Customer demands and marketing competition are continuously growing. In direct digital marketing, it is important to lead a number of granular communications at different touchpoints and to do this in the most individualised manner possible for each user. This is not an easy task, as the recipient determines the location, time, channel and context and he decides whether the content is relevant or not. In brief, marketing communication with the user is increasingly growing in complexity.

The Challenge of Individualised Lifecycle Communication

Modern direct digital marketing does not think in campaigns any more, which go from a sender to a recipient, but in individual measures along the customer lifecycle. It is important at every touchpoint to provide a user with the most suitable information for his specific expectations and his position in the lifecycle. The specific requirements can be identified, e.g. through personal user data, purchase and usage behaviour and via the context of the communication. This step from campaign-centred to a customer-centred communication cannot be handled manually. Marketing Automation and a conceptual, as well as technical integration of the marketing into the business processes, is necessary. This is about managing four areas of responsibility in the best possible way:

  1. automation of the communication flow (dialogue course) according to predefined events (COMMUNICATION)
  2. legal collection and automated processing of the required user data and events (triggers) in the customer lifecycle (DATA)
  3. automation of workflows in the content processing (OPERATIONAL PROCESSES)
  4. comprehensive evaluation of the interplay for optimisation (ANALYSIS)

Successful, customer-centred communication can only happen with the adequate solution in order to meet these challenges. Marketing Engineering deals with this task area.

Successful Marketing Automation in Practice

There are basically no limits to the automation of communication. The most important field of application are dialogue courses related to transactions. One event can be the opportunity for a number of accompanying or service-oriented dialogues. The advantage: specifically relating to an event within the lifecycle creates particularly high interest. An example would be a seminar. Promoted by mailings, the dialogue course will change direction according to the recipient’s response. If he does not respond, a reminder is sent. If he responds, but does not register, another reminder with incentives is sent. If he registers for the event, a thank you email will be sent and he is asked to recommend the seminar. Shortly before the event, the recipient will receive a reminder with information about participation. After the event, he will receive a thank you email for his participation, a feedback form and possibly further information, e.g. the presentation slides of the talks. A person, who recommends the event, e.g. via SWYN, will automatically receive an additional thank you email. A person, who has registered for the event but not taken part, will only receive the presentation. This simple example shows the potential of the automation of dialogue courses and also the complexity you need to manage.

ELAINE Campaign Designer

ELAINE Campaign Designer

In addition to communication, there should always be a successive understanding of the user behaviour and preferences of the individual recipient. Technology-supported scoring models allow you to analyse the user activity, interests and preferences of automated email communication in detail.  Marketing automation helps you to operate a self-learning system in a closed loop. For digital marketing, it is also important to take into account the requirements on data privacy. Profiling a user by means of personal data, e.g. clicks, conversions or the use of downstream websites is only possible with the user’s explicit consent. In practice, these opt-ins in the history of the data collection are often very heterogeneous and with varying scopes. Marketing automation can support you in obtaining suitable and legal consent for the data usage of users – Legal Big Data. The UNO Refugee Aid, for example, focusses on multi-level email campaigns in order to successively develop comprehensive user agreements from different touchpoints. This opt-in strategy is an important task area for the automation in the customer dialogue.
A particular challenge for individualised communication is to provide a large number of suitable and very granular content. The more precise the individualisation, the more specific content and the more individual fragments are required. In most companies, the corresponding content is already available, but the processes to collect, process and release it are often little efficient and become a bottleneck or dead-end on the way to highly individualised communication. Process automation can make an important contribution here. PAYBACK, for example, is saving over 25% of its total time for planning and creation of mailings through clever optimisation of content processing. One of the solutions was the use of campaign briefings in Excel format. These campaign sheets can be directly imported into the email system and “translated” into articles and mailings.

Proceed as follows: 5 Practical Tips for Automated Marketing Communication

  1. Work according to the bottom-up principle. Instead of an often highly sophisticated maximum concept, you should first identify all important touchpoints and events in the lifecycle and use them for automation. In most cases, simple triggers and differentiations during the course of the dialogue can already draw substantial quick wins.
  2. Use event-related and lifecycle campaigns in a parallel way. Your target should be the integration of all dialogue in marketing.
  3. Identify, which data is actually relevant  for the intended purpose. Many companies initially store all data at random, even though most data does not provide any substantial information or the most important indicators are lacking later.
  4. Focus on a slim operative process right from the start, e.g. through standardising mailings and automating content and data flows, as well as clear workflows for release.
  5. Identify the interdependencies of the used measures by setting suitable measuring points. This will allows you to turn the correct adjusting screws and identify a real result.
    Once the most important dialogue courses are set, test each element. A successive, systematic approach will help, in the best case scenario via automated, multi-variant tests.