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Audience-Based Planning vs. Index-Based Planning Which approach won our head-to-head TV advertising field test? A Guide for Marketers

Transcript of Audience-Based Planning vs. Index-Based Planning · 2020-05-05 · Audience-Based Planning vs....

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Audience-Based Planning vs. Index-Based Planning

Which approach won our head-to-head TV advertising field test?

A Guide for Marketers

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Say you’re a marketer for a national brand. You just found out your TV advertising budget may be slashed by 10% in 2018. In the best case scenario, it stays flat. Either way, because TV is the largest line item in your marketing budget, your CFO sees it as an opportunity to trim costs. Meanwhile, she’s pressuring the marketing team—yourself included—to make that money work harder than ever.

You look at your media mix model to assess the performance of last year’s TV spend and seek inspiration for how to do better, but the reporting is too general to be helpful. As you review your TV media plans in search of efficiencies, it dawns on you that despite your sizable database of customer information, all your TV media has previously been planned against indices and standard Nielsen demos, mostly Adults 18-49. You wonder if there’s a better way. All the trades are talking about audience-based buying, but you’re not sure what that means, much less if it’s the answer you’ve been looking for.

What should you do? Should you change some, all, or none of your TV targeting? How do you even begin to answer that question? Your media agency is proposing essentially the same plan as the past year’s, but the more you think about it, the more you’re convinced that if there’s a chance an audience-based approach could save the company money or generate better results, your CFO will find out about it and expect you to have a point of view.

Marketers everywhere are having a conversation like this. In the following pages we’ll explain what audience-based buying is and how it compares to index-based buying. That way, when it’s time for you to allocate your TV ad budgets you’ll be able to make the most informed decision possible and deliver the best results for your brand.

Table of Contents:Intro.......................................................................pg 1

What Is An Index, Anyway?.............................pg 2

How Audience-Based Buying Differs........ ....pg 2-3

People vs Programs...........................................pg 3-4

Head-to-Head Field Test..................................pg 4-10

Q&A.....................................................................pg 11-13

Audience-Based Planning vs. Index-Based PlanningWhich approach won our head-to-head TV advertising field test?

A Guide for Marketers

1www.simulmedia.com©2017 Simulmedia, Inc. 1www.simulmedia.com©2017 Simulmedia, Inc.

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What Is An Index, Anyway?

An index is the relative composition of a target audience watching a specific program or network, as compared to the average audience size in the television universe. Here’s an example. Let’s say you’re targeting W25-54 who have kids and also are cooking enthusiasts. That audience makes up about 7.4% of the total TV viewing universe, according to Nielsen. So if, 7.4% of the people watching a given episode of Chopped on Food Network are W25-54 cooking enthusiasts with kids, then that program would have an index of 100. If 14.8% of people watching that Chopped episode were within the target audience, then the program would have twice the concentration of the target compared to the the entire TV audience, and its index would be 200.

Essentially, indices are a way for marketers and their agencies to gauge the value of a program or network relative to others, given relative concentrations of a specific target audience. Typically, the highest indexing shows for a particular audience are also compared for things like cost, context, and total viewership, and are then ranked in order of priority for a media buying team to purchase.

How Audience-Based Buying Differs

True audience-based buying, like the kind used by Simulmedia, does not account for the relative composition of an audience, or the context within which an audience is likely to be found. Instead, it values the raw number of individuals in a target audience who actually watch a given program, their likelihood of being exposed to an ad, and the cost of reaching them with a particular spot. This requires technology for reasons we’ll explain later in this document, but for now, suffice it to say that the audience-based approach enables advertisers to buy audiences rather than programs.

As an example to illustrate the differences between the two approaches, let’s return to our audience of W25-54 cooking enthusiasts with kids, and compare two potential inventory units for a media plan. You can choose The

Best Thing I Ever Ate on Cooking Channel on Thursday evening, or Edge of

Alaska on Discovery on Sunday morning.

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Which spot would you choose?

NETWORK

PROGRAM

INDEX

TARGET AUDIENCE

CPM

TOTAL VIEWERS

IN TARGET AUDIENCE

Best Thing I Ever Ate

149

$80

9,006

Edge of Alaska

64

$68

9,385

“Best Thing” indexes at 149 and “Edge” indexes at 65. From a traditional perspective, it’s a no brainer. But it’s actually a more complex decision than the index would make it appear, and the spot you choose depends on your approach. Again, the index simply reflects the concentration of the target audience relative to the TV universe as a whole, while the audience-based approach focuses on the total number of target-audience viewers and the cost to reach them. So even though Best Thing has an index 2.3x greater than Edge

of Alaska, Edge of Alaska has more target-audience viewers, and it would cost 18% less to reach them. From an audience-buying perspective, the choice in this case would be Edge of Alaska.

