MarTech platforms are revolutionizing the world of marketing, but they must overcome certain challenges before they can truly deliver on what MarTech promises.
Managing Customer Data
MarTech’s premier selling point is that it can gather and utilize vast amounts of data for analysis, targeting, outreach and customer conversion. But like other technology providers, MarTech companies entrusted with clients’ customer, prospect and other data must be able to handle it appropriately. They must be able to guarantee its security and privacy, and have the bandwidth to batch it for analysis or stream it for real time.
Leveraging Legacy Systems
The MarTech pioneer systems, like bulk e-mail management or CRM, were designed to solve a relatively narrow set of problems—at a much different scale and velocity then we’re now confronted with. Today, these systems’ older languages, frameworks and technologies make it harder for them to expand and remain competitive, but that doesn’t mean the value and investment tied up in them is lost. The challenge is to improve them with new data architectures and analytical tools, and to make strategic code upgrades, all while expanding to new channels. This might mean migrating parts of these legacy systems to noSQL or Hadoop, thereby expanding the systems’ reach with modern data pipelines and making them broader and smarter.
Delivering Actionable Data
In the early days of both AdTech and MarTech, many companies’ biggest challenge was to gather data, any data, about customers and prospects’ behavior. But as their data-gathering ability has grown, the new challenge is to figure out how to use it. It is no longer enough to promise the ability to assemble mountains of information; manual and machine learning approaches must be able to deliver meaning and predictive value from analysis of that data.
Scalability, Fault Tolerance and Latency
MarTech systems must deliver high throughput, low latency and fault tolerance. In MarTech, the pipeline is key; the more data a platform can handle, the more successful its marketing campaigns will be. Systems that aren’t scalable will become choke points, and any system with high latency or significant faults will wreak havoc on the delicately timed interplay between data and outreach.
Integrating Data Types and Sources
AdTech succeeds when it’s able to connect Exchanges, Ad Servers, DSPs and other data sources into an ecosystem out of which that actionable data can be pulled. But MarTech creates its own ecosystem by integrating data sources and automation activity with its CRM, Social, Content as well as those same AdTech partners. Without that integration, MarTech cannot offer the Universal Profiles and 360° Views of prospects and customers that give marketers opportunities all along the buying journey. Proper and wide integration is crucial to maximize data access and its usability in informing marketing engagement activity.