I Social Media (SM) sono applicazioni internet che consentono la creazione e lo scambio di contenuti generati dagli utenti. In questi canali si verifica una fusione tra sociologia e tecnologia che trasforma il monologo (da uno a molti, tipico dei media tradizionali) in dialogo (da molti a molti) e ha luogo una presunta democratizzazione dell’informazione che trasforma gli utenti da fruitori passivi dei contenuti a editori proattivi, sia in ambito personale che lavorativo, con possibilità di gestire, entro certi limiti, l’accessibilità ai dati. I social media vengono definiti anche user-generated content (UGC) o consumer-generated media (CGM).

Il Social Media Marketing (SMM) è la branca del Marketing che si occupa di generare visibilità su Social Media, comunità virtuali e aggregatori, creando conversazioni fra aziende e utenti/consumatori attuali e potenziali. Il Social Media Marketing include pratiche per la gestione delle relazioni online (Public Relations o PR 2.0) all’ottimizzazione delle pagine web fatta per i social media (SMO, Social Media Optimization, affine al SEO adottato i siti tradizionali). Su centinaia di piattaforme disponibili, le principali restano Facebook, Google+, Twitter (microblogging), YouTube (videosharing), Flickr (photosharing) e la caratteristica comune a tutte è che la proprietà non è dell’utente o dell’azienda che le sfrutta, ma di un soggetto terzo che ha pieno controllo sullo spazio virtuale e sui diritti di accesso e pubblicazione che in esso vertono.

Klout score alternatives Kred, Skorr

Klout is dead. What are the social score alternatives?

The epic Klout score, acquired by the digital marketing company Lithium for 200 million, has been killed.

 

What was Klout

“Klout was a website and mobile app, launched in 2008, that used social media analytics to rate all social media users according to online social influence via the “Klout Score”, which is a numerical value between 1 and 100. In determining the user score, Klout measured the size of a user’s social media network and correlated the content created to measure how other users interact with that content.” (Wikipedia, 25-05-2018).

Klout changed from a pure scoring tool to a publishing tool. Not everyone was confident about the reliability of its scores though.

Lithium Technologies, who acquired the site in March 2014, announced in May 2018 that they would end the service on May 25, 2018. The service was shut down on May 25, 2018, the same day GDPR came into force – my latest score was 66/100.

Klout score shut down. The alternatives

Remembering Klout

On May 25th 2018 the following note has been published on klout.com:

“The Klout acquisition provided Lithium with valuable artificial intelligence (AI) and machine learning capabilities, but Klout as a standalone service is not aligned with our long-term business strategy. We appreciate the loyal Klouters out there who stuck with us all these years – keep influencing!”

According to the blogger Paul Colmer, Klout could have been shut down also because it wasn’t fully compliant with GDPR, the new EU General Data Protection Regulation that is resulting very painful for many businesses. Lithium, after all, was only interested in its technology and know-how for its business, whilst Klout itself didn’t seem to be profitable.

 The alternatives to Klout score

Kred

There are two alternatives. One is Kred, on the market for a few years, that will be relaunched the 11th June.

Skorr

The other, launched very recently and less known, is called Skorr. It doesn’t seem reliable like Klout but it might improve in the future. You can check out my social skorr, download the app and check yours.

Florence: digital training for political activists and protesters

digital-activism
A former prison a centre will be the base of a learning centre for human-right activists coming from critical countries, the BBC announced on 22 May.
Students will learn how to run successful digital campaigns, looking at examples taken from the Arab Spring (mainly Facebook and Twitter).
No many doubts that Western soft power leads such operations. Westernisation is the at the core of strategies born to cascade policies and views of the world in areas considered highly critical and not easily accessible by some branches of Western capitalism.

It’s still questionable how influent can be a twitter-revolution in countries with a very high digital divide…

Google Analytics custom filters to tidy up your metrics: how to split up social media from referrals

Note: The Google URL Builder has been updated therefore I advice to have a look to this interesting guide written by Prateek Agarwal.


This post is about adding a custom filter to refine your Medium report on Google Analytics.

I am not going to talk about the “direct / none” aggregate that unfortunately include also visits that are not direct accesses like a user typing your URL or a bookmark, but any other session missing server data information. There is a wide literature about, but the problem remains unsolved.

Let’s talk about another medium category, referrals, that includes also visits coming from social media. Why not taking social media visits away from referrals?

