3 steps to align your stack with strategy

“Stack follows strategy” is a well-known mantra. But how do you actually do it? Many teams claim it’s the right approach, but few can describe what the approach looks like in practice. Even fewer know where to start.

What we’re missing is a practical guide on how to make it work — let alone proof that it works — until now. Our research can show you how to align your martech stack with business strategy.

Decoding strategy and value

In recent years, our team at MartechTribe set out to uncover the real relationship between martech and business strategy, while:

• Studying 1,533 real-life technology stacks from companies across 16 industries. 
• Analyzing 15,384 tools and mapping them against 4,758 specific business requirements. 

Here’s what we found.

• Martech is used very differently across industries.
• Business models like B2B, B2C and B2B2C show distinct patterns.
• Company size influences complexity, but less than expected.

What really stood out were the habits of outperformers, i.e., companies in the top 30% based on revenue per employee. They don’t just buy more tools. They build lean, focused stacks that reinforce their go-to-market (GTM) model and customer expectations. That is their focus.

If your company is planning a martech refresh or reviewing its stack, start by working backwards from your customer and strategy. Don’t begin by adding more state-of-the-art tools. Instead, focus on identifying what truly drives value in your market.

That process starts with three steps.

• Understand the big shift in your industry.
• Detect how it impacts your customer relationships (GTM strategy).
• Choose the martech that enables your most important strategic bets.

Let’s see how that works in three different industries: 

• Banking, financial services and insurance (BFSI).
• Manufacturing.
• Education. 

Each example follows the same pattern: a strategic shift, a big bet and the martech that makes it possible. 

1. Banking, financial services and insurance

Big shift: From compliance-first to customer-first

BFSI organizations are moving away from decades of compliance-driven interactions toward customer-first experiences. Historically, the tech stacks were built around regulations. Today, customers expect instant, mobile-first and conversational service, without sacrificing trust or security.

• 56% of consumers are open to experimenting with new ways of interacting with their bank. 
• While 66% of those aged 18-24 want their bank to offer interacting in a virtual branch or office.

One of the three big bets in BFSI is to set up human-like AI service. The leading bet is on AI that solves human problems. Customers want to message their bank like they do a friend — whether through mobile apps, WhatsApp or embedded widgets — and receive help that is fast, accurate and emotionally aware.

Supporting martech: AI-driven service stack

This shift depends on three foundational moves.

• Train AI on real interactions: Personalization and testing tools adjust tone and timing; analytics platforms help refine response quality.
• Deploy AI across touchpoints: Mobile apps and CMS must support integration with chatbots and third-party platforms like WhatsApp.
• Enable seamless escalation: When AI hands off to humans, context must be retained, yet many BFSI platforms still struggle to consistently deliver on this.

Despite heavy investment and high maturity, the value of customer service platforms and chatbots is limited (see graph below) in BFSI. Interestingly, genAI adoption is growing fastest in these areas, not as an innovation edge, but as a workaround to compensate for the gaps left by legacy systems that haven’t delivered so far.

BFSI outperformers don’t just automate, they rethink the entire support model. The real shift is from call-center processes to AI-augmented, emotionally aware conversations that earn trust in moments that matter.

2. Manufacturing

Big shift: From standard products to tailored service models

Manufacturers are moving beyond mass production toward modular, personalized offerings. Instead of simply delivering parts or equipment, they are expected to deliver tailored solutions, predictive support and seamless communication. 

This shift is no longer optional. Between 2019 and 2023, 98% of manufacturers began digital transformation efforts. Buyers now expect relevance, speed and integration across every step of the journey.

One of the important big bets is to add tailored solutions to the portfolio. Manufacturing outperformers are evolving from fixed SKUs to configurable, need-based solutions. This requires not just adapting the product catalog, but rethinking how solutions are designed, delivered and communicated across channels. The portfolio must flex to reflect each customer’s context.

Supporting martech: Personalization through product and content orchestration

This shift is enabled by a tightly connected martech stack.

• Product management platforms define and automate personalized offerings based on customer data.
• MAP and CMS platforms deliver personalized journeys, content and communications.
• Agile product teams supported by workflow and collaboration tools enable continuous adaptation.

Still, many manufacturers report limited success with traditional personalization tools. GenAI is increasingly used to overcome these gaps, offering new ways to tailor content and recommendations where legacy systems fall short.

Manufacturing’s digital edge is no longer about operational efficiency alone. It is about turning customization into a competitive advantage, from configuration to communication.

3. Education

Big shift: From degrees to dynamic learning

The value of a degree is no longer built to last. Where a diploma once supported a 30-year career, its relevance now fades within four to six years. With the average half-life of a job skill down to just five years, learners are shifting toward faster, more flexible and targeted learning options. The new path to advancement is no longer a multi-year degree, but a modular course that meets immediate needs and keeps pace with rapid change.

One of the pivotal big bets is to deploy learner-driven course customization. To meet this shift, education providers are betting on personalized learning paths. Students expect their course journey to reflect their skill level, interests and progress. This means using real-time data to tailor content, adjust difficulty and provide just-in-time support. Customization is no longer a nice-to-have; it is the foundation for learner engagement and outcomes.

Supporting martech: Adaptive and personalized learning stack

This bet is supported by a combination of.

• CDP and cloud data warehouse (CDW) systems to track learner behavior and surface insights.
• CMS, CRM and MAP tools to deliver the right content and re-engage learners.
• Audience marketing platforms to identify which students need what and when.

Despite widespread tool use, many technologies in this space show limited value unless applied with precision and skill. GenAI is helping close the gap, especially in content generation and real-time learner support via chat.

In education, personalization is not a future state. It is the new baseline. Institutions that embrace this shift are not just retaining learners — they are redefining what learning means.