Marketing Through a Business Operations Lens

With Operations Expert, Rae Lewis

Rae Lewis, founder of ThinkLogIQ, analyzes what marketing teams and businesses in general are getting right and wrong from an operations perspective.

What inspired you to found ThinkLogIQ, and what unique value does a boutique advisory firm bring to growth-focused companies?

ThinkLogIQ came from watching the same movie play out again and again across my career: Businesses often invest millions in cutting-edge technology like cloud platforms or analytics tools, only to find themselves puzzled a couple of years later when the expected returns failed to materialize.

We are seeing the same patterns with AI implementation. Organizations seeking modernization are facing gridlock. This shows up as organizational resistance, delayed milestone delivery, over-investments, too many planning sessions, revenue losses, and unmet promises to shareholders. In general terms, there is a lack of execution.

A detailed examination reveals that the technology itself is not the problem, but rather it is the connection between technology modernization, business value, and people. Bridging these areas unlocks the full value of a transformation.

This is where ThinkLogIQ’s years of fluency across business and technology come into play. We are not the firm that comes in with an army of consultants and a playbook. We work side-by-side to create relevant and sustainable business outcomes. We untangle the complexity of technical debt, business model constraints and internal friction. We co-create sustainable business value.

What happens when businesses go from seeing digital transformation as technology adoption to a core driver of revenue growth?

An organization that sees digital transformation as just another technology project is [trying to] do the same thing at greater speed, hopefully at lower cost and less risk. But there is so much more to be gained.

Digital transformation should not be viewed as an IT project but as an essential part of how the business operates. Everything shifts when digital transformation is seen as a core lever for revenue growth. The questions asked change from “what features should we build?” to “how can we drive revenue?”

[For example] engineering suddenly understands their connection to revenue, sales, and operational constraints. Strategy and execution become the same conversation.

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A lot of companies are betting big on AI right now. What are they getting wrong and what are they getting right?

Here’s what they’re getting wrong:

Most companies just jump into “Lets deploy AI” without considering fundamental questions of what it means in their context: culture of the organization, impact to broader market, customer impact, and risks.

Organizations that stall AI consideration and adopt a “wait and see” approach are also less likely to succeed.

In addition, many organizations are skipping the fundamentals. One of the most critical of these is to ensure that they have clean, quality data, in other words, data that is accurate, timely, and unbiased. They build upon mediocrity by [implementing without] performing a review of workflows, data requirements, systems, and technical infrastructure capacity. For example, an agentic AI chatbot touches multiple systems such as the CRM, billing systems, and customer APIs.

They treat AI as a human replacement technology, rather than tool augmentation and co-pilot. This sets in place the type of organization resistance that creates friction.

Here’s what they’re getting right:

I will say that the companies that are getting it right adopt a people-centered approach to AI implementation. They understand that AI is a tool and not replacement for an individual, human intervention is a requirement, and they continuously frame this for the organization.

They understand the importance of data as the fuel for AI and take the perspective of building out a data-first culture. They pinpoint data risk and deepen their understanding of the need for compliance to HIPAA, GDPR, CCPA, and EU AI regulations.

They invest in change management and AI literacy. Many require foundational AI training before employees can access AI tools.

They understand human-in-the-loop oversight. One example [from our clientele] is the piloting a legal AI tool that accelerated contract review by 80%. It worked because we built it to augment a lawyer’s judgment, not replace it.

The Marketing team might set a goal such as “Increase MQLs by 30%.” This is not a business outcome.

How should marketers use operational KPIs and OKRs to align campaigns with broader business objectives?

This is a tricky question, and this is where most organizations might get stuck. They start with metrics as opposed to business outcomes.

The Marketing team might set a goal such as “Increase MQLs by 30%.” This is not a business outcome.

What is more meaningful is an OKR such as the following:

• Objective: Establish digital channels as a primary revenue driver.
• Key Result: Generate $5M in qualified pipeline from digital channels.

The difference forces you to think about the entire funnel, not just top-of-funnel volume, and makes you accountable for quality, not just quantity.

The most basic test is: “would this OKR make the CFO and CRO see the impact?” If Finance thinks it’s too ambiguous and Sales thinks it’s disconnected, then the OKR needs to be revisited.

KPIs ladder up to the business outcome, so, for example, you will have KPIs for campaigns, engagement, lead conversion, and then the handoff to sales and ladder to revenue.

Measures drive accountability, ownership, clarity, and motivate action—all of which
are needed to drive decision-making, sustain alignment, and execution.

What are some of the biggest misconceptions marketers tend to have about business operations and how their efforts fit into the bigger picture?

The biggest misconception is this: Marketers do not see themselves as operators in business operations when in fact they are.

Another [false] perspective is that creative impact and operational excellence cannot exist side-by-side. But they can, and I dare say that they are the foundation of a virtuous cycle of success.

Here is one example: I scaled real-time performance visibility from 30% to 90% with better BI tools. It did not impede creativity but in fact enabled it through clear and timely feedback loops. Marketers could see what worked, iterated faster, and had data to back their decisions.

They are fully engaged in disciplined data governance, API management, and system optimization if using complex tools such as Salesforce. The complexity of martech requires Marketers to be operators.

Finally, marketers massively underestimate tech stack complexity—your martech stack is as complex as any engineering system and requires the same discipline around data governance, API management, and system optimization.

Without operational excellence, marketers can lack credibility when requesting investment from the broader organization.

Why is operational excellence non-negotiable for marketers aiming to deliver measurable ROI?

Operational excellence is about process optimization, consistent quality, empowered employees, continuous improvement, and minimal friction [through the marketing funnel and sales pipeline and then] from input to customer.

Without operational excellence, marketers can lack credibility when requesting investment from the broader organization. Their programs will remain stalled without being able to achieve the level [they could be at with] investment. They are seen as a cost center not a value lever for customer retention and revenue retention.

Operational rigor and a data-driven culture are essential to measure impact. This cannot be achieved without consideration of OKRs, KPIs, accountability frameworks, and continuous improvement and standard prioritization frameworks. This creates transparency into [the whole process from awareness and engagement] to input and customer value delivered.

I was able to drive eight-figure savings through data-driven programs and operational rigor—clear KPIs, accountability frameworks, continuous measurement. Operational excellence provides the foundation for attribution, forecasting, and optimization.

CFOs and CEOs speak the language of operations, efficiency, and ROI. Marketers who demonstrate operational rigor earn a seat at the strategic table. When marketers look at themselves as operators and embed operational excellence [into what they do], they can be seen as growth drivers.

I once maintained the Rule of 40—a SaaS benchmark balancing growth and profitability—while enabling triple revenue growth. This required operational discipline across every function including marketing.

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About Rae Lewis