As we discussed yesterday, Google recently released Google AdWords Express for local marketers. This program allows local businesses to set up an AdWords account in minutes, and start advertising to their target markets through Google local search. AdWords Express is conceptually similar to the traditional Google Adwords, but there are some key differences. The major difference with Express is that it was created as an automated, easy-to-manage PPC option for local advertisers. Google automatically selects search queries that ads will be displayed for based on category (like an ad group) selections. There is no need to worry about keywords, bids, or optimization.
While there are pros and cons to automating your PPC campaigns, Google Adwords Express presents a compelling case for local businesses that need to expand their reach under time constraints. If you've weighed the pros and cons and made the decision to experiment with a Google AdWords Express account, here are 4 easy steps to set up your account and launch your AdWords Express campaign in just minutes.
Step 1: Find Your Business
Visit http://www.google.com/adwords/express/ and click the blue, 'Start now' button. First, Google will need to confirm the country where your business is located as well as confirm the phone number associated with that business. The phone number will be confirmed, so make sure this information is accurate. If Google finds your business listing, all you need to do is select the “this is my business” button, and you’ve completed step 1.
If you have not added your business to Google’s listings, you can click “add a new listing,” and Google will walk you through the process to add a new listing.
Step 2: Add Your Information
In this section, Google will ask you to enter a few things regarding your business' information. The more information you enter here the better, as Google will have a better understanding of your account and the ability to keep you posted about nuances and updates. Be sure to add your email and website. The one thing to be very careful about is the category selection.
Google is going to decide which search queries your ads will display for based on the category or categories you select. Think long and hard about this section, and try to limit your campaigns to one section so that you can track them properly. Start typing your industry or related terms into the category box, and Google will start to show you selectable categories.
Step 3: Create Your Ad
This is where the fun part begins! For your specific category, now you get the chance to write your own ad. Remember to adhere to the character limits of the headline and ad description, and keep in mind that every ad you write should relate to your category. Within your ad text, also keep in mind that you should always include an offer, show the value of what the offer is, and include a proposition utilizing a call-to-action that will compel qualified searchers to click on your ad and not the competing ads.
Next, it's time for you to decide where your traffic will be directed. You can choose to direct people to your website (or a unique landing page, which we highly recommended), your Google Places page, or Google+ business page. Remember to direct users to the most relevant page containing the information your potential customers are looking for based on their category search.
Finally, it’s time to determine your budget. Based on your category, Google will recommend a budget for you to assign your campaign. DO NOT simply agree with Google. You should decide what you are comfortable with for a test and assign the budget that you think is best based on your budget, not Google’s assumption of your budget. The minimum budget is $150 per month.
Step 4: Checkout
You knew it was coming. Now it's time to set up your billing profile. Your business information will probably be similar to the information you entered in step two, so this should be pretty quick to complete.
The final step is billing details, in which you can select automatic or manual payments. The only difference here is whether you want to prepay for your AdWords spend or not, and it's totally up to you. Your payment method can either be in the form of a bank account or a credit card.
Something to watch out for is the promotional code. Google often runs promotions, offering something like $100 of free ad spend, so if you know of one or can find one, this is the place to enter the code for your discount.
That’s it! Four easy steps, and your PPC campaign will be live on AdWords Express in minutes. Remember to carefully select your category, take your time when crafting your ad, be cognizant of your budget, and make sure to track results! Without the sophisticated insights that traditional AdWords provides such as keyword data, it is imperative to set up a unique landing page or tracking system so you know exactly what results are being generated from Google AdWords Express. Only then will you be able to make changes to improve performance and be able to identify what is or is not working with your AdWords Express experiment.
In what looks to be the last major feature push before the Christmas period, the Google team has today announced a number of new updates for Google+, delivering multi-admin controls, new notifications and +1 analytics.
After listening to user feedback after the public launch of Pages (which saw us reinstate our The Next Web account), Google now allows brands and businesses to nominate up to 50 named managers as administrators for a page — perfect for companies with large marketing and social media teams that previously needed to share login credentials.
Also dropping is a new notification flow that delivers all of the activity on a page, giving admins the chance to keep an eye on conversations, messages and shares of their content.
In an effort to provide managers with a better idea of how Google+ users are interacting with page content, Google has combined counts of users that have engaged with a page, whether it be a +1 or the addition of a page to a circle.
