How To Analyze Keywords With CRM Data

I recently put together a keyword analysis for one of my clients using CRM data, and found a ton of value in it so I wanted to share my process and methodology here.

The benefit of incorporating CRM data into a keyword analysis is that it allows you to see beyond the “conversion” and understand how different search patterns actually contribute to revenue. I’m breaking down my process into four steps.

1. Use UTM parameters to capture paid search keywords in form submissions.

While this isn’t the only way to track keyword performance in a CRM, it is one of the most effective when looking at last click attribution.

Setting up all lead forms with a hidden field to capture the dynamic utm_term parameter can help assign a keyword to a contact once they submit a form. This utm_term property can then be tied to other CRM objects like deals and companies. This will be important for the next steps in this analysis.

2. Set up the proper CRM infrastructure to map contacts to deals, incorporate accurate deal stages, and include pipeline and revenue amounts for each deal.

This step has nothing to do with keyword data directly, but it’s important to understand how deals progress through the sales cycle.

Tracking revenue and deal stages in your CRM is a critical piece of this analysis. This data will allow you to understand which deals ended up being qualified (based on deal stage), and which deals actually generated revenue. As long as a contact is associated with a deal, you’ll be able to start tying performance from all of these different objects together.

3. Download a report from your CRM that contains the utm_term field, deal name, deal stage, and deal amount. You can then join this with a keyword report from Google Ads that has keyword and cost.

This is where you can bring all of your data together. You’ll want to be sure you pull both reports from the same date range.

Your CRM report will have one table that will look something like:

• utm_term

• Deal name

• Deal stage

• Amount/Revenue

Your report from Google Ads can be pretty simple with as few as two columns:

• Search keyword

• Cost

The easiest way to join this data together would be to run a vlookup on your utm_term column against the search keyword column to create a new table that’s:

• utm_term

• Deal name

• Deal stage

• Amount/Revenue

• Cost

4. Start analyzing keyword performance.

From here you can get to the fun analysis portion. Some of the most interesting metrics I found were:

• SQL rate by keyword (number of SQLs / total deals)

• Win rate by keyword (number of closed deals / total deals)

• Keyword ROAS (closed revenue / cost)

You can certainly explore other metrics, but I found that these three gave me the best insight into which keywords and keyword themes were performing the best for my client.

Interestingly enough, when running this analysis for a client recently even some keyword themes that had a strong pipeline:spend ratio ended up having a poor ROAS which indicated that something about that search type / request type wasn’t translating into actual business. This has triggered a deeper dive into user behavior for those types of requests which will most likely change our messaging approach.

Hopefully this process is fairly simple to follow, and allows you to start looking at keyword performance at a deeper level!

Have questions, considerations, or critiques? I’d love to hear them! If you’re reading this via email, just hit respond. Otherwise, you can find me on LinkedIn.