In 1 year revenue increased by 44% for a sushi and pizza delivery site

1) Lack of 24/7 food delivery

The company accepted orders until 21.45, which set certain limitations. Based on this data

the working hours of advertising campaigns was adjusted according to the delivery schedule.

2) No tracking of phone calls (Call-tracking)

In the delivery niche, some of the orders are made by ordering by phone. To understand

the source of the call it is necessary to implement call tracking or hide numbers.

3) Delivery zones

The company’s territory of the city was divided into 4 delivery zones, with delivery time from 60 to 150 minutes. All this had to be displayed in advertisements. To do this, we used geo-radius with bid corrections.

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Cafe Barbaris has its own base of regular customers and re-attracting such customers is ten times cheaper than attracting new customers. Therefore, one of the main joint tasks was the following: after attracting a new buyer, due to high service and a high-quality product, transfer them to the category of regular customers and re-attract it at the lowest price.

For re-engagement, apart from branded campaigns, RLSA campaigns (search remarketing) were launched with bid corrections for users who had already visited the site. In other words, if the user has already been on our site, but continues to drive in not our brand, but, for example, “order sushi”, we will be shown in one of the first positions at a higher price, knowing that he has already visited our site and more likely to place an order.

At the start of work we launched advertising for the main delivery categories in various advertising campaigns; these are sushi delivery, roll delivery, pizza delivery, food delivery.
The main task of this stage was to identify the most cost-effective delivery directions with the subsequent scaling of these categories.

After testing various categories of delivery, the main one was singled out, which brought the most income. For optimization and scaling, we used:

1) Smart bidding

We tested different bidding targets, from “Maximum Clicks” to “Maximum Conversion Value”. Based on the test results, the campaign was switched to the “Maximum Conversions” strategy, which showed the best results. Before fully switching to this strategy, all conversions were disabled in the account, and only transactions were left, so that this strategy was optimized to receive more transactions.

2) Setting up automatic rules for increasing and decreasing the budget by day

The automatic rules had two scenarios: – Increasing budgets from Friday to Sunday. This rule was configured based on the analysis of the transaction by days of the week. Users ordered food delivery most from Friday to Sunday. – Budget reduction from Monday to Thursday. During this period, users used home delivery of food the least.

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3) Extension of the semantic core

The extension was carried out using two methods: search queries, Google recommendations. Suggested keywords were unloaded from Google recommendations into a table, after which they were viewed and only relevant ones were left.

4) Adding audiences of users who visited the site

Adding users and bidding on them to re-engage them since they are already familiar with the brand

1) Attribution

By default, the Google Ads account is set to last-click attribution. It means that only conversions from the last ad interaction will be counted in the results. Using the Multi-Channel Funnel Conversion Path report, you can see that most of the conversions are from Omni-Channel interactions and ads are not always the last source, which means that more than 50% of all conversions will not be counted for Google Ads. Without considering these conversions, you can make wrong conclusions about the effectiveness of advertising.

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2) Buyer behavior

At the start, our strategy was to increase the number of regular customers. The “Shopper Behavior” report is used to make sure that the main cohort of users that brings us income is regular customers.

3) Number of days before conversion
The “Number of days to conversion” report is used to correctly determine the period of remarketing audiences in days .
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4) Sales performance
With the help of the “Sales Performance” report we can see which product items are most popular and how much income they bring. We determine the top ten winners and use this information in advertising materials, in text ads and graphic banners, thereby further increasing the demand for them.
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During our work we managed to reduce the cost of conversion by 49%.
Due to the reduction in the cost per conversion, the number of conversions increased, since the budget remained almost at the same level, periodically decreasing or increasing.
Due to the first 2 points as well as an increase in the average cost of an order, advertising revenue increased by 44%.
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