Custom filters are a very useful tool for aggregating or adjusting some metrics before they appear on reports. In this post I’ll show you how to use custom filters to assign all visits coming from social media sources to a Medium category called “social“. Just follow this step:

Filter to separate social sources from referral on GA

Filter to separate social sources from referral on GA

The source for visits from FB mobile is “m.facebook.com” whilst Twitter is “t.co”. You can add all social media together by using Regular Expressions (RegEx). In this case you might need to do some testing. A RegEx for social filter can be this one:

(facebook.com|m.facebook.com|facebook|vk|vk.com|t.co|twitter|hootsuite|tweetdeck|plus.url.google.com|youtube|linkedin|reddit|digg|delicious|stumbleupon|myspace|flickr|popurls|friendfeed)

Remember to add also “field b = referral” because you don’t want to tas as social whatever is tagged not referral, for example a CPC campaign run through Facebook or LinkedIn.

After applying the filter don’t be impatient with Real-Time stats as custom filters might take a short while to apply properly.

A suggestion to speed up your RegEx learning process is to create a test profile (never play with the main profile!) and apply different filters there, assigning categories called social1, social2, etc. for different RegEx’s so you will reckon which is working and which is not by looking at the variable appearing on reports few hours after applying the filters.

Let’s go back to my proposals. Here’re the filters applied taken:

  1. visits from social media whose source is “facebook”, “twitter” or “google plus” have been all automatically categorised as “referrals” and will now be categorised as “social”
  2. using another custom filter, all medium assigned to “rss” will be renamed “feed” in order to join another existing category:  there is no need to have two different categories of the same type (distinction will be still available under Sources)

Here is what I had before (15/05/2013)

Before the filter...

Before the filter: no social!

and this is what I had after applying the filter (19/05/2013)

...after the filter

…after the filter, social appears!

Observations:

  • visits from social media are taken off from “referral” and placed into a new category called “social” that will also include all future social media activity tagged through the URL builder to be taken away from the “(none)”
  • RSS disappear and joins “feed” for more clarity
  • the site does not have benefit of any paid advertising source
  • direct/none stable (14% / 15%)
  • organic stable (11%)

Filters above apply only to Campaign Medium, but what about organising also Sources by aggregating at least the most relevant URL’s under just few categories? For example you can join www.facebook.com and m.facebook.com under just “facebook”.

Again, to be precise, you can use RegEx but mind that if you select all domains that contain the word “facebook” or “twitter” you might end up in adding sites that are not facebook and still link to you. For example think of the service “twitterfeed” which is not Twitter. My suggestion here is to narrow aggregation just to the most relevant categories: if you’re embracing let’s say 95% of your visits that could be enough, isn’t it?

A further action: tag your incoming links with the URL builder whenever possible

If you want to reduce the amount of “(none)” among your media, start tagging all your social media posting that links to your website using the URL builder. In this case, I suggest to keep “social” as Campaign Medium for non paid (e.g. a Tweet or a Facebook post on wall or tab) and “cpc” or “paid” for paid (e.g. Facebook advertising) aligning it to other paid sources if any (e.g. AdWords).

You can use URL shorteners, but be sure that they keep tags or your link end up in the meaningless “direct/none” category. To manage non-paid incoming links from your own social sources Lunametrics has built a simple but still useful Google spreadsheet, using the shortener bit.ly

Be consistent with tags

If many people have access to your social media stream and run digital campaigns you should do some efforts to align tagging policies otherwise you might end up in a mess on GA reports. I’ve seen reports including many similar tags all together such as CPC, cpc, PPC, paid, ads, advertising, social, socialmedia, facebook, fb, etc.

Why separating social from referrals?

Ok they are all referrals, but usually visits coming from social media come from piece of content that links to your website (e.g. a post on Facebook wall). I say ‘usually’ because such links might be also placed on social media areas such as notes, tabs, twitter profile description, about sections, etc. together with other links, but such places are less relevant than the mainstream. Other referrals (traditional, let’s say), most of the times are link placed on websites (e.g. blogs), either because they like you/find your content relevant/worth mentioning or because of your link building activity. I’m not engaging in a debate if it’s better to have “social signals” or referrals from a pure SEO perspective during the Penguin era. Let’s say that it’s important to be noticed both by search engines and (yes, apparently we’re still humans) real people, but this post helps you to distinguish among digital type of  place where you’ve been spotted on: making a parallel with geography, if the source is the name of the place, the medium is the type of place.

A filter also for email

Usually newsletters/DEM are tagged with “email” medium. Why not doing the same with a custom filter that attributes “email” medium to all sources that contain the word “mail”? It can be mail.yahoo.com, gmail.com, etc. You might also add other relevant email providers like outlook, hotmail, etc. with a RegEx like (mail|outlook|hotmail|etc….). Again, if you want to preserve other medium like cpc, add a field b=referral – this way you will be pretty sure that all links to your site placed on email content will be tagged with “email” medium instead of referral.

Remember: it’s never too late to tidy your reports and to adopt a consistent and constant “tagging policy”.