To demonstrate the new features, Google has posted a new video which describes each of the new features and how to add them:
With additional page controls, Google has taken a step closer to providing users with access to features similar to Facebook Pages. Google says this is just the start of its page updates, we will of course notify you of them as they roll out.
this will help more businesses and organizations use g+
I’m not sure about you, but I’ve seen increasingly less activity on my Foursquare account lately, in my own stream and others’. While I do have a few new friends every so often, those whom I’ve followed for a long time (Foursquare early adopters, like myself) seem to not be checking in as much (and nor am I). The leaderboard has thinned and the checkins seem more and more mundane (Gym, Starbucks, office. Repeat.)
Foursquare now claims 10 million users, and Walmart had 149,484 checkins the week of Thanksgiving. Those feel like very small numbers, at least when compared to Facebook (800 million active users). And considering that there are about 3,800 Walmart stores nationwide, that’s only 39 checkins per store. Through the whole week of Black Friday. Meh.
At the same time, Foursquare has added a ton of new features, which could really attract and engage new users as well as old. A couple of weeks ago I checked into a movie theater and was given the option to select the movie I was there to see. Foursquare has partnered with MovieTickets.com to provide showtimes and ticket purchases in-app, which is pretty cool: if you’re checking in about a movie it’s highly likely you will want to share which movie.
Foursquare also recently announced two new buttons for site owners to use to connect their readers directly the app. The more interesting of the two is a “save to Foursquare” feature which allows a user to add a location (restaurant, event, store, etc.) to their Foursquare to-do list. Instead of emailing myself the page as a reminder, a quick click will add it. The other button will allow you to follow a person or business on Foursquare. I fear that these new buttons will get lost in “button fatigue,” though, and many websites won’t adopt them.
And therein lies the real problem: Do we have time for Foursquare? If the early adopters have dropped off, who’s actually using it? And where does Foursquare hope to get new growth from? It may be from “the kids” – the 13-24 year olds who came later to Twitter and still may be more prone to text than tweet. And the retail buying power of some of these kids is strong, though they don’t control nearly as much budget as the 25-plusses do. I’m worried that if the early adopters no longer care, the momentum for growth will be lost.
What does this mean for brands and local businesses? I’ve never been a huge proponent of Foursquare for businesses, unless you’re a retailer. I’m going to stand by that sentiment for the moment. If you’re JC Penney, Amex, or Radio Shack it may make sense for you to create campaigns, which you can run nationally and amortize over hundreds of locations. And if you are a small business retailer or have a consumer location, you should certainly have a Foursquare presence, because you want to control how your business is presented. But I wouldn’t put a whole lot of time or effort into it, at least not if you’re outside the major East and West Coast cities where there are heavier concentrations of Foursquare users. Unless, of course, you test it and find a great response from your customers. (Isn’t that the key to marketing anyway? Test, test, and test some more!)
I’m not dooming Foursquare entirely, just saying that it feels like growth will be limited and it won’t ever be for every business (or user). Perhaps your local bar is using it successfully today (are you the mayor?), but don’t expect every business you come into contact with to jump on board.
Is your business using Foursquare? And where do you think it’s headed? Do you agree or disagree with my assessment? I’d really love to hear about your successes, or failures, in the comments, as well as your analysis of Foursquare’s future.
- Foursquare Teams Up With NY Mag, Time Out, Other Publishers (paidcontent.org)
- The One-Percenters Of Recommendations (marketersstudio.com)
I'm using foursquare, but often it's through an app like picplz or levelup, so I don't see the new features. also, I tend to check in to venues after I'm settled in, making for a lot of 'doh' moments when I see there's a deal I could have redeemed
This week I’ve been writing about speed and response expectations for business on the social Web.
Ultimately, speed wins. The companies that engage customers on Twitter and Facebook within minutes are making a none-too-subtle statement about their embrace of the social telephone and the primacy of the customer. In comparison, slow response or no response produces a decided “meh” vibe.
So how do you win the speed race that has no finish line? How do you become uber responsive to your customers on the social Web? Not with technology, and not with tools.
You win by eschewing permission in favor of response time.
Beg for Forgiveness Rather Than Ask for Permission
Every time your front line responder(s) need to find out the answer to a customer question, or check with a manager about how to word something, you have failed to truly embrace the real-time nature of modern customer relations.