People vs. Programs: Different Approaches to Reaching A Target Audience

No matter which approach you favor, the goal of TV advertising is to reach as much of your target audience as possible. Now that we’ve defined the two approaches, let’s look at the merits of each when it comes to realizing that goal.

Index-based campaigns follow the model that TV planners and buyers have been using for years: deliver the maximum number of impressions for a given audience at the minimum price. Of course, the most efficient way of doing this is to buy high-indexing media against a traditional age/gender demo, so even if your intention is to target W25-54 who are cooking enthusiasts with kids, it’s likely the buying audience would simply be A25-54. This method relies on the scale of TV to reach a specific audience, rather than precision targeting.

Target Audience W25-54 Cooking Enthusiasts with Kids

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Now that we’ve covered the theory behind each of the approaches, let’s explore what the differences look like in practice.

Simulmedia’s Business Operations team created two media plans targeting our sample audience of W25-54 cooking enthusiasts with kids. One was created using an index-based approach, the other using Simulmedia’s VAMOS platform and its proprietary audience-based method. Each campaign was given a budget of $500K for a one week flight.

Head-to-Head Field Test: Comparing Index and Audience-Based Media Plans

Thirty years ago, this approach worked very well because there were only about 30 channels and brands had the potential to reach millions of people in their target audience with any given spot. Today, the average TV viewing household gets 200 channels and the TV audience is more fragmented than ever, but the average media plan still only runs on about 20 networks. As a result, even if campaigns are still hitting their GRP targets, they’re doing so by increasing the frequency, not total reach. Further exacerbating the reach/frequency dilemma is the fact that indices don’t account for the possibility that the same people might be in the audience of different programs. Given the limited amount of networks on a typical plan, it’s likely that the programs ranking highest for index will draw some of the same viewers.

Still, if you value impressions delivered over a balancing of reach and frequency, then index-based planning might be right for you.

By comparison, if you subscribe to the idea that reaching more likely customers will ultimately lead to better results, then you’ll want to adopt an audience-based approach to ensure you’re putting your message in front of as many unique people in your target audience as possible.

Simulmedia’s VAMOS platform supports this audience-based buying approach. Based on viewing data from millions of homes, VAMOS is able to predict—at a person level—what the people in your audience will be watching during the flight of a campaign. It then uses a patented reach optimization algorithm to assign every viewer a probability of being exposed to a spot. When constructing a media plan, VAMOS selects the combination of spots that maximize those probabilities, and thereby the target-audience reach, based on any parameters outlined by the marketer, including campaign timing and budget.

Keep in mind that many video demand-side platforms, or DSPs, and other advanced TV platforms claim to offer audience-based targeting, but ultimately still rely on indices. Though they may start with a more granular target like the cooking enthusiast audience we’re discussing, they ultimately end up ranking inventory by index because that’s the industry standard for media buying.

Today, the average TV viewing household gets 200 channels and the TV audience is more fragmented than ever, but the average media plan still only runs on about 20 networks.

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Now that we’ve covered the theory behind each of the approaches, let’s explore what the differences look like in practice.

Simulmedia’s Business Operations team created two media plans targeting our sample audience of W25-54 cooking enthusiasts with kids. One was created using an index-based approach, the other using Simulmedia’s VAMOS platform and its proprietary audience-based method. Each campaign was given a budget of $500K for a one week flight.

The index-based plan includes inventory selected to maximize the target-audience index of the campaign schedule according to Nielsen data, and is subject to constraints of budget and minimum network spending levels. The audience-based plan includes inventory selected to maximize the target audience reach subject to the same constraints.

We designed this comparative analysis in order to demonstrate the different outcomes when planning based on composition index versus audience reach. We recognize that in actual TV campaign planning, composition index is one of several factors considered in assembling a campaign schedule, alongside the CPM, a brand’s content preferences, and the commercial relationships a brand has struck with media owners. To provide a truer comparison between the different methodologies and gain insight into their relative values, however, spots for the index-based buy were selected on index alone— without respect to other factors.

