One of the topical problems in 2019 is digital advertising and cross-media measurement. Since there is a growing number of complex techniques and methodologies, but no unified approach, most companies lack expertise to deal with it. Here we cover various measurement tools and their cross-platform application.
We are trying to keep you updated on all marketing measurement trends, that’s why we prepared an article on the use of measurement tools after the phase-out of cookies and IDFA. Get ready to privacy changes and apply solutions that won’t be affected by the new conditions. See how MMM, MTA, brand studies and other approaches are going to function without third-party cookies.
Created in 1997, Interactive Advertising Bureau UK (IAB UK) is a trade association, promoting sustainable development, the best practices and standards for advertisers, agencies, and media owners. Their goal is to address challenges the industry is facing and offer some solutions. Our article is an overview of the guide for marketers on best practices today that IAB prepared with MTM. Here you will find some useful advice on what models and techniques to use for digital advertising performance measurement within the environment of various media, both large-scale and more granular analyses. You will see how to combine them to your best advantage and create your own measurement strategy.
There is no simple answer and solution to successful and effective advertising measurement because so many aspects need to be considered, like audience, media consumption, views, individual and combined performance of media channels, ad effectiveness and business outcomes. This article covers the last two aspects in the context of different media channels.
A strategic approach and careful planning will help you avoid many problems and achieve the best outcome, and the following five steps will assist you in that.
- First of all you need to define the campaign objectives and target audience. While estimating more obvious short-term results, don’t forget about long-term goals and find a way to measure them as well. Each media should have a clear purpose in the campaign.
- Then set KPIs in advance and choose relevant metrics according to the general objectives. IAB doesn’t want marketers to overestimate click-through rates, because they can be misleading and focus on short-term results.
- Use comprehensive qualitative data and take into account information gaps to get more accurate results. Try to constantly improve granularity and coverage.
- Combine the best available tools to overcome obstacles and get unbiased results.
- Use any results, even negative, as feedback and learning opportunity to improve your future marketing strategies.
The four major tools we are going to discuss are brand studies, econometrics, attribution and controlled experiments. Choosing which tools to use and how to combine them depends on your product sales cycle, share of online and offline media spending, and other promotional channels. The tools should be combined in a way that ensures their results do not contradict but rather complement each other. Their combination should also cover the key steps in the customer lifecycle and different time frames, an example of which you can see in the graph below.
Brand Studies
Brand studies measure awareness, familiarity, favourability, consideration, and intent through surveys that are usually conducted before and after a marketing campaign. This flexible tool is a source of insights on various aspects, including creative design, ad positioning on web pages, and the reasons for sale increase. It is perfect for identifying long-term impact of brand activities and is even more helpful in developing marketing strategies when implemented regularly. Due to its flexibility, it can be used across different channels to compare the effectiveness of digital and offline ads, thereby avoiding double counting and misattribution.
However, despite the advantages of this tool, it doesn’t measure sales or other direct consumer actions. Additionally, the results can be biased and inaccurate if the surveyed group is too small. You cannot be certain that the only difference between two surveyed groups is exposure to your ad; there may be other factors that influenced the result. Respondents often forget where they saw the ad, but other measurement tools can be used to address this issue.
Econometrics and Marketing Mix Modelling
Marketing Mix Modelling (MMM) uses statistical tools to predict how different advertising (TV, OOH, print, digital, etc.) and other factors affects incremental sales. Marketers have been using it for a long time usually to measure the impact on offline sales, but now with the proliferation of digital channels it can be applied across various media with more granularity. A popular solution is to use MMM together with attribution, when the former tool identifies the best working media channel and the latter one helps to make short term tactical decisions. Just like brand studies, econometrics can also measure awareness, consideration and brand equity. According to Harry Davison, Facebook Client Marketing Science Manager in UK, MMM is perfect for understanding the bigger picture. With enough cross channel sales data, MMM can compare the impact of offline and digital channels. But without at least two years worth of data it won’t work properly. MMM measures the contribution of each media channel separately and doesn’t reflect amplifier effect of digital. If you are trying to measure different KPIs, you need a new model for each of them, which is more complex and cost-intensive; this is particularly true for older versions of MMM. However, with modern advanced solutions like AdoptoMedia, model building process can be automated and multiple KPIs can be included in the model simultaneously through the use of AI-enhanced econometric methods.
Attribution
Attribution is used to identify which touchpoints on a customer’s journey lead to conversion. Unlike MMM, it is highly granular, doesn’t require massive sets of data to function properly and provides feedback almost in real time, which allows for creative alterations and mid-campaign tactical optimizations. In the pictures below you can see two different techniques: single-touch and multi-touch attribution.
It is mainly used in digital marketing but can be also applied as an addition to MMM. Attribution can easily assess effectiveness of a single channel, especially on platforms that offer their own attribution systems. Different attribution models are intended for different objectives, for example, last-touch model can be used to identify the most effective touchpoint in terms of conversions, while a position-based model gives you a complete picture of a customer’s journey. There are attribution models that combine both channels digital and offline, though it’s still not easy to track conversions across different platforms. And if the purchase happens offline, it adds challenge to the task, but for such cases there is MMM. Another problem is that attribution may give too much credit to digital channels and is helpful only with short-term tactical decisions, so don’t forget about your long-term goals when using attribution. The most commonly mentioned issue with multi-touch attribution is the inability to create a single customer view across different platforms due to restrictions on data access. Furthermore, the effectiveness of this approach has been severely restrictes by privacy regulations and limitation of third-party cookies and IDFA. A detailed comparison of pros and cons of both MMM and Attribution will help you to make an informed decision on how to apply and combine these measurement tools depending on your objectives.
Controlled Experiments
Controlled experiments randomly assign people to a control or test group and compare the impact of an alteration in ads. The test group sees an altered advertisement, while the control group sees no change. To run such experiments you need a clear, testable hypothesis otherwise you might end up misallocating your budget. This methodology is perfect for accurate measurement of incremental sales and can be combined with other approaches. It helps to fill the gaps in data from high volume digital channels and is suitable for stress testing. For example, if MMM shows that paid social media advertising increases sales through higher organic search, controlled experiments can provide more evidence of that and make sure that you don’t waste your investments. This tool can be used as the standard to verify other methods, according to Matthew Taylor, Econometric Program Lead at Google. It is flexible and can be implemented, even though in limited cases, across both digital and offline channels, particularly when estimating their combined impact. However, achieving accurate results requires large control and test groups, which is often challenging.
Finally, there are two worth mentioning trends that affect and reshape measurement tools — machine learning and data privacy. While machine learning helps marketers to find patterns in large, high quality data sets, that can be used to predict KPIs, privacy restrictions seriously limit their abilities. Yet McKinsey seems to have found a way to gather customers’ data complying with GDPR.
Even though cross-media measurement is not a simple task, with strategic planning and practical tools described above you can succeed in it. Before distributing your media budget, make sure that you have completed all five steps mentioned above.
AdoptoMedia offers you an innovative tool that can automate media budget allocation, saving you both time and money. It’s an AI-powered Marketing Mix Modeling platform that can be easily integrated into your existing IT infrastructure. It has already helped companies to simplify work with the contractors and increase ROMI by at least 10-20%. With AdoptoMedia, you can calculate the contribution of every channel in the media mix, take into fators affecting sales or other KPIs (seasonality, competitors’ activities, macroeconomic situation, etc.), run “what-if” scenarios and optimize spending.
