bentleystrategy.com

How CMOs Should Sequence Marketing Technology Investments

Strategy determines the destination. Sequencing determines whether you arrive. Four questions every CMO can use to build a marketing technology investment roadmap that earns defensible wins and compounds in value.

Early in my career, I was tasked with running a global, multi-brand Request for Proposal (RFP) for a marketing automation platform at a Fortune 50 software company. Our current license and professional services costs were north of $25M and migration time would be significant. It was important to make the right decision. We spent months on vendor demos, technical evaluation, scoring sheets, and reference calls. At the end of all of it, leadership at one of the most important brands wouldn't move off the incumbent tool. The deal collapsed and we were back at square one.

I learned a hard lesson with that project. The RFP process was thorough. The strategic alignment underneath it was not. Who owned the customer when the same person bought from multiple brands? Would one brand be allowed to cross-sell to another? Would marketing operations consolidate or stay siloed? None of those questions had definitive answers. Thousands of hours of effort got us no closer to a decision.

Marketing data and technology capabilities are complex and in continual states of innovation and disruption. Even replacing one major capability in the stack is fraught with risk and complexity, and these investments are expected to pay off, often within six months of implementation. Sequencing of investments is a critical part of marketing transformation strategy, and we ignore it at our own peril.

Marketing technology analysis paralysis

Every CMO I work with has a laundry list of capabilities they need to evolve, replace, or integrate. Modernize the data layer. Replace the marketing automation platform. Pilot a decisioning engine. Stand up a content supply chain. Modernize lead generation, routing, and measurement. Move off a legacy Customer Data Platform (CDP). And more. Not only is the list long, but each item on it affects the others. Choose vendor X for your CDP and you have just constrained which vendor will work best for your website content management system. Move to a composable architecture, where you stitch together best-of-breed components instead of buying a single suite, and you have just increased the dependency on, and cost of, your cloud data environment. This dynamic often leaves CMOs in analysis paralysis or forces them to just pick one thing to modernize and hope the rest falls into place.

Most marketing technology prioritization today runs on some combination of vendor pressure, last year's plan, the loudest internal voice, and gut. None of those hold up well when the CFO asks why she should fund your project over another. None of them tell you whether the capability you aren't touching in year one is a critical dependency for the capability you want to build in year two.

In past articles I have offered the Five-One Playbook, five concrete things any marketing leader can do in one week to make forward progress. This kind of heavy lifting cannot be done in one week. Instead, I offer four questions every CMO should answer before approving any meaningful marketing capability investment.

Four questions before you approve your next marketing technology investment

1. Is your customer strategy clear and prioritized? Getting alignment and documenting who owns the customer, how brands or business units coordinate, and what the customer experience and operating model look like a year from now needs to be an input into which marketing capabilities you prioritize and how you sequence the build out.
2. What are the dependent capabilities or inputs? Many marketing capabilities are limited by dependent data, tools, or integrations. Roadmaps that don't take dependencies into account often result in an expensive new technology that is limited by foundational capabilities, like an advanced marketing automation platform that doesn't have access to your customer segmentation data. Make sure you are asking questions about what each new capability needs to work as intended.
3. Can we show a win in months, not years? Transformation budgets are often cut when leadership doesn't see early, defensible proof points. Sequencing for early, visible wins, which will also scale over time, is what protects the additional investments in your roadmap and creates compounding value across the stack.
4. Are we investing in the future state? Marketing technology architecture is shifting fast. Consultants and technology vendors are good sources of information but tend to be biased toward pushing a future vision that supports the services or technology they are selling you. It is important to rely on your own internal technology partners and developers to get an unbiased view of where things are headed.

Question 1: Is your customer strategy clear and prioritized?

In that $25M+ failed RFP I mentioned in my opening, we never addressed that first question. The technology evaluation was rigorous. The strategic prerequisites were not. We were trying to make a major technology decision on top of unresolved strategy misalignment.

It's not because of ignorance. It's usually pretty obvious to everyone in the organization when there is strategic misalignment or dysfunction. Marketing leaders often know that this is a problem but in the interest of progress push on anyway, feeling that either they can't solve the problem or don't have time to. But CMOs are uniquely positioned to lead and find consensus in this area. If your organization has not decided who owns the customer, how brands coordinate, or what the operating model looks like a year from now, your approach and decisions will be rudderless and inconsistent. Buy-in for your technology choices will be weak, and you need strong buy-in for the organization to commit to adoption and change. The fear, uncertainty, and doubt you'll face during and after the decision will be hard to overcome.

A compelling future vision, aligned by top leadership and tied explicitly to your technology requirements, gives you a principled rationale strong enough to withstand the forces that resist change.

Before you sequence your technology investments, align on customer strategy and ensure you have buy-in from the partners you need for decisions, operations, and support. Make sure they understand the company customer strategy and how those investments will support it.

Question 2: What are the dependent capabilities or inputs?

