I run a monthly report which tracks session views by region, most popular knowledge articles, deflection rates, most popular product pages, software download stats, etc.
We have a new ELT member who is keen to get into the numbers around our contact centre. As I only look after the support site I need only concern myself with putting together a report which outlines what I feel will be useful information around web traffic. I want the report to be brief, and to highlight 4-5 key metrics.
Please can I have some suggestions for data you think would be useful given the target audience?
So far I am considering:
Deflection rates
Bounce rates.
Time on page
Most popular software downloads.
Global session views year to date.
Any help would be really appreciated. Thanks!
I think those metrics are great. Ideally, the value in the data comes from slicing your metrics with a dimension, ie pivoting. For example, bounce rate as an average means little whereas bounce rate by Content Group or Device Category would be more interesting.
Speaking of Device Category, consider completely isolating the metrics for Mobile vs Desktop+Tablet. Those experiences are so drastically different you'd be doing a disservice to average those metrics together.
Lastly, I'd say this new ETL member should get their own access to GA and learn how to pull the data need. GA now offers machine learning insights that quickly surface relevant drivers in metrics; a static approach to KPI reporting is becoming increasingly obsolete.
Related
Our main challenge in Google Analytics at the time is to measure the success of our magazine articles.
The problem is that views grow over time so in any timeframe we always have the older articles overshadowing the newer ones. Sidenote: The same problem occurs for measuring social media post success.
My idea of a solution is to measure the rate by which views on articles grow. An article that has a higher growth of views is much more successful than an older article with more views, but with a lower growth rate.
Alternatively something like "views within the first week(s) of publishing this individual article" would also be a good metric.
Unfortunately to some extent also the growth rates rely on this publishing period of individual articles if we are interested in an eternal high score of articles. But since we are mainly interested in recent articles, growth rate would still give us the desired result of showing the most successful recent articles.
Has anyone dealt with the same challenges and found any solution to this, in best case with Google Analytics?
These examples may help, of which I have direct experience.
In the data layer we included a date of publication for the article and then used this to determine growth. This was taken from the CRM and was relatively straightforwards for the dev team. This was stored as a custom dimension in Google Analytics.
We had nothing in the data layer but instead a I just used the date on which page views started appearing as a proxy for date of publication. Not entirely reliable, and you may want to filter by views >5, or whatever is appropriate, to avoid any hits from editors or staff before a page is visible in the site navigation.
In both cases I was exporting data either to Google Sheets (using for example the Google Analytics API addon for sheets) or BigQuery, where it was relatively straight forwards to identify the first date and then calculate, for example, views per day. In your case it would be having a function which looks at the date of publication + 7 days. You may also be able to achieve this with Google Data Studio or similar dashboarding platform.
I've been doing some research on intent data and I have some technical questions, especially about how two businesses might be collecting "contact level" i.e. personally identified web traffic details without using third-party cookies.
Some quick background: Most of the large providers of intent data (bombora, the big willow/aberdeen/Spiceworks Ziff Davis, Tech Target etc.) offer "account" based intent data - essentially when users visit websites in their network, they do a reverse IP addresses lookup, match them to know IP addresses of large companies (usually companies with at least 250 employees) and note what topics are "surging" - aka showing unusual traffic on a given week. This largely makes sense to me. I'm assuming that when a visitor shows up at your site, google analytics and similar tools can tell you what google search keywords were used to arrive at your site, and that's how they can say things like - we can "observe intent signals across an unlimited number of contextual keyword categories, allowing you to customize your keywords and layer these insights onto your campaigns for optimal performance." Third party cookies, and data from DSP's (demand side platform's enabling ad buyers to buy ads across many platforms) are also involved in providing data, those these will be less useful sources of data after google sunset's third party cookies on Chrome.
Two providers - intentdata.io, and intentflow.com are offering contact level intent data. You can imagine why that would be of interest - if the director of sales is interested in your sales SaaS tool, you have a better idea of how qualified that lead is and who to reach out to. Only one of the two providers is specific about what exactly they're collecting - i.e. what "intent" they are capturing and how they're collecting it.
Intentdata.io:
Intentdata.io looks like a tiny company (two employees on LinkedIn). The most specific statement I've found about what their data is was in an Impact+ podcast interview - Ed, the CRO at intentdata.io, mentions that the data is analogous to commenting on a Forbes article or a conversation on LinkedIn. But he's clear - "that's just an analogy." They also say elsewhere that the data they provide mentions specifically what action the contact took that landed them in the provided data.
