Chris Walker is the founder and CEO of Refine Labs. He discusses the importance of RevOps in Go-To-Market tactics and clarifies the typical problems businesses need help with, such as understaffing and underfunding operations research.

Chris emphasizes the value of standardized data, using science to inform strategic choices, and promoting a new strategy that works around account activations, conversions, and a thorough examination of buyer-centric data. He will debunk myths and answer questions related to RevOps.

Myth: RevOps is an essential element in the Go-To-Market

RevOps is now the most important go-to-market function, but in reality, businesses still underfund and understaff it, making it primarily an order-taker role with no creative effort.

Responding to reporting requirements and putting tools in place is insufficient for this role to drive go-to-market strategy.

He sees a mismatch between perceived priority and actual investment. Although it is of utmost importance, it is not effectively implemented in large-scale companies where RevOps teams are significantly smaller than sales and marketing teams.

How can companies make RevOps a priority?

One critical component absent from existing RevOps procedures is strategic decision-making. Companies define RevOps only in tactical duties like implementing tools and producing reports. This reactive-fulfilling ticket ignores RevOps' strategic potential.

He suggests splitting RevOps's jobs into tactical and strategic responsibilities. The strategic department would use data and standard frameworks to inform go-to-market choices and distribute budget across SDRs, Marketing, and Sales based on insights obtained from data.

The RevOps team is currently pressing the CMO and CRO for tactical data due to their lack of strategic expertise. They believe that separating these responsibilities is necessary to improve overall performance.

Chris suggests switching out RevOps' siloed structure with an integrated strategy that involves all departments, marketing, sales, and SDRs collaborating throughout the revenue process to increase efficiency and offer a clearer go-to-market strategy.

Can RevOps strategies be combined with the enhanced LS approach to give businesses effective advice?

Chris goes beyond traditional lead metrics and suggests an entirely different operating model. His suggested criteria for tracking success include account conversions, activations, and a hero pipeline. Performance indicators would be used to standardize this hero pipeline, and it would be connected to revenue.

By altering these key performance indicators, companies can encourage teams to work towards overall business results.

Most CMOs know the drawbacks of the traditional demand waterfall approach, including the mismatch it causes between marketing and sales. Many try to solve the issue using account-based marketing (ABM) solutions. He believes a more substantial change to the core operational architecture is required.

This thorough analysis emphasizes the need to reevaluate the transparent performance indicators of the old paradigm, with winning rates ranging from 4% to 35%.

What advice can the audience use to incorporate one aspect of the hero model into their RevOps strategy?

Companies define qualified pipelines randomly based on stages (e.g., SQL). This strategy is inconsistent and unproductive.

Alternatively, businesses could define qualified pipelines by past win rates. For example, a contract might be eligible for the hero pipeline if its victory rate for the preceding six months was greater than 25%.

Marketing now focuses on goals that align with sales and revenue targets instead of using stage evaluations to measure progress. The hero pipeline is designed to adjust quickly to these variations and, in the best-case scenario, maintain a well-qualified pipeline even if win rates decrease.

What are the technical things that keep the market up at night?

The key market worry is the absence of standardization in RevOps. Businesses recreate the wheel because they depend on the abilities of one or two people. Conflicts result from a lack of agreement and diverse definitions. Everybody perceives evidence differently, leading to the formation of individual ideas rather than a shared view.

Chris compares this to a business's profit and loss (P&L) statement. Using standardized accounting principles, executives can all clearly understand the company. He makes the case for similarly using revenue data. If the organization used a standardized data model, executives could make informed decisions and share a similar perspective.

How does he identify and treat operational symptoms when navigating the complexities of various corporate structures and internal dynamics?

Chris describes how businesses face data issues, highlighting ineffective organization and analysis despite gathering large amounts of data.

He outlines how his business manually transforms customer data into a standardized model to compare it to benchmarks from already examined businesses.

Patterns, trends, and data gaps are found during this process, which produces suggestions for the best possible data architecture.

Companies can solve the problem of insufficient focus on relevant indicators by shifting from manual analysis to real-time insights and making faster, data-driven choices.

Where does Chris see the future of RevOps?

Businesses continue to use outdated measures such as leads and MQLs with the introduction of new tools. He draws attention to the difference between attribution and KPIs, pointing out that although some businesses overstate effectiveness through liberal attribution models, basic business KPIs could be trending negatively.

Core KPIs are given top priority, and the organization projects a move towards a more KPI-driven and attribution-supported approach. His organization tracks key performance indicators such as closed-won revenue, hero pipeline creation, and marketing ROI using a standardized approach, which gives a clear image of business performance and facilitates a more in-depth examination of program contributions.

What measures and modifications will the customer success area see in the coming years?

Businesses have been finding it challenging to bring in new business over the previous six quarters. He criticizes marketing teams for giving Net Revenue Retention (NRR) more weight than "closed net new revenue." He believes that budgets should be assessed according to their effect on gaining new clients, not NRR, to avoid the neglect of ROI and new business growth. He proposes reallocating go-to-market budgets according to a percentage of net new business instead of revenue to address growing inefficiencies as income rises.

What was his journey from being a computer scientist to working in marketing and CRO?

Revenue generation can take on a scientific methodology similar to medicine or pharmacology. This involves identifying and executing effective tactics using standardized data and a current operational model that reflects modern purchasing behaviors.

He criticizes traditional go-to-market methods that rely too much on experience and opinion, highlighting the necessity of standardized data for objective comparisons between companies, similar to research studies in medicine.

RevOps's evolution makes a data-driven approach to revenue generation possible, in contrast to the problem of unqualified influencers on LinkedIn, which makes decision-making difficult because marketing KPIs are not standardized.

Chris provides a unique, data-driven strategy for generating revenue. This strategy is based on a scientific understanding of buyer behavior and standardized KPIs. By utilizing these components, businesses can drop outdated methods and improve their go-to-market tactics.

Listen to the full episode here.