The steps I followed in this interaction were as follows: I liked a post from my newsfeed (in this case an article for Abercombie) and within a minute a ‘suggested search’ popped up in my search bar. This ended up  leading me to explore more about the brand (below).

Implications?  

My first reaction was this was sort of creepy, but also if done correctly might customize my experience on site even more. Thinking about it even further, for a company or media outlet on Facebook this has some notable  considerations:

Where a brand/product gets mentioned: In the example above I had engaged with GQ, a publication I enjoy from time to time. Making sure that brands are visible on publications that their consumers are on ensures a higher likelihood of a ‘suggested search ‘ to your own or further related content. When the user also clicks through to the search they will also have content they may enjoy on the subsequent search result.

How consumers discuss a  brand: Clicking through the search also means that mentions from a user’s friends along with other related mentions are displayed. A positive or negative statement may have an effect in swaying a person’s opinion one way or another. Managing issues and encouraging your fans to advocate and share positive experiences about  your brand will be key in this regard.

SEO/SEM ramifications? On top of ensuring that content is engaging (moving it higher up in search), optimizing branded content so that it appears in relevant conversations is also a consideration. Facebook search isn’t as measurable as Google (yet…)  but being mindful of where content appears outside of the fan page newsfeed is also important.

Measuring how many people actually still care: Something that is still a focus in regards to Facebook fan pages is of course the fan base . While fans don’t really have the option of doing this any more, a fan could previously be a fan but opt out of all of the page’s posts.  Having an understanding of how many people are sticking around vs. just displaying a firms logo on their Like list would be a nice little addition and perhaps avoid inflated expectations.

Who are my new fans/Who are the ones that are leaving?:  Sticking with the idea of fan counts, it would be great to have an approximation of what kind of demographic a type of content brings in in but also pushes away. Perhaps you’re running a campaign that you thought was completely geared towards men 18-24 years old, but it turns out to be that you were off the mark and you’re attracting a completely different audience and sending your target the other way. Getting an understanding of who is liking and disliking a page will allow marketers to better test and plan their campaigns instead of simply just pointing towards their fan count and saying ” Look! Our engagement numbers/fans are up!”.

Quantitative Analysis Tools:  Truthfully, having to read through posts for a month and trying to create an actionable insight is pretty painful. Facebook’s interface for exploring comments makes it very difficult to be able to express the  consumer voice on the page. There are a few social listening firms that do qualitative visualizations really well. Facebook should really tap into this type of technology so  that Marketers can understand the voices of their customers vs. getting just a sample approximation.

Longitudinal post engagement analysis: For those who have been in social long enough, you may remember that Facebook delivered two types of engagement reporting. In what I’ll call Facebook insights v.1  you can get a pull of total Likes, Comments and Shares from all content created since the page was started over a certain time period. For Facebook Insights v.2 (current)  now you only see what engagement content posted during your chosen reporting period has received. I think it would be great to be  able to see a v.3  where you can understand the level of engagement a post receives over a period of time .

What I mean by this is perhaps content was really relevant to an audience and users continued to comment on a post for an extended period of time. On the other hand maybe a post was only sort of interesting and received a spike of interest in the first day or two and then really tapered off to nearly zero. Having just an aggregate number doesn’t really tell me how my fans engaged with content and what sort of impact this content had on the community at large. Additionally in terms of an overall content strategy it lets you understand if you’re making effective use of all of your content assets at hand.

BONUS Benefit!  Outside of measurement something like this  would also be a great tool for community managers as it allows them to see where potential issues or opportunities to engage are happening at any one time.

With the right technology in place I strongly believe that all of these potential features (and more!) fall within the realm of possibility. Facebook gathers a lot of user data and while it is important for privacy reasons to keep a tight control on it, freeing up some of the larger aggregate data would allow marketers to better target and manage their page rather than see their fans come and go based on their perceived benefit from the page.

Is there anything that you would add to improve Facebook insights? Or is it a matter of there is some data on the platform already that is completely irrelevant? Feel free to share your thoughts in the comments below!

What am I talking about?

Displayed in a brief preview video were two aspects of what look to be actions from fan pages (in this case Justin Timberlake’s) that caused a few neurons to spark when I spotted them.

The first was a fan source map showing not only where fans were located but attributed a  fan joining your page  to another fan. This is huge in the sense that you can understand how your community forms and who are essentially the taste makers or ‘influencers’ in your community. By doing some digging you can understand how a fan is sending their friends your way and what makes them trustworthy in that others will follow his lead and join the page. In general by having this information you are understanding why people are joining your page and as a result can deliver better value to these fans.

