Five Major Software Development Challenges In Martech

In order to optimize results, marketing professionals inside high-performing organizations are embracing new technology, tools and data more than ever before. The technological innovations in the martech domain are booming globally and helping digital marketers achieve their digital campaign and lead-generation goals.

While not often thought of as “deep tech,” marketing cloud solutions in major enterprises like Adobe and Oracle, as well as new innovative companies like Marketo and HubSpot, are dealing with an immense amount of data, infrastructure and privacy complexities. This is leading to some unique challenges when it comes to building and maintaining martech software.

1. Dealing With High Volumes Of Data

Marketing professionals are gathering user data constantly from many different sources and platforms. The amount of time and effort it takes to properly source, categorize and prioritize the ocean of data is unfathomable. On top of that, when there is an issue that needs to be debugged, the massive amount of data makes it extremely difficult for engineers to get to the bottom of data irregularities and anomalies.

These companies need to adopt dynamic observability solutions that are built for cloud-scale applications. If you’re not ready to adopt a SaaS platform, you can start by using the open source project OpenTelemetry to start standardizing your data across metrics, logs and traces.

2. Privacy Concerns

Martech companies are dealing with an unusually large amount of highly sensitive, personally identifiable information (PII) that needs to be protected. Dealing with compliance and regulations while trying to move fast is a top frustration for software developers in the industry.

To address this, martech companies need to adopt tooling that allows them to quickly access and pipeline data securely, whenever they need it. They also should consider shifting security left and embracing DevSecOps best practices. There are even great open source tools out there like Checkov that will automatically scan for cloud misconfigurations.

3. Remote Debugging

In terms of application debugging, I previously noted that a software bug can immediately translate into a loss of money in the martech industry. When developers debug critical applications with complex architectures, nearly $300 billion per year is wasted in engineering time and customers’ opportunity costs. Long gone should be the days where debugging code and deploying a fix takes hours or even days. Long gone should also be the days where developers write endless log lines that create a ton of noise, cost and performance overhead.

Instead, developers should be equipped with modern, SaaS-based debugging tooling that enables developers to quickly access the data they need to troubleshoot and solve the customer’s pain. Of course, developers are used to debugging in their IDE every day, but consider solutions that get real-time data from production systems.

4. Modern Infrastructure

Today’s martech companies are built on top of modern and distributed infrastructure like cloud, containers, microservices and Kubernetes. While this makes martech solutions highly scalable, it adds a ton of complexity. Software developers should consider embracing site reliability engineering (SRE), observability and chaos engineering to proactively improve reliability while dealing with highly dynamic cloud infrastructure.

5. The Rising Costs Of Logging

Developers have been using logs to troubleshoot issues for decades. At scale, these logs become extremely noisy and expensive to store — especially in the martech industry, where there are a lot of quick transactions. Finding the right log can be like finding a needle in the haystack. New companies — such as my organization with its recent solution to dynamically turn logs on and off, as well as solutions from Logz.io and LogDNA — are coming into the space to attempt to address this problem.

At the end of the day, many of the challenges faced in the martech industry are similar across other modern industries dealing with cloud-scale applications. Many engineering organizations are balancing the desire to move fast while simultaneously making good decisions and protecting sensitive customer information. As I discussed, developers in the martech industry are adopting dynamic observability, chaos engineering and other modern practices that address modern problems, as well as adopting open source — such as Delve, OpenTelemetry and Chaos Toolkit — and SaaS solutions to transform their organization.

This article was originally published on Forbes.