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Algorithms for effective digital marketing

Algorithms for Effective Digital Marketing

Why digital marketing is important in the present time?
Present times is all about digital devices, sharing, liking, commenting and recommending content on the web and social media platforms. To show its presence to the potential customers, a business must use a smart and effective digital marketing strategy. In any digital marketing strategy, the frequency and quality of the content are two important factors. Different digital marketing strategists have different opinions on the strategies. Some give high priority to the frequency and others to the quality of the content. To implement any digital marketing strategy one must choose the right metric and then apply the appropriate algorithm to make this work in real. So, what is an Algorithm?
 
What is an algorithm?
Curiosity to learn and improve what we do is inherent in our nature. Algorithms can be very useful in doing things optimally and making a complex task easier. So, what is an algorithm? An algorithm is a sequence of steps/instructions to solve a problem or completing a task. For example, finding the greatest common factor, finding the greatest common divisor, a recipe for a dish, a computer program to do a specific task, a smartphone application, online dating, book-recommendation, online flight, and hotel booking websites, etc.
 
Every business wants to be successful and digital marketing strategy is very important for this to achieve. Depending on the requirements and type of business, a suitable algorithm must be chosen. Type of business and the customer’s online activities decide the metric for the algorithm, for example, impression, impression-to-leads, and conversions click-through rate and other data. Choice of the right metric for the algorithm is crucial for the success of the digital marketing strategy and this will reflect in the Key Performance Indicator (KPI). Key to choose the right metrics is that is should help in improving the visibility of the company on the web. Marketing and sales team should be able to measure the performance on a day to day basis.

Figure 1. Supervised Learning.1
 
Some important algorithms:
Designing a successful algorithm is based on a strong understanding of the business and the working of the algorithm. Here we are listing these algorithms.
Predicting customer behaviors comes under supervised learning[ https://datafloq.com/read/machine-learning-explained-understanding-learning/4478] and in this case, we have Decision Trees, Linear regression, Logistic Regression, and Naive Bayes.

Figure 2. Unsupervised Learning.1
 
  • Grouping, clustering, and classification of the customers fall under unsupervised learning1 and in this case, we have k-means clustering, kNN (k-Nearest Neighbors), Logistic regression, and Decision Trees.
  • For data mining and collection purpose, a digital marketing strategy can use C4.5 and EM algorithm.
  • Another class of algorithms is for recommending a product and service on a portal, in this case, we have Collaborative Filtering.
  • Hummingbird is the Google ranking algorithm, which ranks the business web-page online.
  • Predictive churn rate: this is used to identify the attrition of the customers. Here the models that we use are Bayesian Inference and Pareto/NBD model, Logistic Regression, and Q-learning.
  • Predictive customer lifetime value: to calculate how much a business can earn from a customer over the lifetime and how much a business should spend on acquisition of the customer. In this category, we have Gamma-Gamma models and Hidden Markov Models.

Figure 3.   Predicting Customer Lifetime Value.[ https://towardsdatascience.com/predictive-customer-analytics-part-iii-aeb996beafba]
 
  • Replenishment: to identify and know the correct time that a customer requires to reorder a product. Models used in this case are Monte Carlo Markov chains, Probabilistic models, and Time Series Analysis.