One of my favorite aspects of SMX Advanced is the guarantee of emerging with a list of new tests to try out, along with pointers given by the industry’s top experts. SMX Advanced 2017 was no exception!
Maximizing Performance With AdWords Campaign Drafts And Experiments
Michael Elkins’ session, “Maximizing Performance With AdWords Campaign Drafts And Experiments,” contributed to this list rather quickly. Elkins, who is director of paid search at Red Ventures, spoke about leveraging campaign performance with Google Campaign Experiments & Drafts, a somewhat “new” replacement for AdWords Campaign Experiments (ACE).
For a quick overview, Google’s testing capabilities began modestly with indefinite ad rotation, which evolved into ACE in 2014, and then more recently, New Campaign Drafts — a playground that offers plenty of new opportunities to improve our campaigns, including tests for ad copies, extensions, bid strategies, and of course, ad rotations. Elkins offers the following tips for leveraging New Campaign Drafts, starting with implementation:
- Define hypothesis to test.
- Identify primary KPI to determine success.
- Apply only one variable to keep results clean.
Pro tips:
- Append the original campaign name with (1) a test descriptor and (2) the date the experiment launched; this will make it easier to track results.
- Schedule the experiment to end one week after you expect the test to gain significance.
- Toggle split based on how much risk you want to take (50 percent-50 percent neutral split — no risk, different percentages imply more risks).
- Use the performance comparison tool to quickly identify variances, and decide when the experiment has reached significance.
- When deciding between updating your original campaign and converting to a new campaign, ask yourself, “Did my experiment involve a learning phase?”
- Yes? Convert to a new campaign.
- No? Update your original campaign.
Elkins covers three case studies where he tests New Campaign Drafts hypotheses, which you can find in his slides.
Overall, it’s worth trying New Campaign Drafts for yourself, as it opens new testing scenarios that were impossible in the past. The setup is straightforward and intuitive, and the split statistics make it easy to quickly identify significant changes in the relevant KPIs. Yet because AdWords basically duplicates the campaign for the test, there are a couple of things that weren’t addressed in the session and are worth knowing. For example, if you use third-party tracking on the keyword level, you should remember to differentiate those in draft from the original; otherwise one will end up having duplicate tracking.
It is also important to ensure settings and bidding are consistent or untouched during the time of the test — if these are maintained in just one of the two campaigns, results will be inconclusive.
Additionally, it is worth mentioning that New Campaign Drafts is not yet applicable toward Shopping, which in this case we’d need a scheduled A/B test. If you are working with Shopping campaigns, I covered how to implement A/B testing at SMX London, which you can find here.
Taking Audience Targeting to the Next Level
I found one other session incredibly dynamic, which was “Taking Audience Targeting to the Next Level,” presented by David Szetela, Andy Taylor and Michelle Morgan. It’s obvious that “target audience” is a building block all campaign managers must take the time to invest in, and at first glance it may seem like low-hanging fruit — but this session introduced some cream-of-the-crop techniques that marry targeting options with multiple data sources, ultimately maximizing ROI in campaigns and proving audience targeting can reach the highest degree of complexity.
David Szetela, founder and CEO of FMB Media, gave a detailed overview of all types of advanced retargeting options for Google Display Network. GDN is one of the most valuable channels due to its expansive reach, versatility in ad format and numerous targeting capabilities. Check out his slides to find his tips for each targeting capability:
I was particularly intrigued by the presentation by Andy Taylor, Merkle’s associate director of research, about a new(ish) AdWords feature he’s been tinkering around with: Customer Match. I’m sure you were all jumping out of your seats when this came out last year — we definitely were, so naturally we were all very eager to hear his results.
Taylor found that despite Customer Match yielding less than 5 percent of clicks, returns on average double the conversion rate at one-third the cost for Google PLA. Ratios like these never last, so now is a good time to jump into the game if you aren’t already playing. Despite its return, one caveat to Customer Match is that Google experiences a few blips when matching emails with searchers. Match rate of Customer Match varies a lot depending on email provider (with Gmail having a 90 percent match), but also depending on demographics. Younger people frequent Gmail, so if you plan to target that demographic, Customer Match will deliver a more extensive list.
Aside from a small reach, I think that Customer Match is an option that has yet to be explored deeply. I found it especially interesting to hear how to best utilize this type of audience, whether it is for upselling or cross-selling in a separate campaign to test incremental value of remarketing. Taylor mentioned that Customer Match is a small batch that packs a punch. Despite small reach, it is very effective for testing, as one could set up a test and control group in the frame of the Customer Match A/B test, turn off the ads in the test group and keep the ones in the control group running to determine whether remarketing has an impact on the order volume of the users.
Additionally, implementing RLSA and Customer Match can yield substantially higher CR and CTR. From our side at Crealytics, we also dove into this new feature and found that RLSA and Customer Match have proven to drive incremental revenues of 18 percent or more. If you’re interested in fine-tuning your remarketing strategy, we’ve made it easier to assess your status quo with this RLSA benchmark script.
The final leg of the session was on negative audiences, which are imperative for reaching only the audience that is relevant to your business. Our team enjoyed this presentation by Michelle Morgan, director of client services at Clix Marketing, who stressed that negative audiences are used for two purposes: to exclude unwanted users or to shape audiences and deliver a consistent message to each list.
Unwanted users include those who are already a lead, have poor engagement, are the wrong fit or fit a specific audience pattern. Luckily for you, Morgan paves the way to extract these lists, which can be found on her slides (below).
Regarding audience shaping in Display, Morgan advises to begin with layering, or prioritizing audiences by order of importance, and then to exclude down the hierarchy. Hierarchies can include audience size, highest value targets, sales funnel position or audience targeting strategy.
Ultimately, when using negative audiences to shape an audience, we are fundamentally enabling ourselves to deliver the right message to the right people. By shaping audience and buckling down on the appropriate audience, we can avoid inappropriate messaging, poor efficacy, and of course, wasting ad spend.
Overall, from this session, we got a taste of where audience targeting is heading as more information about users becomes available. This data will ultimately be integrated into new scenarios, such as the algorithmically informed bidding using audience data, or “people-based” data. One thing is sure: Audience targeting is becoming multi-faceted, multi-layered and convoluted, allowing infinite scenarios to cross data sets — and therefore many, many testing opportunities in the near future.
Some opinions expressed in this article may be those of a guest author and not necessarily Search Engine Land. Staff authors are listed here.
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Author: Andreas Reiffen
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