Data drives decision making, and in 2015 this has never been more true. As more innovative marketing tactics and technology come to fruition, a more complex way to track user experience and user behavior has become increasingly necessary. Google has begun to address the need for enhanced user behavioral analysis through the introduction of two new reports to its analytics suite. The new features include an “Active Users” report, as well as a “Cohort Analysis” report. Cohort Analysis is a way to look at groups of users over time in order to assess how and why their behaviors differ.
Discovering Micro Trends
Cohort Analysis will be a quintessential assessment tool moving forward as it can help drill down to pinpoint the differences in acquisition, engagement, retention, and response to marketing efforts.
This report tracks a user’s behavior from their “acquisition date,” with acquisition date interpreted as their first interaction with your website. From there you are able to measure trends in retention over periods of time, as well as the different interactions a user has with your brand over a day, week, month, etc. This can help to uncover how frequently users are returning to your websites and the reason why as it relates to your advertisements and marketing efforts.
For a display campaign running different creative executions you’d use this report to analyze behavioral trends amongst users once they’ve arrived on your site via a display ad.
This report will allow you to view the points at which users who saw your creative re-engage with your website, and then segment them based upon patterns you discover. If you observe a trend of users who saw the branded creative on a Monday, and then return to your website on Thursday but typically never return again, this is an actionable insight. You could use this insight to identify the best points for re-engagement, or dive deeper into why site visitors who view this execution only return to your site once. Could it be the content or user experience is not optimized to their needs? These are all questions that Cohort Analysis will help you better understand and hopefully answer.
Likewise, if you observe that typically users who viewed your unbranded creative on a Monday, returned Tuesday, and then came back to convert on Friday, you can use this insight to improve the efficiency of your campaign. Perhaps you allocate more impressions toward unbranded executions due to them leading to more conversions. Or maybe your display rotations on Mondays skew more toward unbranded because you know that users who’ve viewed ads on a Monday typically convert the following Friday. These more advanced optimizations are all possibilities through micro trends that are more evident through Cohort Analysis. The options are limitless; there will soon be more ways to segment your users and their behavior than there is time in the day for the assessment of them.
Engaging Users vs. Retaining Users
Engagement metrics are transitioning toward a model that is much deeper than bounce rate, time on site, and pages per session. Micro trends observed can help you hyper optimize your campaigns, but another great feature of the Cohort Analysis report is the enhanced understanding available of user retention.
Getting users to your site at efficient rates is a staple of any good paid marketing campaign. The next measure of campaign efficiency is that those users who you’ve efficiently driven to your site are engaging with your content.
The evolution of behavioral analysis will soon allow marketers to see that a one-time engaged visitor is not necessarily a success. Brands want loyalists, and must begin to devote more time to measuring the affinity of those who become aware of their brand through marketing efforts. It ultimately will be more productive to market to users who frequent your site once a week, or once a month, over those that are engaged for a single visit.
The retention aspect of Cohort Analysis will provide a day by day, week by week, or month by month view of when users are disengaging from your website. This information is critical to knowing how to address the ebbs and flows of visitors entering and exiting your brand site.
Enhanced Paid Optimizations
From a Paid Search perspective, Cohort Analysis will be particularly beneficial in optimization and persona creation within the campaigns. We will be able to track behaviors on both a monthly and weekly basis and identify patterns in search behavior. This will allow us to identify the relationships between the content and the behavior for both branded and unbranded campaigns. Many marketing campaigns are deemed successful based upon topline metrics that do not tell the story of what a user does on site. A CTR of 3% may give the impression of a success, however these new additions currently in BETA brought to you by Google offer an opportunity to dive deeper.
Search behavior is ultimately different in terms of branded vs. unbranded search.
For branded terms the user is pre-qualified as they’re either already a customer or at the very least familiar with the brand. Unbranded is a bit more open ended and allows the advertiser to win over the user with key actionable insights and unique value propositions. Using Cohort Analysis, we would be able to develop a strategy not only based on user retention for time of day or day of week, but also use our previous knowledge of user behavior based on the type of campaign for another layer of granularity within the analysis.
Cohort Analysis will ultimately help the search campaigns within the following areas:
– View specific acquisition dates to measure whether receiving a click on a certain day promotes more continuous engagement when compared to other days.
– Optimize more thoroughly on a CTR and CPC basis, especially if there’s data that shows returning visits before converting (which will ultimately skew the goals of the account).
- If data shows that a user engages with the site 3 times before converting at an average CPC of $1.25, this analysis would help evaluate what an appropriate goal would be in terms of CPC/CTR as such. Would it be more beneficial to make the goal $3.75 instead? Maybe. It depends on the profitability of that user.
– Measure CPCs based upon user retention.
- If we’re able to establish that certain keywords result in continued engagements over longer periods of time, then we’ll be able to provide a different baseline in terms of what is acceptable to pay per click for that term.
- If “keyword A” has a CPC of $5 and once a user visits the site they never visit again, is that better than paying $17 for “keyword B” if we know that this user typically returns 4 times from other unpaid mediums?
– Observe the quickest paths to conversion based upon multiple engagements.
- If we were to A/B test landing pages on any given campaign, we could identify with this new Beta if one page garnishes a quicker conversion than another and how content assists with conversion funnel. This will also allow us to bid differently, reallocate budgets effectively, and even potentially rework messaging to accommodate these changes in the campaign.
Most importantly, this new analysis tool will allow for a more general understanding of the HCP and consumer search habits, and opens the door for more proactive, intuitive account structure in the future. The engaged user is of the utmost importance to all brands, and how we measure engagement is beginning to evolve across display, paid and organic search. A much more robust way of conducting behavioral analysis of website visitors is coming soon, and layering in this data with current campaigns is the next step in brands separating themselves from the competition.