Build or Buy? A Practical Framework for Your Marketing Tech Stack

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TL;DR: The build-vs.-buy decision starts before you compare solutions

• First, ask whether the capability needs to exist at all. Define the business problem and workflow before deciding how technology should solve it.
• Consider building when your needs are meaningfully differentiated and the resulting operational burden is manageable.
• Consider buying when the capability is relatively standard, reliability matters, or maintaining it yourself would create more work than value.
• Account for what happens after launch. Building may be easier with AI, but maintenance, documentation, adoption, governance, and ownership don't disappear.
• Protect the knowledge that differentiates your company. The software itself may not be your most valuable asset; your organizational context and expertise may be.

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AI has completely changed the economics of building software. 

Capabilities that once required dedicated engineering resources and significant budgets can increasingly be prototyped by marketers themselves.

That opens up real possibilities. But it makes this age-old question even harder to answer:

Should you build or buy the technology you need?

The choice is no longer simply between buying software and commissioning an expensive custom development project. 

You can buy, build, extend something you already own, prototype an internal solution in days—or sometimes, decide you don’t need a new solution at all.

In this article, we’ll cover all of these possibilities, and provide a clear buy-or-build framework to guide your martech decisions in the age of AI.

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Watch the webinar

The build versus buy equation was the focus of a recent webinar conversation between Jack Atlasov, who leads agentic commerce at Right Side Up, and Alex Biale, co-founder of Domestique.

Watch it in full →

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Before you ask “build or buy,” ask: Should this exist?

The temptation to start with tech is understandable. A team identifies a pain point, someone finds a new AI tool to potentially address it (or feels like they can build something themselves) and the conversation moves to implementation.

But that’s starting too far downstream. Martech stacks are already crowded, and there’s data indicating that many orgs aren't getting full value from the tools they have: Gartner’s 2025 Marketing Technology Survey found that martech utilization had fallen to 49%. 

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“The step-zero question is: Does this have to exist at all?” — Jack Atlasov, Director of Agentic Commerce, Right Side Up 

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Before even thinking about solutions, clearly define the problem you're trying to solve. 

What business outcome should change? 

What process produces that outcome today? 

Where is it actually breaking down?

Alex described the sequence his team uses for go-to-market operations as strategy → process → technology → data and enablement. 

The business first needs to know what it wants to accomplish and how the underlying process should work. Only then can it determine which technology best supports that process.

As building becomes easier for brands, this “step zero” becomes even more important, and teams that bypass it can end up creating solutions for poorly defined problems—or automating workflows they haven't fully understood.

In short, sometimes the answer isn't “build” or “buy.” It's to simplify the process or make it more effective, extend an existing platform, or eliminate the need altogether.

The core build-vs.-buy tradeoff: differentiation vs. operational burden

Once you've established that the capability should exist, two questions can help frame the decision:

How much differentiation does this capability create?

If your workflow is genuinely unique, and doing it differently creates meaningful business value, an off-the-shelf tool may not get you far enough. Jack notes that businesses have long dealt with software that handles perhaps 80% of what they need while leaving an important final 20% unresolved.

How much ongoing operational burden will you create?

This is where the economics of building can get deceptive. Getting an MVP running isn't the same as owning production software. Someone needs to maintain it, document it, manage its data, troubleshoot it, keep its context current, support users, and ensure it continues working as the business changes.

From these two core questions, we can create this simple framework:

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It's not a rigid formula, but a starting point. We’re about to cover a lot more considerations.

When building may make more sense

Existing software can't support an important, differentiated workflow

Building can be more compelling when the thing you need is genuinely specific to how your business operates.

If your unique workflow produces better customer experiences, faster execution, proprietary insight, or another meaningful advantage, owning more of the solution may be worthwhile.

A small build can help you understand the problem

Jack suggests that, in some instances, building a small MVP can be useful simply because it forces a team to understand its workflow more deeply. 

Recreating a process quickly exposes where the pain points actually are, which requirements matter, and where existing software provides more differentiation than you realized.

This is basically an advanced version of the “step zero” we referenced earlier, with the build service as a learning tool (and not a technology strategy).

The operational burden is contained

An internal tool used by a few marketers has a very different risk profile from software that touches every inbound lead or passes data among multiple departments.The smaller and more isolated the use case, the easier it may be to experiment without creating significant risk.

The capability contains genuinely proprietary knowledge

Building becomes more compelling when a capability relies heavily on knowledge that is unique to your business. Jack describes organizational context, tacit knowledge, decision-making frameworks, and day-to-day expertise as an emerging “intelligence layer” within companies.

If that context is central to how the capability creates value, owning more of the technology can give you greater control over how that knowledge is captured and applied. 

When buying may make more sense

The capability isn't meaningfully differentiated

No need to rebuild well-established functionalities with AI just because you can. If existing software reliably solves the problem, building your own version may simply transfer the cost from a software subscription to internal maintenance.

Reliability matters more than flexibility

Not every workflow needs an agent.

Take the example of lead routing. If a routing process can be expressed as a defined series of if/then rules (e.g., “if a lead comes from this country and has this revenue, send it to this team”), adding an AI agent may introduce uncertainty without creating meaningful value.

By contrast, a workflow like identifying potential creators for a campaign may benefit from more exploration and flexibility.

You're not prepared to own what you build

AI doesn't eliminate accountability. 

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“Building software does not outsource accountability.” — Jack Atlasov, Director of Agentic Commerce, Right Side Up

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AI can reduce the time and resources required to build software, but it’s very much not “set it and forget it.” Custom technology still needs to be maintained, documented, governed, updated, and supported. If your team isn’t ready to take on that long-term responsibility, buying an established solution may make more sense.