That’s why it’s so critically important to staff your social media front lines with people who not only have extraordinary passion for your company, but who also have the experience and judgement to minimize response delay.
The widely held notion that we should staff community manager and similar positions with young, inexpensive, socially savvy people who juggle smart phones like flaming clubs may actually be a terrible idea.
Instead, what if we staffed community manager and similar positions with experienced team members who know the ins and outs of the company, can subsequently answer most questions without asking for help, and most importantly have the judgement that is accrued only with time?
For a while, Frank Eliason at Comcast (now Citi) was held up as the standard. And experienced, wise, consumer affairs-oriented connector with smarts and empathy. But now, as social-powered customer service becomes pervasive, it seems that more companies don’t want to invest in someone like Frank, but instead hire someone who “grew up with this stuff” – regardless of how little organizational understanding that person possesses.
I don’t often see the logic in putting an inexperienced person at the controls of the only part of your company that is truly real-time and exceptionally visible.
bold, but there's a method to the madness
I won’t write out the entire presentation for you in blog post form – that’s what Slideshare is for – but here are the high points of this presentation on Killer Integration of Facebook and Email Marketing, where I offer 17 specific ways to tie these two important programs together.
2 Sides of the Same Coin
The notion that Facebook is a tool to create new customers is massively flawed. Research from DDB shows that 84% of fans of company Facebook pages are current customers. Of course they are. Think about how you use Facebook. You don’t randomly surf around, clicking the “Like” button for companies of which you’ve never, ever heard. Why would you want their info in your news feed?
Consequently, Facebook is primarily a tool for keeping your brand top-of-mind among customers who have given you permission to do so. Through this messaging, you hope to solicit repeat business and customer advocacy. And email marketing sets out to do the exact same thing.
Thus, the people in charge of Facebook and the people in charge of email marketing in your company should be the SAME PEOPLE.
3 Types of Integration
There are three main areas where Facebook and email marketing can and should be integrated:
- Strategic Integration
- Channel and Audience Integration
- Message Integration
Strategic Integration of Facebook and Email Marketing
There are several areas of overlap here, but perhaps the most illustrative is the fact that the metrics used to measure both tactics are mathematically quite similar, even if we call them different names:
- Email subscribes = Facebook “Likes”
- Email unsubscribes = Facebook “UnLikes”
- Email opens = Facebook impressions
- Email clicks = Facebook feedback
- Email forwards = Facebook shares
You can even derive the value of your overall Facebook marketing effort by examining it through the prism of your existing email marketing investment. I wrote a post about this new way to calculate what Facebook is worth to your business a while ago. It includes a link to a free Facebook valuation worksheet.
Channel and Audience Integration of Facebook and Email Marketing
The goal is not to get an email opt-in or a Facebook “Like”. The goal is to get both. Consequently, whenever you are asking for you, you should be asking for the other, as well.
- Email thank you messages.
- Email unsubscribe preference centers.
- Facebook landing tabs.
- Social log-ins using software like JanRain.
Message Integration of Facebook and Email Marketing
Tons of options here for using (and re-using) your Facebook and email content.
- Use email subject line testing to optimize Facebook ad headlines. And vice-versa.
- Test image effectiveness via email, incorporate into status updates or Facebook ads. And vice-versa.
- Just like Sponsored Stories, incorporate fan expressions of advocacy into your email content.
- Incorporate most popular email content into status updates. And vice-versa.
- Tease upcoming emails via status update.
Do Not Eat This Entire Sandwich
The presentation has 17 ways to tie Facebook and email together. Do not try to tackle all of those at once. Pick the two to four that make the most sense for your company, and try them. Them, add two more. And two more. Until you’ve integrated your programs in many ways. Remember, however, that your Facebook and email marketing will NEVER be optimally integrated if different groups (or even different agencies) are handling them.
You know how you can tell social media is a truly big deal? It’s become too important to stand on its own.
Social marketing platform Roost set out to determine what types of small and mid-sized businesses rule the roost in terms of growing their social audience and remaining active in marketing.
Roost’s findings include:
- Small and mid-sized businesses involved in music, entertainment, and luxury goods had the most reach.
- The most active small and mid-sized businesses were in the medical and health industries.
- The most efficient “signal-to-noise” ratios were posted by companies in the music and broadcast media sectors.
Medical practices were the most confounding, coming in dead last out of 28 industries analyzed by Roost in terms of reach, but topping the activity list.
