3 important questions to ask about marketing studies

Posted by Christopher S Penn on Feb 2, 2012 in Advertising, Marketing, Metrics | 4 comments

Every morning, my first few tasks when I get to the office are to make a cup of coffee, fire up my RSS reader, and start digging into the day’s news. Nearly every morning, I see the same thing that makes me emote a /facepalm: a headline that reads, “New data shows…” or “New study shows…” followed by an infographic or a witty blog post.

In almost none of these articles do you ever read about the data itself, just the hasty conclusions. This is a major problem because marketers who don’t do their own research and rely on other organizations can be led badly astray, damaging their businesses. Relying on bad data and bad research is like sailing a ship by a faulty map: sooner or later, you’re going to hit an iceberg or sandbar or reef and your ship will sink.

There are three fundamental ways that data collection can go wrong. I’m going to vastly oversimplify here – I recommend reading up on Tom Webster’s blog along with the AAPOR best practices guide if you want to seriously dig in.

Selection bias is when you have a sample of the population that is non-representative of the whole population. For example, if I ask for volunteers to take a survey about, say, Jay Baer’s popularity, only people who have a strong opinion about Jay are likely to respond to the volunteer survey. Thus, my data is skewed.

Measurement bias is when you have a problem in how you measure your data. There are so many ways that measurement can go wrong. For example, if you opt-out of Klout, your Twitter handle returns the same error code as someone who was never part of the Klout database. That’s an important distinction. Doing a quick scan of the Klout API and then rushing an infographic out the door about how many people have opted-out of Klout creates bad conclusions because you have a measurement bias problem.

Finally, intervention bias gives you bad data when you’re trying to compare data. You see this most often with companies offering some kind of paid service and pushing a study to back up their claims. I ran into this with an SEO firm that was claiming its method for boosting SEO was incredibly powerful and they rushed to attribute all of the company’s SEO improvements based on their work. What they failed to account for were all of the other marketing activities that were occurring at the same time that were interfering with the data. Amusingly, after I stopped working with the company, I looked at our SEO data and saw that we were getting the same (or better) results without them.

Whenever you read marketing material disguised as content from a company trying to sell you something and offering research or data to validate it, see if their marketing material offers answers to these three questions:

1. Who did you get your data from (and how did you pick those people)?
2. How did you measure your data?
3. If you drew a conclusion from your data, how did you account for other activities messing with your results?

If the marketing material doesn’t include solid answers to these questions, then do not bet your business, your job, or your marketing budget on the conclusions being offered, because there’s every chance that either a self-serving conclusion was drawn or the data is faulty. Accept it as a nice fluffy piece of content to mark as read and move onto the next thing in your blog reader or inbox.

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How to track return customers using Google Analytics

Posted by Christopher S Penn on Jan 30, 2012 in Advertising, Marketing, Metrics | 1 comment

One of the most valuable people to visit your website is your existing customer. This is the person who’s already bought into you, the person who has already decided you’re worth doing business with. This person is leagues more valuable than the random pay per click visitor. Do you know what your returning customers want from your website efforts?

Here’s one way to make that determination. If you’re using Google Analytics and you have a place on your website where only returning customers go, this will help you identify and track them.

First, you’ll need to modify your Google Analytics code on that customer-only page. This can be a thank you page after someone has filled out a form or purchased something from you. It can also be the screen immediately after a login to a web service, or even a special customer-only landing page that you direct email subscribers to.

Create a custom variable on that page in Google Analytics. Here’s the format:

_gaq.push(['_setCustomVar',
1, // This custom var is set to slot #1. Required. You can have up to 5.
'Member Type', // The name of the custom variable. Required.
'Paying Customer', // The value of the custom variable. Required.
1 // Sets the scope to visitor-level. Required for tracking customers.
]);

Place this within your Google Analytics tracking code for that page only. You only need it on the page or pages that returning customers visit the most.

Next, you’ll want to see what your returning customers are actually doing. Create a custom traffic segment in Google Analytics and identify it by the customer variable name and value. For the example code above, it might look like this:

Congratulations, you now have a way to identify returning customers! Browse through Google Analytics data with this traffic segment on to see only those returning customers and what they did on your site, where they went, what was most popular, where they came from, and arguably most important of all: did they convert again?

If there are certain pages which returning customers visit far more than others, you may even want to think about rewriting them or focusing on them. For example, if returning customers are constantly revisiting a tech support page about a certain product, you might have an early indicator that something is wrong with the product.

Obviously, you can tailor these custom variables to anything you like. If you host a website with a variety of subscription levels, you could track to see whether Gold members visit different pages than, say, Silver members. The sky’s the limit with custom variables and your returning customers.