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Make smarter AI decisions with Right Side Up

Not sure which AI capabilities to build, buy, or integrate into your existing tech stack?

Right Side Up’s AI Services help marketing teams identify the highest-impact opportunities, choose the right solutions, and implement workflows that deliver results.

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The capability needs to work across the organization

This is where company stage comes into play.

At a startup, context travels quickly and pivots are easy (or easier). At a larger company, the same behavior can produce a maze of disconnected internal tools. 

Buying an established platform isn't automatically better, but governance, documentation, and cross-functional access deserve more scrutiny as organizational complexity grows.

The hidden costs exist on both sides

It's easy to characterize buying as the safe option and building as the risky one. In practice, both create costs.

Buying can produce overlapping tools, integration headaches, underused features, vendor constraints, and workflows distorted to fit the software. 

Building creates a different set of costs: maintenance, data infrastructure, documentation, governance, usage costs, troubleshooting, adoption, and dependence on whoever understands the system.

The right approach for you is the one that will create the most business value relative to the burden you’ll take on over time. 

The marketing leader’s build-vs.-buy checklist

Before you buy another platform or start building its replacement, work through these questions in order.

There’s no single answer that determines whether you should build or buy. Instead, use these questions to identify which direction the evidence points. Some are gating questions: if you can’t establish a clear need or business impact, stop before choosing either option. The rest help build the case for one path or the other.

1. Does this capability need to exist?

Could you eliminate the problem through a simpler process, an existing tool, or a change in how the team works?

How to interpret it: If the capability doesn’t solve a necessary problem, neither build nor buy. If it does, move on to the rest of the checklist.

2. What business impact should it create?

Define the outcome before the technology. What should become faster, better, cheaper, or more effective?

How to interpret it: A clear, high-value outcome gives you something concrete against which to compare the cost and tradeoffs of building and buying. If you can’t articulate this outcome, hit the pause button for now.

3. Do we understand the workflow well enough to automate it?

Map the current process, including exceptions, dependencies, inputs, outputs, and handoffs.

How to interpret it: If the workflow is poorly understood, don’t commit to either path yet. A small prototype may help you learn, but you need a clearer understanding of the workflow before making a long-term build-or-buy decision.

4. How differentiated is our need?

Does solving this in a unique way create meaningful value, or are you just rebuilding functionality that already exists?

How to interpret it: High differentiation favors building. If your requirements are relatively standard and existing software handles them well, buying becomes more attractive.

5. What is the ongoing operational burden?

In addition to build time or subscription cost, take into account maintenance, documentation, governance, data, integrations, support, usage costs, and future changes.

How to interpret it: A manageable ownership burden strengthens the case for building. If maintaining the capability would require significant resources without corresponding differentiated value, that favors buying.

6. Does the workflow require determinism or benefit from flexibility?

If the same input should reliably produce the same output, deterministic software or rules may be a better fit. If exploration, judgment, or variation creates value, AI-driven approaches may have more upside.

How to interpret it: This question helps determine what kind of solution you need, not necessarily whether to build or buy it. Use the answer to narrow your requirements before comparing an internal build with available products.

7. What knowledge and context should we own?

Identify where your proprietary data, expertise, workflows, and decision-making create an advantage.

How to interpret it: If the capability depends heavily on knowledge or processes that differentiate your business, that strengthens the case for building or otherwise retaining greater control over the solution. If little proprietary context is involved, there may be less strategic reason to own the technology yourself.

8. Who owns this after launch?

Name the team responsible for maintaining, improving, documenting, and supporting it.

How to interpret it: A clear owner with sufficient resources makes building more viable. If ownership is unclear, or maintenance would become somebody’s side job, buying shifts more of that burden to a vendor.

9. What happens outside our team?

Consider downstream systems, adjacent functions, security, and the customer experience.

How to interpret it: The more teams, systems, and critical workflows the capability touches, the higher the bar for building. Existing software may offer an advantage when reliability and cross-functional governance outweigh the value of customization.

10. How long will the advantage last?

If you build something today that an existing platform is likely to ship next quarter, will the temporary advantage justify the investment?

How to interpret it: A durable source of differentiation strengthens the build case. If the market is likely to commoditize the capability quickly, buying (or waiting for an existing vendor to add it) may be a better use of resources.

Reading your answers

You don’t need to tally up “build” and “buy” answers like a scorecard. Look for the overall pattern.

The case for building gets stronger when: 

• The capability creates meaningful business impact
• Your needs are highly differentiated
• Proprietary knowledge is central to the solution
• The advantage is likely to last
• You have the resources and ownership structure to maintain it

The case for buying gets stronger when: 

• Your needs are relatively standard
• Strong solutions already exist
• Reliability and interoperability matter more than customization
• Owning the technology would create significant ongoing burden without meaningful differentiation

And if the first few questions expose an unclear problem, uncertain business value, or a workflow you don’t fully understand, the answer may be neither—at least not yet.

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Make the right build-vs.-buy decisions for your marketing organization

AI has expanded what marketing teams can build themselves. But more options can make it harder to determine which capabilities are actually worth owning.

For more on the “build versus buy” framework, including how company stage changes the equation and where agentic workflows do and don't make sense, watch the full conversation with Right Side Up's Jack Atlasov and Domestique's Alex Biale.

And if you're working through where AI can create meaningful value across your marketing organization, Right Side Up can help identify, prioritize, and operationalize the opportunities worth pursuing—without adding technology just for the sake of it. Talk to us →

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