Use predictive modeling to give your campaigns an edge over competitors
The Search Engine Marketing Professional Organization’s 2015 State of Search Industry Report provides several valuable insights derived from both marketer and agency practices over the past year. The most useful conclusions center on three forms of advertising: paid search, social media, and display media.
In general, marketers were more confident in managing paid search advertising efforts in-house, whereas social media advertising was a responsibility better left to outside agencies. This shows how marketers are often more comfortable managing “tried-and-true” tactics as opposed to navigating the more complex and fast-paced landscape of social media advertising.
Throughout the report, a continuous theme emerges regarding success in measuring return on investment. For a paid search campaign, it’s a relatively easy task because the data and tools used to properly interpret those data are typically included with the management platform, such as Google AdWords. Social media campaigns require a bit more diligence and expertise. Display media advertising is an animal of its own: In those campaigns, the preparation period is as important as its performance and results.
Across the board, but most particularly for display media, tracking and predictive modeling are the keys to both measuring and elevating ROI for these campaigns. While these duties are much better tackled on the agency side, the most common obstacle to successful ROI comes from marketers themselves.
The Pitfalls of Benchmarks and Predictive Modeling
Oftentimes, marketers consulting an agency lack practices for benchmarking, which is crucial for measuring the influence of a display media campaign against the overarching goals. Without internally derived or industry-mandated benchmarks, such as DoubleClick or AdRoll, it’s impossible to understand how the investment in a campaign has performed.
Similar to benchmarking, predictive modeling is another critical step for determining the ROI of a display media campaign because it allows for the projection of conversions or sales prior to launch.
However, predictive modeling often requires a strong in-house analytics team to effectively and accurately report on ROI to marketers. It also requires a strong analytics team member to dually interpret the marketer’s goals and the consumer journey to the product or service. This helps to illustrate the most valuable touchpoints between campaign tactics and conversion.
Our company, for example, takes both of these preparation processes into account each time we develop and plan any digitally based campaign, especially when utilizing display media tactics. As a result of the dramatic changes to regulations and rules surrounding the healthcare industry, one of our current clients, Affinity Health Plan, a New York-based health insurance provider, didn’t have a firm grasp on its ROI at the time it engaged our team.
To effectively develop our strategy, we utilized several sources of industry standards in order to get an accurate picture of the current state of healthcare acquisition. Taking these standards and other insights into account, our analytics team developed a predictive model to forecast the results of a campaign composed of integrated tactics. This step not only allowed our agency to accurately set expectations for the client’s open enrollment healthcare signup, but it also leveraged our case in negotiating higher budgets from the client in order to achieve their desired customer acquisition goals.
By contrast, another client, National September 11 Memorial & Museum, was able to provide historical data outlining its ROI year-over-year prior to approaching us. Again, our process was to take this raw data to our analytics team to shape it into an intelligible model that would be adaptable in real time and break out elements of ROI, such cost-per-acquisition.
With these simple yet diligent preparatory improvements, we increased the ROI for the Sept. 11 memorial to a mark higher than it had ever achieved previously, and in just a few months’ time.
Mapping Measurements for ROI
If you’re looking for ways to measure and improve ROI, I recommend the following:
- Track each and every tactic in a campaign. There’s nothing to report on or measure if you’re not tracking before, during, and after a campaign. Weigh on the side of caution and track every tactic involved.
- Prepare and predict results prior to a campaign. The results from a simple predictive model not only can set expectations aptly, but they also can better inform budgets when shared with clients.
- Avoid nonsense metrics. If the metric isn’t directly related to customer acquisition or conversion, it’s really not necessary. Take, for example, display banner impressions or Facebook likes. These metrics may say something about reach but not conversion.
- Continue testing. Even if a client is happy with the improvements to ROI, don’t take that as a cue to stop testing ways for further improvements. Even when this means a period of fluctuation, the client must hang on for the ride.
- Trust your predictions. The time and effort put into predictive modeling should never go to waste. The predictions should always be trusted and shared with the client — even if the results are not so great.
This last tip is the most important. These predictions take time and effort and are supported by research and proven equations. Therefore, these measures should be the base upon which you start your campaign.
Any savvy marketer or agency can pull a fancy or attractive metric out of thin air (or elsewhere) just to ease the client, but what will this mean for the results of the campaign? More important, what will this mean for a company’s credibility and future business when the results are wildly off-base from inaccurate predictions?
Of all the insights and predictions that arise from SEMPO’s report, one thing stands out most clearly: Without a solid plan for tracking and improving ROI, any internet marketing campaign is likely to be left in the dust.