Data quality and its impact on marketing analytics

When it comes to data, there are three C’s, three key factors that can impact your data. I discussed these at length in Marketing Blue Belt, but I wanted to reiterate one here that I screwed up royally.

The 3 C’s of good data are chosen well (selection), compatible (format), and clean.

Recently, I was doing attribution analysis to find out what has worked for me in 2015 as part of my personal 2016 marketing planning. I looked at my benchmarks and saw that email was underperforming:


I thought I was a pretty good email marketer. Maybe not? I ran a custom report to see what was happening under the hood, and then the answer became clear as day:


I don’t post to social media on the weekends, yet Twitter has been one of my top referring sources on Sundays.

If you don’t get my weekly email newsletter, for the past couple of years, it’s looked like this:


Do you see the problem?

By re-using my tweets as they were, I have been re-using the social media campaign tags built into the shortened links. Social media – Twitter, specifically – is getting credit for email’s impact.


Above you can see the tags Buffer automatically adds to my tweets. When I reuse those URLs in email, they keep their social media attribution.

This is the essence of insight from the MAISTER framework in Marketing Blue Belt. We have the data. We know what happened. We had to establish why. Now we know what to do to fix it.

Be careful as you do your marketing analysis of 2015 and planning for 2016! Understand your data. Don’t blindly assume that it’s correct and infallible. Mine certainly wasn’t – and I have only myself to blame.

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New Product: 2016 Marketing Planning Framework

What if you could put together a plan, a strategy, and a budget rooted in reality that gave you the resources you need to succeed?

In the 2016 Marketing Planning Framework, we do exactly that. Step by step, we’ll look at the data you have, compare it to the model companies in your industry, and engineer a plan for the future that helps you catch up to your competitors in key marketing channels – then surpass them.

In less than an hour, you’ll walk through the construction of a data-driven customer journey and emerge with a plan in hand, the resources you’ll need to succeed, and a clear budget ask to achieve the goals you’ve been given.


When you download this Marketing Planning Framework, you receive:

  • A video screencast in HD MP4 format, enhanced to show clicks and keystrokes in applications for true step-by-step instructions
  • Sample data files you can practice with if you’re not ready to use your own data
  • The actual planning framework Excel spreadsheet so you can slot in your own numbers for an out-of-the-box strategic plan by marketing channel
  • A short PDF of key images and slide material

Purchase your copy now, and get what you need to succeed in your 2016 marketing planning!

Frequently Asked Questions

Do you need Google Analytics?

You need access to a Google Analytics account for the benchmarking data. It doesn’t have to be what your company/office uses; you can use your own personal account. For the customer paths to conversion, many other analytics packages have similar features. For example, Omniture SiteCatalyst calls them customer funnels.

Do you need Microsoft Excel?

No. You can use any spreadsheet software that can read an XLSX file, including Apple Numbers, Google Sheets, Open Office, etc.

Is there a trial or demo?

No. It’s a video and workbook, plus supporting materials. It’s not software.

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How to build your customer journey, part 3

Want a step by step version of this post? Download the new premium webinar, 2016 Marketing Planning Framework!

We’ve now established what the customer journey is not, and what your customer journey currently looks like. Now what?

Let’s begin where we left off in the last post. We’ve established our specific customer journey and noted where our journey differs from the generic journey:


In the example above, we see that direct counts much more up front in my website’s customer journey than it does in the generic model. The generic model, however, hints at what else we may want to be trying. In the direct model, there are channels I’m not currently using, such as generic paid search, display advertising, and branded paid search. These channels might be good opportunities for me to explore.

The other thing the generic model doesn’t talk about is how well each channel should perform and what percentage of the marketing mix I might want it to occupy. Fortunately, Google Analytics’ benchmarking feature gives us answers to these questions. You’ll find Benchmarking in the Audience menu in your Google Analytics account; depending on your setup, you may need to enable it. For a detailed walkthrough of the basics of benchmarking, see this post first.


Above, we see from my benchmark against other marketing sites of similar size that social media and organic search are performing well already. I’m far above the baseline for the marketing space. What we also see is that other channels aren’t doing quite as well. Based on the customer journey we’ve mapped out above, I need to be doing a better job with email, and as my custom customer journey above shows, I’m not doing anything with paid search.

Now, not only do I have a customer journey mapped out, I know which parts of my customer journey are working well and which parts need help. I can work on improving email and adding paid search and display advertising to the mix if I want to make the journey as comprehensive as possible.

The benchmark also tells me at what levels I’d need to invest. Look above at line 7, paid search. Sites comparable to mine get almost 10,000 visitors from paid search, where I get 10 (likely accidental/bad data, since I’m not running any paid ads). If I needed to get 10,000 visitors in a month, that’s roughly 333 a day. Based on this, I could go to Google’s AdWords keyword planner and see what 333 clicks a day would cost me:


To reach the levels of my peer competitors, I would need to invest $300 a day, or $9,000 a month.

You can perform the same assessment for any channel in which you have performance data. For example, I know what efforts are needed to achieve the social media numbers in the benchmark above. If I want referral traffic to match those numbers, it’s a reasonable starting point to experiment with investing the same amount of time and effort as I do in social.

In another example, I know what time and effort I currently put into email, and I see the results above. I’m at half of what my competitors are doing. Thus, it’s a relatively small leap of logic to test doubling my effort to see if I can double the results and get on par with the industry averages for peer companies.

With these tools, I can now make the necessary changes to my customer journey to improve it, to reach customers where they are, in the right order. My marketing effectiveness should substantially improve if I fit the journey to the way customers actually behave and adapt quickly when I’m out of alignment.

In the next post, we’ll talk about taking your customer journey to the next level, quite literally.

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