Digital data has never been easier to collect. Tools like Google Analytics make it possible for one-man shops to glean enterprise-level information. This is both a blessing and a curse. On the one hand, you can measure just about everything your business does online. On the other, analyzing it all is arduous at best and downright painful at worst. And who has the time to commit to this kind of this endeavor? Not any small business owners we know.
That’s where benchmarking comes in. It’s the quickest way to interpret the data you collect, and the simplest way of gauging success.
Benchmarking digital data is the process of comparing your results against a competitive set and finding out you where you stand in relation to them. For example, your data will tell you that your latest digital promotion yielded a 2% conversion rate. Benchmarking that number will tell you if it’s good or not. If the average observed conversion rate for that type of promotion is 0.8%, then it’s fantastic. If the average is 4.5%, your 2% is leaving a lot to be desired.
Step one for any business is to get a grasp on their own numbers. Benchmarking a company’s internal performance metrics over an extended period of time is the first priority when trying to gauge results. How do you know if your marketing efforts are effective without tracking results in comparison to past campaigns?
Step two and arguably more telling, is utilizing external (competitive) benchmarks as a success indicator. An industry average gives you a non-biased and constructive way to evaluate and optimize performance. Though internal benchmarks may demonstrate traction or decline in relation to past performance, full understanding of how your business stacks up against the rest of the industry will provide a much more conclusive and actionable story.
What does success look like? When you’re committing big money to an initiative, that’s something you should probably know. Without a benchmark, you’re essentially throwing darts with a blindfold on. A real average to compare against removes the blindfold and gives you a target.
Less Naval Gazing
Comparing your recent data against your older data is better than nothing, but remember that you’re not competing against yourself. Competitive benchmarking measures your numbers against the ones that matter – the rest of your industry segment.
Instead of taking stakeholders through piles of numbers, just show them how you measure up against the industry average. Nothing will make them happier than seeing themselves in first place.
We’re huge Toronto Maple Leafs freaks. But we’re also data freaks, which is why even though everyone around us was planning the Stanley Cup parade group back in February when the Leafs were challenging for home ice, we were waiting for the bubble burst. We saw it coming, not by looking at the team’s stats, but benchmarking them against the rest of the league.
The Leafs were giving up 36.3 shots per game. This stat alone means nothing, but when we compared it to the rest of league, we saw that that ranked first (or last, depending on how you look at it). Good teams don’t lead the league in shots against. Using the same benchmarking tool (ie: the stats page), we saw that the average team was taking just 30.08 shots per game, making the Leafs performance all that more disturbing.
As for what those shots against produced, they were giving up 2.97 goals per game. Again, that means nothing unless you look at it in context of the rest of the league. Doing that, we saw that ranked 6th in the league, and they were the only team in the Top 10 (or bottom 10) in a playoff position. Even Buffalo, the last place team in the league at the time, was giving up fewer goals.
The signs were there for anyone who bothered to look beyond the Leafs own numbers. Despite the apparent success they were having, this was a team in trouble. But only by benchmarking their numbers to the rest of the league could you see it.
Numbers mean nothing without context. The best way to know where you really stand (and what you need to do to get where you need to be) is to utilize benchmarking tools and compare yourself against the competition.
Analytics can tell you anything you want to know about your last digital promotion – except whether or not it was successful.
You won’t get these insights from your digital marketing analytics because all they can give you are your numbers, which are meaningless unless you have something to compare them to. Our benchmarking tool provides answers by plotting your data against the industry-specific averages for hundreds of metrics. You’ll know what objective success looks like. You’ll know if you achieved it. And you’ll know how your promotion fared versus the competition; also known as your Qoints score or index rating.
As more brand managers and agencies seek out their Qoints scores, they’re seeing value in the context we bring to their entire digital marketing strategy beyond promotions. Some customers use the benchmarks in the planning stages of a campaign to set challenging yet realistic expectations. Others use it as an HR tool to evaluate their marketing managers. Our newest customer, a prominent Toronto ad agency, recently benchmarked seven different contest metrics for a client to demonstrate how successful their work was. Smart.
But they all want their Qoints score because, like Eisenberg and Zuckerberg said, “we all want to know what our friends are up to.”
Your Qoints score is the easiest and most objective way of measuring success. It’s one number that will tell you everything you need to know about the rest of them. If you have a digital promotion running right now, let us tell you if your Qoints score is above 70%. If it is, keep doing what you’re doing. If it’s not, we’ll give you suggestions for boosting it.
Next blog, we’ll look at how benchmarking predicted the collapse of the 2013/14 Toronto Maple Leafs.
Marketing measurement is a big problem, but the solution to the problem doesn’t also have to be big. In fact, it can be small.
On Monday afternoon, I met my friend Reuben to get caught up over a coffee. I always enjoy our chats as they usually cover a wide range of interesting topics. Reuben also tends to ask great questions and make insightful comments. Monday was no exception.
