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?


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?


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:


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


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?


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


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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How volatile is your marketing?

How volatile is your marketing?

Volatility is a concept made popular by the stock market. When a stock is more volatile, it means something is happening that is causing investors to buy or sell it in greater volumes. A nonvolatile stock has similar buy/sell volume and relative price stability every day.

When the market as a whole is volatile, it means instability. Something has happened that is making a lot of people act, whether it’s panic buying or panic selling. Investors don’t like instability. Instability means unpredictability, and that can mean significant, unplanned risk.

Back during the financial crisis, VIX, the market volatility measure, was at crazy numbers as people bailed out of stocks. The VIX spiked and trillions of dollars (admittedly all theoretical) vanished in a just a few days:

VIX 10 year chart.jpg

Why are we talking about the VIX and volatility? You can use the same concept of measuring volatility, but in your marketing metrics and analytics. Volatility in marketing means that something’s happening. It might be good or bad, but whatever it is, it’s worth paying attention to. Let’s take a look at an example, using some of my personal Twitter data. I’ve taken a column of my Tweets and retweets. To measure volatility, we measure how much something has changed from one measurement to the next:


Low volatility means low change. High volatility means big change.

From here, we chart the retweets:


And then finally add our volatility column:


Take a look carefully above at the orange line. In the middle of the chart it gets especially spiky, repeatedly. That was a period of increased volatility. The question to ask is why? What happened during that time period that made my tweets different, more volatile, less predictable in terms of retweets?

The answer, of course, was my speaking at Social Media Marketing World, which was a terrific experience. Michael Stelzner did a phenomenal job of not only marketing the show, but marketing the speakers at the show – which included retweeting our tweets to his highly influential audience. Based on the information above, if retweets were an important KPI for a corporate social media marketing program, I’d figure out ways to increase my participation and engagement in that event. (I will anyway, because it’s a terrific event)

When you’re measuring volatility, determine first if you’re getting volatility that is positive or negative against your marketing KPIs.

Once you know whether it’s positive (such as the example above) or negative, determine whether or not you have the ability to control or influence the cause of the volatility.

  • If it’s positive and you have the ability to control it, do more of it.
  • If it’s positive and you don’t have the ability to control it, figure out ways to influence around it, such as using paid media or earned media.
  • If it’s negative and you have the ability to control it, stop doing it immediately.
  • If it’s negative and you don’t have the ability to control it, do something else you’re good at to mitigate it.

Try measuring the volatility of your key marketing metrics!

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Minimum effective dose in online advertising

A while back, we talked about the minimum effective dose, the dose of medication needed to cause the desired outcome. As I’ve dug more and more into paid media and advertising over the past few years, the minimum effective dose concept has cropped up more and more.

One of the questions I’m often asked is what the minimum spend is for online advertising to be effective. To answer this question, you have to be able to answer two subordinate questions.

First, how much money do you have? This sets guidelines for what ad venues you should pursue.

Second, how competitive is the space you want to advertise in?

Let’s look at a practical example using Google’s AdWords Keyword Planner, a free tool that anyone can try out in order to buy AdWords ads. I’ll start by choosing Click and Cost Performance Forecasts, and typing in a few keywords that I’d want this blog to be known for:


When I hit go, I’m presented with the following chart:


Look at the red arrow. It’s at that point, roughly $8.28 per click, at which the more you pay per click doesn’t really get you more clicks. That’s where we get the desired effect. When you type that bid in, or move the slider, AdWords will then tell you what you need to spend to hit that click volume:


Suppose you don’t have $1,460 to spend every day on advertising? What if you only had, say, $50 a day? Type that into the daily budget box and watch the chart change:


You can see above that your budget runs out before you capture even a fraction of the total number of clicks. If maximizing audience growth through paid advertising is your goal, then the $50 per day budget clearly doesn’t cut it.

The reality is that for these terms, the minimum effective dose to hit the market you want to hit is going to cost a lot of money. Monthly, that budget works out to $43,800 per month in ad spend. That’s the minimum effective dose to win at owning those particular keywords. From here, my choices are to either find cheaper, still relevant keywords, accept far fewer clicks, or find a different means of marketing for the budget I have.

The above is just an example using AdWords. Virtually every online advertising tool has a campaign planner that will help you identify what the minimum effective dose is on that platform.

Before you set off on any digital advertising venture, be sure you understand the minimum effective dose and whether you have the resources to hit it. Create a spreadsheet that shows the cost per click and the minimum budget needed to get your ads to show to the segment of audience you need to be in front of.

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