In June, 2005, Jason Burby from ZAAZ wrote a ClickZ column called “Hot Web Analytics Topics From Jim Sterne’s eMetrics Summit.”
Jason facilitated one of the Roundtable Discussion sessions where the question on the table was: what’s the hard part? He took copious notes and listed the burning issues of the day. After seven years and on the eve of the next eMetrics Marketing Optimization Summit, I was curious to see how many of these issues still walk among us.
Some of those issues are dead and almost completely buried. They aren’t plaguing us anymore, but they still smell funky.
Accuracy: tool limitations (or perceived limitations), cookies, data misinterpretation, and defining acceptable discrepancies.
Yes, the numbers are not absolutely, reliably accurate. We’ve gotten over it. This is not rocket surgery, it’s marketing. If we can improve the results of a campaign by 5 percent or 10 percent, then it just doesn’t matter if there were 2,645,955 or 2,645,958 people/pages/events. Two tools will never report the same numbers. So be it. Time to move on.
In 2005, only a few companies were looking at the web through traditional glasses. Now, the Internet is considered an important part of the marketing mix and brand recognition measurement is par for the course – especially with the advent of social media where public opinion is all that matters. Traditional branding metrics such as increasing awareness and intent to purchase are now in vogue online.
Having a process to create dashboards.
Even the most statistics-adverse marketing executive knows the need for a dashboard. As a result, processes to create them are de rigueur.
Defining functional roles for managers, analysts, and consumers of data.
Analytics has earned enough of a place in the spotlight (thank you, Brad Pitt!) that adoption has engendered the need for governance. As it is no longer a skunk works project and has some real investment attached to it, somebody has to own analytics. Oversight and functional roles are the by-products.
How much data should be kept?
This one’s easy: let’s just call it Big Data and keep everything! Why? Because storage continues to get less and less expensive and it’s all in the cloud.
This just never really caught on. Too geeky for marketing people? Too management-speak for geeks? We many never know.
Vendor and implementation over-promising.
Those vendors who made promises they could not keep learned fast or fled the field.
Inability to make incremental changes.
Way back then, websites were often treated the same as big, batch mainframe programs and making changes required committee approval in triplicate with a wax seal embossed by the CIO’s signet ring. Nowadays, multivariate testing tools are free.
Segmenting customers online.
Time was, all those “Internet people” were one segment. Now, with your grandma, your accountant, and your dog online, we realize segmentation is our friend.
Pernicious Problems That Just Won’t Go Away
Like in-laws who come at Christmas and are still in the spare bedroom come Memorial Day, these problems need care, feeding, and a very stiff upper lip to tolerate.
Lack of standard definitions, benchmarks, templates, and expectations.
This one’s a wobbler. Similar to the accuracy issue, most have come to realize that there is little value in comparing click rates, bounce rates, time-on-site, and the like – except to one’s own numbers. There just aren’t any standards, so quit crying and get on with your job. Sadly, the message has not reached a healthy chunk of senior management and they keep asking for benchmarks. Stiff upper lip.
Political issues: management buy-in; IT vs. business unit objectives; resources and reporting vs. analysis.
Politics? Of course there are politics: there are humans involved!
Identifying a few critical web and success metrics.
Understanding business goals well enough to know what to measure; and connecting web metrics to business key performance indicators (KPIs).
Lack of actionable metrics.
Prioritize and determine the best opportunities to pursue.
I lumped these four together as they are all about the same thing: collection and measurement of metrics instead of mining for business insights. Most realize by now that it’s crucial to start with specific goals rather than the raw numbers. You have to know which metrics can help guide the organization and inform decision making. But I’m placing these common issues in the “Pernicious” column because that last one is a real stickler: prioritization. With so many numbers to play with and so many goals to juggle, which are the most important? Which should be optimized first? A conundrum.
Measuring income/revenue versus loyalty metrics, or conversion versus lifetime value.
Focus on the tactical and immediate is always tempting. It’s much easier to count revenue than determine profitability. It’s more straightforward to tally customer acquisition than work out which types of marketing campaigns generate the most valuable customers over the long haul.
Integrating with marketing and consumer data.
Still tough, but getting better. Yahoo, Microsoft, and companies like comScore are helping with the integration of external, marketplace data.
Problems That Refuse to Die and Will Eat Your Brains
Some issues have thrived zombie-like, roaming the marketing landscape, continuing to suck the lifeblood out of analytics teams everywhere. Wooden stake? Silver bullet? These problems may not even have a solution.
Where, oh where are the bright people who are good at math, understand statistics, live and breathe data collection, know killer creative when they see it, and can hold the attention of a roomful of IT, marketing, and operations people? Just the other day, Andrew Edwards filed a Missing Persons Report.
Data proliferation: multiple sources, reports, and integration.
There is no end to data. There will always be a new data stream around the corner that cannot be anticipated. It has been ever thus.
Silos: multiple resources going in different directions.
Politics? Of course there are politics: there are humans involved!
Education for all team members throughout the organization.
A never-ending cycle of new information to acquire so quickly that it’s already too late. When I started looking into marketing analytics, one college master’s degree would have covered it. Now it takes seven.
To be successful in analytics is hard work.
Yep, there’s that.
Hope on the Horizon?
Is it time to walk away and spend your days turning wooden bowls instead?
While some of these problems seem indestructible, the eMetrics Marketing Optimization Summit continues to bring hundreds of people together to actively share and learn how to conquer them. The next one is in San Francisco, March 4-8. Maybe you should come – we could sure use the help.
Marketers need to know what’s in their data and trim out the filler to provide continuous, data-driven ROI for their brands.
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