LaMetric-Time-Wi-Fi-Clock-Smart/dp/B017N5FP0E - These are cool and quite a bit cheaper than SMIRL and FLAPIT. Plus it is all digital and can display loads of information from different sources.
This one is a classic :
It is a bit more oriented towards bigger businesses than Startups but it helps you having the right mindset to generate impact for sure.
As everybody else here says in different ways, do these three steps 1: find out the business problems people are trying to solve by going to where they work and sitting down with them. LITERALLY where they work. The gemba, as it's called 2: this will tell you the decisions they need to make. 3: this will tell you the data they need to make these decisions. A handy heuristic, once you've started providing data ask the recipients what decisions they COULDN'T make if they stopped getting it. If they couldn't think of any, you're providing the wrong data.
Have a read of what people have found before you. They've written it up so you can learn it quicker than they did. I'd define myself as a systems thinker, and so what I'd recommend is skewed towards that way of thinking This guy is good and has a book coming out soon specifically about how data can provide value when analysed properly. https://www.leanblog.org/tag/process-behavior-charts/ This guy writes well about something most analysts have never heard of it, it's worth an hour of your time and is invaluable. Trust me, browse it. There's HUGE amounts of brilliant stuff online. One of the best books I've ever read on this is Understanding Variation, https://www.amazon.co.uk/Understanding-Variation-Key-Managing-Chaos/dp/0945320531 It's short, oriented to problem solving and process understanding, and eminently practical.
Your job sounds brilliant by the way, but don't get bogged down in learning software packages. People who receive your output need to know what it MEANS. This can often be left out of fancy pretty graphs. Analysis should produce insight, not just the workings out. Get to know the business and be a business person, not just a data person. Data has no meaning stripped of context, and you should steep yourself in context.
Many organizations have poor Adobe Analytics implementations that have devolved over time. I suggest checking out my book on the product (https://www.amazon.com/Adobe-SiteCatalyst-Handbook-Insiders-Guide/dp/032185991X) or you can check out free Adobe Analytics blogs here: http://analyticsdemystified.com/category/adobe-analytics/
Read Web Analytics 2.0 by Avinash Kaushik
Avinash was/is an analytics evangelist for Google and used to head analytics at Intuit. The book will give you a great grounding in online measurement and has examples of a bunch of reports.
I'd also grab a copy of the Excel Bible for whatever year you're using. It gives you scenarios for using different functions and macros and examples of everything.
All the analytics packages have training you can take, just look around their sites.