What is an acceptable score on Page Insights for a Shopify ecommerce site on mobile? Seems that nearly every one I enter scores low and in the red...
Shopify as ready-to-use solution has got it's own limits and flaws, but some of the stores were able to achieve nice and good results.
When it comes to good examples:
soworthlowing.com:
Desktop - 96/100
Mobile- 57/100
www.studioneat.com
Desktop - 91/100
Mobile: 56/100
With little to no apps and responsive images you can achieve even better results on mobile
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I'm reading the PageSpeed Insights documentation and am wondering if anyone knows how Google is determining what is considered a sufficient number of distinct samples per this FAQ:
Why is the real-world Chrome User Experience Report speed data not available for a URL?
Chrome User Experience Report aggregates real-world speed data from opted-in users and requires that a URL must be public (crawlable and indexable) and have sufficient number of distinct samples that provide a representative, anonymized view of performance of the URL.
I'm building a report centered around Core Web Vitals data and realizing some URLs have few data points with CWV timings, and I'm curious exactly how Google is handling these situations. I've been searching through docs and articles, haven't found anything with a specific reference.
The exact threshold is kept secret, so that's why you won't find it documented anywhere. However, as a site owner there are a few things you can do to work around a URL not having sufficient data:
Use the Core Web Vitals report by Search Console, which groups similar pages together, making them more likely to collectively exceed that threshold.
Look at origin-level aggregations in PSI or the CrUX API. These include user experiences from all pages on the origin, so it's much less granular, but it gives you a sense of typical experiences overall.
Instrument your site with your own first-party Core Web Vitals monitoring. web-vitals.js can be integrated with your existing analytics provider to track vitals on all of your pages. If you're integrating with Google Analytics, you can link your data with the Web Vitals Report to see how your site is doing.
Use your site with the Web Vitals extension enabled to see the Core Web Vitals data for your own experience. Your local experiences may not be representative of most users, but this can be a great tool for validating expectations vs reality.
Use lab data as a proxy. For example, lab data from Lighthouse in PSI can tell you how a mobile user on a slow connection might experience your page. This should really only be used as a last resort when no other field data is available.
When running the pages of this website through Google Pagespeed Insights tool, I receive drastically different "Lab Data" (Time to Interactive, First Contentful Paint, Speed Index) speeds when comparing Mobile and Desktop. Desktop tends to receive values under 2 seconds, and as a result, the Pagespeed Insights score is generally in the 80s or 90s on each page. The Mobile score, however, suggests the page load speed is much slower, upwards to 10 seconds. As you may guess, I cannot reproduce anything close to these loading times on mobile. The mobile and desktop experience do not differ dramatically with the primary differences being styling using CSS media queries. Would love any help understanding why these values are so dramatically different!
Images for reference:
Desktop metrics
Mobile metrics
Page Speed Insights uses simulated CPU and Connection throttling to simulate mobile conditions people may experience when displaying your mobile score (no throttling exists on Desktop score).
Not everyone has a flagship phone (far from it) so they slow the CPU speed of their server by a factor of 4 to simulate the slower CPU speeds of mid and low end phones.
Similarly they also simulate a slow 4G connection to account for when people are out and about / have no WiFi connection. SO they add additional latency and slow the upload and download speeds to reflect this.
This is why you see such big differences on your site score between mobile and desktop.
If you want to simulate a similar speed yourself you can open developer tools in Google Chrome -> Network -> Look for the drop down that says "online" and change it to "Fast 3G".
Now reload your page and you can see the effects of additional latency and slower download speeds on your waterfall.
According to my analysis, this is due to the images on this page. However, Google PageSpeed Insights is very sensitive to mobile scores than desktop scores, so the stark difference between mobile and desktop scores is natural for this tool.
Try compressing the image first (you can use tinypng.com or other online tools), then use lazyload for image.
I would like to know if it is possible to detect web forms, payment gateways, and ads on a web page in an automated manner, by running some code after crawling and indexing the web page.
To give the question some context, I would basically like to know if the given web page is being monetized in some way. If there were a program to detect the above, it would provide a way to find out if the web page is capturing leads, selling a product or service, or displaying ads.
Moreover, I would like to know: is there some form of on-page monetization that cannot be detected by using an automated program?
Yes its possible to parse a web page after downloading it - but if you need to ask the question then you still have a very long journey ahead of you before you are capable of understanding how to do this. Your question is also off topic as it does not relate to solving a programming problem.
However it is impossible to determine programatically if the content of a web page represents monetization. It is possible to make some guesses using a database of known advertisers and/or very advanced AI techniques. Come back and ask again after you have mastered data science, antagonistic / back progogated neural networks and image analysis in about 15 years from now.
How to implement mobile data loss prevention (DLP) tools? I have googled but unable to gather the information. Anybody has documentation or life-cycle, flow of Mobile DLP?
Thanks in advance.
If I understand your question right you are looking for a tool that will give you information about Data leakage goes out from your mobile device through apps like Dropbox,google,Trello etc .., We released yesterday a project called SecuriGo to give viability about application of data in more than 100 apps, take a look at www.securigo.com
I am interested in software alternatives to the Google Search Appliance (GSA) for use in a (large) university context. Has anyone experiences of migrating from GSA to an alternative solution? If so, what were the reasons for doing this (technical, financial, staff effort, etc) and have the experiences been positive?
I would recommend looking up Apache Solr , it is IMHO the best scalable, feature-rich search server out there. A F/OSS out-of-the-box solution from Apache Software Foundation and used by organizations such as Netflix, AOL, CNet etc. We had used GSA in our company for an year before moving to Solr. The move was relatively painless compared to the benefits accrued.
Since it integrates with a RESTful interface it can be integrated into your platform of choice without language/platform tie-ins. Give it a whirl!
We are currently moving from Google (GSA) to Microsoft FAST (specifically FSIS).
The reason is simple, we are not satisified with the Google experiance from a supportablity and manageability perspective. We have chossen FAST because it gives us a platform that can scale as our needs grow over the next few years. Also it gives us a very fine level of control. What I mean is it will give us the ability to define custom fields and then control how these fields are populated.
The company I work for is a Google GSA partner and has developed a solution on top of the GSA. We also have a cloud solution with very similar benefits to the GSA and a host of things that the GSA can't do - like scale geographically, scale with load, upload data and have it in the index in near real-time, have nested records, deal with hierarchy etc...
In our experience, the people who migrated from the GSA to the Cloud solution did so for the following reasons.
Primarily, they did not want to manage hardware.
Most of our customers are ecommerce / media companies, and they had a lot of navigation. The GSA search throughput really struggles when you have a lot of navigations / refinements. For example if you have 20 navigations, the throughput drops from around 50 queries per second to about 12.
Indexing time - the GSA has a minimum of 7 minutes for something to show up in the index, and for ecomm / media these times are unacceptable.
GroupBy has written migration tools to allow the smooth transition from GSA --> Cloud and also the cloud platform accepts the same format that the GSA accepts.
Have the experiences been positive? Well, clearly I'm going to be biased and say yes, but there are hard conversion increases that support the clients positivity. :-)
More details at: www.groupbyinc.com