Most marketing technology roadmaps are sequenced by urgency of current pain points or contract renewal dates. Foundational dependencies, especially future ones, need to be thought about and brought to the forefront.

An activation platform without good data just produces bad targeting across more channels. A traditional CDP without a clean first-party data foundation creates two simultaneous migration projects, one inside your company's data cloud and one inside the vendor's data cloud. An AI use case without a unified semantic layer (a shared business definition of your data) answers questions without context.

When I was first asked to lead the marketing technology transformation at a Fortune 500 retailer, the team's instinct was to start with a CDP. CDPs were the hot marketing technology category, and every company seemed to be buying one as their answer to a unified customer profile. But our first-party data layer was siloed, unstructured, and missing the third-party enrichment, dependencies that were necessary for a successful CDP implementation. Buying a CDP first would have required us to build the internal data foundation anyway, and put undue pressure on executing campaigns in the CDP before our data was ready.

When deciding on a new capability to invest in, it's worth asking what needs to be in place for that capability to drive the most value, and building that first, or at least concurrently.

Question 3: Can we show a win in months, not years?

Transformation budgets tend to get cut by leadership without early wins. Even a good, logical plan can wither and die this way. Not because the strategy was wrong, but because nobody could point to a measurable result inside the first six months.

In our case, we started with the data layer, with a concurrent investment in data science models that could deliver value even with imperfect data, plus third-party data enrichment for our sales force. New acquisition and retention campaigns based on the new data and models paid back our investment in 6 months and ultimately generated $120M+ in incremental revenue and $20M+ in incremental EBITDA over two years, a 4× ROI measured by test/holdout methodology.

We did this by building business cases for each phase and preparing campaign experiments to be ready when data and models came online. While the churn model was being built, we built the campaign creative, got offers approved by Finance, and designed the experiment, so that once we had model scores we were ready to execute. For third-party data enrichment, we built the integrations so that once we signed the contract to buy the data, it could immediately be ingested into our cloud data warehouse and show up live in our sales CRM the next day.

This allowed us to move almost immediately from having a new marketing and sales capability to executing experiments and measuring the results, drawing a direct line between the investment and the incremental profit we were making. When you are trying to keep up momentum in a transformation effort, results are always the most convincing.

And we didn't just focus on early wins that had no scale. Once proven, the new data and models were integrated into other engagement channels including email, text, and website. This is what scale looks like: one major investment that compounds across multiple systems, campaigns, and analyses. Knowing which customers are likely to churn is helpful to the entire organization, not just the Marketing department.

Question 4: Are we investing in the future state?

The half-life of marketing technology architectural decisions has shrunk. Cloud data platforms, composable architecture, agentic AI, decisioning at the edge. Each of these has provided new capabilities and new architectural possibilities in the last five years. Most CMOs feel behind the technology curve today. Imagine where you'll be in three years if you are still building out last year's reference architecture.

Marketing leaders need to get educated on where capabilities and customer expectations are heading, and bet on a version of that future they have conviction in. Envisioning exercises help. Document a potential future customer experience (for example, customers setting up buying agents to monitor sales and buy when the price hits a target) and work backwards from it. That kind of exercise keeps your investments aimed at the future, not the past.

The good news is you probably already have a great source for this information inside your company. Your internal technical partners and developers. Every major architectural shift I have understood in time to make a bet on, I learned about from the people building the systems. APIs, cloud, composable architecture, decisioning AI. Engineers were talking about each of these for years before they showed up in the marketing trade press.

Jeff Lawson, the founder of Twilio, wrote a book called Ask Your Developer that makes a related point. Treat developers as strategic partners, not order-takers, and you will see further than competitors who keep technology at arm's length. The same instinct applies inside a marketing organization. The closer you are to the people building, the less likely you are to fund yesterday's architecture.

By staying close to my technical partners at the retailer, we avoided buying a 2018-era integrated CDP and instead prepared ourselves for a composable CDP layered on top of our own enterprise data cloud. By the time we were ready, the composable model was the dominant direction and we didn't find ourselves stuck in the past. The same architectural choice made us AI-ready in a way the legacy stack vendors could not match. Our agentic AI pilots had access to all our customer data, not just the portion that lived inside one tool.

I need to stress how important it is for leaders to be bold here. If you feel overwhelmed by the number of options you have now, trying to map out where marketing technology will be three years from now might seem like a fruitless exercise. The answer is not to give up planning, but to have an agile plan that looks 2 to 3 years out, then re-evaluate and change course every quarter.

You may not see the lighthouse, but as the captain you still need to chart a course.

What to do this week

Block an hour this week to pressure-test your current marketing technology roadmap. Is there strategic rationale for the order of investments? Does each step earn a return you can defend? Are there dependencies necessary for success that aren't included on the roadmap, and therefore at risk of not being prioritized? No marketing transformation is without risk, but getting your sequencing correct will improve not only your chances of success, but also the ROI of each investment.

Strategy determines the destination. Sequencing determines whether you arrive.