Other industries with similarly large gaps included:
- Music, number one, 26th in activity;
- Consumer electronics, number five versus 23, respectively;
- Hotel and hospitality, six versus 25;
- Commercial real estate, 25 versus seven;
- Fitness, 26 versus five; and
- Insurance, 27 and eight.
Google Plus started out growing faster than any social network has so far, but may not be able to compete against Facebook longer term.
The appeal is not sticking because many of the people that quickly flocked to Google Plus have made their way back to the comfort and familiarity of Facebook.
In fact, the inability to keep users engaged has some observers wondering just how long Google Plus will be able to survive.
A Closer Look At The Battle
Google Plus entered the social game at a time when competition was arguably at its fiercest. Facebook was just reported to have an estimated 750 million active users, while both Twitter and LinkedIn were making notable gains of their own.
In order to garner attention, Google would have to give users a different experience, and different is what it strived to be from the very beginning.
Even in its original beta form, Google Plus was equipped with a new friends system in Circles, a discovery engine in Sparks, and a group video chat tool in Hangouts, which recently made its way to the mobile platform.
Apparently all that wasn’t enough, as Facebook went to work with some countering of its own.
The majority of the changes involved making the popular social platform more user-friendly, starting with the news feed.
The news feed has been designed in a manner that presents users with posts that are deemed to be most important to them, opposed to the most recent updates.
According to Facebook Engineering Manager Mark Tonkelowitz, the news feed experience is now like users having their own personal newspaper.
Despite not being embraced by the community as a whole, or at least not at first, the recent changes at Facebook have reclaimed the attention of both the general members and brands who spend their time on the site.
And while Google Plus still has some attributes that enable it to stand out, the lack of activity and return visits is a sign that users are having trouble justifying its worth in comparison to what they already have in Facebook.
Google Plus is not the search giant’s first attempt at social networking.
If you recall, the company launched Google Buzz in 2010, which fizzled out due to a major privacy flaw that accompanied the initial release and the same issue the company faces today — being useful in what can be considered an overly crowded space.
Google Plus definitely has more potential than Buzz, but should it bomb, it could very well be the last shot at ever touching Facebook in the social realm.
Guest writer Aidan Hijleh is a freelance copywriter and serves as the non-profit partnership liaison for Benchmark Email.
Lead image courtesy of Shutterstock.
think reports of g+ demise may be premature
The keyword used to be the exclusive province of Google, and one of the things that may ensure Google doesn’t become completely overshadowed by Facebook. But then Twitter’s trending topics began to eat into that monopoly.
Now Facebook may show you stories from multiple people about the same topic. How does the social network do it? How do they prevent you from seeing a bunch of stories about dogs or bananas?
It turns out, one of Facebook’s engineers revealed the secret sauce on Quora. But he did so in quite opaque, academic language, so I’m going to break it down into real-people-speak (for myself and you).
Ken Deeter explains:
I was the lead engineer on this project so I’ll give this a shot. Without going into too much secret sauce…
1. We build language models based on publicly available corpora for our entity extraction. Based on this data we can extract topics at various levels of confidence. To answer your question, yes, it can figure out terms like “arrested development” out of normal text. It can also disambiguate between words like “Apple” the fruit, and “Apple” the computer company.
2. We have a second level of infrastructure that tries to use other data to increase accuracy. Generally you can think of this adding more context into the equation, whereas the first level only takes into account the text of a message.
3. We have some heuristics to decide to show a particular cluster. Generally this is a combination of trying to filter out noise from the extraction system, and deciding when something is newsworthy enough to show. Two of your friends talking about bananas, for example, is pretty uninteresting.
Like I said, we’re going to have to break that down.
Facebook’s Language Models
Facebook probably also uses lists of the names of pages with many likes (including place and community pages).
Perhaps the company dips into other publicly available lists of hot topics like Google and Twitter trends or the Yahoo Buzz Index.
The social network, however, has all kinds of data on what people on Facebook are sharing, what pages they’re commenting on and so on.
So even if the company uses only internal resources, there’s a huge amount of data on what the most popular topics are at any one time.
Context Improves Keyword Groupings
What this reminds me of is Google’s related keywords. One of the things that goes into Google’s rankings is whether you use ancillary words and phrases surrounding the main keyword.
