Increasing the success rate of CMs with TV data – How TV data can be utilized
Commercials are a natural part of what comes on when you turn on the TV. When companies communicate with consumers, they spent a lot on commercial (CM) deployment. At the same time, people have been said to have been moving away from the TV for quite some time, and its influence has changed from long ago. So how should companies use TV CMs to communicate with consumers? Let’s examine effective “TV data analysis methods” in order to consider how CMs can be used.
The benefits of CM placement on TV, when usage is declining
Fig 1 presents a chronological summary of TV, smartphone app, and PC web browser usage time using the INTAGE proprietary media log i-SSP.
Fig 1
While there was not that much of a gain in TV and smartphone usage time from 2017 to 2018, TV has gradually decreased from 2019 onwards, and in January 2023 smartphones were used for 270 minutes versus 119 minutes for TV, a gap of over an hour.
To make this easier to understand, let’s look at the usage time for each device versus January 2017 (100%) (Fig 2).
Fig 2
The time spent watching TV has been gradually decreasing since 2017, while the time spent on devices that enable people to watch digital media on them, such as smartphones and PCs, is increasing. This downward trend in usage clearly indicates TV’s influence is starting to decline in comparison with other media.
So, what are the benefits of spending a lot of money on CM deployment when TV’s influence is in decline?
Fig 3 presents a graph of the exposure rates for a certain confectionary CM by gender and age group.
Fig 3
The CM was aired around 5000 times, so had plenty of opportunities to be exposed to consumers, and reached a broad range of people in their teens to 60s of both genders. The power of TV CMs can thus be said to lie in their potential to communicate with a wide range of age groups, something unachievable with ads in digital media. So, why do TV CMs reach this far despite the decrease in the time TVs are used for? One of the reasons behind this is TVs high usage rate. Fig 4 presents the results of a device usage rate survey conducted annually by INTAGE.
Fig 4
TVs have the highest usage rates of all 3 devices, and are currently top in terms of the breadth of the media exposure they can achieve. Despite their decreased usage time, a large number of people still own TVs, making using TV as communication channel an effective way to connect with a wide range of consumers.
Achieving the goal of “reaching your target efficiently” through TV data analysis
When TV used to be watched a lot, the more CMs were deployed, the higher sales would proportionately be. However, these days TV usage rates are high, but the length there are viewed for is limited, so even if one were to deploy lots of ads, it might not necessarily have the desired effect. In addition, despite not having as high usage rates as TV, many companies are now deploying ads on digital media, making it difficult to engage in the sort of bold TV CM measures like in the past on a limited budget.
Under these conditions, optimal advertising placement focused on target that reaches the target one wants to strike a chord with in a pin-point manner is recently a must in TV CM placement and ad communication. This type of planning utilizes “TV (CM) data”, which is the theme of this article.
Two representative examples of TV data are the “TV ratings” which are often used to evaluate programs, and the “GRP (Gross Rating Points)” based on those TV ratings. GRP have been utilized from long ago as an index for the evaluation of ad slots when deploying commercials to buy deployment slots with, although at present, an increase in data providers and the diversification of measurement methods means that a variety of other TV data is also starting to be utilized. Let’s examine the types of TV data available out there. TV data is broadly divided into two types based on collection method: “panel survey-style” and “smart TV-style”.
Panel survey-style
Panel survey-style has a membership base known as monitors, with viewing data gathered from those monitors. There are various ways to do this, from gathering this via questionnaires, the operation logs of TV remote controls, the audio playing on the TV, and even services that collect data from the viewer’s perspective to provide viewing “quality”.
The most distinctive characteristic of panel survey-style is that the data gathered is based on “people”. The data gathered can tell you the sorts of programs and CMs that were viewed, and by linking this with who was watching, is mainly used to measure the effectiveness of CMs and to plan for the deployment of CMs.
Smart TV-style
Conversely, smart TV-style data is gathered from viewing logs from TVs connected to the Internet. The fact they are conducted via the Internet means they making it possible to gather data in a stable manner, and have much larger sample sizes than the panel survey-style. Since sufficient sample sizes can be secured for analysis, they enable us to analyze viewing logs with a granularity down to city, ward, town, and village level. They also deliver data on a second-by-second level with stable accuracy. They are used for area marketing analysis, and for measuring the effectiveness of CMs akin to panel survey-style.
So, what sorts of things can you do with this TV data? Let’s examine some examples of analysis INTAGE has actually conducted.
Identifying your next issue through examining “what this CM changed”
After deploying a CM, it’s natural to wonder “what the point of deploying the CM was”. It’s common for advertisers to be concerned from perspectives like to what extent the CM contributed to sales, improved purchase rates, or contributed to management goals.
In these cases, since advertisers need to confirm how their CMs impacted results, we use “panel survey-style” TV data that tracks the same monitors long-term and makes it possible to deep-dive by segment. This data is used to compare the purchase rates of people exposed to the CM and people not exposed to the CM “before the CM is aired” and “after the CM is aired”, with the pure advertising effect excluding external factors analyzed by calculating the difference (Fig 5). It is also important to confirm convincing results in line with reality through the analysis of behavior log data in terms of exposure to CM and whether or not the individual goes on to purchase.
Fig 5
Fig 6 presents the actual results of a verification of two alcoholic beverage brands using i-SSP, a panel survey-style form of TV data from INTAGE.