Let’s look at the top-line numbers of the two plans. Once again, both are based on a $500,000 budget and a one week flight:

W25-54 food enthusiast with kids

$55.75

8,968,571

39.59%

127

4,054,508

2.21

54

W25-54 food enthusiast with kids

$82.84

6,039,216

26.66%

188

2,975,830

2.03

23

Index-Based PlanAudience-Based Plan

AUDIENCE

TARGET AUDIENCE CPM

IMPRESSIONS

% TARGET AUDIENCE REACHED

AVERAGE INDEX

REACH

FREQUENCY

NETWORKS

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As you can see, the inventory selected for the index-based plan had an average index of 188, or 32% higher than the average index of 127 on the audience-based plan. This is as you would expect. The audience-based plan reached far more of the target audience, however—nearly 40% in total and 48% more than the index-based plan.

The other data point that immediately jumps out is the CPM. Simulmedia’s plan has a target-audience CPM of $55.75, which is 32% lower than the index-based plan. What do these two metrics tell us? That optimizing for unique reach and efficiency, rather than index, helps marketers do more with each TV advertising dollar.

While these results indicate that audience-based buying is more efficient—driving significantly more reach at the same budget—they don’t tell us why that’s the case, so let’s look a little deeper.

An index-based plan will tend to fall on a fairly narrow range of networks. In this case, the index-based plan included 239 spots across 23 networks, but just three of those nets—VH1, MTV, and TLC—accounted for 45% of the impressions delivered.

The audience-based plan leveraged VAMOS’s patented reach-optimization algorithm and selected 512 spots across 54 networks. That’s more than twice the number of spots and networks found in the index-based plan. VAMOS more evenly distributed the media weight across the plan, with only two networks—Ion and Investigation Discovery—accounting for more than 10% of the total impressions.

Number of Networks and Spots

Optimizing for unique reach and efficiency, rather than index, helps marketers do more with each TV advertising dollar.

Reach More Of Your Target With Audience-Based TV Advertising

Contact us to see how Simulmedia's VAMOS platform can help you reach more of your audience,

more efficiently, than any other platform.

GET IN TOUCH

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Media Weight of Audience-Based Plan:

50

% Media Weight

ION

ID

TLC

BOUNCE

LIFEMOV

HALL

NICK

DAM

ESC

MTV

LAFF

FRFM

WE

TWC

MTV2

LOGO

AETV

APL

GSN

POP

UP

VH1

TVONE

BET

FUSE

NATGEOWILD

DLIF

DISC

SCIENCE

AHC

CMTV

REELZ

FOXMOVIE

21 More Networks Weighted Less than .5%

1510

0.57%

0.58%

0.94%

0.97%

0.99%

1.00%

1.02%

1.06%

1.07%

1.08%

1.12%

1.21%

1.23%

1.30%

1.34%

1.42%

1.82%

1.89%

2.20%

2.23%

2.44%

2.52%

2.72%

3.19%

3.35%

3.77%

4.33%

4.87%

6.41%

6.53%

9.61%

10.16%

10.69%

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Media Weight of Index-Based Plan:

0

% Media Weight

VH1

MTV

TLC

NICK

ID

LIFEMOV

MTV2

LOGO

TVONE

FRFM

FUSE

CMTV

BET

LIFE

WE

BOUNCE

AETV

DAM

COOK

UP

REY

FUSION

FM 0.01%

0.02%

0.19%

0.44%

0.99%

1.06%

1.11%

1.29%

1.33%

1.67%

1.92%

2.82%

The next step is to look at how the impressions were allocated by daypart. As previously stated, most media planners prefer primetime because they believe it’s the best daypart for reaching the highest percentage of their audience. This may be true, but primetime is expensive—and by weighting that daypart too heavily, marketers sacrifice efficiency of reach for the plan as a whole.

Impressions by Daypart

3.43%

3.49%

3.49%

3.73%

4.31%

7.38%

7.75%

8.84%

13.84%

14.78%

16.12%

10 15 20

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Audience-Based Plan Index-Based Plan

Early Morning

Daytime

Fringe

Primetime

Late night

Overnight

Weekend

Percentage of Impressions by Daypart

5.00

24.64

18.14

21.59

4.98

9.99

15.66

9.92

12.58

14.80

34.41

6.92

10.00

11.38

Now, about those spots. Let’s look at a few of the ones selected by each plan.

The highest indexing show on the index-based plan was also the most cost-efficient spot selected for the audience-based plan. That honor went to a re-run of Malcolm & Eddie on FUSE, with an index of 364 and a target-audience CPM of $10. The Golden Girls on LOGO was also selected for both plans, ranking very high for index (297) and cost efficiency ($20 target-audience CPM), while reaching about 9,000 viewers in the target audience.

