data analyticsOnline advertising and onsite optimization, but even individual channels such as SEO, SEA, display and social media are considered and evaluated too often separately: although a holistic implementation can often be realized with existing tools - even without large, expensive and inflexible fully integrated suites. New approaches through artificial intelligence and a focus on the evaluation and use of massive data, are a real game changer.

Success in online marketing doesn’t dependent on a single channel. On the contrary, the individual online marketing activities and channels interact – and even offline marketing has a certain impact on the overall success. The reason for this is the customer journey, since a purchase impulse is only rarely triggered with the first ad contact, rather needs several contacts: depending on which study you believe, an average of six ad contacts are optimal for the click probability; and even those who click do not buy immediately, but look around first and then go back, hence, continuous addressing is needed to trigger the purchase impulse consistently, e.g. via remarketing.

Within the customer journey, the potential buyer also goes through different phases, in which different types of advertising material and approaches are required: customers often start with information-driven searches in a search engine (mostly Google), then try to find more specific individual properties and functions, until they know what they want to buy. This is then often followed by a comparison of prices, delivery terms and other conditions, until the purchase decision is finally made. And so, the entire customer journey of the online shoppers includes all from the first information search to the re-address of visitors who have left the shop without buying.

In order to be able to plan and control (online) advertising effectively and efficiently, all measures must be intelligently linked together: starting with SEO and SEA, through display advertising and remarketing to optimizing the website itself, combined with continuous tracking and the most automatic possible optimization of the individual channels. All those who do not work as data driven as possible and ignore innovative technologies will ultimately be left behind.

It certainly helps to understand how the path from the first touchpoint to conversion can be optimized to increase conversion rates and reduce costs across channels. By tracking different devices, synergies between the touchpoints can be identified and used to increase the performance of the various marketing channels. All in all, valuable customer insights are gained by understanding the buying behavior of the target group so that the marketing activities can be orchestrated much more efficiently.

The respective "optimal attribution model" depends on the specific business model, the objectives of the company and the complexity of the market. A distinction must just be made between static and dynamic attribution models: static models are based on simple rules, while dynamic models are based on calculated relationships. The latter clearly offers greater potential and require less manual maintenance and development, but both can be used as a basis for budget analysis as well as the optimal allocation of the marketing budget, so that the optimal attribution model can be determined individually based on their own data and taken into account in the determination of the model of multiple influencing factors.

Driven by machine learning and self-learning algorithms, the control of the individual advertising channels can be automatically optimized - with individually adjustable goals and emphasis on the individual touchpoint in the customer journey. The tracking is not only limited to paid channels, but takes also into account the organic traffic, which makes SEO successes not only measurable individually but in the context of the entire customer journey.

By Daniela La Marca