Fig 6
2.81% of those exposed to the alcoholic beverage A CM bought the brand (its purchase rate) before airing. Post CM airing, this purchase rate was 3.65%, an increase of “+0.83 points” in terms of lift before and after the CM was aired. On the other hand, the purchase rates of those who were not exposed to the CM were 2.47% before CM airing, and 2.43% post CM airing, with this gap virtually unchanged at “-0.04 points”. Since an increase in purchase rate is only observed among those exposed to the CM, in this case it seems likely the CM impacted the purchase rate.
To see the extent to which CMs impact purchase, let’s examine the difference in lift between those exposed to the CM and those not exposed to it. With Brand A, the result is 0.87 points, which is obtained by subtracting the lift of those not exposed (-0.04 points) from those exposed (0.83 points). That is, this 0.87 points can be said to be the pure effect of Brand A’s CM. If what this 0.87 points represents is hard to grasp merely in figures, it may be easier to understand the CM’s impact by converting this into the number of people if applied to Japan’s actual population.
In a similar format, it is also possible to measure a CM’s impact on various KPIs through analyzing the extent to which attitudinal change indicators (such as product awareness, overall liking, and purchase intention) asked about in the questionnaire survey changed due to the CM.
In this way, in addition to confirming results, identifying indices the CM is unable to increase enables us to identify “what to do next”. The measurement of CM efficacy is not a once-off examination of answers, but also a way to search for hints with which to drive one’s next results.
Putting together an optimal deployment plan in line with “what your target is watching, when”
Broadly speaking, there are two ways TV CMs can be deployed: by “time” and “spot”. To briefly explain the difference, time CMs are those where the program the CM is to be deployed in is specified, whereas spot CMs are those where the time of day, not the program, for the CM to be deployed in is specified. The difficult part of considering TV CM deployment plans is which of these formats to choose, or if already deploying in one of these formats, whether to continue with that format. TV CM data can also be utilized when unsure regarding these cases.
For example, Fig 7 divides people according to their frequency of exposure to both time and spot for a certain cup noodle brand’s CM, and tabulates composition rates by age group and gender.
Fig 7
On observation of these results, it is clear that more men are exposed at a high frequency to the time CM. Similarly, on observation of cup noodle consumption frequency by exposure frequency in Fig 8, it is clear that a large proportion of people highly exposed to the time CM eat a lot of cup noodles.
Fig 8
Let’s also examine differences in attitudinal change.
Fig 9
When comparing those exposed to time and spot CMs on attitudinal change indices, while there is little difference in CM and brand awareness, the high exposure to time segment rated higher on mid-funnel indices like overall liking and purchase intention. These results enable us to conclude that time CMs are an appropriate channel for delivering messages to the target, and considering their positive impact mid-funnel, can be used to come to the decision that time CMs should be continued with. By comparing the kind of differences time and spot have, it is possible to use data to aid consideration in planning.
In addition, when planning the deployment of spot CMs, it is a good idea to consider which sorts of programs the target normally watches using a heat map as depicted in Fig 10.
Fig 10
This is a summary of which times targets watch the TV at in a heat map format, in the case where people who buy energy drink products are being targeted. The dark red areas are the time slots more targets are exposed to, and can be used as intelligence to make concrete decision-making with when deploying spot CMs.
Purchase track record, consumption frequency, and other segmental information can thus be used to define a specific target, and by accurately identifying their viewing tendencies, this can make it possible to consider and make decisions on deploying CMs that are more likely to reach the people you want to connect with while keeping costs down.
Departing from ad deployment based on guess-work through convincing effectiveness validation
We have introduced TV data utilization methods using several case studies in this article. This sort of data-based grasp on the current status quo can offer the sort of analytical results that not only inform you of how a CM performs, but that also guides your next actions.
There are a diverse range of TV CM data utilization methods depending on how it is analyzed, from effectiveness measurement to deployment planning and creative evaluation. A key point here is whether the data is convincing or not. If the data seems unreliable after going to the expense of verifying effectiveness, you may feel uncomfortable with the conclusions you can draw from results based on it. When considering the utilization of TV data, we recommend that you choose convincing data.
INTAGE provides advertising communication support through its panel survey-style media log data i-SSP (INTAGE Single Source Panel) and smart TV-style data Media Gauge TV/Media Gauge Dynamic Panel. We offer a variety of analysis packages to meet your specific issues and state of deployment, so please feel free to contact us for more information.
[i-SSP® (INTAGE Single Source Panel ®)] Based on INTAGE’s SCI (nationwide individual consumer panel survey), this data is newly collected from the same respondents regarding their website viewing and TV viewing from PCs, smartphones, and tablet devices. This data clarifies the relationship between consumer behavior and information exposure as well as ad efficacy through analysis of their usage trends and exposure rates to TVs, PCs, smartphones, and tablet devices along with the shopping data gathered from these very same respondents. In addition, a separate questionnaire survey can be conducted with respondents to probe and analyze them on their outlooks, values, and state of purchase of durable goods and services. * Single Source Panel® is the registered trademark of INTAGE Inc.
【Media Gauge® Dynamic Panel®】 Media Gauge® Dynamic Panel® is a service that estimates and links Media Gauge® TV with di-PiNK (DMP) owned by DOCOMO Insight Marketing, Inc. (herein referred to as DIM), breaking this down using segmentals such as estimated at-home information, gender, and age group, and calculates viewer data by statistical processing for each specified target.
INTAGE commissions DIM to estimate and link Media Gauge® TV with di-PiNK, with processing and tabulation implemented by DIM. DIM is a business entity that does not own personal information, so Media Gauge® Dynamic Panel® data is never linked to personal information. Media Gauge® Dynamic Panel® ‘s reports are also anonymized and tabulated.
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