What determines whether a life sciences advertising campaign is successful? This is a question that has been plaguing marketers for years. It has not always been easy to quantify, but as the field of marketing analytics has advanced, it is easier to connect campaigns to market share gains, HCP prescribing, patient behavior, and ROI.
In order to run a successful ad campaign, marketers need to have a clear measurement and optimization framework in place prior to campaign launch. With the right plan, campaigns can start strong and continue to improve over time. By evaluating audience quality, understanding the impact of ad costs and timing, and using the optimization strategies outlined below, marketers can improve media efficiency by an average of 25%.
Monitoring and Assessing Audience Quality
Once a campaign is in motion, monitoring the quality of the audience reached by specific publishers and tactics on the plan will provide clear and timely data about campaign performance. Advertising placements should be evaluated in order to understand how effectively they are reaching HCPs, diagnosed patients, those patients treating in category, and other audience definitions as leading key performance indicators (KPIs).
Assessing the root causes behind variations in audience quality will help to further understand ad performance. Some areas of consideration could include ad frequency relative to unique audience reach and competitive performance relative to health data targets.
Moreover, it is important to gauge the success of new tactics by holding them to the same standards and comparing them to industry benchmarks. Benchmark data compares campaign performance within similar size conditions and publisher types. By measuring the performance of the campaign against competitive campaigns and publishers, marketers are better able to see where their publishers may fall short and find ways to improve their performance.
It’s important to compare similar campaigns and tactics. For example, comparing an endemic healthcare publisher to a programmatic partner may show dramatic differences in audience quality. The programmatic partner may show a lower audience quality rate but can deliver efficient scale. Similarly, an endemic publisher may reach an audience actively researching health conditions, but that inventory can be scarce and expensive. Likewise, comparing campaigns with dissimilar condition categories and incidence rates will also yield inaccurate results.
Optimizing Ad Placements
Once the causes of the campaign results are better understood, and how they compare to industry benchmarks, marketers can find ways to optimize the campaign. Marketers can approach optimization in several ways, but audience quality data is typically the key lever to use when making campaign adjustments because the data is available shortly after launch and marketers can make faster decisions based on those metrics.
Understanding ad costs can factor greatly into optimization strategies. By layering in data such as cost per qualified audience reached, marketers can understand how much they are spending to reach qualified patients or HCPs through each partner. If the cost is high, but the tactic is reaching a highly qualified audience, then continuing to advertise with that partner could make sense. On the other hand, it may also be worth continuing with a partner that is reaching a less qualified audience if the cost is low enough to tolerate some media waste.
Most marketers work with their current media partners to assess ways to drive up performance. Many partners are willing to help advertisers reallocate spend within their platforms to ensure that the campaign will be as successful as possible.
Audience quality, together with cost, informs optimization strategies as well as identifies where to increase investments in tactics that are working and away from those that are not. This is what ultimately makes the most impact. Conversion metrics are an important way to measure the campaign’s impact on health behavior, but they typically come in the later phases of campaign measurement and can be less useful for making timely optimization decisions.
Timing Is Everything
Timing ad optimizations can be tricky. On one hand, making changes quickly can move the campaign in a more positive direction if its performance is poor. On the other hand, not giving a campaign enough time to work before making optimizations can be a pitfall for marketers. As with all ad campaigns, some anomalies can be in the data in any particular week or day. For this reason, it’s imperative to understand the impact of trends you are seeing in the data over periods of time rather than at one set point in time. Marketers may also make an optimization and not give the ad enough time to run before making further changes to the campaign.
Partners should also be continuously evaluated, even those that appear to be successful. As an example, if a partner is on the top end of targeting effectiveness or efficiency, it is still important to ensure performance is not dipping week over week. It is also helpful to understand how publishers and tactics were performing prior to optimizations in order to make a comparison between the two.
In order to learn from past campaigns, it’s important to evaluate how optimizations have improved performance over time. Marketers can then take this knowledge and use it to refine an existing campaign or leverage the data to improve their annual media plans.
Rigorous, state-of-the-art analytics tied to health data are crucial to a comprehensive measurement plan. Don’t be led astray by proxy metrics such as click-through rate.
The best life sciences marketers know how to connect ad exposure to real script impact and are able to tease out marketing’s impact compared to a control group. Continuously validating the success of optimizations will lead to more efficient and better targeted media campaigns to reach patients and HCPs.