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Analytics has been a part of the digital landscape for over a decade. Businesses now know that analytics trends are shifting to more holistic views of data and metrics. The question facing every industry being transformed by data is what tech should be integrated as a strategic solution to enhance data management. Marketers are especially interested in martech and analytics that enhances customer experience.

There are a few questions a leadership team can ask to see if a given martech stack is providing value or if adjustments are necessary. In a recent post on purchasing marketing software I note key questions that should be asked:

  • Which API connectors for data sources does the platform offer?
  • How does an IDE or solution help communicate technical updates?
  • What communication is available for data visualization?

Many of the answers to these questions lean towards analytic solutions. But when mapping martech, the true answers are amplified in scale and scope. The real answers require identifying capability gaps in the operations that support marketing campaigns and associated data where analytics is applied. 

To appreciate the choices involved in a martech stack we need to appreciate the meaning of the word stack. Its concepts comes from the developer world. It is a term that refers to how various platforms are grouped together — a solution orchestrating their function to deliver results. The idea of a stack has crept into the business lexicon as more data-driven initiatives have called for more developer and IT involvement. Business analysts are increasingly using several technologies that deliver a marketing solution.

For marketers, the experience is no different. Mapping a martech stack is forcing marketers to seek a clear vision of what each application is influencing in terms of data ecosystem and how well the system can be monitored for advanced tactics such as supporting machine learning or accessing data warehouses. A martech stack is meant to orchestrate support for the digital journeys marketers want to offer their customers.

Related Article: 3 Questions for Marketers to Ask Before Buying New Software

What to Seek in a Martech Stack

A martech stack should reveal where integrations are needed or require considerable resources to implement. Each solution in a given stack should reveal where data is shared and what functions are triggered as a result. Many analytic dashboards and models require constant updates of data. The volume of data requests or more constant requests need more efficient resources to deliver results. That can signal discussions on the continued usage of legacy data system and the technical debt that can occur from voiding any changes.

A martech stack should also enhance alert protocols. As I mentioned in my facial recognition post, brand transparency for machine learning  usage can shift. The martech stack must have robust alerts and debugging as a system so that poor performance within machine learning systems can be identified over time. Systematic process such as observability and continuous integration/continuous delivery (CI/CD) become important.  

CI/CD is the use of pipelines, one or more stages of tasks, scripts, or references to external templates that initiate a process such as "Build this app," "Run these tests" and “Deploy this code to preproduction.” Observability is the monitoring of logs, metrics, and system traces within distributed systems such as a pipeline. It answers key questions regarding the activity within a system — is this given activity normal or abnormal, and is the given system condition ok. Examining how well a martech stack delivers these systematic processes can reveal the degree of complexity that is initiated when an alerting system notifies of a performance change.

A good martech stack should help analysts and managers easily communicate the shared vision on related documents and data between different platforms. Version control has been adopted in many advanced solutions, and has filtered down into less complex software. The work at home environment ushered into the spotlight this year has raised the importance of keeping a shared dialog in the same vein as version control for software. The choices to integrate solutions has become more complicated, so it’s easy for teams to lose track of the original intention of what a solution was suppose to do.

Business priorities are critical to building good tech stacks. Assessing priorities raised from a martech stack is no different. Outlining a martech ecosystem in your organization should initiate good conversations with IT team as well as with partner department and vendors, about data management. Given the marketplace interruption created by the COVID-19 pandemic, now is as good as time as any to map how a martech stack delivers the best customer experiences possible.