Fall is in the air, and that can only mean one thing for most digital marketers: budget season.
The approaching fourth quarter is often the time when companies begin the budget and planning process for the next fiscal year. And it seems that ROI, while always considered a top priority, has renewed importance now. Advertising Age recently reported that intense demand for ROI is causing companies to replace their CMOs at a rapid rate — as much as a 48-percent turnover in top retailers.
You’d think that ROI would be easy to track on digital, right? Compared to offline media, digital clearly has a tracking advantage. But integrating tracking correctly can be difficult, especially for what may be influencing channels and not the final purchase channel, which can be the case at times for organic search and SEO.
So what’s the answer? How do you integrate SEO into the tracking mix and prove the organic search channel’s ROI? How you’ll track ROI may differ based on the tools and data you have access to in your organization.
If your organization hasn’t yet determined the attribution model to use, that’s where you’ll need to start. The attribution model is the basis for allocating credit to each marketing channel. There is no correct or incorrect attribution model or one that applies to all organizations. Each model is different, and you’ll need to decide which model best fits your business.
The most common attribution models are single-source attribution, measuring first touch or last touch. First-touch, as the name implies, gives all credit to the first channel or lead source that brought the customer or lead to your website. The first-touch channel is recorded and then never changed. By contrast, the last-touch attribution model credits the last channel the customer or lead used to come to your website. The last-touch channel is always updating as the customer or lead continues to interact with your site over time.
In part, these attribution models are most common because many measurement tools, like marketing automation or CRM (customer relationship management), often only have one field to store attribution data. Unfortunately, first- or last-touch attribution essentially ignores all of the channels that may have influenced a customer or lead in the process.
If you want to use a model that gives some level of credit to all channels that may have influenced along the way, consider a fractional attribution model, such as linear or time decay. Linear attribution credits all influencing channels equally, whereas time decay gives the most credit to the most recent channel and the least credit to the oldest channel for that customer or lead.
To track each lead’s or customer’s fractional attribution, however, you will likely need a new field created in marketing automation and/or CRM. I’ve often created what I call a “running lead source” field, which appends the last lead source to the end of the field every time a new channel is encountered by this lead:
I can then download my leads into an Excel spreadsheet and break apart and examine the array of data in this field. I also find this approach useful for reviewing which content pieces had an impact on the buying cycle for leads.
Ideally, your website(s) already have Google Search Console (GSC) set up. And I expect that for many, it goes without saying that GSC is an essential SEO tool, helping you to understand measurements that you can’t typically ascertain on your own.
For instance, when we advertise using Google AdWords or other paid search platforms, the platforms provide us with impression data and click through rate (CTR). This helps us to understand how many people, when presented with our message, seemed interested enough to click through.
With organic search, however, it’s a bit more difficult. You don’t know how many people searched for your keywords and the CTR — unless you use GSC.
However, there are a few pitfalls to avoid with GSC:
If you have to create multiple website properties in GSC, you can now at least tie them together using Property Sets, which allow you to see the data in a combined report.
Whether you use Google Analytics (GA) or another website analytics package, website analytics data is incredibly helpful for understanding ROI. With GA, there are several steps I recommend to help track ROI:
If you want to get really sophisticated, you can try to upload your offline sales data into GA as well, using Data Import. Data can be uploaded manually or via the API; so if you don’t have a developer who can help you, it can be a highly manual process. Data Import will then reveal much of what you need to know about sales data directly in GA, including lifetime value. However, it still does not allow you to personally identify specific customers or prospects — just overall trends.
While website analytics are helpful, they cannot identify individual buyers and how those individual buyers found your site. Also, it’s difficult to ascertain lifetime value of a marketing channel when you can’t ascertain the lifetime value of an individual customer through a given marketing platform. That’s where your marketing automation and CRM tools come in.
Earlier I mentioned the running lead source field I created in my Marketo and Salesforce.com platforms. This allows me to pull data from Salesforce, along with lead status and opportunity and value information to determine which lead sources contributed to actual qualified leads, opportunities and total sales.
In every case I’ve seen, organic search plays a significant role, if not the most important role, in conversion. Here’s the model I like to use to demonstrate the value of SEO in an ROI report, showing all of the stages that an organic search visitor likely came through. I use this particular table in Excel to calculate B2B ROI from a first- or last-touch attribution model:
Another good report to run to determine the value of each channel is separate from ROI — Average Order Value (AOV) and Average Lifetime Value. If you are an e-commerce company, then you can likely track this by customer in your e-commerce platform. But when you’re tracking offline sales, you may need to calculate this yourself.
If you use Data Import for GA, you can track AOV in GA. Average lifetime value may be more difficult to track directly in GA, so you can use this table to help you calculate that:
Once you have a list of all of your customers from the organic channel, you can determine what the average lifetime value is across the organic search channel by dividing the total lifetime value of all customers in this channel combined by total customers in this channel.
These tables are important because, when run against other channels, you’ll often find that organic search has high values. This can certainly help justify your value and the value of your service to the company.
If you use a fractional attribution model, however, you can’t really use the table above, as you might double-count conversions and sales against multiple channels. That’s where things get a bit more complicated. You’ll likely need to assign a percentage value to each channel that touched the customer, then only attribute a percentage of that sale’s value to each channel.
Once you finally know these numbers from organic search, begin focusing on how to improve them. If you’re driving lots of organic traffic to your site, but that traffic isn’t meeting your site goals (lead generation or purchase), then consider how you can test improvements to your site through conversion rate optimization techniques.
Since our ultimate measurement is ROI, it’s not enough for marketers to consider SEO successful just because organic site traffic is high. ROI isn’t about traffic — it’s about revenue. Do everything you can to improve that progression from organic search visit to conversion so that those visitors have a greater opportunity to influence your ROI.