Ed from intentdata.io is also asked about GDPR compliance in his Impact+ interview - he basically says, some lawyers will disagree but he believes their data to be GDPR compliant, and it is in use by some firms in the EU. He does mention though that some firms have asked them to exclude certain columns from the data, like email addresses.
Edit: Found a bit more on intentdata.io - looks like they build a custom setup to pull "intent" data for each customer - they don't have a database monitoring company interaction with content across social media and b2b sites, instead you provide them with "lists (names and URLs) of customers, competitors, influencers, events, target accounts and key terms that would indicate intent at different stages in the buying journey. Pull together important hashtags, details on your ideal buyer (job titles, functions, seniority) and firmographics (size, industry, location)" - then they create a custom "algorithm" from this info, and they iterate on that "algorithm" a little bit over time.
They also make this statement on their site: "IntentData.io's data is collected from observing public actions that users are taking around the web. That means that first, we observe action (not reading, searching, browsing, being shown an ad, etc.) which we believe is a more concrete manifestation of intent. Second, people are taking these actions publicly for the world to see. We do not use any cookies, bidstream data or reverse IP lookups."
Finally one piece of their sales collateral asks: What ad budget do you have for PPC nurturing ads? So their may be some targeted PPC ads involved in the "algorithm."
Edit 2: Their sales collateral also states that they use "a third-party intent data methodology that uses multi-variable linear regression analysis to correlate observed actions with a specific contact. This is the method that the LeadSift engine of IntentData.io data uses."
Intentflow.com:
Intentflow.com seems like the sketchier of the two providers if I'm honest. They provide a video walkthrough of how they get their data at intentflow.com/thesis - but I'm not following how using "traceable urls" with no cookies involved, could give you contact level information. They also say they lookup what the most popular articles/pages are for 5k to 40k unique keywords or phrases that are related to 10-50 keywords or phrases you give them to target. And they use "traceable urls" to track who visits those sites. Again - no cookies involved. Supposedly fully compliant at least with US laws. They don't provide data for the EU "by design" so presumably they're not GDPR compliant? They also claim they can identify the individuals who are visiting your website, again using "traceable urls" - it seems clear from the pitch that you're asked to reach out to your backlink providers around the web to use this traceable url.
I've seen an interview where a rep from Bombora says they tried for a while to do contact level intent data and it wasn't very useful - and it wasn't really doable in a compliant way. Ed seems to be aware they've said that publicly, and he says "that's just not true."
So what's going on here? How exactly are these two small firms getting contact level intent data? Do you think they're doing it in a compliant way?
Got more information:
Intentdata.io use public comments, likes, shares etc. on blogs, social posts via web crawling and scraping for events, influencers, hashtags, articles etc. that the customer deems worth tracking. They do some work to try and connect the commenters with an identifiable contact. They bill on a quarterly basis for this.
Intentflow.com doesn't seem to use "traceable urls" at all. They take bidstream data, and identify the individual visitors via an "identity graph." They provide a minimum of 5k contacts per month at $2 per contact, making their data very expensive ($120k+ per year). You can't get lower than however many contacts their system spits out per month so it seems like there's not a good firm limit on what you will be charged. They say they can identify ~70% of web traffic, and they only provide data on US site visitors. Each row of their output would include not just the contact, but the site that contact was shown an ad on. Definitely interesting data - but I'm guessing they will be very affected by upcoming changes to third party cookies, privacy laws, etc.
I'm looking to use google analytics for its web interface only. A large dataset such as gasoline prices would be submitted to analytics via the api and viewed. Is this possible? Or is analytics purely tailored to viewing website statistics?
The Google Analytics data model is really geared toward datasets that can be thought of in terms of users, sessions, and hits (hits being things like pageviews and events).
If your data can be thought of in these terms, it will probably work. If, on the other hand, you're trying to do things like joins or calculate averages or other statistical operations, you're probably better of using something else.
While the others are correct, Google Analytics is geared towards users, sessions, and hits. It is none the less simply an application for data analysis. The question will be how to get the data into the system.
I think you need to give us a little more information about your data set. But let me assume a few things.
You have a dataset with gasoline prices over a period of days.
you have a dataset with gasoline prices for different gas stations.
It would be really nice if this wasn't old data that this is new gas prices coming in.
If I had this dataset I could insert it into Google Analytics. Directly using the measurement protocol.
The measurement protocol has a few required things, the first being hit type. 'pageview', 'screenview', 'event', 'transaction', 'item', 'social', 'exception', 'timing'. the second would cid or session id.
