Let’s take a look at this entire idea of data. More specifically, let’s look at how we are using data to inform business and marketing decisions.
I’m going to wind my way about the entire thing, starting with the mass spread of data in today’s world, segueing into identifying where the data world and the marketing world suffer from connection issues, and hopefully taking a look at some idea and principles to better measure what we can’t actually see.
By the end of it, we’ll all hopefully take away some good thoughts on how to better approach the application of data to what I like to call ‘abstract marketing activities’. Or basically, things businesses do to promote themselves that we can’t easily trace back to a result.
Welcome to the data driven world
Working largely in e-commerce lends itself to a lot of data. A lot of metrics. A lot of analytics. A blitz of numbers that are supposed to inform if you’re doing your job well or not.
In the digital world, it’s a numbers game more than ever, and if you can’t count it, you’re in trouble.
Of course, this isn’t exclusive to the the Internet or anything digital. As digital and analog bond tighter, we are able to collect more data on less tangible things. When we use this data properly, we’re using these metrics to make better decisions.
We’re solving problems that were once impossible in the same way that Rubik’s Cube seemed impossible this first time we laid eyes on one.
Our previous solutions have gotten better, more informed, as well. As the feed pulses in like an avalanche of water from a busted dam, our solutions and tactics rapidly advance.
However, not everything perfectly lends itself to digital improvement. I think at the crux of it all is this idea:
For everything we can track, quantify, and analyze, we are able to turn our attention to another two things that are even more abstract than the former.
As marketers, not everything we do has a data footprint
In a figurative sense, we’re hunting mythological beasts. We’re Captain Ahab hellbent on hunting down the notorious Moby Dick, or Bigfoot, or the Loch Ness monster.
Advertising legend David Ogilvy often lauded direct-response advertising because of how measurable results were. In his book, Ogilvy on Advertising, he remarked:
For all their research, most advertisers never know for sure whether their advertisements sell. Too many other factors cloud the equation. But direct-response advertisers, who solicit orders by mail or telephone, know to a dollar how much each advertisement sells. So watch the kind of advertising they do. you will notice important differences between their techniques and the techniques of general advertisers.
Today, we have many other forms of advertising that can measure to the dollar – to the individual – to whatever little behavior we want to track – how effective the advertisement (and platform) is.
Relative to their early days, we can even see results of TV and print ad campaigns with a clarity that makes the gap between 14th century and 20th century optometry look like a popsicle stick joke.
Even so, not everything is making the jump out of the metric stone age so easily.
I can’t not mention it, since it is what we do.
USImprints sells promotional products. Now, we customize stuff for all sorts of reasons, but one of those big ones is so that businesses can brand themselves and inundate our (and hopefully their customers’) lives with this interesting form of advertising meets benevolence.
It’s a $20 billion industry for a reason.
But whether a small business owner or a piece of a huge marketing department, how do you tangibly justify giveaways, ‘swag’, and such?
How do you prove that the continued practice is doing anything more than clawing into the budget?
Many of us have come up with approximations (such as our simple ROI calculator for experiential marketing), or compiled industry statistics over decades (both of which are tactics that we’ll see are still critical), yet, as data frenzy spreads, the demand to show results will grow.
Smart marketers (for some reason I had a huge urge to say ‘smarketers’, forgive me, world for I have almost sinned) will find ways to go with the current, while those who can’t will either become obsolete, or will lose out on the potential that abstract marketing practices bring.
Contrasting traditional and abstract
Let’s stick with another example to uncover what some of the biggest differences that we experience between say, advertising for ‘custom tumblers’ on Google AdWords versus 15 seconds worth of product placement on Hell’s Kitchen.
In fact, let’s just ride the product placement example all the way through. It might not apply to most of us smaller guys, but it’s a fascinating marketing tool.
Here we have a behemoth under the water, so to speak.
In the U.S., product placement revenue doubled from $1.5 billion to just under $3 billion from 2005 to 2007.
Global spend on product placement was $7.5 billion in 2006. Before the economic crisis of 2008, that figure was predicted to almost double by 2011.
The industry has rebounded quite well, though. In 2012, global spend was $8.3 billion while the U.S. spent $4.75 billion – each growing by more than 11%.
Traditional advertising – and any other form of advertising that relies on interrupting our activities for attention – are being sidestepped by tech. The better we get a parrying, the greater demand becomes for different forms of promotion.
On the other hand, we are better equipped to assess the effectiveness of traditional advertising. We control everything about the advertisement, when and where it airs, and so on. A product placement or integration is kind of like tying a message around the leg of a pigeon and sending it on its way.
Into the great unknown.
But it also has two way value, and not in the, “I’ll give you money so people can watch the shows you make,” manner.
Good product placement is needed to add believability and an anchor reality in many narrative shows. In a reality or game show, it’s simply a necessary organ.
Differences and Challenges
For a placement agent or marketing director, what differences are you facing as opposed to a more direct form of marketing?
