Michelle Eule discusses the relationship between click though rates and branding metrics March 2, 2010
Posted by Mark Blei in : Staff posts , trackbackMore than ever before, agencies are feeling pressure from advertisers to leverage the “real-time” metrics available in the digital environment to optimize their media plans on the fly. Certainly, one of the many benefits the medium offers is the myriad of metrics, many of which are available in real-time, and the ability to make quick changes to media delivery.
Typically, the metrics used for optimization online are behavioral in nature, such as click-through or interaction rates. While such metrics give an appropriate indication of performance for campaigns with direct response goals, they are not a good fit for campaigns that have longer-term branding goals. A study conducted by Dynamic Logic and DoubleClick in 2009 showed only a very weak positive relationship between click though rate and branding metrics. People may interact with ads for reasons unrelated to the brand message, such as interesting games. With such a weak correlation between the metrics, using behavioral data to optimize a branding campaign gives, at best, an incomplete picture of campaign performance and, at worst, a deceptive picture that can lead to bad decisions.
While branding metrics are certainly the ideal criteria to use for optimizing a branding campaign, there’s also a danger in making changes to the media delivery too early in a campaign. Branding metrics that are more attitudinal in nature, like Favorability and Purchase Intent, generally take time to develop. Our normative data show that multiple exposures to a campaign, which help reinforce a brand’s message, ultimately help build lower funnel brand metrics. Often, the best creative or site placement in a campaign doesn’t show its full impact until consumers have seen it multiple times. If an agency makes changes to site placements or creative rotation too early in a campaign, they may be moving impressions away from a critical campaign asset before giving it a chance to make an impact.
A client interesting in using sophisticated models for planning and optimization could leverage Dynamic Logic/Millward Brown’s marketing sciences group to build tools that incorporate survey-based branding data with normative information and external data sources. For clients that are looking for a simple and inexpensive solution that provides a quick read on branding metrics to make optimization decisions early in a campaign, Dynamic Logic recently launched a new solution called Adometer. The metrics used in Adometer are recall-based, such as brand recall or message recall, which are the building blocks to generating an attitudinal shift in consumer opinion. These recall-based metrics, meanwhile, aren’t as influenced by frequency levels as lower-funnel attitudinal metrics like brand favorability, and therefore offer better guidance early in a campaign. They simply offer an early gut-check as to whether consumers even notice the ad at all, recognize what brand is being advertised, and understand the message or key benefit the brand is trying to communicate. Comparisons in performance can be made between creative themes and between site placements so that the agency can reallocate impressions towards the best performing ones. The Adometer solution uses short surveys, usually 4-5 questions long, so results can be collected quickly and delivered in real-time via an online interface. Because no control group is needed, there is also no need to worry about balanced audience profiles.
If a client is looking to understand their campaign’s performance across the full funnel of branding metrics, and needs deeper insights into why a campaign is performing well or poorly, then AdIndex is a better solution. However, for an early read into what’s working and what isn’t while it’s early enough to make changes, Adometer may be the right solution.
Michelle Eule is Managing Director, AdIndex Solutions at Dynamic Logic. In this role, Michelle is responsible for maintaining and enhancing Dynamic Logic’s suite of solutions for analyzing the in-market branding impact of digital advertising. She also acts as a consultant on strategic accounts and customized projects. Michelle joined Dynamic Logic in July 2002. Prior to joining Dynamic Logic, she managed a research laboratory for a professor at Columbia Business School, with whom she studied marketing and organizational behavior from a social psychological perspective. Michelle received an MBA at NYU’s Stern School of Business and a Bachelor of Arts in psychology from Barnard College. Michelle has been a speaker at many industry events including conferences hosted by The ARF, OMMA, AMA, Ad:Tech, and OPA, and has been a guest lecturer at Baruch College and NYU. Michelle was a judge for the 2008 IAB MIXX awards and is a member of the Research Committee for the Advertising Council.
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