Audience based targeting is becoming one of 2017’s most used PPC buzzwords (seemingly topped only by machine learning). Similar audiences for search, which has just recently moved out of beta, lets you create lists of users that share similar interests and online search behavior based on your defined remarketing lists (RLSA). It works for both Text Ads and Shopping Ads.
We tested it in the office & industral supplies segment and are ready to share some insights with you.
Similar audiences as an addition to remarketing as we know it
As a sort of addition to classical remarketing as we know it, AdWords now offers the ability to reach new potential customers through “Similar Audiences” for search campaigns. Based on defined remarketing target groups, or RLSA, Google identifies and indicates other similar users as potential customers. Google determines characteristics and attributes that can indicate similar audiences, including shared interests and online search behavior. As Google puts it: „AdWords looks at the search activity in a short time frame around when visitors are added to your remarketing list . . . Based on this information, the system automatically finds new potential customers whose search behavior is similar to that of people in your remarketing list.“ Useful to know: similar audiences can only be created from remarketing lists with at least 1,000 cookies.
When “similar” users become visitors
People who began in the „Similar Audience“ list and then visited the website will be removed from the list — they are no longer similar users but instead visitors, converters, drop-outs, etc. On the illustration below we can see the list size of the different “Similar Audiences”.
A simpler way of finding new potential customers
By characterizing similar users based on their search behavior compared to the behavior of existing users, it is more likely that similar users will complete a conversion than people who are not associated with any list.
The „Similar Audience“ lists are updated immediately and hence are always up-to-date.
Similar users can be divided very granular, for example in „similar to converters“, „similar to visitors“, etc.
Beta tests for Similar Audiences
We also tested „Similar Audiences“ extensively in the office supplies segment. Our aim was to identify the potential of “Similar Audiences” to gain new customers. We were also curious to see if there was an incremental uplift of the click through rate due to bid adjustments.
Implementation in three phases
Our „Similar Audiences“ tests were implemented in three phases.
- In the first phase the similar user lists were built and assigned to the respective search campaigns. The development was monitored continuously over a period of two and a half months.
- In the second phase the bids for the „Similar Audiences“ were adjusted. More precisely, a +20% bid adjustment was applied to the similar users lists to increase the bids for „Similar Audiences“. The development of this change was also observed continuously, over a period of one month.
- In the third phase all the results then were evaluated and compared.
Significant increases in CTR
The similar user lists show a considerable proportion of clicks within the campaign: approximately 10%. By the end of the first phase, some significant changes could be seen. Both the CTR and the conversion rate increased strongly compared to the rest of the campaign without RLSA, by 51.74% and by 40.51%. After this phase, the bids were adjusted by +20% for „Similar Audiences“. Toward the end of this phase, the next changes could be seen: The CTR remained at a level similar to that in phase one compared to the non-RLSA portion, with an increase of 52.16%. Moreover, the conversion rate also showed a boost. Compared to the portion of the campaign without RLSA, the CR increased by 52.62% in the „Similar Audiences“ list.
In short, a significant increase of the click-through-rate and of the conversion rate were recorded. Here are the results again in a short overview:
Our key findings in phase 1 (without bid adjustment and compared to the remaining campaign without RLSA)
- CTR increased by 51.74% with „Similar Audience“
- Conversion rate increased by 40.51% with „Similar Audience“
- Position at “Ähnlich wie Produktseite angesehen” 2.8
- Average CPC at “Ähnlich wie Produktseite angesehen” € 1.87
Key results of phase 2 (with bid adjustment and compared to the remaining campaign without RLSA)
- CTR increased by 52.16% with „Similar Audience“
- Conversion Rate increased by 52.62% with „Similar Audience“
- Position at “Ähnlich wie Produktseite angesehen” 2.2 – increased by 0.6
- Average CPC at “Ähnlich wie Produktseite angesehen” € 2.36 – increased by € 0.49
Best Practice Tip – Mapping the target groups to the customer journey
Especially in retail, it is useful to map the target groups (and thus also the “Similar Audiences”) to the decision making process of the customers. The following lists, for example, can be created: Site visitors – product page visitors – visitors who have canceled a conversion – all converters. This allows advertisers to pick up users at different stages of the purchase process. In addition, a granular control of the target groups, for example through bid adjustments, is possible.
„Similar Audiences“ offer a powerful opportunity to address completely new potential customers who are similar to the existing customers concerning their purchase process and their online search behavior. Even though measuring incremental effects is difficult, we are able to provide some interesting insights concerning these effects: Through bid adjustments of +20% at “Similar Audiences” we received a further CTR push of 0,8% (compared to no bid adjustment) and an increase of the Conversion Rate of 29,9%. So we can say that the bid adjustment at least influences the CTR in an incremental way.
Bearing in mind the rule of thumb „Acquiring a new customer is five times as expensive as keeping an existing customer,“ the „Similar Audiences“ represent quite an interesting means to attract new, qualified users (or even new customers). In this sense, wish you the best using this strategy.