How to Quantify Brand or Engagement Marketing With Paid Search

user-engagement-straight-aheadPaid search has long been the domain of direct response advertisers. The ability to track sales and signups back to individual ads and keywords, along with the ability to quickly change bids and creative messaging, makes search engine marketing (SEM) ideally suited for the direct response crowd.

But what about advertisers who aren’t directly selling anything online and are more interested in engaging users and building brand affinity? How do you focus your paid search efforts on bringing in a new audience, creating active users and exposing more of what your company does to increase true affinity?

Driving engagement through SEM isn’t as quantifiable, leaving many brand marketers with a choice:

  • Try to turn brand engagement into some form of direct response by measuring specific online actions, such as email signups, video views, and overall page views; or,
  • Throw money blindly into the ether without being able to truly measure specifically what’s working.

But there’s a third, and better, way to do this. By measuring the right set of metrics, you can create scenarios around users exposed to your different marketing efforts. This can allow you to hone in on effective strategies and tactics for your engagement marketing.

John Lee wrote a great piece on using personas to plan your SEM efforts. Think of engagement marketing as another scenario-based approach. In this case, your personas are your different users by channel.

Rather than focusing on qualitative details about these fictional users, leverage your analytics to describe them quantitatively. Some of the metrics you might use include:

  • Average time on site
  • Average page views
  • Number of repeat users
  • Number of active users (users who engage in a certain amount of activity on your site)
  • Probability of returning

By creating a “control” group of new users with no previous media exposure, prior to the paid search click that brought them there and no remarketing exposures afterward, you can set a baseline, like the following example:

control-group-metrics

After implementing your campaign, you can analyze the same metrics for your experiment group to see how impactful your campaigns are in driving active users who are more likely to return.

experiment-group-metrics

In this example, we can quantify a 26 percent increase in time on site, a 33 percent jump in page views per session and a 41 percent increase in a user’s probability of returning. With this data in hand, you can also plug in your cost data to come up with your cost per user and your cost per active user. From an engagement standpoint, this might be the equivalent of CPA.

Ideally, your SEM platform or digital marketing suite includes these metrics natively and ties them to campaigns, groups, ads, and keywords. Even better, some systems even have proprietary scoring metrics that create a value for each user based on their engagement. This allows you to optimize your search – or display or any other form of digital marketing, for that matter – based on user engagement. All of a sudden, brand or engagement marketing through paid search is very quantifiable.

This also opens the door to attribution by showing you how each channel works to draw in new and/or active users in much the same way attribution helps the direct response marketer make the right media mix decisions to increase overall sales.

This can provide valuable benefits for the direct response marketer as well. While sales and signups may be paramount, understanding what goes on "beyond the conversion" is immensely important. This kind of measurement can help any marketer correlate their efforts to offline sales and branding initiatives.

Direct response marketers have taken advantage of paid search’s unique ability to provide easy to measure efficiencies. There’s no reason brand marketers can’t do the same.