The oh-so-elusive engagement metric

I was fortunate enough today to catch Eric T. Peterson‘s webinar about engagement, held by the International Institute for Analytics. The presentation was informative and, in some ways, reassuring. Why? Because even one of the leading experts in Web Analytics essentially agrees that engagement is not an objective, clearly defined metric, nor an easily measurable one. (What a sad day it would be to find out that measuring engagement is clear and simple, and I was just missing the point!)

While Peterson spoke of various definitions, as well as a “formula” by which he has measured engagement, he was very clear that this wasn’t the only possible formulation, nor that there was even one agreed upon industry definition.

What it came down to essentially was that:

  • Engagement truly doesn’t have a clear definition, at least not in the sense of “it is comprised of X + Y + Z metrics”. We all agree on the concept generally, but not necessarily what elements go into measuring it.
  • Sites really need to evaluate what engagement means in relation to their experience.

Perhaps this should be disheartening. Perhaps I should want a clear, defined notion of “engagement”.

But here’s why I don’t …

  • Web analytics is not simple (and anyone who thinks it probably isn’t doing much with it – if you are, and you still think it’s simple, please send me your resume!) Therefore I can’t believe a concept as powerful as engagement can actually be simple. Few (if any) web metrics are useful in and of themselves. We need context for our data to be meaningful. Engagement should be the same – it needs to be defined in the context of the site in question. (And its definition should be continually repeated and reinforced within an organisation, so everyone understands. A metric becomes more meaningless as we start forgetting what it actually represents and how it is defined.)
  • This fuzzy lack-of-definition of engagement allows flexibility. It allows the concept of an engagement metric to be truly tailored to the site it is measuring. No cookie-cutter solutions, or square pegs shoved into round holes, but something that is thought out, keeping in mind the goals of the business and the site’s visitor behaviour.
  • But most importantly – sites that work to define engagement as it pertains to their experience, to capture the data and to process, analyse and segment by engagement level will not let it turn into another useless metric touted at executive meetings. It will have meaning because of its specificity to the site in question, because it is truly helpful in understanding the site and its visitors’ behaviour.

Web Analyst = information architect

Everyone knows that analysts are constantly elbow-deep in numbers, math and data sources. However, in seeing my own skills develop from my very first analysis, as well as training and working with other analysts, it quickly became very clear that an analyst’s ability to translate large volumes of data into a concise, clear summary separates the mediocre from the invaluable.

Yes, web analytics can be granular. Yes, you are looking at a thousand different things, pulling together multiple data sources, segmenting and diving into detail, even investigating theories that did not pan out. But if you can’t tell others what you found, even just the one most important point, in a sentence or two, and in plain language, then you are missing an essential skill that we need as analysts. Your role is not just to dive into the data and draw out insights. It’s to share them with others in a way that they can understand.

Why?

Executives are busy. If you can’t fill them in on your findings in one or two sentences, they don’t have the time. You are not always going to be given an hour to present your findings in a lengthy PowerPoint. At times, the closest you may get to “presenting” your analysis may involve bumping into your President in the lunch room and having exactly 15 seconds to respond to a, “So how’s that home page redesign performing?”

Same thing goes for email. Eyes glaze over upon opening a lengthy email (normally followed by “Mark as Unread” with a, “I’ll come back to it later …”) Ask yourself this: “If someone only reads the first paragraph, have I given them everything they need to know (even if it’s abridged)?” By all means, provide more information below, or in an attachment, for those who are more involved and need additional detail. But understand that many just want (or only have the time for) the CliffsNotes version.

The simple truth is that executives are also not as close to the project as you are. You need to be able to pull yourself out of the trenches and find a way to summarise your insights to someone who is not as close to the business and the details of it as you are.

What it comes down to is that your job is not just to analyse data, you are also an information architect. Your role involves taking what is complicated, and making it feel easy to understand and digestible to a less-analytically inclined audience. This involves perfecting two crucial skills:

1. Summarising. (Then summarise your summary. Chances are, it’s still too long!)

2. Presenting your findings in the right way to the right audience. A twenty-five words or less approach may work with your executive team. However, further details with visuals may be appropriate for your data-driven business user. Know the difference. So much of our online business is in trying to present the right offer/ad/site experience/etc to the users of our site. We need to do the same to the users of our insights.