- trying to hit a moving target
- targeting different points in the sales funnel
- more subtle
- success/conversion is defined differently
The moving target idea is tricky to define, which parallels its nature. It’s kind of like the wide net concept. Basically, you don’t necessarily know who you’re targeting. You know what your customer base looks like, you can define buyer personas. You can find them in a variety of spaces they are known to reside; professionally and leisurely.
In product placement, you’re baking these assumptions into everything you do.
So say you’re Gatorade, a placement in a sports movie like Remember the Titans or during an NFL game is going to be more effective than a placement in the latest movie being made for Lifetime Movie Network.
But you don’t know where you’re going to be reaching any of these prospective customers in their buying cycle, or really anything else that is directly related to a decision to do business with you.
In traditional advertising, you can pick out targets based off of that distance.
"Ok, we’re making an ad about our latest sales. We are trying to do the last step to induce people to come in our store and spend money"
"Ok, we’re going to make this ad just to stay on customers’ minds. They don’t have to be hungry for our food right now, but they’ll see the ad a few times, and one of these times they’ll be hungry and that’s when they’ll make the decision"
Experiential marketing, sponsorships, contests, product placements, and more. All of these are dealing with moving targets, which dilutes the ability to measure results, or at least the bottom line result, but more on that in a moment.
The Sales Funnel
This is close enough to the last point that I almost merged them, but there is enough difference to classify separate.
This is both a difference, as well as something that I think an abstract marketing activity does much better than any traditional marketing approach could.
Geoffrey Giuliano spent 1.5 years working full-time as McDonald’s mascot and spokesman Ronald McDonald. In an interview he gave, he recounted the following memo:
And then one day, as I was getting dressed in the dressing room I found a memorandum from one of the McDonald’s executives and it said: ‘To all personnel re: The Ronald McDonald Safety Show, the purpose of this show is to increase the public’s awareness and especially the young peoples’ awareness of McDonald’s goods and services’. I thought, gee, I thought it was to help kids.
Now, I’m not trying to condemn McDonald’s, I think that this is a great illustration of a common tactic. Ronald McDonald, cartoon character endorsements, and basically every cereal mascot you’ve ever seen all follow this idea. First, to target younger people. Second, to turn them into lifelong customers.
In any of these instances, you’re not directly targeting a decision maker. Maybe the child could be classified as a customer ready to buy, but the one making the decision (the parent) might not even be on the radar. Just as important, they want these children to grow up as consistent customers well beyond childhood (it certainly worked for me and my favorite cereal brands).
In the most direct cases, this is like a long range sniper, picking off targets from great distances. In other cases, the difference in where we are prospecting in the sales funnel is akin to laying down the groundwork for a railway or road hundreds of miles away.
Either way, the scope and distance makes this another difference with results that are hard to measure.
Because we’re laying groundwork as opposed to applying a X + Y = Sale formula, there is a lot more subtlety.
At least 90% of product placement is about subtlety (except when it’s not). Let’s take a look at a more specific example using a sphere that we’ve discovered is much more about subtlety, branding, and interaction than it is about selling.
Take a look at a company who does it well (and an example I use often), Shwood Eyewear.
They do a great job of promoting lifestyle, culture, and the awe-inspiring beauty of nature (great photography, too). Their exquisitely crafted wooden-frame sunglasses blends nature with cool. All of these elements are a perfect fit for their actual products, which they show off on their social media accounts.
The key is this, when they show-off their products, they will give you some small details and context.
Here’s the description they wrote:
Our Canby Fifty/Fifty in Black & Ebony. Shot by @julianbialowas on his trip to Sentinel Dome in Yosemite. #shwoodshop #experimentwithnature”
Notice the sales pitch in there?
Neither did I. Just information and a little bit of context. Cool.
Perhaps they could get a few sales if they had put a picture like that up and said something like:
[notification type=”alert-warning” close=”false”]Buy our dazzling Canby Fifty/Fifty in Black & Ebony here on our website for only $105! You’ll be such a rustic phenom that Elk will wait outside your door every morning to carry you off with the wind while birds softly perch on your head, filling your ears with the sweetest harmonies of your favorite Beatles songs! Buy today![/notification]
Then imagine that this is all anyone would see (plus I’m pretty sure it violates the TOS of most social networks). A few sales? Maybe, and you can measure that, but I know I wouldn’t follow them and fawn over everything that they put up.
And this isn’t just me, this is what most social media marketers have found. If you sift through the Instagram accounts for most large companies, you’ll see that they’ve all gotten on board with telling stories, contributing to lifestyle or culture, and really anything else besides trying to generate sales.
All this subtlety bleeds into the final primary difference.
A good goal needs to be measurable. The cloudier everything becomes, the harder it is to solidify this. Even in social media, we get murky metrics, at best. Likes, shares, and followers are all good, but they are really only a sentence here and a few words there of a chapter in a larger book.
