Data is everywhere. A few years ago, our meetings were about content and execution. Now, we find ourselves in more and more metric meetings and KPI crash sessions. The flood of information is fun, exciting, and an immense help in building world class campaigns. However, it is easy to lose sight of data fundamentals as our dashboards become prettier and the insights more granular.
Data is where pharmaceutical marketers are most likely to miss the proverbial forest for the trees. It’s also where confusion can arise between marketers and vendors. In the face of increasing amounts of digits heading our way, it is important to step back, breathe, and recall what data is, what it does for us, and its limitations.
Aggregate Data Only Goes So Far
Performance software, Google Analytics, is an incredible tool for gauging program performance but it’s important to note that our dashboards show aggregate data as opposed to target audience engagement. As an industry, we are not interested in the number of people who see our creative assets. We care that the right healthcare professionals do. Therefore, we have to take the metrics on our dashboards with a grain of salt.
In contrast, physician level data (PLD) tells us who in a target audience saw the content and engaged with it. These figures reflect the economic value of our actions. As a rule of thumb, PLD should show less activity than performance software general dashboards. The key difference is PLD reflects the activity of a specific group of users while most dashboards reflect all activities around an asset.
Different Systems See Different Activity
It is not only the debate that aggregate and PLD often differ, vendors and marketers will often disagree about the specific levels of activity. The source of disagreement has nothing to do with the two parties but rather with their respective data software.
Baked into every software package are a set of assumptions that shape the end results of the software. In the case of marketing performance software, this often takes the shape of defining ‘spurious activity,’ which tends to be caused by bots. Different software offerings have different parameters for filtering alleged non-human activity which then leads to different reported metrics. The marginal cases foster disagreement.
Confusion often arises when pharma marketers and vendors forget about software differences and become convinced that their figures are the single source of truth. After all, the data looks right to everyone involved.
To avoid confusion and suspicion, marketers and vendors ought to expect reasonable differences in reported data. If a marketer is seeing 100 activities and a vendor is reporting 1000 then there is cause for concern, but in general, the difference between 100 and 113 is most likely caused by differing assumptions. Ultimately, these differences are matters of trust rather than data.
The Value of Trust
Do you trust your vendors? When they report performance data, do you feel good about it? These questions are far more important than any software considerations. If you do not have trust in your partners, then all the dashboards in the world will not eliminate the feeling that something is up in the data.
The best way to eliminate suspicion is to invest in your marketer-vendor relationship by learning each other’s processes. At some level, you can never be 100% sure in a vendor’s reported data but if you understand the mechanics by which they collect and report data, you can come to trust in the process. It is only through trust that you can become comfortable with the inevitable variations in data. It is not about eliminating differences but about explaining and understanding them.
Expecting Trust in A Cookie-less World
Data is only increasing in importance yet marketers’ abilities to collect it are becoming more and more difficult. Trust in first party vendors will become paramount as third-party cookies are phased out. Pharmaceutical marketers ought to expect that in the years to come there will be a direct correlation between the strength of their relationship with a vendor and the perceived quality of their data. If data requires trust and trust requires a relationship, then ad spend decisions will need to rely = on trust as opposed to checked boxes on RFP responses.
Data allows us to better understand campaign performance but it’s critical to remember that it is not a silver bullet capable of alleviating suspicions and concerns. Two sources of data will never show identical results. It is incumbent upon pharmaceutical marketers and vendors to come to terms with the slight ambiguity of data. Fruitful relationships require trust and understanding. Slight differences will remain, but it is a win-win when vendors, marketers, and brands can come together and agree about general performance. Otherwise, there is nothing for us except endless meetings, acrimony, and headaches.
