Case Description
Our client is an online store selling and delivering coffee produced in-house and by other brands.
Target audiences:
- B2C: retail customers who buy coffee in small amounts for themselves, home, or office. Prices range from low to premium.
- B2C: online stores, coffeehouses, and wholesalers.
We divided advertising into two directions, targeted at visitors of the coffeehouse and online store.
- LOCAL PERFORMANCE MAX (COFFEEHOUSES)
We decided to set up and launch a Local Performance Max campaign to engage people who like visiting coffeehouses and cafes in Lviv.
Our goal was to show advertisements on Google Maps to people located around 6 coffeehouses in 6 different locations of the city and encourage visits.
We created two ad groups based on the audience types:
REGULAR COFFEEHOUSE VISITORS
- By keywords:
- By interests:
This how the ads looked like:
COFFEE FANS
- Website visitors:
- By interests:
This how the ads looked like:
Results after 30 days of advertising with Local Ads
The ads received 1,217,398 impressions on Google Maps, 4,986 clicks, and 1,151 conversions (requesting directions to the closest Kredens Cafe) at 3.44 UAH each.
- PERFORMANCE MAX SHOPPING
When looking for an effective method for advertising the online store, our PPC team quickly found a solution: setting up and launching Shopping Performance Max Google Ads, a new generation of automated advertising campaigns powered by artificial intelligence.
Opportunities of PMax:
- setting up Google Ads in real time
- reaching the target audience no matter the device
- showing ads on all Google’s advertising platforms — search results pages, Display Network, Gmail, YouTube, Discover, and Google Maps
- maximum autonomy: Performance Max generates ads based on the uploaded ad creatives and uses AI for placing bids without manual intervention, focusing on conversion goals.
Another advantage of PMax is engaging a relevant target audience. It analyzes data about people who carried out desired actions and looks for those who are interested in similar goods but haven’t visited your store, showing them relevant products you offer.
We launched this type of campaign using product categories:
Results after 6 months:
With gradual increase in budget, we spent 30,907 UAH and got 130,235 UAH conversion value.
The average cost per conversion is 143 UAH, which equals a big strong latte in the Kredens chain coffeehouses.
Our next step involved segmenting the existing Performance campaign based on the categories of goods that had been most popular and generated most revenue, which resulted in increased efficiency and revenue in 3 following months.
RESULTS
THE EFFICIENCY OF CAMPAIGNS BASED ON THE NUMBER OF TRANSACTIONS:
Smart Shopping generates 65.59% transactions that account for 57.24% revenue from all contextual advertising;
Performance Max generates 35.11% transactions (20.69% of revenue).
During the 6 months of our partnership, the client’s website has received 62,622 visitors and 5,220 transactions, meaning that each 12th visitor coming from PPC made a purchase.
Conclusion: It’s always interesting to work with different types of goods. When working with online stores, it’s essential to set up and launch shopping campaigns with feeds, connecting e-commerce, and constantly optimize and scale them. Segmenting feed goods into categories and optimizing feed attributes allow you to improve results, decrease customer acquisition costs, and grow your revenue.