What also caught my interest in this video was the option for the page owner to be able to reach out to “top fans’. Considering what was discussed earlier and using the idea of influencer marketing this could  allow organizations to better spread the word not only online but offline.

So for an example  say a new product is launching. With the option of contacting your ‘top fans’ you can share this information allowing them to spread the word  within their social spheres. Not only are you rewarding your top supporters by giving them exclusive information but you now have a trusted source who will be likely to pass on this information with others. You’re not spending thousands on an ad spend to get the word out, instead you have someone embedded within the community you want to target that will happily spread the word.

Are Facebook and Twitter Falling Behind?

Based off of this video my opinion is that Myspace has taken a direction that understands communications and social better than its competitors. What I mean in this is that Myspace has taken a direction that focuses on the actions of individual users and their contribution to building communities and spreading messages vs. Facebook/Twitter that have gotten too focused on pushing messaging out to as many eyeballs as possible.  On one side there is focus on who your messaging is getting out to and on the other a largely pay and spray approach is being taken.

Measurement Isn’t So Simple:

Knowing how complex websites and search are, Avinash should know that good measurement cannot be simplified into a few key metrics across everything and everyone. Despite this he tries to do just that with his proposed 4 metrics for measuring social media.

Different companies have different goals for what they want to achieve in Social media and assigning metrics that don’t take this into account can potentially side track these initiatives. For example in the case of say Avinash’s Conversation rate  it doesn’t speak to the quality of the conversations that a firm may want to see or the  overall goal of the content they put out. With such a focused scope these metrics don’t  take into account the many other variables that can be tracked on corporate social media channels.

The size of the fan base does matter:

Another downside I see with the type of measures that Avinash suggests is that it does not take into account the audience that the company taps into. Without taking into account a firm’s fan base an even grounding is not created to ensure a comparable measure across fan sizes. Instead what more often than not will happen is that these measures will present  a constantly increasing ratio because a larger fan base often results in more engagement.

Outside of large spikes when there is a fan base drive or large campaign, a measure that does not take fan base into account will most likely continually go up in a linear fashion. The downside of this  is that it’s not easy to discern what proportion of a fan base is engaged. As a result there is no clear way to determine whether an initiative was successful.

Measuring Awareness Still Matters:

Much like with television or radio advertising, simple exposure to social media messaging still has an effect on consumers whether they act on this immediately or if this changes their habits further down the road. While this makes sales attribution difficult, measuring how far your content reaches  is still important. Unfortunately for Avinsash’s framework it does not take content exposure into account. By knowing your content reach you are a better able to compare and contrast initiatives to see if there was a discernible change in a firms end outcome as a result of marketing messaging.

With developing field like Social Media to make broad statements like “the 4 best social media metrics” in my opinion is harmful. What this does is it has the potential to close people’s minds to other alternatives and  more meaningful approaches. That’s why beyond the fact of perhaps not being too public with my work (for confidentiality reasons of course…) I won’t say that one measure stands above all the rest.   Instead my answer will continually be that measures need to be formed based on the end user’s goals and what they are trying to better understand.

So how should this be measured? First of all it’s in my opinion that Facebook should be providing this data as ultimately they offer the function of fan page unsubscribes. As this is unfortunately not the case then the only way of going about this is determining a proxy measure. On the top of my head the only solution (I’m open to others if anyone has an idea!) is developing a tab hosted survey with an email opt in for allowing a follow up survey to be sent.

My idea regarding this type of system would be that a first initial survey would be administered through the fan page with a request to be able to email the participant in the future with a follow up survey. In a selected time period (of say 3-6 months) the follow up email would be sent where fans would be asked if they are still subscribed or recall any content from this page. I admit that there are some weaknesses to this type of approach:

• Low initial user response rate: Most people dislike surveys. Without a substantial incentive only the most active of your fans will likely participate meaning that you won’t get a fully representative sample.
• Low follow up rate: It is very likely that a large amount of survey participants will not respond to your follow up survey meaning that you won’tt get a fully accurate representation of your initial sample.

After getting some sort of idea how many users from a page are falling off I would go about developing a fan degrade rate. With that I mean along with measuring how many users become fans of your page you would also have a  stand in variable for calculating approximately how many of these fans become inactive over a period of time. An example of this sort of calculation would be ( current fans + new fans) – (current fans *fan degrade rate)= current active fan base. A note about taking this approach is that the survey data needs to be renewed on a consistent basis to ensure that the degrade rate is kept up to date.

Strategic Implications:

By understanding the rate of which your fans are becoming inactive a brand can understand when it needs to put into place initiatives to increase user involvement (such as user appreciation giveaways etc.) but they can also have a better idea of the overall growth of their fan base. If it’s being calculated that there are more fans unsubscribing than fanning (a sign of a mature fan base) the brand needs to take a look at what steps (if any) they need to take moving forward.

