I was thinking about our small boutique agency. As we continue to grow and create successful campaigns for our clients, we work to carve out a space for those companies who greatly desire our skill, expertise, creative tech skills & bandwidth -while meeting and exceeding their objectives. Yes and keeping the money in their pockets with low cost innovation and implementation and high returns. Some believe the more “likers” and followers you have the better success you will be – yet they forget that it is quality not quantity you want via information and engagement. There is today no accident that your neighbor, former high school teacher, doctor, dentist and boss former & current are all on Facebook. (Yes we may all want to take an extra minute to review our privacy settings) It means that all the brands you can think of, businesses, products and services know we are all there too and they are looking for new marcom partners and business advisers to help them reach all of us. Both online and offline. It will be those such as ourselves with a wealth of award winning traditional talent and  savvy experiential technical talent – who clearly understand and can translate that user experience – on an array of platforms, that will help you knock it out of the park- in reaching that customer in the place you desire to have them go.

In the past – the key to audience targeting was focused on assigning people to demographics such as age, gender and location. While this info. is still vital – with so much data available to us now and the idea that understanding that data first- before going forward with that “knock it out of the park campaign” means much success in the campaigns you create.

“Targeting can be and is much more dynamic and can gauge your interests and preferences.” Ever notice that the ads on Facebook and Twitter, the suggested people to follow and things that relate to what you like and care about are truly on par just for you? It is this behavioral targeting that is now the future of where the internet and your marketing and communications is going both offline and online.

Mashable.com has a great article from a week ago that speaks to this very topic. Lauren Drell writes about 4 Ways That Behavioral Targeting is Changing the Web. It is a brilliant article that I encourage all of you who are looking to better understand and target your customers to read.

Drell gives a great explanation of how this works for those that are not yet familiar -“Here’s how behavioral targeting works: Targeting companies establish an agreement with a publisher, who puts a piece of code on his website. (That publisher must have a clearly stated policy for the consumer to opt out from having data collected.) Then, when you’re browsing the web, the site will put a cookie on your browser, which populates as you surf. (Though one interviewee, ContextWeb, targets based on content and not cookies.) Now that your browser has a cookie, the targeting begins. Data points amass as you click your way from site to site, taking note of what you buy, what you read and what you search for. The more time goes on, the more data is collected.”

Companies that are paying attention to this understanding and moving towards  behavioral targeting with their data – through their advertising- can’t help but to expect more success and engagement by people who have indicated on the web what their preferences are and that they would be interested in YOUR product and or service. Of course this detailed data collection can be more costly, but the sales conversion rate of targeting to the correct buyer is sure to offset this cost. The viral advantage grows as well – as those accurately targeted customers- then SHARE those products , your products – with prequalified friends, family and colleagues.

Viva the future.

Best Nicole

I came across a post on Mashable.com written by Tim Trefren that provides 3 new ways to measure the social web. As with anything that is demand – the best thing that you can have – to ensure that you are making methodical choices is data.

At the end of the day you want engagement, you want the customers to return and you want them to spend more. By collecting data that focuses on those goals -you leverage social media content rich tools, that best fit your business.

Best Nicole

When most people think of web analytics, they think about pageview tracking; basically, measuring which pages on a website are being viewed. Pageview tracking is a well-established technology, but it’s no longer meeting the needs of many of the most well-known companies in social media. Companies like Facebook (), Zynga, Slide, and RockYou are spending tons of resources building their own internal analytics tools.

There’s a reason for this: Social media is highly competitive, and the biggest advantage you can have is data. To improve and grow, these companies need to gather as much information as they can, and they need more than simple pageview tracking.

In the following sections I will cover three of the most important things to measure for social applications.

1. Funnel Analysis: Measuring Conversion Rates

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One critical kind of analysis that social apps require is called Funnel Analysis. This is a way of measuring conversion rates, which is the lifeblood of all applications. The term “conversion rate” refers to the total number of visitors who came to a site, compared to the number of visitors who did a desired action (such as creating an account or purchasing an item).

What Funnel Analysis gives you is a more granular way of analyzing conversion rates. Instead of simply looking at signups divided by total visitors, you figure out the steps that have to be taken to get a user to sign up and measure the individual conversion rates between steps. As you can see from the image above, there’s often a pretty steep dropoff between each step, giving you the namesake funnel shape. (Note: the image uses made up stats and is for illustration purposes only.)