Protect YOURSELF [Facebook Privacy]

Amidst debates about Facebook privacy, I can’t help but being amused.

Don’t get me wrong. I am concerned about my online privacy like anyone else. As much as possible, I have tried to set up my Facebook account to be private and secure, and continue to check my settings as the privacy policy changes. I check how my profile looks to people in certain groups of permissions. I am cautious about who I accept as a friend. I am careful with what I post, and even careful about what comments my friends post on my wall, photos or statuses. I have Facebook configured so that people I work with can only see certain content.  I have two Twitter accounts, one private (personal) account, and one public account.

But at the end of the day, I am acutely aware that information you post on the internet is public. What I find interesting about the Facebook privacy debates is that it seems we have forgotten this.

Where did this naivete come from? Why do we think that the internet is suddenly a secure space, where corporations will build their business around protecting us? (And corporations we’re not even paying!)

I remember early users of the internet being conscious of this, perhaps even concerned or paranoid about their privacy. Internet banking and online shopping had to convince users they were a secure way to transact online. We knew that emails weren’t Fort Knox and were warned not to share confidential information openly online.

When did we get lulled into this sense of false security? And why did common sense fly out the window?

If you want the benefits of the internet and social media, you have to accept the downsides too. It’s rather simple. Don’t pose for photos you wouldn’t want posted. Don’t post photos you wouldn’t want shared. And don’t write, say or do anything that you couldn’t comfortably show your grandmother or your boss. Take responsibility for your online privacy. A corporation will do what is in its best interest, and we must do what is in ours.

A few thoughts on forecasting

It seems fitting that my first post should involve something that occupies a tremendous amount of importance (and potentially, debate) within an organisation (and certainly involves a lot of sleep loss for me personally!)

Forecasting.

If you are new, or fairly new, to forecasting on your website, I’ll share some hard-learned truths.

You’re always going to be wrong. Always. The very nature of a forecast means you will always be wrong … and that’s okay. (Don’t get me wrong. When it actually happens, it’s thoroughly depressing, and often has you chasing your tail to find out why, but it’s still okay.) Your aim is just to be wrong as little as you can – and to be able to identify why your resulting actuals are off from your forecast. I would argue that divergence from your forecast today will make tomorrow’s re-forecast better, but only if you can explain it and learn from it.

Your forecast is only as good as the information you have. As you look back over your site’s history, if there are events you can’t explain, or inputs into your traffic that you fail to identify, your forecast will be more off than you would like it to be.

Don’t have all the information you need? Get it. Gather anyone/everyone/any information or inputs you need. If the company’s eyes are on your forecast, their gaze will stray if you frequently prove too far off. If they’re not yet looking at your forecast, they won’t ever start if you can’t prove your history of accuracy.

There is a difference between a forecast and a goal. As you start forecasting site traffic, ad space, conversion rates, lead generation (etc), you’ll need to explain this. Many times. Your forecast will be based on your site’s history and its inherent trends. But as an analyst/statistician/forecasting guru, you alone can’t identify everything that will happen in the future. (And if you can, give me your number – I have a few questions I would love answered.)

This is where your business/development/product team come in. Your forecast can estimate where your site will be in the future, based on your current trajectory. But you need inputs from others to anticipate future planned growth, that’s not evident in the data.

Let’s say your forecast suggests your site will be up 5% year-over-year. If your executive team want your site to  be up 20%, you need your business/development/product team to either a) temper this expectation, if it’s not reasonable, or b) advise how they will achieve this. If your fine-tuned, well-informed forecast suggests you’ll be up 5% year-over-year, 20% is not a forecast, it’s a goal. You can’t reach 20% YOY without at least a basic idea of how you’ll get there, and any attempt to incorporate it into your forecast without a skeleton of a plan will reflect poorly on your forecast, rather than reflecting on the failed execution of the plan for growth.

The moral of the story? Forecasting can’t occur in a silo. Analysts, business and executives must all get their “feet wet” to produce something that all are comfortable with and can rely on.

Not forecasting (yet)? Even if it’s rudimentary (forecasting your basic web traffic metrics only, e.g. Visits, Unique Visitors, Page Views) get cracking. It’s wonderful to be able to analyse, segment and test your history, but your business and executive teams will really appreciate even a lightly dotted line of where they’re headed.