If you’re in marketing, you are probably familiar with Scott Brinker’s annual Marketing Technology
Landscape Supergraphic. For those of you who are not familiar- Scott Brinker is the Editor at
chiefmartec.com and VP Platform Ecosystem at HubSpot. He created and published the first Marketing Technology Landscape infographic on chiefmartec.com in 2011, and it included roughly 150 company logos.

It might seem like Amazon started ecommerce, but the beginning of the monetization of the
internet happened in a rudimentary marketplace for used computers. In 1983, Boston
Computer Exchange established an electronic salesfloor on a public access bulletin board
system, giving people a vehicle to showcase their used computers and then consummate deals
over the telephone.

For retailers, understanding their customers- their preferences, purchasing behaviors, and even things that they don’t like about a product or service, and using this information to personalize the customer’s experience is critical.

Most marketers today are aware of machine learning (ML) and how many companies are using it for a wide variety of use cases- from automating business processes to creating highly personalized applications. Some marketers may be concerned that machine learning will leave them without jobs. However, the core tasks of marketing involve creativity- an attribute machine learning does not have. Machine learning can’t take over every marketing task, but it could be used to assist marketers in a wide variety of ways.

As marketer’s accountability to their business organization continues to broaden with the evolution of  marketing / sales unification (think smarketing), their understanding of the customer journey needs to keep up the pace. While the journey has been customer-centric for some time, we now have to be executing in-the-moment marketing, knowing our customers well enough to deliver experiences that meet their needs and interests in real time. The revenue opportunities can be great when you offer customers context.