In this analysis I looked at only per post engagement counts and the content of the post. I didn’t take into account the size of the respective fan bases in evening out engagement as a rate (that may come later…).

To analyse  basics we’ll have to look at what content came out on top. Looking at the top 10 posts out of the data set it broke out as follows: 5 posts from Ron Paul, 3 from Mitt Romney and 2 from Newt Gingrich. I suspect that  a small fan base and high posting frequency were reasons why Rick Santorum fell off this list.

What was the highest scoring piece of content overall? Well it wasn’t hard hitting political rhetoric or an announcement of a big win. It was something that showed a softer side of the candidate that the general public general doesn’t see.

My initial count had this post at more than 80K engagements ( likes,comments, shares) and the highest of each individual engagement category. Interesting enough anniversary content also rounded out the top three posts with #2 announcing the anniversary of Mitt Romney and #3 as a follow up post to Ron Paul’s picture. Looking through the remainder of this content I think candidates missed an opportunity to differentiate themselves as more of a person rather than an icon. This may have opened up more people to their messaging.

There were also some interesting findings on a per candidate level that I felt were useful enough to share:

Mitt Romney: The common thinking among those who want to use edge rank for the highest reach  in achieving the highest post reach is to use photo content as it generally receives more engagement. Well looking at Mitt Romney’s content that may not be the case in all situations. In looking at Mitt Romney’s top 20 posts only three of these were photo content. Instead fans of this page were most affected by brief but resonating status posts positioning Mitt Romney as someone with strong leadership skills.

Ron Paul: Outside of his 1^st spot post it was interesting to see Ron Paul’s tone. Out of the 4 candidates the tone of this page was much more first person like the candidate was writing it rather than someone on his campaign. In terms of data trends it looked like “Like” and “share” engagements were more common with “comment” engagements occurring less often. Perhaps some conversational content would have been useful to spur on response and increase post engagement.

Newt Gingrich: Out of all of the candidates Newt Gingrich made the most use out of photo content including vivid imagry and strong messaging within the photo itself. Placed along with strong calls to action such as “ Can we get 5,000 likes for an UNHAPPY Obamacare birthday?” Newt Gingrich was able to boost his engagement despite having a comparably small fan base (296K vs 925K for Ron paul and 1.5 million + for Mitt Romney).

Rick Santorum: Ignoring the data itself the sheer amount of posting was what really surprised me about the Rick Santorum page. Of a total of 669 posts recorded, the Rick Santorum page came in with 316 (47%) posts. To put this on a per day perspective that’s approximately 5 posts a day. In looking at this data on a by fan base perspective it will be important to see whether what seems to be over posting had an effect on engagement or not.

Looking at the data, Rick Santorum did not seem to be in the running when it came to the volume of engagements his posts received. Looking down the list his first post doesn’t register until 107^th position. Arguably he did have the smallest fan base ( 188K) but it’s still interesting to see that none of his content particularly stood out especially as there seemed to be so much effort put towards it.

Part 2 of this set of posts looked at the bulk count of metrics but didn’t take into account the relative fan bases and only touched upon the different content variables such as content type. In the next post I hope to dig a bit deeper in seeing where the Candidates stood in terms of how engaged their fans were and who in the end of it all was most engaging. Stay Tuned!

ADDITIONALLY: As the data I used turned out to be a giant data set I’m hoping to make it accessible for download via a Google doc for any interested party to check it out. Once I’ve added fan base estimates and I’ve cleaned up the set I hope to have this going.

This first post is a simple one to start things off. Looking at the publicly available fan and demographic data from each candidate I came across some interesting observations:

Internet Popularity ≠ Real Life Action:

Currently in the delegate count the standings from first to last are Romney, Santorum, Gingrich and Paul. Organized by Facebook fan base this is dramatically different and goes as follows: Romney, Paul, Gingrich, and Santorum. Romney simply by being the front runner in the race dominates in terms of fan membership but whats more interesting is Ron Paul is beating both Gingrich and Santorum while being last in terms of delegates earned. This points towards Paul having a strong presence online but a weak ability in converting this following to actual votes.

Fan Base Demographics Are Split Amongst The Candidates:

Another interesting finding I had was that fan base demographics were spread across the GOP candidates. Perhaps as expected Ron Paul attracts more fans aged 25-34 lending to the idea of his internet fame. On the other hand Romney and Gingrich are more popular among users 45-54 leaning more on the older side of the spectrum. Comparatively Santorum is able to bridge a bit more of a gap with his popularity among the 35-54 demographic. If Santorum uses this demographic spread to his advantage he may have an edge over the other candidates in terms of building awareness for his platform.

