Optimizing Campaigns With Low Conversion Volumes Through Soft Goals
Management Summary
This post introduces an innovative approach to optimize SEA (Search Engine Advertising) campaigns with low conversion volume: Softgoals.
Challenge in campaign optimization: Little & non-constant hard conversions
Every company wants SEA campaigns that are optimized for sales or revenue. However, in order to continuously maintain or even increase the efficiency of campaigns, a certain number of conversions are required. Depending on the type of campaign, Google Ads specifies that at least 30-60 conversions should be achieved within 30 days. However, in practice it turns out that even this minimal conversion volume does not provide an ideal basis for effective optimization approaches.
This can be a challenge, especially for small and medium-sized companies or companies with new products. They want to increase the efficiency of their campaigns, but the conversion volume is either insufficient or highly variable.
In this blog post you will learn how you can use Softgoals to optimize campaigns with low or highly fluctuating conversion volumes and increase efficiency.
State-of-the-art in Google Ads campaigns: Value-Based Bidding (VBB) and tROAS bidding strategies
The leading method in Google Ads campaigns is so-called “Value-Based Bidding” (VBB) or tROAS bidding strategies. This involves giving the algorithm information about the value of a sale so that the bid is adjusted accordingly. Higher bids are made for expensive products, while lower bids are made for cheaper products. In this way, the budget should be used optimally to address high-quality users.
But what happens if the conversion volume is not enough, or if only one product with the same value is sold? At first glance, the idea of VBB may not seem helpful. However, there are ways you can benefit from it.
Consideration of soft goals and upstream conversions
Purchase decision processes often take a long time. The path from first contact to purchase involves multiple interactions with the brand or product. These interactions are called “soft goals” or “upstream conversions.” They provide information about the quality of a user.
Examples of such soft goals are:
- App downloads
- Lead forms
- Newsletter registration
- Page session duration
- Click depth
- Shopping cart
- Favorites list
- Steps in the checkout process
- and much more
Although these interactions before the actual purchase have no direct monetary value for the company, they do show the user’s strong interest in the product. Incorporating this information into your bid management makes it easier for the algorithm to target users who make these upstream conversions. It is important to assign different weights to the different soft goals so that the algorithm recognizes which upstream conversion is more likely to lead to the final conversion.
An analysis delivered the following results: A user puts a product on his favorites list. This event ends in a conversion 20% of the time. When a user adds products to the shopping cart, 60% of them are purchased. 75% of an app download ends in a conversion.
If these soft goals are to be integrated into the bidding, they should be given the following weighting:
- Favorites List: Average Conv Value*20%
- Cart: Average Conv Value*60%
- App Download: Average Conv Value*75%
- Coonversion: Actual conv. value
It is not always possible to establish clear connections between soft goals and conversions. In such cases, you can gradually optimize the weighting. It is advisable to reconsider the weighting after a test phase. To do this, you analyze the proportion of the total conversion values and ensure that the various conversions are in a balanced relationship to one another. If necessary, adjust the weights again. Make sure that conversion values are continuously updated without changing historically. It may also be necessary to adjust your bidding strategies.
Expanding data and opportunities for low-converting businesses
Taking these additional (micro) conversions into account expands the amount of data for the bidding strategy. Companies that have difficulty achieving the minimum conversion volume can create a stable database that the algorithm can use for optimization. By understanding that soft goals lead to conversion, the algorithm can target more users who achieve soft goals. The weights prioritize the different conversion types and the algorithm tries to achieve as many high-quality conversions as possible.
Restrictions:
This approach shows promise and is a great opportunity for many companies to take their campaigns to a higher level. However, there are two important points that are not yet fully developed and need to be considered.
The fictitious value for a soft goal cannot be adjusted dynamically. This means that it assumes an average conversion value and the values of the soft goals remain unchanged. A feature to dynamically adjust these values may be introduced in the future.
Additionally, this approach requires a certain level of control relinquishment. tCPA strategies are no longer applicable, and tROAS no longer refers only to actual sales, but to the conversion set, including soft goals with no direct monetary value. However, if we talk about low conversion volume campaigns, this was hardly possible before.
Conclusion:
As already mentioned, this approach is particularly suitable for campaigns with low conversion volumes. Data enrichment helps target qualified users and steer the campaign in the right direction. While complete control over CPAs or actual ROAS is limited, with careful monitoring and campaign management this can also be ensured. Numerous campaign tests have already shown very positive results.
