Google Ads Case Study: Optical Store

The multi-branch optical shop had 2 main business objectives. They wanted to regain their online visibility for their 67+ local branches and increase the number of Eye Test bookings through their website. 

Client’s local strategy wasn’t delivering results. After auditing the account, it quickly became clear that their branch location assets weren’t used in their campaigns. There was also a risk of bid cannibalization in account with multiple campaigns bidding for the same keywords. 

Another challenge we faced was that the account’s search strategy utilised Product and Gender based Categories to organise their campaigns 

We also faced some technical challenges at this point: 

1).the local campaigns were being discontinued soon after we started working with Optical Shop(so we could not utilise them long term) 2).the Location Extensions have had a Google update - they were no longer easily accessible via the extensions tab. 

3). outdated / broken tracking for the Appointment Bookings conversion Results: Quarter 1 

After initial 3 months since Minty took over the Optical ShopGoogle Ads account 

● +515% increase in conversions 

(Jan 2023- March 2023 )- compared to the previous Quarter ● decrease in cost per conversion by 82% 

● decrease in cost by 13% 

Graphs to illustrate the above:

We took the 2nd Quarter to the next level by continued monitoring KPIs and exclusion of what wasn’t converting while implementing keyword expansion into new relevant search trends. 

● further increase in conversions by +412% 

(1st April 2023 - 30th June 2023 compared to the previous 3 months) ● even lower cost per conversion by another 80% 

● even lower avg cost-per-click by 13% 

We restructured campaigns for keywords that performed well in the past. In addition to that, expanded the keywords groups, depending on the latest trends and new searches. 

The Initial Approach for Search was different keyword theme grouping. Instead of creating campaigns based on product or gender categories (which weren’t working), we used intent based categorisation for our campaigns. 

We implemented negative keywords lists to manage and eliminate irrelevant impressions. 

We started with solving issues with location extensions by checking the Business Profile link. We then updated the location extension so that they became location assets (this was a Google update and out of our control). We then created Location groupings to make the location assets available to be used with campaigns. 

We optimised location targeting by adding negative location targeting to avoid geo target overlap. 

By using Location Groupings, we were able to roll out a comprehensive local targeting without the need to create 67+ single campaigns for each location. We redesigned and launched the local strategy from scratch using Performance Max campaigns, which were a completely new solution at the time. But it made sense to us due the future potential to scale. 

We revamped Ads and added a Call-To-Action to Headlines and Descriptions. 

As mentioned above, we also started a gradual move of local strategy away from smart campaigns and towards performance max.