Growth Is Starting To Decline And One Candidate is Losing Steam:

My last bit of observation to share is of the slowing fan growth amongst the candidates. Over the month of March fan acquisition has  sees a progressive drop off  among all candidates with Romney then Paul leading in most fans gained.  A stand out in this slump has been Gingrich who has started to receive nearly no new fans. With talk suggesting that he drop out of the race perhaps his momentum has come to a halt.

Like I had mentioned this is the first post in a sequence. As I begin to get my full data set together and get deeper into the results I’ll begin sharing more. Stay tuned!

Impressions vs. Engagement:

A key point of focus for digital marketers has been encouraging consumer engagement with brands rather than blasting out messaging. With the recent changes in its insights platform and expansion into how brands can promote itself through the site, Facebook seems to be disregarding this idea by placing brand impressions at the forefront.

Potential for Backfire:

As even brand page content has now become potential ad space, consumers will become continually exposed to branded content but also may become dis-engaged. As brands begin to fight their way onto user’s newsfeeds marketers may see a potential backlash where consumers decide to unlike pages to decrease the onslaught of content aimed towards them. This will be because while the content will have higher visibility it may have little relevance to the audience it hits.

Getting back to basics:

My thought on this is that it’s a move backwards towards pay and spray advertising and away from the relational marketing that I personally hold in higher regard. As a consumer a brand creates little to no interest to me by continually exposing itself through ads and promotional activities. Instead I have higher affinity for a brand and its product when I feel a sense of value from the relationship it has built  and the worth that I place in using the product. While through advertising I may see the brand more often, it probably won’t change my opinion when this advertising provides me with no demonstrable value.

The Potential For Location Based Data

In a recent update of its systems Facebook has improved the insights dashboard that fan page owners can use to analyse their efforts. Companies can now have a more in depth look at how and how much of their fan base and Facebook users in general interact with the brand generated messaging  being  put out. Adding data from a location based service could add an even deeper (and more meaningful) additional layer to these new features.

There is a large list of potential benifits to measurement and analysis that location based data could create (I’ve had some time to think about it) but in regards to Facebook and fan pages I can think of particularly two scenarios of how location based data could be used when thinking  about brands with retail locations:

Analysis As To What Drives Fans To Purchase: Businesses could potentially see the correlation between the traffic to their stores and the content they had posted during a particular time frame. In the case of for example a product announcement,  a company could potentially measure check ins to the company’s stores to see if there was an increase in visits and linking it back to the firms sales data they could determine if against past product launches there was an increase of decrease in sales.

Determining Where Your Fans Shop: For retail chains knowing the makeup of your customer base on a store by store level is another potential use. By taking a look at the demographic data of users who have checked in, the firm can see if a particular type of customer is more likely to shop at a certain location. From this data  the firm can also have a look if there any particular purchasing trends among this sub set. Looking at this data in a time series could additionally provide insight as to if particular promotions or products should be added or augmented to fit the particular grouping of customers.

In the next few weeks we’ll see if the rumours of Gowalla’s acquisition by Facebook are true or if a few news sources  have to maybe review who they get their info from . None the less, for companies on Facebook and otherwise tapping into the databases of  location based services still hold a lot of potential for improving their results. As brands continue to look deeper into the data that’s available through social media and online sources cwe’ll have to see if these location based services will come into play.

Like this if you like Puppies!

Asking users to like something does have its tactical uses. Those who are a bit educated about the ins and outs of the Facebook news feed know that a user engaging with a source’s content frequently equals a higher relevancy score to the content source. Throwing up a piece of content that is generally enjoyable and asking users to like it means that the relevancy score is  bumped up a few spots and fans are just a bit more likely to see your content. Does this mean you should flood your feed with “LIKE THIS!” content? Well if that’s the sort of depth you want your brand to have then go for it! What this won’t do is sell your product or improve a users thoughts on certain attributes of your product unfortunately.

Time to throw away the ‘like’?

Am I asking people to ignore the ‘like’ completely? Absolutely not! Should the like engagement be considered along with other factors? Yes!   Compare it to consumer response (what are people saying in the comments) , the propensity of users to like your key messaging compared to other content  and I could go on…. Measuring channel success  in my opinion means measuring how you are changing people’s perception of your brand and product. Are people more likely to talk positively about your brand and as a result  increasing sales because of WOM? Has your brand gone from being seen as stale to something that people have feelings for? And lastly at the end of it all have you been able to track increased dollars going into your firms bank account?  At the end of the day changing minds rather than encouraging clicks should be the end goal, not the afterthought.