The 4 Strategic Phases Of Lean Display Advertising
Professional stand-up comedians are known to practice their routines with smaller audiences in preparation for their big shows and HBO specials. They do this in order to find out what works and what doesn’t and to hone all the elements of their routine: timing, delivery, wording and so on. That way, when they hit the big […]
Professional stand-up comedians are known to practice their routines with smaller audiences in preparation for their big shows and HBO specials. They do this in order to find out what works and what doesn’t and to hone all the elements of their routine: timing, delivery, wording and so on. That way, when they hit the big stage, they have the confidence that they are delivering an optimized routine.
This is not unlike the “lean startup” approach described by Eric Ries in his book, The Lean Startup. In it, he advocates the “build-measure-learn” cycle, which puts experimentation, measurement, and learning at the heart of the organization — the goal being to figure out how customers respond to a product before dedicating larger resources toward its development.
The reason why this approach is popular among comedians and start-ups alike? It’s far less risky to go big when you know what works based on prior first-hand data.
We will now discuss a similar framework for approaching display advertising from a “lean” marketing mindset. By using real-time bidding (RTB) as an efficient means to experiment with campaigns and gain insights prior to scaling with direct buys, marketers can figure out the most successful elements of a campaign prior to allocating larger budgets.
Let’s dive deeper into the four strategic phases of this lean display advertising approach:
Phase 1 – Build Your Test Campaigns
“Never stop testing, and your advertising will never stop improving.”
The goal of the first phase is to create various campaigns aimed at a variety of potential audiences to see how each responds. This is where baseline data is gathered for further analysis. By creating a series of well-crafted test campaigns (i.e., experiments), it’s easier to learn from them in the analysis phase.
There are several keys to the testing phase, the primary ones being:
- An ample variety of ads
In terms of tracking, you want to properly measure your campaigns. Measurement is extremely important when it comes to analyzing and optimizing your campaigns, which are the keys to extracting the highest value from them. It also sets the stage for intelligently scaling up your campaigns in the future.
To do this effectively, make sure that you are tracking as many variables as you can. At the very minimum, you will want to track conversions or desired actions (preferably with an associated value). In an ideal scenario, you’ll want to track not only conversions and revenue, but the impact of campaigns on brand searches, view-through conversions, bounce rate, landing page engagement, and even lifetime value.
With respect to segmentation, this simply means properly defining the scope of each campaign. You can’t assume that audiences in different regions, age groups, or income levels will respond to the same ad, on the same website, in the same way. This is why segmentation is important: control the variables to make for better data.
Lastly, having a wide variety of ads within your campaigns is the key to enabling good performance comparisons. If you create many nicely segmented campaigns, but they all use the same standard banner ads, you miss the opportunity to split-test the impact of multiple ads with each of those audiences. Having variety enables you to increase the amount you learn from your campaigns.
Phase 2 – Analyze The Data
The second phase is where you measure, analyze, and learn from the data that was collected in the first phase. In order to extract insights from your campaigns, digging into the data on different levels is crucial.
Some key areas to analyze in this phase are the engagement and impact of:
- Your ads on a placement level, site level, and in aggregate
- Visitors from specific regions, on certain devices, at certain times, etc.
- Specific websites and placements in general
- Specific audiences in general
When analyzing the data, you should be able to discover which combination of campaign elements and audience factors show the most potential, and which need to be pruned in the optimization phase.
Phase 3 – Optimize Your Campaigns
Once a proper set of data has been collected and analyzed, it’s time to cut the weak elements from your campaigns and allocate more resources to the elements that are working. This is the goal of the optimization phase: to improve your campaigns by using the insights learned from the previous phase and applying them in a meaningful way.
One example of how to improve a campaign is to disable or prune certain elements — such as ads, placements, or sites — if they are found to be under-performing. This allows the elements that perform well to receive a larger share of resources, thereby improving overall campaign effectiveness.
Another way of allocating more resources to elements and campaigns that work is by increasing budgets, bid prices, and frequency caps (incrementally) in order to drive more volume.
Optimization should really be viewed as a continual process of learning from the data and improving campaigns over time. Once you have optimized campaigns on your hands, the next logical step is to scale them up.
Phase 4 – Scale Your Winners
“What enables the wise sovereign and the good general to strike and conquer, and achieve things beyond the reach of ordinary men, is foreknowledge.”
It is only after you have acquired real-world data (foreknowledge) that the time becomes right to invest the effort and dollars into scaling your campaigns with direct media buys. Here is where the complementary nature of RTB and direct buys reveal themselves to the advertiser.
We already know that buying display ads with real-time bidding (RTB) is more efficient, so your initial testing and optimization are best conducted on agile platforms that enable you to exploit the benefits of RTB. Armed with your insights, you can now confidently approach publishers to reserve more inventory.
Imagine the following conversation with an ad sales team, where you say:
“Your inventory is performing well for us via RTB. We are paying around $2.50 eCPM, but we would be willing to pay a slightly higher rate, or commit to a certain order size, to reserve more inventory directly.”
The publisher’s ad sales team might then say:
“We’ve only been putting a fraction of our inventory on RTB, but for a monthly commitment of $X dollars at $Y CPM, we could probably guarantee Z million impressions per month for you.”
Savvy publishers are already well aware that RTB is great channel for prospecting direct sales. If a specific website or publisher is performing well for an advertiser through RTB exchanges, there’s a good chance they want more of the same inventory. Knowing the inherent volatility in RTB volumes, approaching publishers for direct buys (after testing, of course) only makes sense.
A note of caution: this may not always be a practical course of action. While exploring direct buys, you may notice that CPM rates exceed a level that is feasible for reaching your performance goals — so always keep your key metrics in mind.
In any case, buying display ads via RTB is an ideal way to gain knowledge and test out the performance of specific publishers and audiences, without blindly committing thousands of dollars on high-CPM direct buys. Once you’ve discovered valuable placements, you can then approach the publisher directly to reserve your own inventory on a guaranteed basis.
This strategy enables advertisers to build impactful display ad campaigns, all while minimizing risk and wasted resources, and maximizing the amount of learning in the process.
Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.
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