Reframing Digital Metrics to Increase Confidence as a Brand Building Medium
Digital media can have a significant and efficient impact to brand building; consider these metrics for better indicators of success.
Digital media can have a significant and efficient impact to brand building; consider these metrics for better indicators of success.
Digital media has earned a reputation for delivering immediate and significant returns on investment, supported by precise, real-time tracking of consumer interactions with brands. Sectors that rely heavily on digital transactions to drive their business, such as travel, retail, and finance, can predict outcomes with reasonable accuracy and therefore, are able to scale initiatives with confidence.
While the ability to track the impact of every variable to the nth degree and maximise returns has led to growth in direct-response advertising spends, digital has had limited success in gaining traction as a brand-building medium.
In fact, while 63 percent of total ad spending is aimed at building brands and 37 percent aimed at eliciting an immediate response, nearly the opposite is true of digital ad spending, with 77 percent considered direct response spending and only 23 percent used for branding. Is this simply a reflection of each medium’s ability to contribute to each marketing objective? No. We know that digital media can make significant and efficient contributions to brand-building initiatives. Dozens of published cases have demonstrated digital’s ability to increase awareness, perception, preference, and purchase intent, with efficiency.
Unfortunately, many factors work against digital media; notably, a lack of understanding about how to measure contributions to brand-building goals. While the ideal solution is to measure a change in cognitive metrics, employing a partner like Millward Brown, many marketers are reluctant to increase their ‘non-working’ investment. Instead, some default to familiar metrics, such as reach, frequency, and TRPs (target rating point) as a proxy for success and basis for comparison across channels. For decades, these metrics have informed allocations across television day parts and across various offline channels. However, when asked to provide these metrics for digital initiatives, agencies cringe. Why?
Most digital media plans are designed to target explicit behaviours that are more indicative (than demographics) of a potential need or interest. With better indicators of interest available, demographics lose their usefulness, and worse, they shortchange the plan. For example, if a marketer’s infant formula message is delivered within infant nutrition content, and a planning tool indicates that W25-49 make up 70 percent of the audience reached, then what percent of the delivered impressions are ‘targeted’? Is an involved father or a 24-year-old mother less valuable than a W25-49? No, but neither would be represented in the R/F metric.
Even if R/F runs could be adjusted to reflect a behavioural target, efficient delivery alone is not strongly correlated with brand building. For example, a highly efficient approach, built specifically to maximise R/F, might leverage remnant inventory across thousands of sites; delivering billions of impressions for relatively little cost. However, in order to achieve this extreme efficiency, frequency building, relevant context, a proactive consumer mindset, and other factors that are tightly linked with branding success are traded off.
Again, ideally, if a marketer wants to build the brand via a multi-channel plan, changes in cognitive metrics should be tracked via a campaign impact study (e.g., Millward Brown) and attributed back to all influencing variables and combinations of them, so that future plans can replicate successes, eliminate weaknesses, and expand to test new possibilities. However, in the absence of this, I suggest looking at a variety of readily available metrics, across and within all channels, to aid conversation about how each element contributes to each marketing objective and to gauge relative success:
First, provide R/F/TRPs for the desired demographic cut if requested; a familiar and comfortable place from which to start the conversation. Supplement this with projected delivery against a behavioural target. Explain the methodology (e.g., 100 percent of gross impressions reach people reading about infant formula, so 100 percent are ‘targeted’ impressions). Augment with other metrics that are important to achieving success, such as frequency distribution and, if a complex message, a projection of time spent. Calculate cost-per-:15 (for ease of comparison with television) by dividing the program cost by the sum of all projected time spent (x 15), including:
Remember to give television or other media credit for additional time spent as well. We’ve historically given non-digital media credit for 100 percent of visits that could not be tracked back to our display ads; assigning more credit than due. Still, digital media has delivered a more efficient cost-per-time spent than offline media. Last, consider the context in which the media is delivered and the mindset in which the audience is reached. In total, you’ll have half a dozen highly influential metrics, which can be scored, blended, and weighted to give a more accurate projection of future performance.
There are caveats to consider, as with all metrics, but this approach represents significant progress from traditional evaluation metrics. When faced with requests for flawed, incomplete, and outmoded metrics, such as R/F/TRPs, take the opportunity to shift attention toward a new set of metrics that are not only better indicators of success, but are also applicable across a broad set of media. By using familiar concepts and language, you will be able to alleviate some of the trepidation associated with new media and will hopefully help marketers to begin harnessing the power of digital media to build their brands.