Now cid I think I would probably set to the different gas stations and probably add a custom dimension with the gas station name.
As for hit I think I would probably say screenview and make an application Google Analytics account. Mainly because well this isn't a website its a little different.
Then every time the price of Gas changes I would send a screenview, cid of the station with the custom dimension of the station, add a custom metric with the price.
The main problem you are going to have is that Google analytics doesn't handle old data well. If you are going to insert this data with a date associated the date and time cant be grater then 4 hours ago or the server wont process it.
Have you considered putting it in big Query instead?
This question really is to broad or opinion based, but it was fun to consider.
It is possible to send all kinds of hits with the Measurement Protocol. But Philip is correct in stating that the data model is largely geared towards users, sessions and hits. But you could probably get a good ways with custom dimensions and metrics.
I'm currently researching a solution to monitor the performance of specific sections of a page. For example, you have a simple page with 2 images with links to other pages. You are driving lots of traffic to this page and you are experimenting with different contents on that page.
6 months after, you want to see which section of the page performed better with what kind of specific imges.
Let's imagine you require a report that should tell you the following: on average, the first spot performs better, but last week the image was bad and that's why you had less conversion from that spot.
I'd like to use such a system on a high-traffic homepage of an eCommerce website, in order to better monitor the usage of the selling spots.
I was thinking to use Google Analytics events with a positioning scheme (splitting the website in columns and rows, giving to each cell an identification ID such as a1 for column a, row 1) and keeping a local datawarehouse of creatives (images, promotions etc.), but apparently, after 10.000.000 hits per month, Analytics is recommending the premium version which is quite pricey (12k USD per month, 1 year upfront payment).
I was thinking about PIWIK as an alternative, but there is no event tracking there - or am I missing anything?
Looking forward to hearing your input on this matter.
You're better off with a provider like Optimizely for this use case. Still gonna be expensive, but it'll more quickly get you the information you need to make decisions.
We normally use multi variation tests or A/B tests to measure the success of user interfaces. Google Analytics have this feature and it is free.
This links maybe useful
https://www.youtube.com/watch?v=yDWTMOC_Dp4
https://support.google.com/analytics/answer/1745147?hl=en
The company I work for has just purchased 4 32" LCD screens to be mounted at the front of the office for demonstration purposes. Whilst we are not demonstrating (most of the time), the screens are to be used as development information screens for the whole team.
What information would people recommend displaying to be most useful to the team? Our focus is on hosted business web-apps but I am interested in what other teams doing other types of development find useful too. Pointers on how to gather the displayed information would be useful also.
Information about your continuous integration status.
Major Development Milestones that have been hit in the last week
Releases within the last month (including a short description why this release is awesome)
Use it as motivational board. The achievements of software development are seldom communicated well enough.
Since you're hosting apps for your customers, server and network status information would probably be useful.
Heck, why not create a "chat room" for the dev team to discuss issues and post a streaming version of that as well?
Schedule information, Scrum notes from that morning, a gantt chart...the possibilities abound.
Outstanding bugcount, sorted by priority and severity. You can likely get this from your bugtracking tool programmatically.
Depending on your process management
system, possibly a list of feature
requests and the percentage complete
on each of them. Again, you can probably get this programmatically from your process management / time tracking tool.
Time spent in the current development
cycle, and time remaining. Again, this should be available from your process / management / time tracking tool. You may want to use this data with your bugcounts as well to give a bugs / day fix rate.
If you're a public company with a
profit-sharing plan (i.e. stock or
options), the current price of the
stock (this can be surprisingly
strongly motivating). You can get stock data from several sources online programmatically (although a small delay may be injected unless you're paying for the service).
The movie 'Office Space'
Weather radar from intellicast.com
Latest Checkin.
Number of checkins per day
Number of customers that use software
Metrics on Bugs found/fixed and the ratio.
One screen could be an aggregated RSS feed of development topics pulled from sites such as Stack Overflow (or even Coding Horror). Not sure what your goal for these screens is, but I could see it useful to me if you had a feed with topics specific to your development team headlined. If I were there, I'd glimpse them, maybe catch an interesting thread, and go learn something. Funnel a bunch of keywords and tags through a Yahoo Pipe and dump it to the screen.
That's if they are more "informal and informational."
I think most popular pages from your webapp(s) would be a fun/interesting thing to show on a big monitor up front.
Another would be a live feed of your error reporting.
We have one monitor showing all meetings for the day, with start-end, subject, and room. I find this helpful, not only for my orientation, but also to see what other people do at our company.
xkcd, bunny, dilbert and savage chickens :-)