On the index-based plan, the spot that reached the largest number of target audience viewers was VH1’s Love and Hip Hop: Hollywood. It reached over 155,000 target audience members and indexed nicely at 224. However, at a target-audience CPM of $190, it didn’t make the cut for the audience-based plan because Simulmedia’s VAMOS platform was able to find those same people more efficiently through spots they watched on other programs.

.

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Spot-Level Comparison

In the case of the index-based plan, primetime accounted for 34.41% of the impressions delivered and 59% of the overall budget. Contrast that with the VAMOS audience-based plan, in which just 21.59% of the impressions were delivered in primetime, accounting for just 29% of the budget. Because primetime spots tend to be the most expensive inventory, this difference enabled the purchase of hundreds of more spots across several additional networks, which led directly to the increase in target audience reach.

Reducing the number of

primetime spots enabled

the purchase of hundreds of

more spots across several

additional networks, which

led directly to the increase

in target audience reach.

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For years, TV advertising has been bought and sold based on indices and context. Until recently, they didn’t need an alternative. In 1990, when there were only about 30 networks for a viewer to choose from, a marketer could buy a 30 second spot on each of the major networks in primetime reach and about 38% of America’s TV viewing universe.1 The notion of an audience-based approach to media planning didn’t exist because it didn’t need to. Today, it’s a different story. As previously noted, the average US TV-watching household gets nearly 200 channels. Top networks and cable channels have seen their viewership decrease, while the bottom 25% of rated networks saw viewership climb by 21% from 2011 to 2016.

Audience fragmentation isn't going anywhere, so marketers need to find a way to make it work for them. One way of doing so is to take an technology-enabled, audience-based approach to buying TV advertising.

Simulmedia’s VAMOS platform offers a solution. By matching customer attributes from high-quality 1st and 3rd party data sets with viewing data from millions of households, VAMOS is able to build a target audience based on actual viewers. In doing so, VAMOS can understand the viewing behaviors of the people in your target audience. It then uses a patented predictive algorithm to forecast what each of them will be watching during the flight of a given campaign. The resulting media plan—often containing thousands of spots across 50 or more networks—is designed to maximize your target-audience reach in a way that no human could calculate. By buying media in this way, rather than focusing on a narrow set of high-indexing networks, marketers can start treating fragmentation as a friend, rather than a foe.

But the best part is that audience-based buying doesn’t have to be an all-or-nothing proposition, either. By allocating just a portion of available TV ad dollars to an audience-based approach, marketers and media planners can see immediate improvements in the reach, efficiency, and performance of their overall ad buy. What’s more, with the insights that can come from an audience-based approach, marketers can also determine which days, dayparts, and networks are most effective for reaching their audience. In turn, this can lead to the optimization of future campaigns and begin to lay a foundation for sustained business growth.

1. http://tvbythenumbers.zap2it.com/business/where-did-the-primetime-broadcast-tv-audience-go/

On the flip side, VAMOS selected Law & Order: SVU on ION for the audience-based plan, with a target CPM of $45 and a target audience reach of nearly 95,000, even though it only indexed at 99.

Once again, audience-based planning reveals a tendency toward maximizing reach in the most efficient way possible, whereas index-based buying values audience composition ratios.

Audience-Based Buying Makes Fragmentation Your Friend

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For a more in-depth look at Simulmedia’s approach to planning, and how it’s different from the rest of the industry, we sat down with Simulmedia’s Chief Technology Officer and top data scientist, Kyle Hubert, for a few questions.

An index tells you the relative difference of an audience's composition within a viewing event compared to the average audience size in the television universe. If 17% of everyone in the TV universe is within the target a marketer would like to reach, and a program has an index of 140, that means 24% of the people watching that program are members of the target audience. Really, an index is a way for marketers and their agency to evaluate the value of a program against their target audience. It should be noted, though, that a higher Index doesn't always correlate to the best purchasing decision, because a lower-indexed program may be priced more favorably on a target-audience reach basis. A perfect example of this is illustrated earlier in this paper, where Edge of Alaska indexed much lower than Best Thing I Ever Ate for a specific target audience, but Edge of Alaska cost less to reach more people in that audience. Because of this, agencies typically consider additional factors like cost, context, and viewership when ranking the value of an inventory unit.

What does an index tell you about the makeup of a TV audience?

Though VAMOS enables advertisers and agencies to plan media in several different ways, Simulmedia believes that a marketer's goal should be to maximize reach against the target audience within a given purchasing cycle. It is our responsibility to effectively evaluate where to spend TV ad dollars in order to help the marketer accomplish this goal. This requires a fundamental change in how spots are selected and purchased for a media plan, moving from a relative composition to a true audience-based method, where the viewing habits of specific audience members are accounted for. Maximizing audience reach also may mean buying thousands of spots across more than 50 networks, a technique few other media buyers can match.

