Author: Allyson Dietz | Source: neustar
Buying linear TV has always been equal parts art and science. It requires a strong analytical base—sizing up the right mix of programs, networks, and dayparts for your brand and budget isn’t for the faint of heart—but much of the work is done so far in advance that the reality doesn’t always match expectations. By the time your campaign is in flight, you’re often stuck with the results, good or bad, with limited recourse to make adjustments. So you make do with what you have and store the lesson for future reference. It’s like planning the final play of a football game in the opening quarter.
While linear TV buying remained a long game, digital took off. It offered an immediate feedback loop between creatives and audiences—a boon for marketers who, for the first time, could quickly react to changes on the field and make corrections where necessary. It also allowed them to analyze the effect of every single creative along the consumer path-to-purchase. Multi-Touch Attribution (MTA) was born.
It took a while for the pieces to fall in place, but we’ve reached the point where TV data can be captured at the same scale and with the same level of granularity as digital data. Digital and TV advertising working together in perfect harmony? The battle lines have been drawn for so long that it’s hard to believe we’re finally within reach of this holy grail. At Neustar, we’re thrilled to be partnering with iSpot to expandopen this new frontier, and we believe that the benefits to ad buyers are going to be far-reaching.
This development comes at exactly the right time too.
For one, recent progress in the identity space is making it possible for marketers to manage increasingly complex consumer profiles. Every day, new media and shopping interactions are added to these consumer profiles without jeopardizing their privacy. Without robust and scalable identity management, it would be impossible to stitch together the thousands of marketing touchpoints that make up our daily lives
The COVID-19 pandemic is transforming consumer habits at a much faster pace than anticipated. While the peak of the crisis is hopefully behind us, consumers have discovered new ways to shop and consume media, and many of those habits are here to stay. For instance, OTT programming was already rising in popularity, but two months of stay-at-home orders have clearly accelerated that trend. While many advertisers at the beginning of the year were still tip-toeing around OTT for one reason or another (because of concerns over ad inventory, measurement capabilities, and corporate buy-in, among others), they can’t ignore it any longer.
Add to it recent surges in online video, live streams, mobile video, and shifts in linear TV programming (more news, less sports) and daypart viewing (more daytime, less primetime), and you get a sense of the scale of changes facing the industry.
Of course, the effect of the pandemic on the economy goes far beyond shifting viewing habits from live sports to local news programs. The toll of the economic crisis is heavy, but it also varies greatly from industry to industry, and advertisers need to pay close attention to reallocate their media buys as efficiently as possible. With shrinking budgets, it’s now more important than ever to invest in campaigns that can demonstrate measurable business impact.
It’s no secret that digital media has traditionally been easier to measure than television. At a time when every marketing dollar needs to prove its worth, why not focus entirely on digital media?
The continued rise in Smart TV penetration in the U.S. is changing the equation. The TV set is quickly becoming another connected device in consumers’ entertainment quiver, and as such can be measured just as precisely as other devices in the home. And with TV production and programming schedules in limbo at the moment, there are bargains to be found for savvy ad buyers. All the more reasons to bring all media types into the fold, and invest in holistic attribution solutions to understand the consumer journey across all touchpoints—and figure out what works best.
Predicting a consumer’s chance of conversion has always been a complex problem, and with all the rapid changes in the marketplace this year it’s become even more complex. To have any hope of doing it justice, a modern MTA solution must account for three important things:
Propensity to Buy.
It must first account for rich offline and online consumer attributes. This is where having a strong identity framework is really critical: You need to know who each consumer is. Have they purchased from your brand in the past? How frequently? How recently? Where are they located, and what type of consumer are they? Are they likely to buy from your competitors too? All of that data will help you assess someone’s propensity to purchase from your brand before any exposure to your current campaign takes place.
It must also include some way to control for external factors that aren’t specific to any one individual but are likely to influence their behavior: An economic downturn like we’re experiencing today certainly qualifies, but also product seasonality, inflation, the price of gas, promotions, competitor discounts, even something as mundane as the weather.
Sequence of Exposure.
Finally, it must compile an exhaustive list of all addressable media interactions for every consumer in the dataset: What were the touchpoints (offline, digital, and TV) that defined that customer’s path-to-purchase? In what order? How far apart? What was the ultimate business outcome? If you can see TV touchpoints (campaign, creative, network, daypart, target, etc.) with the same granularity as display, or paid search, or paid social, or email, you’re opening up a whole new dimension in your media buying decisions.
When we talk about MTA at conferences or client presentations, we often focus on the math involved in figuring out what weight to attribute to this or that touchpoint in the campaign. If your customer just clicked on a paid search link to get to your website, does that paid search unit get all the credit, or does it go to the display ad that got the ball rolling two weeks ago? How about the TV ad they got exposed to three times the night before? That math is fascinating in its own right. For the first time, we’re able to measure how exposures across multiple channels can feed off one another to boost conversion rates. But those calculations won’t do you any good if you can’t be confident that you’ve accounted for every single touchpoint along the way. And that should include data from walled-gardens (like Facebook).
Then, and only then, can you start experimenting and using what you learn to make winning adjustments to your creative and targeting strategy. In a true cross-channel world, reach and frequency—the backbones of TV measurement for the past 70 years—take on a whole new meaning.
In today’s volatile environment, you need identity at the center of your marketing operations, agility in your media buying, and ad exposure data that covers the gamut of consumer interactions leading up to their purchase of your product. That’s a tall order. But if you make sure that your attribution framework includes the three pillars discussed here (propensity to buy, external factors, and sequence of exposure), and adopt an activation platform that can feed off that framework, you will make every opportunity count.
To learn more about how Neustar, in partnership with iSpot, can help you optimize your cross-media campaigns, click here.
Product Marketing Director
Allyson Dietz leads Product Marketing for Custom Analytics at Neustar. She is responsible for defining the positioning for the company’s Marketing Mix Modeling and Multi-Touch Attribution solutions and tying the benefits of those to our client’s most pressing needs.