For example, for consideration of whether you should rank for “camping gear,” do you talk about things like tents, boots, hiking, fires, food, and water purification? It could work like that on Facebook, which might also use a social context.
I suspect from Facebook advertising’s topic targeting that the company has quantified the affinities between various precise interests. In other words, Facebook knows that if you like the band Coldplay, there’s a 35 percent chance you also like Death Cab For Cutie.
This is just an example, and probably the wrong value. But if Facebook wonders whether you’re writing about a politician and you have many politically-oriented likes in your profile, that would be a context that would increase confidence that you’re talking about that keyword.
Heuristics, Important Topics and Salience
I just love to use the word salience whenever I can. I once studied attention deficit disorder, and in this mental condition the brain has trouble determining what is most salient (important or high priority).
If you have a low signal to noise ratio, cognitively, you can’t focus on something (signal) and ignore all the other stuff going on at the time (noise).
So Facebook is using some rules of thumb (heuristics) to arrive at whether a topic is important enough and talked about enough to show in the news feed.
The example he gives is something mundane (bananas — who cares?) and a small amount of conversation (two people).
However, we must assume that if 10,000 people talk about bananas and Google News is carrying a story about a problem with bananas, it’s an important topic and we should show posts around that keyword.
Will Facebook Kill Google With This?
The fact that Facebook has developed algorithms around keywords is a big problem for Google. As soon as Facebook includes keywords as an option in Facebook advertising, Google AdWords (Google’s primary revenue source) becomes much less important.
AdWords may always have a leg up since it analyzes keywords for all websites, but why shouldn’t Facebook move this direction? Why shouldn’t the social network make its search functionality as good as Google’s?
Google has not proven they can successfully imitate Facebook’s strengths, but Facebook may be showing they can duplicate Google’s.
Brian Carter is the author of The Like Economy: How Businesses Make Money on Facebook. He’s also speaking at Socialize West this Thursday.
Influence scores, as we know them today, are all based upon algorithms. Algorithms are commonly confused with formulae, but they are surely two different things. The volume of a circle is a formula – it’s math. That x number of retweets has y effect on your influence score, however, is an algorithm. There might be some math in there, but I like to think of algorithms as math plus assumptions.
An influence score makes assumptions about the value of your follower count, how many people click on your links, etc., and then bashes those assumed values together with yet another set of assumptions – their supposed relationship to each other. Yes, there are mathematical functions involved, but just as the “likely voter model” many pollsters use for pre-election polls can never predict whether or not a specific individual will actually vote, the influence score will never be able to predict the impact of an individual on the behavior(s) you are trying to influence.
And that’s really the biggest issue with these scores, isn’t it? All of the algorithms being used by these services are amalgamating the behaviors of the many, and attempting to assign a value to the individual. This kind of inductive reasoning is always problematic. Here’s why:
Measure Three Times, Cut Once
There are, broadly, three kinds of measures: descriptive, diagnostic, and predictive (and these aren’t mutually exclusive – the best measures have elements of two or three of these all rolled into one.) Descriptive measures tell us what happened. Diagnostic measures tell us why it happened. And predictive measures help us make good guesses about what might happen in the future. The modern crop of influence scores (and I’m talking specifically about the single, reductive and non-context-specific number from 1-100 most of these sites spit out) are, I would argue, purely descriptive measures.
What Klout scores (or those from PeerIndex, or TweetLevel) can fairly be said to reflect is this: activity. It’s demonstrably true that increased activity on social networks (particularly Twitter) has a correlation with higher scores. Activity is not “influence,” of course, but it is something, and I’m not prepared to dismiss that something out of hand. So my influence score may in fact reflect some measure of my activity online, and my ability to encourage some form of activity in others. Thus, my score is descriptive of that activity level. It is not diagnostic of that level, however.
The scores, as they are presented, are inscrutable. My Klout score has fluctuated a fair amount in the past 60 days. I’m not sure why. I’m sure there are some very defensible assumptions for that fluctuation built in to Klout’s algorithm, but the point is that the reasons for that variance are entirely opaque to me. In other words, my score, and even the peripherals around it to which I have access, do not tell me why the fluctuation occurred. Thus, influence scores can not be used as diagnostic measures. (My topics, however, are right on the money. Klout is nailing this lately.)
