Customer Data & Analytics Blog

Janet Wagner

Recent Posts by Janet Wagner:

The martech landscape is still growing

Janet Wagner | 2 minute read

This year marks the eighth release of Scott Brinker’s annual Marketing Technology Landscape Supergraphic. The size of the martech landscape is amazing, and it’s still growing. The 2018 supergraphic charts 6,829 marketing technology solutions. The 2019 supergraphic features 7,040 martech solutions sorted into more than four dozen categories; and there are hundreds, if not thousands, of martech solutions that aren’t included. Every year, marketers have more martech solutions to choose from. So today, we’re taking a look at a few martech solution categories: conversational marketing and chat, call analytics and management and collaboration.Infographic Credit: ChiefMartec.com

Topics: MarTech

What is all this buzz about the Julia Programming Language?

Janet Wagner | 3 minute read

There seems to be a lot of buzz around the Julia programming language lately. After nearly ten years of development, Julia 1.0 was released in August 2018. And according to the KDnuggets software poll published in May 2019, Julia is one of five major analytics, data science, and machine learning tools with a significant increase in usage compared to the 2018 software poll. This post takes a look at the Julia programming language and highlights a few of the advantages and disadvantages of Julia compared to Python.

Topics: data science

Common algorithms in marketing: Decision trees

Janet Wagner | 3 minute read

Organizations that have incorporated machine learning (ML) into their platforms (or plan to) are finding that there are many decisions to be made when it comes to models and algorithms. One of those decisions is which algorithms should be used for which applications. Decision tree algorithms are commonly used in marketing. This post highlights some of the advantages and disadvantages of decision trees. This post also includes a few examples of how decision tree algorithms are used in marketing.

Topics: machine learning

Machine learning can help companies avoid the commodity trap

Janet Wagner | 3 minute read

Marketing teams at any company can fall into the commodity trap- where the competition for products and services are based solely on pricing. And many companies specialize in selling commodity products, making it all the more difficult for their marketing teams to avoid falling into the commodity trap. Today, however, companies selling commodity products have access to a wealth of data- data that often contains information about customers, manufacturing processes, operations, logistics, and worker expertise.

Topics: machine learning

Self-Learning AI enables intelligent recommendations

Janet Wagner | 2 minute read

Recommendations are an essential part of marketing and sales. However, traditional recommender systems often produce recommendations that are not relevant or personalized enough. This post highlights some of the limitations of traditional recommender systems and how self-learning AI enables intelligent recommendations.

Topics: Customer Intelligence