Posted by Marshall Sponder on June 07, 2010 | Link It
Read a post on How Google’s Time Dimension Will Disrupt Your SEO showing a new feature of Google Search that allows the searcher (you) to chose any period of time and see the most relevant search results for a query. But the post brings up another point, the results being shown are based on the real time data that Google collected at any point in time, and, erase much of the advantage big brands have/had with SEO due to backlinks that big brands find it easy to collect.
According to the Search Engine Land post:
….. Brands that focus on dynamic site content with fresh social media output stand to gain searchers, at the expense of those brands who stay stagnant, one query at a time. The speed at which the gains and losses occur will be magnified by the availability (or lack) of content within each time filter. Now the “recency” of social media will begin to matter in search.
The post then suggests you can measure your on recency of search results from Google and I tried it with Webmetricsguru.com using Google Analytics and Google Webmaster tools – no luck getting the data. I tried getting the server log files off Dreamhost where my blog is hosted but could not find the data.
Past 24 hours: “&tbs=qdr:d”
Past week: “&tbs=qdr:w”
Past month: “&tbs=qdr:m”
Past year: “&tbs=qdr:y”
Custom range: “&tbs=cdr”
So I can’t tell you how much of my traffic is real time – but if you have access to raw server logs, you should be able to accomplish that.
There are two ways in which you can launch a search: “Simple” and “Advanced”. The first will let you look up two words (like two verbs) plus two other words (say, two nouns) in three different sites: Facebook, Twitter a Topsy.
On the other hand, an advanced search lets you specify the words that go between the two sets – you can specify 0 to 8 preceding words. Other than that, you are scouring the same three services as before: Facebook, Twitter and Topsy.
The reason I was attracted to this new tool was it’s focus on the Search Query – it’s really hard to write good search queries that get the information you want from Social Media Monitoring and if this tool can help, it’s worth looking at, so I thought.
While SearchTwix didn’t exactly do what I hoped, it looks like an interesting approach that might yield different content than you’d find otherwise.
Getting to the other theme of this post – I have been thinking about how one finds the “next big thing” or future trend using Social Media. In this case, finding the next musical or dance start – the next recording artist legend – could social media monitoring cull data from all of YouTube and other video/music sites and find a way to identify new artists who might be commercially successful?
Talking with some talent scouts this weekend – finding new talent (for reality shows) is usually something that happens spontaneously – you have no idea what your looking for but when you see something unusual and the scout realizes this person “has it” – you then push that person to audition for a spot in an upcoming show or event.
Herein lies the problem of finding new talent using Social Media or Search – you can’t write a query to capture the “IT” factor when you don’t know what having “IT” is or really means. The sheer volume of new content appearing every hour on YouTube alone is beyond any single human’s ability keep up with.
Solutions like Crimson Hexagon, Apple iGenius and My6Sense are applications of machine learning that could potentially solve the problem of finding breakout talent but they were not designed with for it. Potentially, a talent scout could train My6Sence to crawl all of YouTube and Twitter and only look for a certain type of talent that is as yet undiscovered. But here we get into another problem – guess what it is?
The problem is musical and video content are too complex for today’s programs or processors to handle – and the same problems that exist in detecting copyright violations that also penalize artists who “remix” work laced with irony or satire – which is not easy to distinguish – a human being can easily, but a machine can’t (yet).
Of course, by crowdsourcing talent scout via Mechanical Turk or a Facebook game (be the next celebrity judge) using 1000′s of people it becomes possible to tackle enormous amounts of traffic and even qualify the quality of your team members – but no one has done it yet successfully.
Here’s the post for my readers (and feel free to read it on the RockStars blog, as well). I admit that I use content I have already written about and adapt it – but then, I’m evolving a model where my constant blogging is the diamond in the rough – where all my ideas get thrown out in open, to be looked at – where the hard thinking happens. Later I might choose to refine those ideas – but I would be foolish to ignore them, and try to start from scratch.
Geolocation and mobile computing are trends that are now in the mainstream so it’s about time to examine what kind of analytics we can get and what we can do with it.
For one thing, Geolocation and Foursquare can be your best friend, especially if your business is brick and mortar, like a restaurant or even a hardware store (though, besides Home Depot, there aren’t that many hardware stores that are fun to hang around in).
Take Havana Central, a New York Cuban Restaurant chain who is a client of mine and who aspires to be the Roger Smith Hotel of local restaurants here. Through my WebMetricsGuru.com blog I have become known to many in the Social Monitoring sector and have access to many of the best platforms, tools and agencies of choice to work with. One of the tools I use often is Radian6, a Social Monitoring platform that is used by many marketing, PR and communications agencies to monitor “online chatter” and “buzz” for their clients or own businesses. Radian6 is also known as the first “listening” platform to integrate with WebTrends (and Omniture) as well as SalesForce for SocialCRM.
I set up Radian6 alerts set up on Havana Central that sends email status every 10 minutes when anyone tweets or mentions the restaurant chain in any way. It just so happens that I was in the 46th street Havana Central location one evening and received an email alert from a customer who was saying she was in the restaurant – via Twitter. When I read my email alert from Radian6 I immediately realized the customer was in the restaurant at the very same moment I was.
This is what the alert looked like on my iPhone:
TWEET FROM: KIMBERLY819
Source: twitter.com, Posted on: Mar 01, 2010 9:36 PM by KIMBERLY819
Chillin with my girl Yesenia in the city!! Great restaurant Havana Central!! Great Live salsa band!! Oooooooowwwww!!!!
