Put down the Oreos: real-time marketing is dead

Put down the Oreos. Real-time marketing is dead.

I mean that metaphorically, of course, and in reference to the famous real-time marketing incident in 2013. If you’re eating actual Oreo cookies, please do carry on.

Why is real-time marketing dead already? For the same reason that the retail investor on Wall Street has no hope of outsmarting high-frequency traders and their automated platforms: humans aren’t fast enough for actual real-time marketing.

During the Republican presidential candidate debate, I had the opportunity to watch the “engine room” at Zignal Labs (client of my employer) real-time monitoring system scan the debate on social media, broadcast media, traditional press, and a few other data sources. It looked a bit like this:

The Matrix

The number of conversations happening at any given split second was somewhere between 750,000 and more than a million. One of their tools displays a word cloud of what’s being talked about; imagine a word cloud that changed every millisecond, hashtags flying by faster than you can see.

In an environment like that, the tradition of “news-jacking” popular hashtags and conversations is almost impossible for a human being to keep up with. Can you jump on a popular tweet or a news story when a literal million more appear every second? Watch how fast opinion changes in this animation:

By the time you make a statement about who is ‘winning’, the data has already changed under your feet a million times.

In digital marketing analytics, something usually is considered trending when it shows a growth curve, a certain mathematical change. When you look at the actual data stream flowing by with a tool like Zignal Labs that can truly display what real-time looks like, growth curves for content are measured in milliseconds. Individual pieces of content start out, grow, trend, and fizzle in the blink of an eye.

The reality is that for anything significant that’s a broad conversational topic, real-time marketing is beyond the capabilities of humans to keep up with. At best, we can look at summaries of what’s happening to pick and choose what we want to give additional focus to; the very best monitoring tools like Zignal Labs will elevate those items that need our attention most.

Beyond that, we need to leave it to the machines and stick to our strategies as best we can.

Disclosure: Zignal Labs is a client of my employer. However, I was not asked to write about their product, and I was not compensated to do so, beyond general benefit to my employer. Zignal Labs did give me a slice of pizza while I was on-site.


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How to measure success without goals in Google Analytics

One of the first maxims of great marketing analytics is to have a goal with an objective value set. Tools like Google Analytics make this elementary to configure; simply decide on a goal and decide on the value of the goal, input it into the software, and you’re up and running.

But what if you don’t have any goals? For example, say you’re the new CMO/VP Marketing and you walk into the company. On day one, you look at their Google Analytics and it’s a mess. Nothing is set up right. How do you begin to estimate what’s successful and what’s not?

Google Analytics has a number of tools ready to go and operational out of the box. One of those is the ability to segment your website’s traffic into new or returning users. Could either of those segments correlate well to goals such as lead generation and purchases?

To find out, I looked at some anonymized data from various types of companies to see what the correlation was. A reminder, of course, that correlation is not causation, but in the case of a website, it’s logically quite difficult for someone to convert without visiting your website, so there is some order of operations.

Let’s look at a few examples to see if there’s some logical connection between conversion and new users, or conversion and returning users. We’ll start with a B2C services company. What’s the relationship between new users and conversion?

b2cfsnew.png

Strong, as seen above by a Spearman correlation of .747. If you’re unfamiliar with Spearman correlation, it’s a scale between -1 and +1. A +1 means a perfect correlation; as variable 1 changes, variable 2 changes in exactly the same proportion. Above, we see new users and conversions in a strong relationship.

What about returning users and their relationship to conversions?

b2cfsret.png

That’s an incredibly strong .958. Returning users and conversions are very tightly bound together.

Let’s look at something a little more mundane, a B2C consumer packaged goods (CPG) company, someone who sells brick and mortar goods. New users and conversions look like this:

Cursor_and_SOFA_Statistics_Report_2015-08-06_05_29_45.png

The correlation is still a moderately strong .612 for new users and conversions. What about returning users?

b2ccpgret.png

We’re at .738 there, a strong relationship. Returning users correlate more strongly to conversions than new users for the B2C CPG company.

Let’s flip over to our colleagues on the B2B side. What about a B2B technology company, the kind of company that has long sales cycles and expensive products that only other companies buy?

b2btechnew.png

The relationship of new users to conversions is .913. Very strong. What about returning users?

b2btechret.png

That’s as close to perfect as you’re going to see in the real world, a super strong relationship between returning users and conversions.

What can we conclude from these three cases above? While new users to your website are important for growth, returning users show incredibly strong relationships to conversion.

Thus, if you’re walking into a Google Analytics installation that has no goals set up, but you still need to judge how things have gone so far, I’d say you can safely use returning users as a general proxy for success while you get goals and goal values set up correctly. Inside Google Analytics, you can examine, using segmentation, which channels drive returning users most and best. You can see what pages attract returning users the most, and ultimately use that as a foundation for determining intermediate goals.


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The flip side of agencies as marketing partners

Mark W. Schaefer wrote an excellent piece about why more and more marketers are going in-house, and why companies sometimes can be better served by an in-house professional rather than an agency. If you haven’t read it yet over on HBR, do so.

One key reason why a marketer might be better served at an agency rather than in-house at a brand is diversity. This is the key reason I joined SHIFT Communications almost three years ago.

IMG_4678

When I was starting the process of searching for my next thing, I had coffee with the ever-inspiring Mitch Joel at Dreamforce 2012. Mitch, entirely with love, told me that I was an idiot for staying in-house because no one brand needed the odd assortment of things I could do.

I was an email marketer and a podcaster.
I was a social media practitioner who also understood marketing analytics.
I was a longtime SEO professional who could also design in Photoshop and Illustrator.
I could create marketing strategy but also write code.

Unless I was working at a top brand with big marketing dollars, I’d never be able to use my skills to their fullest potential, and even then, working at a top brand would have meant managing people to do those activities and not being able to do them myself. I still enjoy getting my hands dirty and trying new things.

Mitch was quite clear with me that in-house was the wrong choice. I’d continue to be bored, constrained by the endless limitations of working at a single company. At an agency, the fast-paced life and opportunity to work with many different kinds of businesses would stretch my capabilities and challenge me to grow my skills. I’d work with companies that had radically different business and marketing models, and be able to use all of my skills to their fullest potential.

For example, recently at SHIFT, I and my team launched a bake-off among a native ad platform, a DSP’s network, and an AdWords campaign to see how well each platform does at achieving one particular client’s goal. In-house, that sort of experiment would almost never have been approved at any of my recent employers. (I’ll tell you who won on the SHIFT blog once the test is concluded)

I get to use almost all of the skills above on a regular, nearly daily basis. No one client wants or needs them all, but in aggregate, the companies I serve do make use of them, which keeps me sharp and in practice. That’s not an experience I can get in-house anywhere.

To Mark’s last point about attracting talent, talent absolutely is a challenge. Agency life isn’t for everyone. It’s extremely fast-paced, and the demands on your time can be extreme. Top that with the necessity of marketers everywhere who need to be both left and right brained (yes, I know that’s not actually a real construct) and there absolutely are challenges finding and retaining the best and the brightest.

That said, having peeked inside more than a few companies over the past 3 years, there are plenty of companies that maintain the same furious pace and pressure on their in-house teams as well.

Ultimately, I’d make the case that agencies are as uneven in quality as any other employee. Some will be great. Some will be terrible. Most will be good enough, most of the time, and like hunting for good employees, hunting for the very best is a quest that never ends.


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