Yesterday, we went over the need to create an activities timeline that basically plots every relevant action your company takes across all media. Press releases, product launches, blog posts, white papers, ad campaigns, Twitter engagement, etc. Today, we are going to look at creating outcome timelines. Same basic process, but actually easier based on what you choose to measure.
Here. Before I go any further, check out this video. It will hopefully be a good intro into some of the content of this post:
You can kind of see where this is going right? Once we have the activities and the outcomes timelines mapped out, we are going to overlay them. (That’s right: stack them on top of each other and look for commonalities.) That’s how the R.O.I. analysis will begin: By looking for obvious correlations between activities and outcomes, and then either proving or disproving causality.
So what types of outcomes should we map out along timelines? Well, that’s really up to you. Depending on your budget, capabilities and resources, you can create as many as you want. There is probably no limit to what you can measure and analyze. Every company is different. That said, here are two things to keep in mind:
1. Focus on measuring what matters. Ever heard the term “paralysis by analysis”? It starts when companies start getting bogged down with nonsensical measurement. When you measure everything, you end up measuring nothing. So my advice here is figure out what metrics actually matter to your business and start there. (A piece of advice shared by Avinash Kaushik in this post - Go straight to #5.)
Speaking of Avinash, let’s borrow some of his advice when it comes to figuring out what matters (what you should measure first):
“If you can’t get your management to identify goals for you, update your resume and apply for other jobs.
While you are waiting, focus really hard on only reporting metrics that will help 1. increase revenue 2. reduce cost and 3. increase satisfaction. Can’t go wrong with those three.”
Incidentally, although Avinash’s post on measurement focuses mostly on web analytics, it’s a great read and most of his lessons are adaptable to other types of metrics as well. Read the post, bookmark it, and revisit it often. (Hat tip to Christopher Penn for that link, by the way.)
So the lesson here is to focus first on metrics that truly matter, and then (assuming you want to assign additional resources to the measurement of secondary metrics) expanding your measurement repertoire.
2. Focus on what you can actually measure. Unless you have a quasi-unlimited budget, enormous resources and extremely sophisticated data management capabilities, you aren’t going to be able to capture and measure every bit of data that comes your way. Every company’s capabilities, expertise and toolkit is different. While some of you may be able to implement fairly impressive measurement practices over the next few weeks and months, most will find that much of the data you wish you could capture, plot and analyze will be beyond your reach. Don’t panic. Heck, don’t even sweat it. Measure what you can, make the most of it, and don’t worry too much about what you aren’t able to measure yet. Your ROI analysis will require a little more art than science, but that’s okay. As you will soon see, certain key metrics should give you a pretty good idea of the effectiveness of what you are doing.
Okay. The first step is to identify key metrics for your outcome timelines, right? For the sake of clarity, let’s divide them into two groups: Financial outcomes and Non-financial outcomes.
A. Financial Outcomes
Financial outcomes are among the most basic business metrics. Raw performance measurement. No interpretation or estimation required. The most obvious is of course sales performance. So go to your VP sales and get yourself some sales data. (Chances are that your company’s sales data is already plotted over time, so your sales $ timeline may only be an email or database query away.)
Along a timeline, your sales data will hopefully look a little something like this:
Simple enough, right? (Again, most of this data can be mapped out in Microsoft Excel, which ought to work well for most companies, but the platforms you use are entirely up to you.)
Another way to look at financial outcomes might be to look at the number of transactions along a timeline rather than just looking at sales dollars. (Remember the F.R.Y. methodology that started this whole series a few weeks ago? Frequency, Reach and Yield? Looking at deltas in the number of transactions might help you figure out where some of the changes in sales revenue are coming from. (Hint: If the number of transactions stays flat but your sales revenue increases, you know that you have increased your Yield – the “Y” in F.R.Y.) When it comes to analyzing the impact that your activities is having on your sales (the return or “R” in the R.O.I. equation), knowing whether revenue deltas are coming from Yield, Frequency or Reach is pretty important.
All this to say that tracking transaction numbers in addition to sales $ is a pretty good idea.
Also in keeping with the F.R.Y.methodology, consider tracking active (transacting) customer counts so you can see if your increase in sales is coming from existing customers or net new customers. (It would be nice if you could see how many new customers you have gained over the last six months, wouldn’t it?)