Following: 86 | Followers: 65 | Updates: 270 | Sentiment: Positive
The alert took place in real time – I suggested to the management the customer and her friend should be given free drinks and discounts that evening. That’s all I did – and as we acted in real time- within 10 minutes of the initial tweet – the response was interesting.
The customer, Kimberly819 and her friend got their free drinks.
Later on that night I got another alert – guess what this one said:
That got me thinking … if we could do something like this – foster customer loyalty – that easy (hell, just give the lady a free drink) what would happen if we gave everyone who tweeted at one of Havana Central’s 3 locations a free drink?
I used analytics to figure it out. How often could Kimberly819 happen and what would it mean to Havana Central in increased revenue? I found on first pass, exporting Radian6 data from a “River of News” Widget I set up for the restaurant alerts that at least 20 times in the last month a customer tweeted they were in one of Havana Central’s locations – though in retrospect – that number is way, way too conservative – I put it more at 100 times a month, at least, and maybe even double that – if we take every variation of announcing “I’m at Havana Central”.
Source: Radian6 – Tweets & Facebook announcements of presence at Havana Central
For those customers who have linked their Foursquare accounts with Twitter and Facebook the numbers are even higher with about 5% of the total conversation recorded as having happened at one of the restaurants – and I can swear the number is closer to 10% as we get 2 or 3 tweets a day from people who are announcing they are at one of Havana Central’s locations.
Source: Radian6 – Alerts with Foursquare check-ins included
Suppose we go with the higher number (around 60 individuals a month say “I’m at Havana Central” in one slang way or another) and estimate a typical loyal customer will return a certain number of times and spend a certain amount in per visit – we can get a approximate ROI number.
I’m going to make a deduction the a typical “rewarded customer” we find via Twitter, Foursquare and Facebook might spend $300-$500 a year at the restaurant in addition to anything else they might have spent there if they had not been rewarded. I was told by Jeremy Merrin, one of the owners of Havana Central that the number might be considerably higher than that (add up all those blueberry mojitos and live Latin dancing, etc)– but I’ll be conservative, just to be safe.
One possible result is increased revenue of close to 30K a month – over a year that could mean as much as 360K – just by making someone’s visit a little bit friendlier and better for them.
What about Advocacy? Is figuring out how many active advocates you had this month for your brand compared to last month any better? Well … not really, but there’s hope.
One way this could work is if your community manager who engages with their brands’ audience.
Community Manager engages with audience
While engaging, tracks which members express positive/negative statements and advocacy to the Brand.
Community Manager tags audience members based on their stated online positions to the Brand withing the Social Media monitoring platform (or by hand, in Excel – whatever).
As time goes on, Community Manager is able to chart active advocates this month vs last month, etc.
You can also divide the number of active advocates by “total advocates” – except the formula to determine “total advocates” was left undefined by Altimeter and WAD.
So your not much better off here than with the other KPI’s I looked at so far – but at least this one, Active Advocates could be operational once the little detail of how to determine the total pool of advocates to your Brand is specified.
But, let’s forget about how Altimeter and Web Analytics Demystified are defining Advocacy for a minute, or the platforms they say can be useful to get Advocacy out of like Biz360, Filtrbox (Jive), Radian6 – I’m pretty sure Radian6 supports tagging, I think Biz360 does at well.
The fact of the matter is those platforms being suggested for Advocacy aren’t the right ones – I’d put in it’s place a platform like KeenKong.com which is a much more natural fit for Active Advocates, or perhaps Radian6′s new Engagement Console, when it becomes available.
So I fired up KeenKong and read in my Facebook and Twitter messaging – this is what it looks like, and I can tag my messaging as well, helped by KeenKong’s structured semantic underpinnings.
Here are some stats I can easily pick out of KeenKong.com for my conversations.
February 2010 Total: 301 conversations from 177 people reaching 116,362 people
February 2010 Adv: 30 conversations for 26 people reaching 15,283 people
I used KeenKong to easily select what I think to be advocates for me, focusing on the “Why” column.
March 2010 Total: 289 conversations from 159 people reaching 95,414 people
March 2010 Adv: 29 conversations from 26 people reaching 23,256 people
So far, it looks like February and March, I had the same number of “advocates”, 26.
April 2010 Total: 373 conversations from 206 people reach 127,922 people
April 2010 Adv: 28 conversations from 21 people reaching 17,016 people
If I assume the total advocates is the top number (ie: 206 people in April) while Active Advocates is 21 (see above) then we can attempt to do the formula for the Social Marketing Analytics Framework.
Online Advocates February 2010 = 15%, March 2010 = 10%, April 2010 = 8%
Judging from the above percentages – it would look like my online advocacy is deceasing rapidly, but that doesn’t seem to be the case in real life.
Plus, even if the calculations are correct, the information provided does not appear to be very convincing.
However, Radian6 and Biz360 can also do this calculation providing your willing to categorize all your mentions and alerts for advocacy and divide the total mentions into it (for a certain time period).
Marshall Sponder is an independent Web Analytics and SEO/SEM specialist working in the field of market research, social media, networking and PR. He provides digital data convergence generating ROI and develops data metrics, KPI’s and dashboards that drive businesses by setting, evaluating benchmarks and teaches Analytics at UCI Extension and Social Media for The Arts at Rutgers University.