How to audit your martech stack — and why you should

Start with the business, not the tools

The most common mistake in a martech audit is starting with the technology. What platforms do we have? What do they cost? What could replace them?

That’s not the right starting point. A better bet is to start with the business objective and the customer experience. What are you trying to achieve? What does the customer journey look like? What capabilities do you need to support it? In other words, running a requirements gathering process. Once you’re clear on that, you can evaluate your current tools against those requirements rather than against each other.

Questions to ask for each platform in your stack

Use these questions to assess the purpose, value, ownership and integration of every marketing technology platform:

• What problem was this tool bought to solve?
• Is that still the right problem to be solving?
• How much of its capability are we actually using?
• What AI capability does it already include — and are we using it, paying extra for it, or duplicating it with another tool?
• How easily can we get data out of it — via API or export — to combine with other sources for analysis?
• Who owns it, and who is responsible for getting value from it?
• What would we lose if we switched it off tomorrow?
• Is it integrated with the other tools in our stack, or does it sit in isolation?

Common patterns we see

After running martech audits across a range of organisations, a few patterns come up repeatedly:

• Tools that were implemented for a specific project and never properly adopted
• Overlapping platforms doing similar jobs because different teams bought them independently
• Standalone AI point solutions bought in a hurry that duplicate capability already built into platforms the organisation owns
• Data sitting in multiple systems with no single customer view
• Licences being renewed automatically without anyone assessing whether the value is there
• Technology decisions being driven by IT or procurement without enough input from the marketing teams who use them

How does AI change your martech audit?

In three ways. First, the platforms you already own are shipping AI faster than most teams can absorb it. Your CRM likely has lead scoring and next-best-action built in, your email platform has subject line and send-time optimisation, your CMS has personalisation and content generation, and your analytics tool will surface anomalies and write summaries. Before buying any new AI tool, audit the AI already sitting in the stack — the cheapest capability is usually the one you’re already paying for.

Second, AI has dramatically lowered the barrier to cross-platform insight. Data that used to require an integration project — CRM records, sales results, channel performance — can now be pulled together and interrogated with AI in hours, not months. That means the value of your stack is no longer just what each platform does individually, but how easily its data can be accessed and combined. An audit should test both: the in-platform AI you’re paying for, and how readily each tool’s data feeds cross-platform analysis.

Third, AI changes what’s worth automating. Reporting, audience segmentation, content variants for testing, campaign QA, and data cleaning are all candidates now, which shifts the question from ‘which platform does this?’ to ‘does this need a platform at all?’

What good looks like

A well-functioning martech stack is one where every tool has a clear purpose, is actively used, is properly integrated with adjacent platforms, and is evaluated regularly against the business outcomes it’s supposed to support. It doesn’t have to be complex, but it should be cost efficient — it should be the right size for the organisation’s current and future plans.

Thinking about reviewing your marketing technology? We help organisations assess, right-size, and plan their martech stacks.

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