The Definitive Guide To Digital Brand Lift
Columnist Peter Minnium explains why with the right metrics, marketers can prove the effectiveness of digital as a brand-building medium.
“And we’ll do a brand lift study,” added the seller to sweeten the digital media deal she was proposing. I was in a midtown restaurant in New York eavesdropping on the adjoining table’s conversation about a cool new type of digital media.
I expected the media agency executive to respond with questions that would lead to a robust conversation of his client’s objectives and how the campaign could be measured against these. Instead, I heard, “Great, send over the paperwork.”
I was depressed by this conversation, as it provided further proof of a troubling phenomenon I’ve increasingly noticed over the last 24 months. Brand effectiveness research has become a commodity — so generic as to have lost its meaning — and demoted to just another tactic in sales negotiations, not the strategic driver of digital brand advertising that it could and should be.
This is incredibly dangerous for the industry, as brand marketers will hold back spending in digital without proof of the medium’s effectiveness in driving the “brand metrics” that matter to them.
Brand marketers recognize that consumers continue to flock to digital media and that they must meet them there — but the industry continues to be trust-challenged, made worse in recent times by the triple evils of viewability, fraud and ad blocking.
It’s more critical than ever for all parties in the ecosystem to offer definitive proof of digital’s effectiveness as a brand-building medium.
The good news is that brand marketers are willing participants in this process, as they made clear when the Association of National Advertisers (ANA) partnered with the Interactive Advertising Bureau (IAB) and the American Association of Advertising Agencies (4As) in the “Making Measurement Make Sense” (3Ms) initiative, which seeks to bridge the gap in digital measurement, including defining the brand “metrics that matter,” to allow marketers to evaluate digital’s contribution to brand building.
Additional good news is that brand marketers have been successfully measuring the impact of their brand advertising for years with a variety of post-exposure success metrics, such as awareness, brand affinity and likelihood to purchase.
These brand health metrics span all channels and demonstrate how consumers’ attitudes, beliefs and emotions about brands change based on communications: they have proven to correlate with in-market success and are often seen as trusted proxies for actual sales.
In addition, these metrics come with historical norms that provide longitudinal perspective and allow for benchmarking.
Bringing the same metrics used to measure and optimize advertising effectiveness in the analog world to the digital one is a valuable starting point to strengthen brand marketer trust in digital advertising.
Further confidence and value can be realized by integrating digital measures of behavioral engagement specific to each ad format — as this can provide a 360-degree view to enable marketers to best understand holistically the branding effects of their digital efforts.
Brand Lift And The Purchase Funnel
In a nutshell, brand lift is the increase in the achievement of the main marketing objectives of a brand advertising campaign.
The term is used broadly by marketers, but at its core, it refers to measuring how effective their communications activities are in changing consumer perceptions on one or more of the primary purchase funnel stages.
In this space, the evolution of the purchase funnel and digital’s effort to flatten it have been debated, but for the sake of this discussion, we will use the model’s current incarnation, still based on the original AIDA. Here, then, is the current best practice in measuring brand lift across this funnel.
There are three steps to successful awareness. Marketers must measure if an ad breaks through the digital advertising and branded message clutter, if it is retained in memory by the viewer, and if it is associated with the sponsor brand with a properly branded impression.
Attention: This can be measured by asking the respondents in a survey if they recall seeing an unbranded visual representation of the ad (i.e., with any brand mention removed from the visual stimulus).
This ad recognition data can be viewed together with viewable impression and interaction rates (from behavioral data sources available to the agency or media) to get a full picture of an ad’s ability to stand out from the digital clutter.
Brand Linkage: Standing out is of no value unless the consumer identifies the ad with the brand. This can be measured by asking respondents in a survey if they can name the brand sponsoring the unbranded visual representation of the ad.
This is often referred to as brand linkage, and, surprisingly, is a hurdle many ads fail to get over.
Getting branded awareness is the first step, but it is meaningless unless the ad works to communicate what the brand intends (rationally and emotionally) in the intended fashion.
Message Communication: Is the ad’s strategic message really being conveyed by the ad and received by the viewers? To measure this, survey respondents are often asked directly, “Other than getting you to buy the product, what was the main idea of the ad?”
In addition, it is important to measure how differentiated, relevant and believable the main idea is.
Brand Attributes: How does the ad improve perceptions on key brand attributes, for example, “faster speed,” “understands what’s important to me,” or “safer for my family” and so on? Best practice in surveys is to assess respondents’ views on these versus a non-exposed, matched control group.
Ad Diagnostics: Why is the ad performing the way it is? Ratings often look to understand an ad’s likability, newsworthiness, entertainment and/or informational value, importance and uniqueness, as well as whether it is confusing, believable, humorous, factual, buzzworthy, shareable, relevant or annoying.
While message communications and brand attributes can only be truly measured by survey methodologies, the understanding of ad diagnostics can be significantly enhanced by layering in online behavioral data.
For example, interaction rate, interaction time, assets viewed, completion rates for video, likes, shares and comments can add perspective to consumers’ stated ad perceptions.
Desire metrics should measure the “response” to the ad, i.e., a change in intention or behavior, or perhaps a change in attitudes toward the brand, which ensures that consumers are more motivated toward the brand after hearing and seeing the message.
They might be more likely to try or buy the brand, or they might have improved brand perception or brand equity.
Persuasion: Here, one is most concerned about a change in attitudes related to behavior — that is, are people more likely to buy the brand more often (intent) and/or use the brand more often (frequency) after being exposed to the advertising?
This is most often characterized as a “likelihood to purchase, consider, test drive, sign up” and so on. In addition, purchase and usage frequency allow for a more nuanced understanding of the persuasion of an ad.
Brand Favorability: One can also consider desire in terms of brand equity, whether people feel more positive or more favorable toward a brand after experiencing the advertising.
Brands will often look at two components to understand their equity, affinity (brand closeness) and relevance (how well the brand meets a consumer’s personal needs).
While online behavioral metrics are more accurate in capturing what people actually do, they lag surveys considerably in how people feel, and so persuasion and favorability are best captured in most cases via brand lift research.
That said, for some categories where purchases are most frequently made online, it is often possible to measure an ad’s persuasion directly via sales — although this requires a working attribution model, which is an area where significant improvements still need to be made.
Similarly, the growing ability to like, share and comment on ads driven by the rise of social media can yield a considerable cache of data to assess favorability, but practical tools to do so are still in the early stages of development.
Putting It All Together
While there is no one-size-fits-all set of metrics for quantifying digital brand lift, smart marketers, agencies and media are leveraging the learning, experience and robust infrastructure in place for ad effectiveness research and complementing these with digital-specific behavioral metrics.
By integrating both, brand marketers can validate the efficacy of their campaigns within digital — and lead the way to a cross-screen future.
Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.