We don’t use indices because they can only tell you how high the concentration of your target audience is likely to be within a given program. By comparison, it tells you nothing about the overlap of the audience between two programs. So even if you buy two high indexing shows, it’s likely that you’ll be exposing some of the same viewers to your message in both instances, thus boosting your frequency of exposure rather than extending your reach to those who haven’t already seen your ad.

So if most in the industry use indices to rank their ad buys, why does Simulmedia take a different approach?

Q&A with Kyle Hubert, Simulmedia’s Chief Technology Officer

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What does an index tell you about the makeup of a TV audience?

It starts with SimulPanel, our viewing audience population of about 7 million households, which shows what viewers within any given target audience are watching down to the second. We then analyze their viewing behaviors and use that analysis by applying a patented predictive algorithm to forecast what each member of the audience will be watching during the flight of a campaign. We’ve gotten pretty good at this, too. VAMOS's campaign-level R-squared, which is a measure of the accuracy of a prediction on a scale from 0 to 1, is .98. So once we have that forecast, we’re able to deduce which combination of available inventory units will most efficiently reach the most consumers within a flight window, at a given budget. And because we have unique agreements with networks that allow us to buy quantities of inventory at the daypart and program level that most other buyers cannot match, we’re able to make a media buy that’s faithful to the plan and maximizes the benefits to the marketer.

We know, of course, that marketers and their agencies also have relationships with networks for specific contextual buys that are highly effective in contributing to their business goals, and which are usually planned in advance to coincide with product announcements, key sales windows, and impression loads marketers depend on. Our platform can also evaluate this upfront inventory. In this way, we help advertisers look for placements that extend the reach of a target audience within a specific flight. This also allows a marketer to take a portfolio approach to their media spend—focusing on a core buy while also leveraging a data-driven complementary buy that Simulmedia provides. This two-pronged approach has been very effective for brands that prefer an incremental approach to evolving their TV advertising.

The fundamental change sounds good in theory. How does it work in practice?

This wasn’t an issue when there were fewer networks, so everyone bought that way. Most still do because that’s the way their systems are designed. In today’s age of audience fragmentation, though, there are literally hundreds of billions of other media plan options. Consider this: there are about 14 minutes of commercials per hour on TV, give or take a bit depending on the network. If a network ran only 30 second spots, that’d be 28 ads per hour on one network. That comes to 672 ads on one network in one day, and when you factor in that the average US household gets 200 networks, then each household would have the potential to be exposed to over 134,000 spots per day, and we haven’t even accounted for :15s yet. When you multiply that over a two-week flight and then consider all the possible combinations of spots you can mix and match to create a media plan, it ends up being a number that’s greater than all of the atoms in the universe. That’s why we take a different approach, because with numbers like that, there’s no way a person can develop the optimal media plan without technology to help.

There’s no way a person can develop the optimal media plan without technology to help.

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Yes, that is correct. To do this, we created VAMOS, which is software built on statistics and machine learning. What is important to note, though, is that we build our audience-based plans at the individual level which is how we can predict what a person is likely to watch. As a result of partnerships with the likes of IRI and Oracle, we can define these audiences using tens of thousands of different attributes and create precision media plans for strategic segments like like pet owners, yogurt buyers, or frequent travelers. Using the predictive method I previously described, we will reach as many of these granularly-defined audience members as possible, given campaign budget and timing. Another aspect of this is that Simulmedia executes this on linear TV, an environment in which tracking all users is impossible. That’s why ours is a probabilistic approach, leveraging scientific principles that allow for a verified sample at the core. Our methodology has been analyzed independently by Neustar Marketshare Partners and others, and has proven to be effective.

So you’re saying you can predict if a person is going to be watching a certain show?

In truth, because it’s really hard. We’ve spent more than nine years building and patenting our VAMOS technology. It enables a holistic view of targeting, planning, buying, and measurement. It essentially contains inter-operative point solutions within a single system. Nobody else is doing it this way because nobody has developed the same type of end-to-end technology. That’s what sets us apart.

Why isn’t anyone else doing it that way?

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Simulmedia was founded in 2008 with the belief that data-optimized, audience-based advertising on national linear TV would produce better results. Having run thousands of campaigns for top brands and networks, there are countless others who share our belief. Now you can too.

Visit www.makemytvadsperform.com to contact us today.