The top events report in analytics is showing really strange numbers and I'm not sure why. It was noticed because a bunch of the same event category/actions (with different labels and pages that they would happen on) would have the exact same amount of events occuring (ie: 8 with 83, ~15 with 62, ~75 with 21) yet these events are on pages with drastically different pageviews so they shouldn't have such similar counts for clicking the contact button)...
Also, if I make a custom flat table report and report on the same numbers they show what seems to be a much more accurate picture... Is there something odd about the numbers in 'Top Events' that I'm not understanding that would mean the numbers it's reporting are correct, or is it actually just messed up/a bug/etc?
note: also notice in the custom report it also reports on 4 different events from the same page happening throughout the year (as the email changed several times) whereas the top events report only shows 1... The single item reported in Top Events corresponds to the 3rd item in the flat table
Top Events:
Custom Flat Table:
I'm under the impression that you didn't set these event triggers up, so these are spambots that are sending fake event data to your analytics. You may see some spammy referral data in your Referral reports too (unless you've done some filtering already).
Since you mentioned that the events don't correlate to pageviews, they are likely ghosts (They are just sending analytics data without actually visiting your site). You'll want to set up something like a Hostname filter to prevent ghost referrals from sending data to your property without actually visiting your server.
For reference, if they were not ghosts (and were actually going to your site), you'd need to either set up more specific Source filters in GA, or a server-side blacklist.
Here is a good article on the motives behind spambots, and here are some options for how to filter them.
Related
Not sure if this is even possible - but we are looking for a way to trigger mailchimp newsletters based on a custom field value in a Wordpress website.
Basically we will have a field value that holds "the number of miles" a person has walked based on the data they enter. We will be calculating the "total miles".....when they reach 100 miles for example we will need an email to trigger from Mailchimp....then 200 miles will trigger a 2nd email and so on....
Does anyone know if this can even be done with Mailchimp? If not is there a better approach to handling this?
THANK YOU!
If you are familiar with Python, I'd recommend using a Jupyter notebook for this to cut down on development work. You could set it to run at regular intervals checking the status of each user (running either on your computer or a server), then updating the merge tag of the status in mailchimp. You can have automations that are triggered when the merge tag of distance is a specific value, say 100 they get the 100 email, 200 they get the 200 email. (You could also do it so when a user hits a certain milestone their merge tag is updated in MailChimp but from my experience that's a little more work.)
Net net there are a few ways to achieve your goal but I think using a Python notebook using pandas to manipulate the data and the mailchimp3 mailchimp API client would be the lightest lift.
TIP: Mailchimp currently has a bug where merge tags information is not always accurately represented in the UI. So for example if via the API you added 500 people with the Distance merge value of 200, and checked that via the UI how many people had a value of 200 for Distance you would likely see an inaccurate number displayed for the count in the UI. If you export the list, you will see the correct number that is reflected in your API update. To be clear, in some cases UI does not display the accurate number for users with that merge tag or value, but if you export the list with that merge tag/value via the UI it should match what you pushed to the API. This is currently an open ticket.
I have recently been building an application on top of Greg Young EventStore as my peristance layer and I have been pondering how big should I allow an event to get?
For example I have an UK Address Aggregate with the following fields
UK_Address
-BuildingName
-Street
-Locality
-Town
-Postcode
Now I'm building the UI using React/Redux and was thinking should I create a single FAT addressUpdated Event contatining all the above fields?
Or should I Create a event for each of the different fields? and batch them within the client until the Save event is fired? buildingNameUpdated Event, streetUpdated Event, localityUpdated Event.
I'm not sure if the answer is as black and white ask I have asked it what I really would like to know is what conditions/constraints could you use to make the decision?
should I create a event for each of the different fields?
No. The representations of your events are part of the API -- so you want to use spellings that make sense at the level of the business, not at the level of the implementation.
Now I'm building the UI using React/Redux and was thinking should I create a single FAT updateAddress Event containing all the above fields?
You don't need to constrain the data that you send to your UI to match that which is in the persistence store. The UI is just a cached representation of a read model; there's no reason that representation needs to have the same form as what is in your event store.
Consider the React model itself -- your code makes changes to the "in memory" representation of your data, and then the library computes the new DOM and replaces it, which in turn causes the browser to update its view, which in turn causes the pixels on the screen to change.
So taking a fat event from the store, and breaking it into field level events for the UI is fine. Taking multiple events from the store and aggregating them into a single message for the UI is also fine. Taking events from the event store and transforming them into a spelling that the UI will recognize is also fine.
Do you have any comment regarding Arien answer regarding keeping fields that need to be consistent together? so regardless of when your snapshop the current state of the world it would be in a valid state?
I don't believe that this makes sense, and I'm not sure if it is possible in general.
It doesn't make sense, because "valid state" is a write model concern only; events are things that have happened, its too late to vote on whether they are valid or not. For instance, if you deploy a new model, with a new invariant, it still needs to respect the history of what happened before. So you can build a snapshot for that new model, but the snapshot may not be "valid". Too bad.
Given that, I don't think it makes sense to worry over whether each individual event in a commit leaves the snapshot in a valid state.
In particular, if a particular transaction involves multiple entities, it is very likely that the domain language will suggest an event for each entity (we "debit cash" and "credit accounts receivable"). The entities themselves, of course, are capable of changing independently of each other -- it's the aggregate that maintains the balance.
