SEO

Perfect Details for the Essential Web marketing for a Dentist

Many companies do not (yet) know how to use the collected customer data. It is about the potentials and dangers of algorithms in the marketing mix.The days when you did not know which 50 percent of the marketing spend was thrown out have largely come to an end, thanks to Big Data and AI (Artificial Intelligence).

The automation of marketing processes has been common since around 2001, as the collection of big data has gained in importance. The data sets consist, for example, of customer databases or clickstream data, which are a record of the customer’s navigation between different websites. However, the volume of data has increased explosively, so in early 2016, a good 90 percent of all data in the previous twelve months emerged. For the Dentist Marketing this is the perfect deal now.

  • Since many companies do not know how to use this data volume with the existing database systems and software solutions, the full potential of Big Data is far from exhausted. The traditional methods of marketing automation also do not provide deep insights into the data, suggest any action, do not anticipate the impact of the measures, and do not affect customers in real time.
  • However, if algorithms are used for marketing, the records can be edited more efficiently. Algorithms can analyze, subdivide and recognize patterns and trends in large data sets. They can observe changes and provide recommendations for action in real time, that is, during interaction with the customer. In addition, marketers can devote themselves to more demanding tasks through the use of algorithms, which can result in a more efficient and cost-effective marketing process. In the long term, a company can achieve a competitive advantage through the use of algorithms in marketing as well as greater customer loyalty through increased customer proximity.

Data Pool: Customer Journey

Based on Big Data Tracking, the customer’s “customer journey” can be systematically measured via various touch points such as search, social media and advertisements. Thus, with the help of the so-called attribution modeling on the basis of this obtained data, the media and marketing planning can be optimized. The data mining model calculates the optimum channel mix from a variety of dates and times by automatically calculating the value contribution of each touch point in the overall channel context. This makes it possible to say exactly which touch points have a direct conversion function and which more of an assistance function. Likewise, conclusions about the temporal cause-effect chains are possible.

The most important thing for companies is to store customer data from the pre-acquisition phase to the conclusion of the customer relationship the entire so-called customer journey. By combining these customer data with other billing information, customer service aspects, and other sales and marketing aspects, intelligent algorithms can make business decisions, make recommendations to the business owner, and conduct market research. Even the journey of the customer to the purchase of a product provides strategically valuable information.