While discussing how pervasive technology, analytics and big data are in marketing, we concluded that in contrast to all of that complexity and big data, I come at marketing measurement from a different angle; with something we might call a small data approach.
There is an emerging definition of small data as the few key pieces of meaningful, actionable information that we can uncover by analyzing big data. Those insights you extract from your big data become the last steps along the way to making better marketing decisions.
Actually, neither one of us had that definition of small data in mind during our discussion. Rather, we spoke of my “small data” approach to marketing measurement as small relative to other approaches and to the complexity of the problem.
My approach does align with the above definition of small data in the sense that I am very focused on organizing the chaos of all that data, uncovering insights and helping marketers to learn what they need to know so they can make better decisions. That is the reason to measure marketing and it needs to be the focus of any approach to measuring marketing.
Where my scorecard-based approach might also seem a bit contrarian is in its emphasis on measuring results vs. objectives and in not trying to calculate a financial return on investment (ROI). Although it would be ideal to accurately measure the financial ROI of marketing programs, as I have written about in the past, I think there are too many problems with doing financial ROI calculations for individual marketing programs.
I’ve always thought of my approach as a practical approach to a complex problem. As of Monday afternoon, I’m also starting to think about it as a small data approach to a big data problem. To explain what I mean by a small data approach, let me start with some thoughts on big data.
Big data flows out of a set of circumstances that will tend to occur at bigger companies, and might include some combination of the following:
These circumstances lead to a whole lot of data to analyze and understand which in turn leads to big data measurement solutions that will also tend to be big, complex, sophisticated and expensive.
With all the buzz around big data, it is easy for small and mid-sized companies to conclude that a high-science, big data solution must be the only legitimate way to approach marketing measurement. For many of these companies, a big, costly sophisticated approach isn’t needed or practical under their circumstances. A smaller, more practical approach can do the trick.
Most small to mid-sized companies don’t operate under the same set of circumstances. Their budgets aren’t as big, their marketing activity is much less involved, their world is much less complex and they generate and collect a smaller amount of data. They also have fewer resources with which to take on the problem that all marketers must solve, which is to determine the best ways to invest their budgets.
A small data approach can be a great fit under these smaller circumstances. Yet, given the range of company size and marketing activity within the small to medium sized businesses segment, a one-size-fits-all approach doesn’t work. Any approach needs to have some built in flexibility so you can scale up or down to be appropriate for the size of the marketing budget being measured.
That’s really where I stand on marketing measurement. Right size your approach to your circumstances, and don’t overspend on measurement by bringing an over-sized solution to your problem.
Don’t over allocate resources to measuring something that you can’t measure perfectly, as the law of diminishing marginal returns will ensure you waste some of those precious resources. This is not about measuring perfectly; it’s about perfecting your marketing.
About the Author: Rick Shea is President of Optiv8 Consulting, a marketing effectiveness consultancy with a focus on helping small to mid-sized organizations measure their marketing so they can stop wasting money.
This is one of the top findings by Adobe’s research “Digital Roadblock: Marketers struggle to reinvent themselves.”
Marketers know they must reinvent themselves, but don’t know how
Future marketers need to take more risks
Companies need to hire more digital talent
Mobile and personalization are becoming bigger priorities
To view the full report: click here
This article was originally published on Feb 28, 2014 and provided by Data-Driven-Marketing.net
According to a new report from Econsultancy and Responsys , just over two-thirds (70 percent) of businesses are planning to increase investment in digital marketing technology in 2014, whereas 28 percent maintain and just 2 percent decreases investments.
CRM takes the top spot when it comes to technology investment, with half (49%) of companies surveyed planning to spend more in this area (up by 4% in the last 12 months).
Other areas organizations are likely to be increasing investment in are business analytics and web analytics software (47%), email platforms (40%) and content management systems (40%).
The year-on-year comparison shows there has been a significant decline in the proportion of organizations that plan to increase investment in social media management systems, from over a third (38%) in 2013 to a quarter (26%) this year.
Compared to last year, fewer companies are planning to increase their investment in paid search/bid management (-8%), video advertising (-6%) and cross-channel/multichannel campaign management (-4%).
Paid Search/bid management, video advertising and multichannel campaign management are relatively established practices; lifecycle wise, marketing organizations are –usually- looking at cost-efficiencies and therefore getting the same or more for the same or lower amount of investment.
The fact that social media investments don’t further increase is due to the fact that many of those systems provide an (almost) one-stop-shop and for those that have licenses revenue models, at one point the clients’ marketing organization is saturated with licenses.
Do any of the increases in marketing investments surprise you?
This article was originally published on Feb 28, 2014 and provided by Data-Driven-Marketing.net
This infograph was originally published by BlueKai and demonstrates how marketing decisions are made in leading organizations today compared to the recent past.
How has Big Data helped you make better and more profitable decisions?
Qoints Launches Digital Benchmarks for Household Goods and Health & Beauty