Where Engagement On Facebook And Google Diverge

Here's a comparison of engagement patterns on Facebook and Google from Dr. Siddharth Shah, senior director of business analytics at Efficient Frontier.

Pop quiz: One of these charts represents the query volume for “back to school” on Google and the other represents the number of unique users commenting on several brand fan pages that are actively promoting back-to school marketing campaigns on Facebook. Can you tell which one is which?

The answer to the question is that A represents the total number of daily active users on Facebook of back-to-school brands, and B represents query volume on Google for terms related to “back to school.” At first glance we could not tell the difference, right?

Both graphs show a similar trend: a relatively stable pattern until early July when both show a sharp increase in activity. The only difference is in the magnitude; B shows a much sharper increase than A.

Social Signals Versus Search Signals

The currently-held notion is that search and social signals are fundamentally different. Search is a more direct-intent-based signal that reflects a shopper late in the sales cycle, while data from Facebook represents someone earlier in the funnel. However, the above data suggests that both signals are very similar. So should we treat Search and brand engagement signals in the same way?

Yes and no. Yes as the above example shows that consumers’ engagement behavior on Facebook and intent behavior on Google follow a very similar temporal pattern. No because they fundamentally represent different behavioral aspects.

Facebook comment data indicates how many and how frequently users are engaging with brands on their ffan pages, while Google query data indicates what questions, products or services need immediate answers. The similarity in time trends means that both of these behaviors are taking place simultaneously albeit in different channels.

Leveraging The Cross-Channel Effect

The data reveals several interesting trends in consumer behavior. First, while the context of consumers on Facebook and Google is different, they are often pursuing a similar end goal. In this case, they are
looking to buy back-to-school related items. Second, these activities are taking place simultaneously. Finally, they are often switching back and forth between the two channels before making the final purchasing decision.
Advertisers would do well to consider these insights when formulating their marketing campaigns. They must engage and actively manage the perception of their brands within the Facebook environments. Simultaneously they must also have a substantial presence on the search engines to guide consumers during the intent stage of the sales funnel.

There is a significant cross-channel effect when it comes to direct marketing — between 40 to 50 percent of conversions that begin with a social ad convert on a different channel.

The above trends also tell us that there is a significant cross-channel effect in the research phase of thepurchase process (impressions are the early stage metric in paid Search while comments on brand fanpages are the Facebook analog).

Advertisers must also have a cross-channel tracking and optimizationsolution in place to understand the nature of their traffic and answer the hard questions, such as what isthe effect of the posts they (the advertisers) make on the paid Search, organic and direct website traffic.

Thus, as chief marketing officers look to maximize the return on investment of their social media efforts, they must revisit all their assumptions. They must plan their marketing campaigns holistically considering all the cross-channeleffects. A siloed view of channel performance would only give a narrow understanding of consumer behavior and could lead to decisions that would leave money on the table.

Guest writer Dr. Siddharth Shah is senior director of business analytics at Efficient Frontier. Sara Miller, business analyst at Context Optional, helped compile the data.