The Situation
Bennison Brown are a London mortgage broker. Their service is centred around finding the best possible mortgage deals available for their customers, and making their mortgage journey as stress-free as possible.
Bennison Brown hired me in 2017 as their 4th member of staff, my job being to scale the business by getting leads in as a Google Ads manager. They had experimented with Google Ads for a few months but hadn’t managed to make it a profitable venture.
The campaign averaged a Click-Through rate of 1.40%, a conversion rate of 2.04% and a Cost Per Conversion of £27.31 and a Cost Per Click of £0.56
- Click-Through Rate: 1.4%
- Cost Per Click: £0.56
- Cost Per Conversion: £27.31
- Conversion Rate: 2.04%
The Challenge
The primary issue was that they were attracting the wrong traffic using broad match keywords (these keywords give Google freedom to match your keywords with thematically related phrases, and these are often unwanted.
Combined with a poor negative keyword list, their ads were showing for a lot of search terms that were either completely irrelevant, or showed a small amount of interest in using a mortgage broker.
A lot of their recorded conversions were people who had no intention of using a mortgage broker, but were instead calling to ask for advice on the current best rates on the market. Essentially, although they were getting phone call (Marketing Qualified Leads), a very small portion of those became actual customers (Sales Qualified Leads).
The Process
After completing some initial keyword research, I removed all broad match keywords, and replaced them with a mixture of Broad Match Modified, Exact Match or Phrase Match keywords. I also created a comprehensive negative keyword list.
Whilst keeping an eye on the search terms report, I was able to make sure that all search terms that their ads showed for indicated potential interest in using a mortgage broker
The Results
The KPIs were now the following:
- Click-Through Rate: 1.53%
- Cost Per Click: £3.20
- Cost Per Conversion: £57.75
- Conversion Rate: 5.54%
The CPC and Cost Per Conversion increased, but this was a good thing as it reflected that the keywords that Google was bidding on were more valuable and profitable than before. This translated into better quality leads, thus a higher conversion rate from MQL to SQL.
Further Improvements
Phase 2 Although the conversion rate was higher, and they were consistently getting leads profitably, the Click-Through Rate was poor at 1.34%, which has a negative impact on the quality score of the ads, making them more expensive
The business, now at 17 staff members has scaled significantly. Despite this, the campaign budget needed to be limited as staff can only cope with a certain capacity of leads.
With a limited budget, there was room to make the most of it. Using the data previously collected, I created an ad group containing only the highest performing keywords, and created ads specifically for those keywords.
As of now that, ad group is performing with a CTR of 5.60%, a CPC of 6.93%, a conversion rate of 12.83% and a Cost / Conv of £54.04
The Latest Results
As of April 2021, KPIs are now the following:
- Click-Through Rate: 5.6%
- Cost Per Click: £6.93
- Cost Per Conversion: £54.04
- Conversion Rate: 12.83%
Translated into percentage changes compared to when I started:
- Click-Through Rate: Rose by 300%
- Cost Per Click: Rose by 11.4%
- Cost Per Conversion: Rose by 98%
- Conversion Rate: Rose by 529%