The Role of Automation in Web Analytics

Posted on Tuesday, 23. January 2018 in category Web Analytics. 3 min read • Written by

Jeff Sauer

Automating analytics tasks saves my team at Jeffalytics 400 hours a year. 

While we still do our fair share of heavy lifting and crunching of data, automation of repetitive tasks gives us back 50 days a year in productivity gains. Time that can be put to good use taking action on the insights we find within the data.

At inOrbit 18, I’d like to help you do the same. I’ll be sharing some of my best strategies for automating your analytics data collection, analysis and reporting. Strategies, techniques and tools that you can put into place right away. 

To get an idea of what you can expect in this presentation, I wanted to walk you through our process for evaluating ways to make analysis more efficient. My team focuses on three key areas of automation, and each area contributes to the overall time savings and productivity gains. Here’s what you will learn from each focus area.

Data quality over quantity

More data is not necessarily better.

 Data without context and insights just slows down the decision-making process. Sharing more data with others does not make them better. It overwhelms them.  Why? Because sharing data is not the same thing as sharing information.

It’s rare for someone to say “I can’t wait to see another report in my inbox.” Because they are already drowning in data.

But business owners are always asking strategic questions, like “What’s causing this spike in growth?” Or “How much money did our content marketing bring in?”

Do you see the difference? A report provides all the numbers, but none of the context.

What stakeholders really want is answers (instead of more questions). They don’t want data, they want information that will inform their decisions.

So before you start to automate your analytics reports and dashboards, ask yourself.

1. Is this information actionable?
2. Will it save us time or money?

If you can’t answer “yes” to both of these questions, then the report isn’t worth sending. Focus your efforts on creating something meaningful for your organization. No need to automate right away, because you’ll just be automating confusion.

Knowledge institutionalization

Once you start producing valuable information, you will start looking for more ways to grow the value of your analytics program. Naturally, your next efforts should focus on producing institutional knowledge for your organization. There are many simple ways to accelerate your team’s knowledge, many of them can be found right inside of your Google Analytics account.

Annotations 

Annotating reports is a quick way to share your analysis and let others see your work. Annotations help to provide context to events that influence your data.  They can also save other team members from unknowingly duplicating your analysis.

Custom Alerts

Custom alerts are a great way to track significant changes in your data, proactively.  Alerts allow your team to respond quickly to unexpected spikes in web traffic.  Or to fix system outages before they cause massive problems for your entire business.  

Automated reports

Computers with artificial intelligence can produce similar-looking reports to those of humans. Not only that, but they can produce these reports faster and more efficiently.  There are free and inexpensive tools you can use to automate reporting on critical areas of your web analytics. Save valuable time by letting computers generate reports that are faster, cheaper, and of similar value to human efforts. Use that extra time to analyze the results and make positive changes. At inOrbit, I will share my favorite automated reporting tools.

Accelerated insights

The most time-consuming aspect of analytics is trying to connect multiple data sources into a single repository of information. It’s a lot of work to connect the dots. Data translations, manipulation, correction. Manually, each of these tasks can take hundreds of hours to do effectively.

Or you can automate these integrations. Connecting Google Analytics with our other data sources is easier than it has ever been. There are 100’s of apps that partner with Google Analytics to help us connect our data points.

Use third-party tools to manage these connections, and deliver the data into an organized KPI-focused reporting system. Use report templates to pull together the information you need, as you need it.

Make your organization smarter by going deeper into your analysis. Instead of drowning in data, you can start to wade in the pools of wisdom.

In my presentation, I’ll show you my favorite tools of the trade. The tools that help us connect our data points, and accelerate our analysis. I will also discuss the best way to use these systems to help you make timely and accurate business decisions.  

Are you ready to save time and deliver more value from your analytics programs? Make sure to attend my session at inOrbit18!

 

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2 responses to “The Role of Automation in Web Analytics”

  1. Great piece regarding the usefulness of automation in web analytics and determining whether the report is worth looking at or not. With my company we’re drowning in reports, where they all come across as equally important, but at the end of the day the data is dumb with asking strategic questions to put the number in the right context. I’ll have to look at it from a different way from now on in the office.

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