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Stop measuring audience in social media

Posted by Christopher S Penn on Jan 20, 2012 in Advertising, Marketing, Metrics, Strategy | 15 comments

Have you heard any of these questions lately:

What’s the value of a Facebook fan?
What’s the value of a Twitter follower?
What’s the value of an email subscriber?

I know I certainly have, and these are the wrong questions to be asking. Why? They assume that all people are the same. Let’s instead crib from Batman:

It’s not who I am underneath, but what I *do* that defines me.

There are, broadly speaking, two types of audience members: active and passive. Active members read your newsletters. They click on your tweets. They like your status updates on Facebook. They share with their networks. They read and forward your emails. They buy your products or services. They recommend you to other people.

Passive members… do nothing.

Here’s an example. I have, at the time of this writing, almost 49,000 followers. Awesome, right? I must be a social media success story. Not so fast. If I segment out the traffic on my website using Google Analytics’ Advanced Segments and ask me to show number of absolute unique visitors in the last 30 days from all things Twitter, the true number of followers I actually have that did the bare minimum of clicking on one link to my site in a month is:

1,293. That’s how many followers I have that actually showed up in the last month. That’s a pretty far cry from 49,000. Thankfully, there’s no cost to having the other 47,000+ in my network, but they’re basically dead weight that are providing nothing at all. It’s not like I’m asking them to buy a car or something, just click once on one link in 30 days in order to show up in the chart above.

Here’s another slice of life, my email list. Over 12,000 people subscribed. Great success story on the surface, but if we dig a little deeper…

Yep, less than half opened or clicked on ANYTHING in the last year. The rest of the list is dead weight, and I can and should just ditch ‘em since most email companies charge based on the number of emails sent.

If you’re trying to figure out the value of a person in your audience, you’re barking up the wrong tree. A person in and of themselves has no value until they actually do something, anything, to show that you have some level of engagement with them. Active members of your audience have value. Passive members do not. Start by figuring out how many active members you have, and you will have a much better idea of how your social media efforts are actually performing.

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Klout vs. PeerIndex: data challenge for the data junkies

Posted by Christopher S Penn on Jan 9, 2012 in Metrics, Social media, Social networks | 3 comments

Rather than just outright publishing my own conclusions, I’m going to try an experiment with you, my data junkie friends. We’ve talked about influence scores and reputation scoring systems like Klout in prior posts. We’re not going to rehash that here.

What I do want to pose to you is this: what’s the difference between Klout and PeerIndex, and which is a better indicator of influence, if any?

To that end, I present to you a simple data file. Here is a list of 15,737 Twitter handles scored by both Klout and Peerindex. For the most part, these are people who tweeted in the past month or more using the #Marketing hashtag at least once. In the data file you’ll find the following:

Klout score, PeerIndex score, Difference, Twitter Handle

Take a look at the file (it’s a text CSV). I did the boring part of the work, pulling all the scores. Now it’s up to you to do the juicy part and find the goodies. Mess around with it in the spreadsheet or data crunching tool of your choice. See what conclusions you come up with, then either post your conclusions in the comments or blog it on your own blog, linking back to this post so we can all find it.

Good luck! I’ll post my own conclusions separately after I’ve heard from you.

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How to improve marketing ROI

Posted by Christopher S Penn on Dec 12, 2011 in Advertising, Marketing, Metrics | 2 comments

Let’s talk a bit about improving marketing ROI today. How do you improve your marketing ROI? First and foremost, decide whether the outcome you want to measure is financial. A non-financial outcome, by definition, has no ROI because ROI is a financial formula. For example, if your goal is to get elected to political office, the outcome is either you are or are not elected. Unless you count bribes and “favors” as your actual outcome, you cannot by definition measure election to office with an ROI calculation. You can determine how much you spent to achieve that result, but that’s it.

So, assuming that our outcome is financial in nature, what comes next? Let’s go back to the Line of Sight Digital Marketing formula.

We know that net profit comes from margin times volume. To improve ROI, we can either move the margin lever up or the volume lever up.

There are two ways to move the volume lever up. We can either convert more people (increase action) or grow audience. There’s a catch with growing audience: without more investment of resources, you plateau fairly quickly with audience growth. You can invest more time or money to grow audience, but you have to watch your numbers like a hawk so that increased spending on audience growth doesn’t actually reduce your ROI.

The place you can move the needle much more is action. When you look at the numbers surrounding action, from clickthrough rates on emails to conversions on your website, you’re often looking at single or low double digits. We may say that a Twitter DM campaign has a highly successful conversion rate of 4%, but when you think about that, you’re effectively saying 96/100 people aren’t buying. An email campaign might have an open rate of 10%, but that’s saying 90/100 people never laid eyes on your email. There’s a tremendous amount of growth there, and is probably the first place you should look for moving the lever up on the volume side.

