Can’t quite put your finger on what’s happened to your previously successful paid search campaign?

This client couldn’t either and tasked us with trying to help them solve where things are going wrong.

Here’s how we approached solving the problem.


Client A is a nationwide telecommunications company.

They provide TV, internet, and phone services to customers primarily in Arizona, Arkansas, California, Louisiana, Missouri, North Carolina, Oklahoma, Texas, and West Virginia.

In 2015, we started our engagement with Client A as a partner of another agency and have provided search engine optimization services since then.

We were tasked with building authority and increasing traffic to the website, but in this process we also became a digital marketing partner by providing outside insights into their overall digital marketing, including paid search.



Every month we report against the Return on Ad Spend for organic search traffic, branded paid search traffic, unbranded paid search traffic, and any additional paid channels that were being run as part of an experiment for new opportunities.

Return on Ad Spend Findings
Return on Ad Spend Findings

It was in our reporting on Return on Ad Spend, we were able to establish trends in Client A’s paid search performance and inconsistencies in the alignment between the SEO and PPC agencies.

Client A had changed paid search agencies in May and there were major increases in spending with a negative return on ad spend.



Client A already knew a few problems regarding their new geographic targeting, but through our investigation we were able to establish additional insights into causes that contributed to this negative return.

To caveat this a bit, we weren’t actually allowed to go into the Adwords account directly and we were only able to pull adequate information from Google Analytics.

We found that from paid search year over year (YoY), there was an increase of ~17% to the BuyFlow Storefront (there initial step to completing a sale), but this increase in the traffic came with an ~11% decrease in sessions to the second step of the process. The alarming part was the increase in visits to their “Not Serviceable” page by ~105% which is a clear indication of the geographic targeting issue that was established in the beginning. 

This meant that people were starting the conversion process but then found that they didn’t live in Client A’s service areas. 


State Targeting

Looking deeper into the ~105% YoY increase to the “Not Serviceable” page, the most significant increases by regions (state) were Texas (118%), California (331%), and Missouri (192%).

Compared to overall traffic, there was an increase in NoService sessions in Texas of 102%, California of 188%, and Missouri of 180%.

While those are states in which Client A provides telecommunication services, they were targeting areas where they didn’t provide any services. 


City Targeting

Dallas (80%), Houston (135%), San Antonio (198%), and Los Angeles (302%) had the most “Not Serviceable” sessions.

So this allowed us to report on not just the state level declines but also where there were opportunities to clean up specific cities/zip codes where they can provide services.


Keyword Targeting

Finally, we took a look at the keywords and any discrepancies that exist year over year that are contributing to this decrease in Return on Ad Spend.

It looked like there were some additional broad match modified keywords added that weren’t in Google Analytics the previous year.

Take, for instance, “internet,” where there was a spend of $122,467.15 and an average cost per click (CPC) of $6.47 that had a return of $23.325 if we used $85 per completion. We’re not completely sure of the lifetime value (LTV) of a confirmation, but there were 275 confirmations from the addition of this keyword match type.

If we compare that to last year, when internet was just using the broad match type, there was a spend of $11,988.11 at an average CPC of $1.54 that saw a return of $12,665 or 149 confirmations. 

We also found some spend on keywords like “uhaul” and moving in general. While they didn’t spend a lot, ~$8,000 and see a return of 10 confirmations or $850 ($85 value for confirmations), there was definitely opportunity to pause some wasteful keywords. 

Finally, there was a significant increase in average CPC’s due to a change in match types from Broad which are typically cheaper but provide less control. The additions of Broad Match Modified, Phrase, and Exact drove the average CPC’s up by $0.46 CPC on branded terms and up to $6.15 CPC on unbranded terms.



There were too many cities and states that were being served ads even though they couldn’t provide cable and internet services at those locations.

We could tell this was happening based on the increase in Not Serviceable page sessions. We recommended a closer look into the targeting by state and city.

When looking at the limited keyword data, we recommended they turn on a few of the campaigns that were running by the previous agency. This was in an effort to only turn back on the top performing past campaigns and hopefully stabilize the loss in Retrunon Ad Spend while decreasing the number of Not Serviceable page sessions.


To learn more about our PPC services, contact us for a free consultation.

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