If you can, also try to track the frequency with which transacting customers do business with you. (Membership/Discount cards are pretty helpful with that last one.)
By the way, if your well paid measurement “expert” doesn’t understand this stuff, perhaps it’s time for a new expert. It’s okay if you don’t quite grasp this stuff, but if your expert is still stuck on Google Analytics and web conversions only, or “impressions” as ways to “estimate” the value of media and potential returns, chances are that you aren’t any closer to calculating the R.O.I. of any of your activities than before you cut them a check. Remember: Measure REAL performance. Not eyeballs, not media, not what may happen in some magical marketing-friendly future. Measure what’s real. Measure what you can prove.
B. Non-Financial Outcomes
Now that we’ve covered financial outcomes, let’s get into the realm of broader metrics. (This is more fun but requires a lot more work.) Web measurement people will probably feel more at home in this section, as will Social Media measurement purists. As discussed in parts 6 and 7 of this series, non-financial outcomes (or forms of non-financial impact) typically influence financial outcomes. (At least that’s the goal.) They can be any number of things, from visitors to your website and followers on Twitter to (social) mentions of your companyand foot traffic to your stores. The best way to describe this category is this: Non-financial outcomes are all of the things your customers do as a reaction to your activities except transact (buy something). Any activity that is not a transaction falls into this category.
Warning: There are tons of things you can measure in this category, so remember the two precepts we covered earlier: Measure what matters, and measure what you can. (Don’t worry about measuring everything. Give it some thought, test things out, experiment, and see what works for you.) That said, a few key metrics should immediately come to mind: Web traffic, clickthroughs, non-financial conversions, (social) mentions, multi-channel engagement, foot traffic (yes, in the real world), postive WOM/recommendations, negative WOM, blog activity, retweets, linkbacks, etc. Some are web-based while others are not. Don’t get bogged down with media categories: Get out of the traditional media measurement mentality and instead, learn to measure customer behavior. That’s where real insights and valuable metrics are. What people do is usually the best indication of how they feel about your brand/company/product. So learn to observe and measure behavior.
Again, whatever you choose to measure has to be be plotted along a timeline. We will be overlaying outcomes and activities next, so this is important. (We’re only skimming the surface at this point, but you should be able to see how this is starting to come together.)
Some of your non-financial outcome timelines might look a little something like this:
Note: Yes, I could be showing you screenshots of tools like Google Analytics, PeopleBrowsr, Techrigy and Radian6 reports, but I am trying to keep these posts as tool-neutral as I can. My own biases for certain tools shouldn’t get in the way of the principles conveyed in this post. (Just know that the number of tools out there is growing, so feel free to test them all out and see what works best for your needs, budgets and business culture.)
Okay. I could go on, but I’d better stop this post before your brains explode. Let this stuff sink in, digest it a little bit, and we’ll be back with more later: In Part 10 of this series, we will talk about the importance of deltas (changes) in patterns, as well as causality and correlation. (We’ll start putting all of these puzzle pieces together.) Think of it as detective work for measurement geeks. (Oh yeah. Exciting stuff to be sure.) Any of you starting to wish you hadn’t asked me to show you how to do this yet?
Let me know if this is making any sense yet. It doesn’t need to be 100% clear at this point, but as long as the fog is starting to lift a little, we’re all on the right track.
And remember: As I mentioned in the video, this series isn’t intended to be a detailed A-Z “how to” for every company. If I tried to be THAT specific, each post would be 30 pages long, and even I won’t put you through that. Think of this series as a methodology “how to”: Principles that you can then adapt to your own business measurement practice. These are guidelines. Bend them as much as you want to make them fit your needs. Once you understand these principles and feel comfortable with them, it’s up to you to either adapt them to your specific needs (based on your capabilities), or recruit the help of someone like me to help you build a measurement program that will actually work. Doing this right is pretty serious business, so feel free to experiment but also understand that the success of your company depends partly on the quality of the analysis that you extract from your measurement program. (Knowing what works and what doesn’t work – and why – is pretty vital stuff.)
One last thing: Feel free to share with me what non-financial metrics you think would be crucial to measure (whether you measure them already or not). I have listed a few here, but I would love to hear what you feel should be added to the A-list.