A Cosmetic Problem
Similarly, the scores are predictive of nothing, which actually makes them very difficult to use. For example, I’m fond of comparing my Klout score with Snooki’s Klout score. After several months of concentrated effort, I have finally pulled ahead of Snooki (see, Mom? I told you I’d eventually make you proud.) But if you represented a cosmetics company trying to launch a new brand of sub-premium skin bronzer, who would you target – me, or Snooki? The answer is obvious, of course, but consider this: if my Klout is 68, and Snooki’s is 65, how much worse would I be at pushing bronzer? Would Snooki be twice as effective? Three times? A thousand times? There are two answers to this, of course. One is that as I am just one shade darker than an albino, the right answer is probably one million. The other answer is – you cannot possibly tell, and the scores obfuscate this, if anything.
So we have a purely descriptive measure – the influence score – but we lack the diagnostic and predictive measures that would allow us to do what every organization should be doing: learning, optimizing, and getting better. How can your company or brand take a flawed measure – the influence score – and make it better?
What Are We Really Trying To Measure?
Well, since the various influence measures are based upon a series of assumptions, let’s make a few of our own, here. First of all, most popular influence measures are heavily, if not entirely, based upon Twitter activity. Twitter’s asymmetric nature essentially means it functions as a broadcast platform – the few, reaching the many – so let’s start with something we can sink our analytical teeth into: reach and frequency. When an individual tweets out a link to some kind of content or offer, they do so with two hopes: that their followers will click on the link, and that their followers will retweet or otherwise disseminate the link to their networks, thereby increasing the potential reach of the message. So, when someone solicits, either explicitly or craftily, one of the various social media power users to help disseminate a message, the clear hope is that their message will be spread to as many people as possible using network effects.
While the exact relationship between followers and impressions is nearly impossible to calculate using clickstream measures (you have no way of knowing, after all, how many of your followers actually had the opportunity to see your message, let alone read it), it’s safe to say that more is better; in other words, there is undoubtedly a positive correlation between follower count and the number of people who interact with a given message to those followers. So, let’s assume that the behavior you are measuring for is retweets: tacit endorsements of your message, and increased exposure. Again, this is a pure reach and frequency game, and far easier to measure than “influence,” per se.
Here is a thing you can know: the average number of retweets per follower on Twitter. If you sifted through all that clickstream data from Twitter and examined tweets that contained links (we’ll exclude “conversational” tweets,) you could come up with the number of people who retweeted a given message, and then compare that to the number of followers to the original tweeter. In other words, if I had 5000 followers, and my typical links are retweeted by an average of 20 people, then I have a concrete number to look at: I can generate one retweet for every 250 followers, or 4 for every 1000. This smells suspiciously like a CPM number, doesn’t it? But to be cute, let’s call it “APM,” or actions-per-thousand. If my average link tweet gets retweeted 20 times, and I have 5000 followers, I can generate 4 APM.
With me so far? Now, let’s say that we do this for all Twitter users over a period of time to come up with an “average” APM. It won’t look as linear as the graph below suggests, but roughly let us assume that the average tweeted link is retweeted 10 times for every 1000 followers of the original tweeter. So, as the graph below shows, 20,000 followers would get me 200 retweets, 30,000 would elicit 300, and so on. So, the “Twitter average” APM is 10 (it isn’t, by the way ) .
So now I have a benchmark by which to measure my influencer campaign. Back to my original example, suppose my sub-premium bronzer brand (Ecruage, by CASPER) used Klout Perks to identify people with Klout scores above 65 to target. Now, since neither Snooki nor I have “Cosmetics” as a topic, this requires a bit of a leap of faith on the part of our brand, but not the worst one I’ve seen. So, Snooki and I each get sent a crate of bronzer, and we go to town on the Twitters. Snooki has a lot more followers than I do, of course, but we can both fairly be graded on the APM scale I’ve outlined above.
