Let’s first take a look at common definitions in Sales/Website Data and where you can find them in your marketing platforms.
In our last article, we talked about where to find Ad Cost & Website Session Data on platforms such as Paid Search and Youtube Ads. Now, we’re going to see how we can bring it together on our dashboard with unique calculated metrics.
First though, let’s take a look at the calculated metrics we’ve done and how far we’ve come in our analytics journey.
We’ll see where we can find them on common marketing platforms, and then figure out a way to piece them together for further insight and analysis.
Let’s get started!
We also learned that it’s possible to calculate new metrics and visualizations, such as CAC (Customer Acquisition Cost) from these previous metrics.
In this article, we’re going to be exploring how we can visualize another important formula – Return On Ad Spend – which is possible across all platforms through holistic data. Take a look at our last article to see which metrics make up this calculated metric.
Here are the topics to cover today:
In our last article, we talked about where to find spend on various marketing platforms, and what that looks like aggregated.
Now we’re continuing with that and going deeper…
So how do you find the best marketing analytics solution for your business and how do you then get internal buy-in?
Here are 3 ideas on how to get internal buy-in when upgrading your marketing analytics stack:
It’s officially the end of marketing, says Marie-Gulin Merle, the CMO of Calvin Klein and Chief Digital Officer of PVH.
How come? Well, marketing is becoming more and more “MarTech”, or marketing technology. Before, digital marketing and traditional marketing were considered separate. Now, there’s been a mindset shift where involving advanced technology and analytics is considered the norm. What is this shift – and how does it change marketing going forward? Read more to find out!
Do You Have A Data Problem?
Most marketers today do. With traditional and digital marketing becoming one, marketers are inundated with so much data. This includes web data (page views, clicks, signups), ad data (impressions, CPM, frequency, CPC), email data (open rate, unsubscribe rate, engagement) and more.
This doesn’t include a CRM, which hosts information on all your prospects and leads, acting as the heavyweight in gathering all customer contact information. How can the average marketer create a complete blueprint of who their customer is and where they come from?
Everything from monitoring the impact of your campaigns to tracking engagements on your e-commerce website generates large amounts of data. But how are you as a marketer supposed to prioritize the right e-commerce metrics to further make the right decisions?