You have to bundle al the information together in one event when this data has to be consistent with each other.
So when you update one field of an address you probably get an unwanted address.
This will happen when the client has not processed all the events at a certain time due to eventual consistency.
Example:
Change address (City=1, Street=1, Housenumber=1) to (City=2, Street=2, Housenumber=2)
When you do this with 3 events and you have just processed one at the time of reading you could get the address: (City=2, Street=1, Housenumber=1).
If puzzled, give a try to a solution that is easier to implement. I guess "FAT" event will be easier: you will end up spending less time for implementing/debugging/supporting.
It is usually referred as YAGNI-KISS-Occam's Razor principles.
In theory and I find it to be a good rule of thumb is to have your commands and events reflecting the intent of the user staying true to DDD. You can find a good explanation of the pros and cons about event granularity here: https://medium.com/#hugo.oliveira.rocha/what-they-dont-tell-you-about-event-sourcing-6afc23c69e9a
I'm developing a basic messaging system on the Parse.com at the moment and I have noticed in the Events Analytics screen I'm hitting 30,000+ requests per day. This is a shock considering I'm the only person using the system at the moment. Obviously with a few users I would blow my API request limit straight away.
I'm pretty experienced with Parse.com these days, so I'm lean with queries and I'm alert to not putting finds, saves, retrieves, etc in for loops. I also understand that saveAll() on an array of ParseObjects doesn't always limit the request count to 1 (depending on relationships inside that object).
So how does one track down where the excessive calls are coming from?
I see the above Analytics > Performance > Served Requests data, but how do I drill down to see if cloud code or iOS is the culprit?
Current solution is to effectively unit test each block of Parse code and look at the results in above screen.
For the benefit of others who may happen upon this thread with the same questions, I found some techniques to hunt down where excessive requests are coming from.
1) Parse's documentation on the API's themselves is really good, but there isn't a lot of information / guides for the admin interfaces. Under: Analytics -> Explorer -> Make a table there is a capability to download all the requests for a specific day (to import into a spreadsheet). The data isn't very detailed though and the dates are epoch timestamps, so hard to follow. At least you can see [Request Type, Class, Installation ID] e.g. ["find", "MyParseClass", "Cloud Code"].
2) My other technique was to add custom Analytic events to the code. So in Cloud Code for example, I added the following line to each beforeSave and afterSave event:
Parse.Analytics.track('MyClass_beforeSave', null);
3) Obviously, Parse logs these calls in the Logs window, but given you can only see the most recents transactions and can't clear them, I found it mostly unhelpful in tracking down the excessive calls.
I want to look at the effect of having performed a specific action sequence at any (tracked) time in the past on user retention and engagement.
The action sequence is that of performing an optional New User Flow.
This is signalled to Google Analytics via sending it appropriate events. That works fine. The events show up in reports as expected.
My problem is what happens to results when I used these events to create segments. I have tried two different ways of creating a segment based on this in Advanced Segmentations, via Conditions (defining the segment via the end event, filtered over users not sessions), and via Sequences (defining start and end events, again filtered over users not sessions).
What I get when I look at various retention/loyalty reports, using either of these segments, is ever so very clearly a result which is doing this segmentation within session, not across uses sessions. So for NUF completers , I am seeing all my loyalty/recency on Session 1, in which people are most likely to do the NUF, if they ever do it at all. This is not what I want. (Mind you it is something that could be really useful in other context, with another event! But not for the new user flow.)
What are my options for getting what I want? I see two possible ways forward:
Using custom dimensions, assigning a custom dimension value in the code when the New User Flow is completed. However I do not know if this will solve the cross-session persistence problem.
Injecting a UserID, which we do not currently do, and (somehow!) using the reports available when you inject a UserID to do this.
Are either of these paths plausible? Is there a better way forward? Is it silly to even try to do this in Google Analytics? I'm way more familiar with App Tracking solutions (e.g. Flurry, Mixpanel, DeltaDNA) which do this as a matter of course, than with Google Analytics, and the fact this is at the very least awkward in Google Analytics is coming a bit of a surprise.
thanks,
Heather
we've got a GWT application with a simple search mask displaying the results as a grid.
Server side processing time is ok as well as network latency.
Client rendering time is ok even on low spec hardware with internet explorer 6 as long as the number of results is not too high (max 100 rows in the grid).
We have implemented a navigation scheme allowing the user to scroll up/down the grid. That's fast enough also.
Has anybody an idea if it is possible to display the first 100 results immediately and pull the rest in the background? The GWT architecture allows this. However I'm interested in possible pitfalls e.g. what happens if the user starts another query while the browser is still fetching previous results etc.
Thanks!
Holger
LazyPanel and this blog post might be a good starting point for you :)
The GWT Incubator has also many interesting (albeit not always complete/perfect/stable) tables and other pagination solutions - like PagingScrollTable.
Assuming your plan is to send the first 100, and then bring the rest, you can use bulks for the rest of the results. then, if a user initiates another search, you just wait for the end of the bulk ( ie, check between bulk retrivals if you have a pending query ).
Another way you can go is assign identifiers to the user searches. this will make the problem of mixed results non-existant, and will also help you with results history for multiple searches.
we found that users love the live grid look & feel, which solves most of those problems, but that might not be optional always.