Pay-per-click ads for big tires eCommerce

We got this project in July 2015. We have worked very hard on the project during this time, and it is now ready to be presented as a case study for pay-per-click.

On the basis of search campaigns and a non-segmented Google Shopping campaign that had already been launched at the time, the Y Direct and Google Ads advertising accounts were used. Google Analytics without an eCommerce configuration and 3rd party analytics tool with an eCommerce configuration

What was done initially (during the initial months of our work):

• eCommerce setup in Google Analytics (implementation using GTM);
• Setting up dynamic remarketing in Google Ads;
• Optimization of an existing Google Shopping campaign (working on negative keywords, structuring of a campaign by brands);
• Expansion of search campaigns (breakdown by brand and use of search campaigns by model);
• Expanding of Google Ads search campaigns (breakdown by brand and use of search campaigns by model);
• Optimization of a retargeting campaign.

Pay-per-click ads for tires shop results for the 1st month:

The first month after the start of work turned out to be completely disastrous, especially for Google Ads – the analytics tool indicated that there were more orders for Ads, but that these orders also cost more money.

The quantity of Y Direct orders increased a little bit, but the order value stayed roughly the same.

It was decided to assess the effectiveness of advertising campaigns after a longer period of work because the first month fell during the “off-season,” or a time when there was little consumer demand.

The following tasks were completed during the second month:

Google Ads:

• Optimization of the Shopping campaign (by the end of the month – the cost per click increased by 72%);
• Optimization of launched campaigns by brands and models (Google and Y);
• Optimization of Google Ads remarketing;
• Continued scaling of search campaigns in accounts.

Pay-per-click ads for tires shop results for the 2nd month:

According to the results of the second month of work, the following results were recorded:

Google Ads

• Growth in the number of transactions – 265%;
• Reduced price per transaction by 46.5%
• Income growth – 242%
• Conversion rate growth – 153%.

Wherein:

• Expenditure growth by 95.5%;
• Cost Per Click growth – 72%.

Y Direct

• Growth in the number of transactions – 99%;
• Reduced price per transaction by 30%
• Income growth – 149%
• Conversion rate growth – 35.6%.

All indicators gradually increased over the ensuing months (if one takes into account the seasonality of goods).

The resulting change in indicators after a year and three months (exactly such a time interval was chosen to cover the time from the start of work in July’s “off-season”) are as follows:

• Paid traffic growth – over 101%;
• Growth in the number of transactions – over 144%;
• eCommerce Conversion Rate growth – over 21%;

Tools and methods that were used in the first year and beyond to address scaling and optimization issues:

• Segmentation and optimization of shopping campaigns based on the seasonality of the product;
• The massive use of DSA campaigns like in Google Ads. In our case, the client has a very well-built and well-indexed site by Google, which allowed us to significantly expand the reach in search results for low-frequency queries.
• DSA campaigns in Y  Direct (this type of campaign eliminates the need to use API to load keywords by item from a feed)
• Use of RLSA/RDSA campaigns;
• Segmenting remarketing audiences by time since the last visit of the user to the site and building dynamic remarketing campaigns based on these audiences – made it possible to increase the number of sales from dynamic remarketing and reduce the price per order;
• The use of Smart Banner campaigns in Y made it possible to compensate for the lack and reduced capabilities of basic retargeting campaigns.
• Switching from conversion tracking in Google Ads using Google Analytics to the Google Ads pixel (with the transfer of order data to Ads). This change brought a number of benefits:
  • The order data is delivered to the account almost instantly (up to 30 minutes delay), unlike the Google Analytics data.
  • The number of orders is much higher than that recorded by Google Analytics due to the difference in the principles of the codes, in turn, a larger number of orders allows you to speed up learning and simplify the “life” of Google Ads automation tools (enhanced CPC, CPA and ROAS strategies, own strategies).

After switching to this type of tracking, we received the following results:

• Increase in the number of transactions by 32.8% compared to last year;
• Income growth by 25.8%;
• Reduced expenses per order by 27.6%;
• Reduction of expenses by 3.9%.
• Launch of YouTube-shopping video campaigns for narrowly segmented dynamic remarketing audiences. As a result, there is a large number of associated conversions and an increase in brand traffic.

The final growth for 4 years, despite the partial suspension of campaigns during peak activity periods to reduce the load on the call center and logistics department, was as follows:

• The number of transactions for contextual advertising systems increased by more than 130%;
• The income increased by more than 126%;
• The total Ecommerce Conversion Rate increased by more than 19%.