The goals themselves are entirely different than what you might find in an e-mail blast announcing a sale, or a trial for a new feature of your SaaS company.
I can only imagine that product placement is one of the most abstract because of that control issue. There is no telling how your product will actually show up in the final product.
Instead of setting a goal to increase sales by 65% like Reese’s Pieces did with a product placement in ET, a realistic goal in product placement would be along the lines of:
[notification type=”alert-info” close=”false”]Have brand visible for an average of 30 seconds per episode in season 2, increase viewer recall without prompting by 20%, increase brand recognition by viewers of the TV show by 25%.[/notification]
I’m not a placement agent, so these goals are kind of made up, but these are based on the 3 most important means that placement agents use to measure effectiveness, so you get the point.
This entire difference can be summed up like this: the primary goal of abstract marketing practices is not to increase sales.
Go Hungry Hungry Hippos for Data
We’ve already touched on a number of methods used to plug in to the data stream. We might not be plugged in like we are with Google Analytics, but if we apply the concept of the kid’s game, Hungry Hungry Hippos, we can compile a pretty useful set of tools.
- Keep the bottom line in mind
- Establish a baseline
- Dig for what isn’t there
- Establish specific goals
- Integrate / Cross-channel
The bottom line
The bottom line isn’t the key indicator, true, but there are still tremors to be felt. You’re not starting with the bottom line, but I’m mentioning it first because it is critical to remember it.
The goal of this entire process is to filter as much noise as possible and then at the end of it all, look at the bottom line.
Of course, this process has to keep in mind the long distance that the effects any hard-to-measure marketing activities have to travel before they can impact revenues.
Establish a baseline
Part of establishing a baseline means getting your hands on any data you currently have and starting from there. Also, pulling out any industry wide data (e.g, Nielsen’s Place*Views, Visure Corp, PQ Media Global in the product placement industry) and applying what you can to a timeline will do wonders to establishing a baseline.
Once you’ve established your baseline, you can process everything moving forward and use that baseline to identify factors that are affected by whatever marketing activity it is, while keeping in mind that these factors do not necessarily directly tie in to correlation or causation.
The point is, know where you were before you started (or at least when you decided you needed to measure impact), and then continue to build on that rough data set.
Over time, what is important will be better identified, and you’ll have it all there.
Dig for what isn’t there
Whatever your baseline looks like, you’re going to have a lot of missing links. Dig for what isn’t there, that could be.
Once again using product placement as an example shows that tracking viewer recall, press coverage, using control-test groups, and surveying for consumer brand awareness are all methods that provide measurable results.
This is all data that has to be dug out from the ground, so to speak. Focus groups and control test groups won’t be an option for many businesses, but if some form of customer feedback is going to help out, find a way to dig that out economically (e.g., online surveys).
Look at that baseline, identify what isn’t there, and find ways to dig it out.
Establish specific goals
With the baseline there, you can better identify specific goals.
Moving forward, align your goals to their related marketing activities.
If the numbers show that your company sponsoring something like the Live on the Green concert series factors in a spike in inquiry calls and e-mails during Spring and Summer, add it to the goals.
Increasing effectiveness and finding other factors can be improved.
Discover key factors, use them to create measurable goals, improve from there
Integrate with cross-channel marketing for Marketing Triangulation
This is a tricky one, because it risks diluting what is already tough to measure. However, if you’re covering your bases, then you will be able filter out and separate where you need to.
There is a strong movement for tighter integration and increased cross-channel marketing. This includes but isn’t limited to product placement. For instance, promotional offers linked to placements are a common method that professionals have noted using to greater measure (and deliver) results.
We see even more cross-channel integration with something like product placement as we are able to experience TV and movies not only in our living room, but socially online via smartphones, tablets, and computers.
Using the foundation above with well-thought out cross-channel integration is the marketing equivalent of triangulation.
Tightly integrate other marketing channels with your initial baseline to gather more detailed information on results
Leave room for experimentation
Finally, continue to carefully wiggle around not only to better measure results, but also to discover what works best.
This should be the most exciting part for any marketer because it helps take cookie cutter practices and approaches, and humanize them by finding what is real for your customers.
Cross-channel integration will continue to gain popularity as it also gains complexity. It’s kind of like Casper the Friendly Ghost; what is originally an abstract, ethereal object just wants a place in a very tangible, physical world.
If you’ve done everything else right up to this point, experimentation will not only help the ghost become more tangible in a data driven world, but also establish your business well ahead of everyone else who hasn’t put in the arduous work of tracking the untrackable.
Even if you’re most comfortable in a simpler world without the data sensory overload, these principles can be applied at a smaller scale with great impact.
[notification type=”alert-success” close=”false”]Have any great examples of measuring data where it’s hard to measure? Have any improvements to add to the foundation covered in the blog? Let us know in the comments, and don’t forget to subscribe to the newsletter![/notification]