In this article, we will touch on the current environment surrounding Internet advertising and explain not only the positive reasons for "getting better results" but also the negative reasons why you should start using offline conversions as soon as possible, even if you don't see immediate results.
Here, the definitions of "online conversion" and "offline conversion" are as follows.
If lead acquisition is considered an "online conversion," sales negotiation data managed by SFA (sales force automation) is defined as an "offline conversion."
"Online conversion":
Conversion that media such as Google Ads can track using online information such as cookies and tags.
"Offline conversion":
Conversion that media such as Google Ads chinese overseas europe phone number list can only track by importing 1st party data from the advertiser company.
*1st Party Data: User information collected on a company's website. Companies themselves can freely manage and control it.
*This definition is used because the definition of offline CV may differ depending on each environment.
If online conversions are used to generate leads, delivering ads based only on online conversions means you won't know whether the ads are actually leading to sales, and you'll end up incurring a lot of costs on ads that aren't leading to sales.
To avoid this, it is important to take into account offline conversions after lead acquisition when managing advertising . By importing offline conversions (manually or via API integration) into advertising media such as Google Ads, non-online behavior can be measured and machine learning can be applied based on that information, improving the accuracy of automated bidding predictions and targeting.
However, just because you introduce offline CV does not mean you will immediately see improved results.
>>Learn more about advertising using offline conversions<<
Why it is difficult to recommend the introduction of offline conversions based solely on results
Although it is better to introduce offline conversion, the reality is that it is not easy to achieve visible improvements in results . The biggest bottleneck is conversion volume.
Naturally, offline conversions are smaller than online conversions. For example, if you try to optimize offline conversions such as sales negotiations, the volume of sales negotiations will be at most 10% of online conversions. In some cases, the number of conversions (sales opportunities) accumulated in a campaign in a month may be in the single digits, and even if machine learning is optimized for sales opportunities, it may not work well and results may deteriorate.
In that case, Google often recommends using ROAS. This is a method of weighting offline conversions (for example, the value of one online conversion is 1, and the value of one business opportunity is 10) and using tROAS . In theory, this seems like it would improve results somewhat because it would learn more about business opportunities than if you were to use only online conversions, but in fact this is not as straightforward as it sounds (though it can work).
The reason for this is that humans have context that cannot be digitized or interpreted by machines, so it is thought that personal operation may result in higher accuracy.
For example, automated bidding does not understand the meaning of keywords themselves and make bids; it simply statistically evaluates the contribution of a specified objective variable based on past results and determines whether or not to make a bid.
"AI" sounds smart, but AI (machine) is different from humans and can only make statistical judgments based on the data it has. Therefore, even if you use ROAS, it does not necessarily mean that offline conversions will be successful.
However, there are other effective ways to make offline conversions successful: creating a conversion point a little earlier .
For example, if you define conversion points as "first visit rather than sales negotiation" or "valid lead rather than first visit," you can increase the volume of offline conversions, which can lead to improved optimization and results.
In this case , a valid lead refers to a lead acquired through online conversions, excluding "individuals who are not target customers," "your company's competitors," or "leads with false information such as email addresses."
With valid leads, you can often get about half of the online conversions, and you can guarantee a sufficient number of conversions for machine learning to work. However, there are many hurdles to overcome when actually trying to do this (e.g. "SFA does not flag anything other than sales negotiations"), and in most cases it is not easy to implement.