This more granular look at conversion rates can have surprising results. Let’s take a look at Twitter’s () signup funnel:

1. Hit homepage
2. Go to signup page, fill out registration form
3. Browse suggested topics
4. Add () e-mail friends
5. Search for someone

As you can see, the signup process is pretty complicated, and will benefit from detailed analysis. We might find, for example, that there’s a huge dropoff rate (a “dropoff” occurs when many of the people who made it to one step don’t make it to the next) at the “Add e-mail friends” step. Once we’ve discovered a dropoff rate like this, we have to figure out the root cause. The dropoff rate at the “Add e-mail friends” step could mean that users are unsure how to continue, causing them to leave, or they might not want to add their e-mail information. We would have to test to make sure.

Ultimately, Funnel Analysis is about finding and improving trouble spots in a website. With continual analysis, changes can be measured and ideas can be tested over time.

2. Engagement Tracking: Measuring What People Do

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As I mentioned earlier, pageview tracking is becoming less and less relevant for many web companies. Instead of the basic unit of measurement being the pageview, they are starting to track more directly relevant things, like the actions people are taking. Twitter, for example, may want to know how many tweets the average person sends and what they are searching for, not how many pages they viewed. Pageviews are just a way of approximating the information we really want, and as the web grows more interactive, they become less and less relevant.

Think about this: Sites exist today on which you never actually change the page. These are highly interactive sites, but they are impossible to track with pageviews, so traditional analytics tools are useless.

This will only become more common as time goes on and more companies develop highly interactive applications and adopt AJAX loading techniques.

3. Visitor Retention: How Many People Come Back?

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This next technique measures a fairly complex but extremely valuable metric for successful web applications.

You can think of Visitor Retention as a measure of how “sticky” your site is. What we’re really measuring is the percentage of people who come back again and again. The most common way of approaching this is to look at a group of users from a single time period (a week, for example) and track their behavior over time.

Here’s an example of a retention table that should help clarify things:

Each row shows the weekly retention rates for a single group of users (sometimes known as a “cohort”). The first row, for example, is the cohort seen between December 7 and December 13, 2009. We can see that 15.15% of the users in that group came back after 1 week, 13.4% after 2 weeks, and so on.

This is crucial information, particularly for social applications, because most of the value lies in the size of the community. An application with low retention is like an empty shell — many installs but few active users — and you don’t want to build an empty shell. You want a thriving, vibrant community.

Retention is a huge factor in building a strong community for a few reasons: You don’t have much of a community if everyone is a newcomer (so more old users is a good thing), and the nature of retention is such that you get disproportionate returns on any increases you make. Without going into too much detail, an example would be that increasing retention by 33% might give you 50% more users in the long run.

Twitter is again a good example for us, as the network has been plagued by low retention rates. Twitter may seem successful now, but their low retention rate is troubling. In the past, companies that seemed to be extremely successful (think early Facebook apps) ultimately lost their edge because they couldn’t retain their users.

It’s entirely possible that Twitter itself could be a fad. With such low retention, I wouldn’t necessarily be surprised — but it is still too early to tell.

Conclusion

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There’s a lot to learn about analytics from the frontrunners in social media. The intense competition has resulted in many new and innovative ways to track and analyze visitor data.

We covered three such concepts in detail today: Funnel analysis, which lets you track conversion rates across whole parts of your site, engagement tracking, which is becoming more relevant than pageviews, and visitor retention analysis, which helps you understand and optimize the number of repeat visitors you get.

There are some serious hard cold facts that point out that even the biggest brands are experiencing HUGE changes and drops in brand loyalty! Everyone should be reading this article. I hope that you will pass it on to your colleagues and friends. It is time to take note and make the changes needed—to get those customers back now. In this new economy, you want to show your customers how much you value their brand commitment, and how eager you are to make adjustments that reflect the times and the changes in their lives. You want to prepare for a committed journey with them as we move towards the future…a future where the customer is put first and foremost.

Nothing could be more important than that!

Best Nicole

I thought this post from today was so brilliant I couldn’t wait to post it. Everyone—in most aspects of what they do—is constantly searching for time instead of making decisions that will give them more time. When the facts and evidence lay before you and the decision is clear, most people will wait and mull over all the angles that are distinctly outlined rather than stopping and just making a decision: Yes or No.

Time is the one thing we all can’t get back and time is the one thing that is worth the most in dollars. Why not use it wisely so that you have more of what you are constantly looking for? Imagine the possibilities if you had time for that next thing in line. Thanks Seth Godin for such a great post.

Best Nicole

I Need More Time

First rule of decision making: More time does not create better decisions.

In fact, it usually decreases the quality of the decision.

More information may help. More time without more information just creates anxiety, not insight.

Deciding now frees up your most valuable asset, time, so you can go work on something else. What happens if, starting today, you make every decision as soon as you have a reasonable amount of data?