So I try this crappy bronzer, and I tweet about it. My followers expect me to talk about social media research, consumer behavior, bad music and gin, so my crappy bronzer message comes off as a bit of a non sequitur, as the graph below illustrates:
So while the average Twitter user might generate an APM of 10 (10 actions per 1,000 followers), on this particular message I only got an APM of 4.2. Not so good, CASPER! Snooki, however, gets all serious about this bronzer, and tweets the crap out of it. On an apples-to-apples, retweets-per-follower basis, her graph might look like this (Snooki is the top line):
So, on the topic of crappy bronzer, Snooki might have initiated an APM of 15. There is a clear delta between Snooki’s effectiveness in disseminating this message (the top line) and mine (the bottom line). Two things about this delta: first, it’s endlessly reassuring to me (this is not a contest I’d care to win.) Second – that delta between the expected value (10 APM, or retweets-per-thousand-followers) and Snooki’s (15 APM) can fairly be described by one word:
This is influence, folks. Whatever magical power Snooki worked on this crappy bronzer message (a likely mixture of the relevance of her message to her audience, her perceived authority on the topic, and the actual logical content of her tweet) she was simply better at disseminating this message than I was – and not by a little. The variance shown between her APM and the expected APM IS influence – it’s the mojo she worked using the same system as everyone else, measured like-for-like, that made her far more effective at getting people to spread her message. More message dissemination = more awareness = more trial = more usage. The circle of marketing life goes ever on and on.
The APM Index
Now, if you’d really like to wow your CMO, you could convert Snooki’s effectiveness and my (in)effectiveness into indices, which allows you to compare all of the “influencers” whom you targeted relative to the average. Here’s a primer on calculating index scores if you need one, but essentially all you do is divide the average for the category into the number you are comparing it to, and multiply by 100. This means that the average for ANY index is 100 (in essence, if you divide the average into the average, you get 1, which multiplied by 100 = 100.) Snooki’s APM of 15 equates to an index of 150 ((15/10) x 100), while my paltry effort comes out to an index of 42.
So, to close the loop on this, we started with two similar Klout scores:
…and we end up with our own, topic-specific measure of actual, observed influence – as expressed by the differential in message dissemination:
In my example, there is considerable difference between the original descriptive statistic (the Klout score) and this statistic, which moves us much more in the direction of a predictive statistic (at least on the topic of bronzer, and perhaps the category of cosmetics) that the learning organization can use to make the next “influencer” campaign even better. The influence score helped to make the initial cut, perhaps, but the only way for your company or brand to truly gauge influence is to do the work, and determine which individuals outperformed the average, and which underperformed.
Caveats, Carefully Considered
Now, there are a couple of things (at least) that one might take issue with here – both of which could fairly be described as oversimplifications on my part. The first, obviously, is that the mystical force that allowed Snooki to generate an APM of 15 compared to the average of 10 might not wholly be attributable to “influence.” But if it ain’t an answer, I don’t care – it at least serves as a handy heuristic for the nearly unmeasurable constellation of circumstances between the original tweeter and his/her audience that caused the message to mysteriously do better than the average would have predicted. Influence? Yeah, I think so. It’s at least behavioral, relevant, and a lot closer to “influence” than the activity-based scores we currently have – with the bonus of being relevant to your brand.
The other bone you might pick with me here is that my calculation – and reducing the whole model to differential message dissemination – is also overly reductive. I’ve taken what is surely a complex system and turned it into a back-of-the-envelope calculation. You’re right – it is a back-of-the-envelope calculation. That’s why companies might actually do it. You don’t need an analytics whiz on your staff to take this first pass at measuring your influencer campaigns, and until everybody catches up with you, this’ll do. Master this first, then break out the HAL 9000 when it’s time to make finer distinctions. (I also know a really smart social media research company that could help. Just sayin’.)
The bottom line is this – let’s say you actually use influence scores as some kind of crude segmentation – how will you test your work? How will you know, in other words, if your efforts were successful – and more importantly – what you can learn from them to make them better? The answer, I would submit, is to start with the current crop of popular influence measures as a first pass, but remember that they will never be as accurate as your own performance measures, even as crude as the one I’ve suggested here. There is nothing wrong with Klout, PeerIndex or any of these measures. There are only lazy marketers. And if you are reading this far, my friend, at word 2,200, you are surely not that.
this reminds me of the reasoning I used back when I was doing analytics for the grocery biz. first we'd do a demographic breakdown of a group of zip codes or census tracts around retailer locations by age of head of household and presence/absence of kids. next we'd do a consumption grid for a given brand or size, flavor, whatever against those demos. finally, we'd map that grid (usually national data with a minimal sample size) against the zip codes and tell the retailer "you should carry these size/flavor/whatever in your stores - here's the analysis showing that it will appeal to your consumers." then we'd run away and bury the data in a deep hole.
this is a little like that, except we never went so far as to identify specific people in those neighborhoods....