Uniform models for measuring advertising impact are still missing. Until solutions are available, advertisers should follow these five steps to measure effectiveness and optimize processes, says guest author Daniel Skoda.
One of the biggest challenges in maximizing advertising impact is measuring the effectiveness and efficiency of digital media measures. This can be attributed in particular to the lack of uniform models for measuring advertising impact. A uniform and comprehensible system would be the solution. Existing approaches lack holistic applicability across various format and inventory categories. Until the industry reacts with comprehensively applicable, completely neutral solutions, there are already a number of steps that should be considered by advertisers in order to measure the effectiveness of marketing measures and optimize processes in the best possible way.
1. Avoid misunderstandings in the evaluation
The effectiveness of campaigns depends on several criteria. However, some parameters and crucial variables are often ignored. This includes, among other things, the actual distribution of contacts. It is important to consider the difference between the calculated contact dose, in terms of average contacts (OTS — opportunity to see), and the actual contact distribution. The OTS value does not provide any information about the distribution of contacts in individual contact classes. It shows how often the target group reached (net reach) has seen the advertisement on average, and not the individual people. However, there is only an advertising effect or effect on the “advertised person” if a defined frequency of contact (depending on the industry, for example 4-5 contacts) has taken place with the advertising medium. has been achieved. It is therefore crucial for success that the actual contact dose per user is evaluated in detail via an ad server and then optimized.
The problem of measurability and maximization of advertising impact can be attributed, among other things, to the lack of comparability of the net coverage of some media. The moving image market in particular is reaching the limits of panel logic due to progressive fragmentation. Advertisers must be aware that real user behavior and actual net reach of target groups cannot yet be represented for TV campaigns, for example. In the online sector, however, the implementation of the MRC and IAB standards in collaboration with the relevant measurement providers can ensure transparent measurability and achieve consistent media management for efficiency and effectiveness.
2. Tighten KPIs
Defining and continuously optimizing KPIs is an essential part of measuring effectiveness. A distinction should be made between qualitative and quantitative factors. Quantitative KPIs include target group reach, format and environment quality (measured by advertising material visibility) and achieving the desired contact dose. All of these factors can be measured and compared. Qualitative KPIs are insights that help improve campaigns. This allows advertisers to collect meaningful data on the willingness to recommend, brand sympathy and advertising reminders. Online surveys, to which users are invited via the campaign or website, are an effective way. In order to measure the effectiveness of campaigns, it is important that both quantitative and qualitative factors are considered.
3. Consider multidimensionality
Findings on advertising impact (effectiveness) are only meaningful if a comparability of different channels is created and the multidimensionality of the customer journey is taken into account. Instead of using one-dimensional distribution models, companies should distribute conversions as a percentage of several points of interaction during the customer journey. Appropriate attribution models can also show what contribution a channel has actually made. Multi-channel attribution allows a precise presentation of campaign performance and can identify inefficient and unprofitable campaigns. One example of a measurement that allows digital and traditional TV measures to be compared, for example, is measurement via the baseline of online shop traffic. This shows which target groups have really been reached and whether media investments are paying off.
4. Define tools and use data
Advertisers must be aware that data is often pre-interpreted by third parties. This is due to the fact that third parties act as filters and their methodology is limited in many cases and does not allow a complete picture of the advertising effect. When companies are willing to interpret data themselves, the problem is that the “raw data” from major platform providers (such as Google and Facebook) is not freely available. It is therefore recommended that advertisers buy their own ad server or CDP or carry out active tag management and activate the data obtained in DSPs. Depending on the solution provider, deterministic matching helps to make the data more precise. Deterministic matching makes use of common identifiers, such as email addresses, login details, postal address and telephone numbers — insofar as advertisers (can) collect them. As a result, companies are able to match their users deterministically on different devices with a high degree of accuracy. Campaigns can thus be evaluated more precisely, which in turn has a positive effect on effectiveness and efficiency.
5. Derive actions
Only through continuous evaluation of data in real time can an ideal mix of channels be found, budgets allocated in the best possible way and media purchasing optimized so that the greatest possible advertising impact (effectiveness) is achieved with optimized costs and processes (efficiency). Advertisers must be aware of these processes and encourage their partners to professionally plan and execute campaigns accordingly so that an effective and efficient campaign result can be achieved at the end.
This post is first posted at W&V appeared.
