Here at Workshop Digital, we are all about PPC account efficiencies. There are a number of optimization tactics out there to trim wasted spend in an Adwords or Bing PPC account. Most analysts focus on day parting, bid adjustments and lowering bids, which are all great. However, query mapping is my favorite and most efficient optimization tactic I have found to eliminate wasted spend in a PPC account.
What is query mapping, you ask?
According to Amy Bishop at Clix, query mapping is defined as: “filtering through the search queries to see which ad groups and keywords queries are being paired with and subsequently adding negatives to ensure that queries are matched most appropriately.”
When analyzing the health of any PPC account, this concept is definitely one you should keep in mind because it takes a deeper look at the overall spend of your keywords by ad group and their performance.
Although this tactic is not new, it is definitely underutilized and one that should be considered. For that reason, I will share the 3 step process I took to cut wasted spend in one of my PPC accounts, which also helped decrease the overall account cost per lead by 46% and increase the conversion rate by 65%.
Step 1: Pull The Right Data to Analyze
Pulling the right data is very important, especially for this type of optimization because you want to ensure you’re analyzing the correct metrics.
First, download your account search query report for the last 2-3 months. In the report, you want to make sure you have the columns for your search terms, ad groups, clicks, impressions, average cpc, conversions, cost per conversion and conversion rate added.
Next, you want to sort for duplicate keywords with the same match type showing in multiple ad groups.
Step 2: Analyzing the data
Once your keywords are sorted by duplicates and match type, you will then look at how each keyword is performing by ad group. The four most important metrics I look at for my analysis are: conversions, cost per conversion, conversion rate and average cpc.
I will walk you through how I further analyze these metrics.
I’m sure you have already realized the keywords are performing very differently in each ad group. The keyword in ad group A is definitely performing better than when it is served in ad group B.
To highlight further, the keyword in ad group A is showing a 28% decrease in cost per conversion, a 5% increase in conversions, a 5% increase in conversion rate and a 9% decrease in cost per click. This tells me that the ad copy is very specific to the query and it’s also taking users to a very highly relevant landing page in ad group A.
Step 3: How to Fix the Problem
The first thing you want to do is shift the traffic to the ad group that’s performing the best and in this case, it is ad group A.
How to do this?
Add the exact match version of the search term as a negative keyword to the underperforming ad group. Doing so ensures that the keyword will not be served in the underperforming ad group and the traffic will shift to the better performing ad group. In my case, I added the exact match version of [t-shirt] to ad group B as a negative, forcing the keyword to only be served in ad group A.
Once you have implemented this change, it’s best to wait about 1-2 weeks to re-pull the data. In my case I re-pulled the data to analyze performance a week later, since my client has very strict KPI goals.
I looked at ad group A’s performance for the first 9 days before the implementation compared to the 9 days after implementation and realized that the cost per conversion for ad group A declined by 83% and the conversion rate increased by 3%.
Since this tactic worked so well, I implemented this optimization across three additional ad groups that were experiencing the same problem. Again, I saw cost per lead decline and conversion rate improve; however, this time the account’s overall cost per conversion declined by 46% and the conversion rate increased by 65%.
In closing, keyword query mapping optimization may not be the fastest optimization technique out there. However, the time it takes is definitely worth the results, especially for an account that’s spending a lot with a high cost per lead. I encourage you to test it out and see if it helps you improve your KPIs.