The best type of data analysis takes data and turns it into value from actionable insights. But the road in between is by no means a straight path, and has several pit stops that can derail that end value.
In my 1,389 hours of data analysis at Seer (that’s nearly 2 months straight – 14% there, Gladwell!), I’ve found that analysis that reaches that valuable destination has a few characteristics in common. By highlighting how to avoid common pit stops, we can ensure that your data analysis is more likely to produce value.
I’ll highlight five major themes of the ways you should be analyzing your data, and along the way, show why each is so effective compared to alternatives. Let’s dive in!
So many companies are flooded with data “reports”. Reports are the death of business data! “Reporting” in and of itself implies a static document that serves a singular purpose: to let you know what happened. Sadly, we’ve seen SO MANY companies stop right there, and lose out on the value from analyzing their business data.
- Organic traffic is up 15%, great!
- Blog traffic spiked by 75%, our content is working!
- Our campaign drove 4K sessions during the last month, we’re marketing rockstars! *high five*
While this approach can stem the tide of some data hungry stakeholders, it serves as a blip in a vast data ocean. Meanwhile, great data analysis can shift the full tide. So relegate pure data updates to automated check-up reports. You should never have a single analysis point that doesn’t answer the question “what can I do with this data?”
By assigning actions to your insights, you can change the story.
- Organic traffic is up 15%, great! Our content marketing worked, so let’s expand this approach to other relevant article types.
- Blog traffic spiked by 75%, our content is working! This was due to one strong new post and a backlog of evergreen content, let’s remarket this new post to old users, and find new ways to leverage of evergreen content in other marketing channels.
- Our campaign drove 4K sessions during the last month, we’re marketing rockstars! *high five* This campaign worked because we geo-targeted the right regional markets, let’s expand to our secondary markets with less traffic exposure and see if this trend continues.
Although the view may sometimes be foggy, most decisions that all businesses make come back in some form or another to money (as they largely should, it is the job of most businesses to make money in the long-run!). If that’s the case, why doesn’t most data analysis tie back to money?
Well, there are a few reasons: Many companies don’t have relevant and set revenue goals for digital marketing efforts (you’d be surprised…) It can also be really hard to tie back specific user actions to estimated value. And, therefore, most people don’t take the effort to do this task.
This seems difficult to most people, but through setting boundaries and narrowing down values, you can get closer. Is a form conversion for you worth closer to $ 1 or $ 1,000? How about $ 100 to $ 500? Keep shortening your range and find at least an estimated value.
What if you could quantify the value you lost from inaction?
If people are leaving your site due to a poor experience, and you lose out on that $ 100 form fill, would improving the site experience to keep 5% more of your audience make up for the effort it’d require your team to put in? What if you could raise that number to 10%, or even 15%, more of your audience?
Data becomes immensely more valuable if you can tie back the estimated value of an action (or inaction) to what it could win (or lose) your company in dollars. If you know an action a user takes on your website is worth $ 1,000 (or keeps your from losing $ 1,000), how much more likely do you think you are to act on increasing, or just improving that over time?
As someone who has spent plenty of time digging around in Google Analytics, Adobe Analytics, and qualitative data sources, you can find plenty of interesting data, but how much of it matters in the grand scheme of things?
Uncovering what truly matters in relation to your business is the key to actionable analysis. Whenever possible, tie back action items to the main goals your company is trying to achieve. It will instantly become more actionable, and if done right, could be the missing link towards reaching that goal!
We all read a lot, every day. Think of all the emails, text messages, social media posts that you intake in a day. I’ll save you the math, it’s a lot of words to process! And with you so graciously taking the time to read a few more here – I’ll make this short and sweet.
Visuals break up text, and allow users to easily digest (if done right) what you want to communicate. A great data visualization highlights exactly what you want the user to notice, and leads them to the action before you can even mention it.
Forgo the tables and metric scorecards – that’s what data exports are for! Use interactive tools like Google Data Studio, Tableau, or Power BI to tell a story with data and grab stakeholder attention with what you find.
Give your stakeholder’s eyes a break! Read my post here for why it’s crucial to convey the importance of data to executives (without making their heads explode with data overload!)
Everyone (or at least most mature data companies) have a data source of truth. Google Analytics. Adobe Analytics. Your Data Warehouse. Whatever it may be, that naturally becomes the go-to source for data.
But, what if you break out of the single data source mindset, and think about how you might marry quantitative and qualitative data to tease better insights. Integrating your data can lend tie user action data from Google Analytics and match it up with data on users in Marketo, or SalesForce.
Are you tying offline, online, and cross-platform conversions back to a data source of truth? If the answer is no, watch the Analytics team’s video on Closed Loop below.
Don’t limit yourself to your go-to data source! Consider discussing Closed Loop with your Developer team, and if they’re on board – contact us next. We’ll help you get value from your disparate data sources.
What type of analysis is your company doing? Start analyzing data to make decisions by answering these 4 questions:
- What are the 3 most important actions for a user to take on your website?
- How would you monetarily value each of these actions?
- What are all of the data sources that you currently leverage?
- In what ways can you combine data to form stronger insights?
Ultimately, data analysis done right can be the difference between an email buried and lost forever and an action that can lead to thousands of dollars gained or saved, and hundreds of new customers earned. So quit messing around – use data to make business decisions and measure the impact with Analytics.