Today, analytics is playing an ever-expanding role in developing marketing strategy as clients have become aware of the importance of data in guiding campaign decisions. Like the Paint by Numbers crafts of our childhood, marketers can use stats and data points to guide the creative marketing process, resulting in a more predictable end-product.
However, according to a recent Accenture study, the same brand managers who understand the importance of analytics tend to rely on gut instinct instead of logical recommendations, preferring to paint outside the lines rather than follow the data.
The reason for this departure is that analytics is still typically brought in on a project-by-project basis. While a team of expert analysts may provide insight on one particular channel or campaign, they do not have a panoramic view of the overarching strategy or history of the brand. The brand manager’s gut, on the other hand, has years of experience in overall performance, customer relations, and sales. This often results in a strategy that conforms to a “more of the same” mentality.
Within the Ogilvy Healthworld Marketing Analytics & Consulting team, we have found that insights and recommendations can be more impactful when done at a portfolio or enterprise level. For example, we had been performing analytics for a particular brand, observing that over time, the paid search costs were increasing for unbranded terms. Over the next year, we grew our analytics practice across this pharma company’s entire therapeutic department. When the data started to pour in, our analysis uncovered that two brands were competing against each another for the same unbranded terms, artificially driving the costs up. By taking an above-brand look at the data, we were able to identify an issue and resolve it in a way that benefited both brands and became a best practice across the therapeutic area.
While this example looks at a very specific issue, enterprise analytics has a number of strategic benefits:
- First, it sets a tone of accountability across brands, defining a standard of data quality that can be enforced in measurement and optimization. Not only does this ensure that different groups are using the same metrics to define success, but also it makes it easier to compare performance across brands and categories. Over time, this organized collection of data can serve as a starting point for performing more advanced modeling and predictive analytics.
- Second, strategic data collection and analyses can offer dramatic cost-savings as each brand does not have to finance its own projects and can anticipate a more organized array of reporting and analysis options.
- Third, enterprise-wide analytics enables across-the-board education in reporting and data. At this time, many brand managers are in the habit of glancing at a report for information, but not yet using it as a compass by which to navigate. With an enterprise-wide analytics presence, these brand managers are forced to embrace the numbers and start making more strategic brand recommendations. The result is a more consistent and strategic step forward in marketing growth and optimization.
Ultimately, analytics and reliance on predictive modeling are here to stay. As marketing partners, it is our responsibility to make our clients as agile as possible and ensure they have the most accurate information in their toolbox while making decisions. So the next time your clients go to the easel and begin painting their strategic plan, make sure they have numbers to guide their work of art.
CONTINUE THE CONVERSATION:
Questions? Comments? You can contact the author directly at email@example.com.
Please allow 24 hours for response.