We're setting up adwords tracking at the moment, but one of the requirements is that we let adwords optimise based on our net earnings figures, which only our backend is aware of. For google analytics, we send these figures via the data measurement protocol. Is there something similar to use for adwords? Or what is the approach given those requirements?
https://developers.google.com/adwords/api/docs/guides/conversion-tracking
I've seen there's offline conversion tracking here: https://support.google.com/google-ads/answer/2998031?hl=en
But if my understanding is correct, this will require some manual work. Is there a way to achieve the same thing in an automated way?
Related
I'm having trouble pulling just the price for these sites into a Google sheet. Instead, I'm pulling multiple rows/currencies, etc. and I don't know how to fix it
1---->
https://www.discountfilters.com/refrigerator-water-filters/models/ukf8001/
//main/div/div/div/div/div/div/div/div/div[1]/span/span/span
2---->
https://www.discountfilters.com/refrigerator-water-filters/models/ukf8001/
//div[1]/form/div/div/div[1]/div/div/div[2]/div[1]
3---->
https://filterbuy.com/air-filters/8x16x1/
//div[2]/div[1]/div[3]/span
I tried the xpaths above and it's giving me all the data instead of just the discounted price (row1) that I'm looking for.
try:
=INDEX(IMPORTXML(A1, "//div[#class='price mt-2 mt-md-0 mb-0 mb-md-3']"),,2)
regarding issues on multiple websites you are trying to scrape.. ImportXML is good for basic tasks, but won't get you too far if you are serious in scraping:
If the target website data requires some cleanup post-processing, it's getting very complicated since you are now "programming with excel formulas", rather painful process compared to regular code writing in conventional programming languages
There is no proper launch & cache control so the function can be triggered occasionally and if the HTTP request fails, cells will be populated with ERR! values
The approach only works with most basic websites (no SPAs rendered in browsers can be scraped this way, any basic web scraping protection or connectivity issue breaks the process, no control over HTTP request geo location, or number of retries)
When ImportXML() fails, the second approach to web scraping in Google Sheets is usually to write some custom Google Apps Script. This approach is much more flexible, just write Javascript code and deploy it as Google Sheets addon, but it takes a lot of time, and is not too easy to debug and iterate over - definitely not low code.
And the third approach is to use proper tools (automation framework + scraping engine) and use Google Sheets just for storage purposes:
https://youtu.be/uBC752CWTew
I am working in an application that gathers a user's voice input for an IVR. The input we're capturing is a limited set of proper nouns but even though we have added hints for all of the possible options, we very frequently get back unintelligible results, possibly as a result of our users having various accents from all parts of the world. I'm looking for a way to further improve the speech recognition results beyond just using hints. The available Google adaptive classes will not be useful, as there are none that match the type of input that we're gathering. I see that Twilio recently added something called experimental_utterances that may help but I'm finding little technical documentation on what it does or how to implement.
Any guidance on how to improve our speech recognition results?
Google does a decent job doing recognition of proper names, but not in real time just asynchronously. I've not seen a PaaS tool that can do this in real time. I recommend you change your approach and maybe identify callers based on ANI or account number or have them record their name for manual transcription.
david
I was looking at the documentation for uploading anchors and at first I started looking at Microsoft Azure Spatial Anchors. Then I came across the Google Cloud Anchor. I couldn't find any documentation mentioning the pros and cons of both libraries.
On an abstract level, I think that both libraries function the similar way to upload the anchors along with the features to a cloud service and be able to retrieve them by a uniqueId.
Is there any difference between them? Which is better?
Google Cloud Anchors is built-in to the ARCore library. If you're already using ARCore for Android, adding it is pretty straight-forward. That said, the docs recommend that the user scan for 10 seconds (around an object of interest), so you probably want to change the UI / onboarding for the user. The biggest limitation, is that the Cloud Anchors are only saved for 24 hours.
Azure Spatial Anchors do not have the 24 hour limitation. Their docs are pretty bare-bones. No API documentation or anything, but it looks pretty straight-forward based on their sample app and allows for either java(kotlin) or the NDK.
I've noticed that certain apps on Android (ie. gboard) support translating phrases such as 'poop emoji' into the actual emoji as part of speech recognition. I was wondering if this is something that is supported through google's cloud speech APIs that I could similarly use in my own applications?
In my initial scan of the API I can't see anything that might indicate a way to turn this on (ie. RecognitionConfig et.al has no obvious toggles for it), and in some quick one-off tests in my own app I wasn't provided emoji-fied results from the service.
I've done a bunch of googling but found nothing so far.
Any insight here would be awesome, thanks!
-edit- Thanks to the answer below I have learned this currently is not supported. I've gone to Google's issue tracker to request this feature. If anyone wishes to track the feature request the link is:
https://issuetracker.google.com/u/1/issues/113978818
The Cloud Speech-to-Text API service doesn't currently support emoji phrases recognition; however, you can use the Send Feedback button located at the lower left and upper right corners of the service public documentation, as well as take a look the Issue Tracker tool in case you want to raise a Speech API feature request in order to notify to Google about this desired functionality.
Finally, you can refer to the Release Notes section of Speech-to-Text API to keep the track of the new features and functionalities added to the service.
I plan to write a thesis about using sentiment information to enhance the predictivity of some financial trading model for currency.
The sentiment data should be twitter threads including some keyword, like "EUR.USD". And I will filter out some sentiment words to identify the sentiment. Simple idea. Then we try to see whether here is any relation between the degree of sentiment and the movement of EUR.USD.
My big concern is on twitter data. As we all know that the twitter set up the limit to see the history data. You could only browser back for like 5 days. It is not enough since our strategy based on daily sentiment.
I noticed that google have some fantastic thing like timeline about the twitter updates: http://www.readwriteweb.com/archives/googles_twitter_timeline_lets_you_explore_the_past.php
But first of all, I am in Switzerland and seems I have no such function on my google which is too smart to identify my location and may block some US google version function like this. Secondly, even I could see some fancy interactive google timeline control on my firefox, How could I dig out data from my query and save them? Does google supply such api?
The Google service you mentioned has shut down recently so you won't be able to use it. (http://www.searchenginejournal.com/google-realtime-shuts-down-as-twitter-deal-expires/31007/)
If you need a longer timespan of data to analyze I see the following options:
pay for historical data :) (https://dev.twitter.com/docs/twitter-data-providers)
if you don't want to pay, you need to fetch tweets containing EUR/USD whatever else (you could use the streaming API for this) and store them somehow. Run this service for a while (if possible) and you'll have more than just 5 days of data.