There are two ways to move the margin lever up. We can either increase income or reduce expenses. There’s a catch here as well! Imagine a rubber band holding these two levers together. Pull income up hard enough and the expense lever eventually comes with it. Logically, this makes sense – if you make some kind of good or service, you eventually need to hire more people to help you produce it if you want to grow your business beyond your capability to do it all yourself.

The converse is also true. Drag the expense lever down hard enough, and the income lever comes with it. You can only cut so far in expenses before you reduce your ability to create income. Logically, this also makes sense – fire everyone and you’re out of business.

As a marketer, there’s a good chance you will have little ability to change the pricing of your products and services. There’s a good chance you will have little ability to change what your company spends on salary, benefits, and other large expenses as well. Thus, if you have a directive to increase your marketing ROI, focusing on the margin side of the house is likely going to be a long and difficult uphill battle. Make changes where you can for easy increases in income or decreases in expenses, but then turn your attention back to conversion and audience growth, as these should be your domains.

Improving your marketing ROI means measuring your margin and volume, plus the subsequent subcategories. Keep an eye on your key performance indicators and attaining improved ROI should be within your reach!

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Should you opt-out of Klout?

Posted by Christopher S Penn on Dec 7, 2011 in Advertising, Marketing, Metrics | 17 comments

More than a few people have posted recently about opting out of Klout. Here are a couple of pieces that are worth your time to read:

• Read Liz Strauss on why Klout violates 3 important principles to her
• Read Martjin Linssen on how many people have de-Klouted and lack of trust

Given some very well thought out pieces about opting out of Klout, should you consider it?

If you’re like Liz and Klout is operating against your principles or ethics, then it’s an unequivocal yes. One of my favorite tenets is by the musician Jewel, who famously said, “No longer lend your strength to that which you wish to be free from”. Depart Klout and don’t look back.

There’s a flipside to not being a part of Klout: anyone and anything using its algorithm is going to exclude you. Why? Here’s what Klout’s API returns when you pull a Twitter user ID that doesn’t exist:

{“status”:200,”headers”:[],”body”:{“error”:”No users”}}

And here’s what the API returns when you pull a Twitter user ID that opted out:

{“status”:200,”headers”:[],”body”:{“error”:”No users”}}

They are identical. When you opt out of Klout, you effectively declare that you no longer exist.

Publicly, that will mean little things like +K votes (and the associated Tweets that come along with them) and exclusion of pointless ads like Klout Perks for body wash and test drives for cars. That’s no big deal, and if that were the only consideration, there’d be no reason NOT to leave.

Privately, however, the Klout API is being used fairly heavily. I can tell you as a developer that I run into “Service too busy” notices more often than I’d like. Klout’s API gives you at the free level 10 calls per second, 10,000 requests per day, which is a tremendous amount, and people are using it. I know I certainly am. How is it being used?

Here’s an email service provider that pulls Klout score into lists so that you can segment your lists by Klout score. If you’ve opted out of Klout, you obviously will show up in the segmentation of unknown user.

Here’s an integration with Zoho, a small business CRM, to pull in Klout scores:

And here’s one that is probably the most eyebrow-raising of all, a plugin to integrate Klout scores into the Salesforce CRM, the gold standard of large enterprise CRMs:

You may say, rightly so, that you don’t especially care how you show up in someone’s email platform or CRM, or that your other behaviors such as purchase history should matter more. I don’t disagree. I think generally marketers do a lousy job of using the data they already have access to. The caveat with that position is this: right now, marketers and businesses like Klout enough to be using it and integrating it, even if it’s a terrible measure of actual influence.

That means that without a Klout score, you show up to these systems as an unknown user, as a second class citizen (even if you are clearly not, like Liz Strauss).

If a call center has two emails in queue to respond to and an automated customer importance priority system, and one customer has a Klout score of 25 and the other is a zero, your average minimum wage customer service representative isn’t going to care about your ethics or principles. They’re just going to get to you last in the queue because people with scores higher than unknown will be automatically ranked and queued ahead of you.

Here’s the huge problem: neither I nor anyone else except maybe Klout’s IT department have any idea just how many systems are using Klout’s API. Mark W. Schaefer has indicated that in anecdotal data, HR systems are integrating it now.

If Klout doesn’t violate your personal principles, then the safe, conservative choice for now is to leave your account as is. You definitely don’t need to participate with it or give it any mindshare, but removing it outright might have deeper impacts in third party systems than might be overtly apparent at first. Ignoring Klout’s existence it is a safe, no-effort strategy.

For those who did choose to opt-out, there’s this to give you hope: people are using Klout right now because there isn’t a better, more accurate, more insightful measurement. In the absence of good metrics, we often choose to rely on bad ones even knowing they’re bad. There is both incentive and demand for someone to create a better social media influence metric than Klout, so you have that to look forward to.

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