The Internet is the easiest measurable advertising medium. But the click-throughs and digital touchpoints that are easy to capture, don’t tell the whole story. They do not provide insights into the entire customer journey including all digital and traditional advertising measures, nor do they consider the impact of offline media on online sales.
Marketing experts want to know exactly which media - online and offline - have what kind of impact on sales figures and how the advertising budget can be best distributed. This can only be achieved with the right system, for it’s too big a project to handle manually.
SUCCESS EVALUATION SHOULD NOT BE LIMITED TO ONLINE MEASURES ONLY
In 2017, according to a forecast by NetzwerkReklame GmbH, digital advertising measures accounted for around one third of all marketing expenses in Germany. The other two third were offline media such as newspapers, TV or radio.
It would therefore almost be careless to evaluate the success of marketing measures by only considering online channels. After all, an effective budget allocation is impossible based on purely digital customer journeys. Besides digital touchpoints, offline channels and external effects such as the weather need to be considered as well in order to holistically explain the advertising effect of different measures.
FIRST STEP: BASELINE MODELING FOR A HOLISTIC VIEW
Marketing attribution already measures touchpoints on a digital level. Cross-device tracking and machine learning attribution further extends the customer journey, and the individual touchpoints are allocated to a value contribution which measures the impact of the touchpoint on the conversion.
In order to view the advertising effectiveness holistically, however, offline channels need to be included as well. The first step for a successful integration is baseline modeling. Successful modeling requires the data of the entire media mix of the past two to three years since some disciplines may not be a permanent part of it. This can be digital data, but also TV, print, etc.
Besides measuring digital touchpoints, offline channels and external effects such as the weather or seasonal differences are combined to create a holistic model to explain advertising effects. Once the external effects are eliminated, you can give reliable recommendations on a digital channel level where offline measures are generically included.
In coordination with machine learning attribution, it is then possible to make a relatively exact forecast for the entire budget allocation. Like this, advertisers get a holistic perspective on the customer’s behavior and their customer journeys; at the same time online and offline measures are connected.
CONCLUSION: MAKING INFLUENCES MEASUREABLE WITH THE RIGHT TOOL
When measuring the customer journey, many analyzing tools provide only a technical measurement of touchpoints and use standardized attribution models. However, it is much more important to find out the actual contribution of the different online and offline advertising measures to reach the targeted marketing goals.
Undoubtedly, offline media have an impact on online sales. That is why they are still an integral part of the marketing mix. How large of an impact, however, always depends on the individual campaign.
CMOs who rely on an intelligent system that combines baseline modeling and machine learning attribution, can now measure this impact more precisely and view the advertising effect of their online and offline measures holistically. They can make accurate forecasts for an ideal budget allocation as well as long-term optimizations of future advertising expenses and better control the impact of different online and offline channels on company sales.