Running RevOps
Business is challenging in any environment.
The current climate presents unique challenges, however.
We have more data about our prospects than ever before. There are endless data sources, enrichment providers, intent signal providers and other companies catering to the problem of attention — how do you get the attention of your ideal clients?
The top of funnel is wild these days. There are more channels than ever before. Inbound, outbound, nearbound… boundless avenues for direct sales and partnership-based approaches.
The middle of the funnel is truly uncharted territory. While there is a great deal of emphasis on lead counts, MQL conversion rates, cost per lead and other metrics related to the top of the funnel… pipeline development metrics are less often discussed.
That’s largely because pipeline development metrics are not measured.
What goes unseen stays unimproved.
Orchestrating our outreach through these labyrinths requires careful planning and even better execution. That is precisely what Revenue Operations brings to the table. Planning and execution as we work collectively toward the mission of generation revenue.
What does it take to run revenue operations in an organization?
The DNA of a RevOps Leader
A world-class RevOps leader possesses a valuable combination of technical, analytical, interpersonal, and strategic skills that enable them to drive significant revenue growth and operational efficiency within an organization.
There isn’t a perfect blueprint to being a RevOps leader. Below are the common traits among all the great professionals I’ve been fortunate to work with and learn from.
Data-Driven Decision Making: The ability to analyze complex data sets, extract actionable insights, and utilize those insights to inform strategic decisions is paramount. This involves proficiency in data analysis tools, statistical methods, and an understanding of KPIs and their connection to business outcomes.
Cross-Functional Collaboration: Revenue operations is inherently cross-functional, requiring close collaboration with sales, marketing, customer success, and finance teams. The ability to build strong relationships, communicate effectively, and foster alignment across these functions is crucial.
Process Optimization: A deep understanding of business processes, the ability to identify bottlenecks and inefficiencies, and a passion for continuous improvement are essential. This includes expertise in process mapping, automation tools, and change management strategies.
Technology Proficiency: Revenue operations leaders must be well-versed in a wide range of technologies, including CRM systems, marketing automation platforms, sales enablement tools, and data analytics software. They should be able to evaluate, implement, and optimize these technologies to support revenue goals.
Strategic Vision: The ability to think strategically, anticipate future trends, and develop long-term plans that align with the overall business strategy is critical. This involves a deep understanding of the market, the competitive landscape, and the customer journey.
Leadership and Communication Skills: Inspiring and motivating teams, communicating a clear vision, and building a culture of collaboration and accountability are essential leadership qualities. Effective communication skills, both written and verbal, are also necessary for conveying complex information to stakeholders.
Change Management: Revenue operations often involves implementing significant changes to processes, technologies, or organizational structures. The ability to manage change effectively, overcome resistance, and ensure smooth transitions is vital.
Problem-Solving and Critical Thinking: The ability to identify problems, analyze root causes, and develop creative solutions is crucial in a dynamic and complex business environment. This involves strong analytical skills, critical thinking, and a willingness to challenge assumptions.
Customer-Centricity: Understanding customer needs, preferences, and behaviors is essential for developing effective revenue strategies. This includes the ability to gather and analyze customer feedback, identify opportunities for improvement, and deliver personalized experiences.
These are great skills to take anywhere in business, or life in general.
By mastering these skills, revenue operations leaders can drive significant improvements in revenue generation, operational efficiency, and customer satisfaction, ultimately contributing to the overall success of the organization.
The Job Description
RevOps plays a vital role in modern business. You provide brains, brawn, duct tape and one of the few sets of eyes on the entire revenue engine.
Assuming you have some or all of the characteristics I described above, your next step in running RevOps is looking at where your company is now, and where you want to go.
Look at the current design and performance of the revenue engine.
Let’s imagine you take over as Head of RevOps and the revenue engine performance can’t even be analyzed because the data model is so bad that it makes accurate reporting impossible.
You need a plan.
This plan must outline a strategic approach to transform the current disorganized revenue engine into a world-class operation. The primary focus will be on establishing a strong foundation through data organization, process optimization, and technology alignment.
This will be followed by a phased implementation of best practices to drive efficiency, predictability, and revenue growth.
The plan can’t just say what’s going to happen, it needs to discuss the logistics of how.
Phase 1: Assessment and Foundation
Data Audit and Centralization:
Conduct a comprehensive audit of all data sources (CRM, marketing automation, finance, etc.) to identify inconsistencies, gaps, and redundancies.
Establish a centralized data repository (e.g., data warehouse) to consolidate and clean data for analysis.
Implement data governance policies to ensure data accuracy, consistency, and security.
Process Mapping and Documentation:
Map current lead-to-cash processes across sales, marketing, and customer success.
Identify bottlenecks, manual steps, and areas for automation.
Document standardized processes to create a baseline for optimization.
Technology Evaluation and Alignment:
Assess current technology stack for gaps and redundancies.
Identify potential tools to streamline processes and enhance data visibility.
Develop a technology roadmap for implementation and integration.
Phase 2: Optimization and Efficiency
Data Analytics and Reporting:
Implement dashboards and reports to track key performance indicators (KPIs).
Utilize data insights to identify trends, optimize sales and marketing efforts, and improve forecasting accuracy.
Establish a regular cadence for data-driven decision-making.
Process Automation and Optimization:
Implement automation tools to eliminate manual tasks (e.g., lead scoring, data entry, reporting).
Streamline processes to reduce cycle times and improve efficiency.
Continuously monitor and refine processes based on data and feedback.
Sales and Marketing Alignment:
Develop shared goals and KPIs for sales and marketing teams.
Implement a service-level agreement (SLA) to define lead quality and quantity expectations.
Foster collaboration through regular meetings, shared dashboards, and joint initiatives.
Phase 3: Growth and Scalability
Advanced Analytics and Predictive Modeling:
Utilize advanced analytics to gain deeper insights into customer behavior and predict future trends.
Implement predictive models to forecast revenue, identify high-potential leads, and personalize customer experiences.
Continuous Improvement and Innovation:
Foster a culture of experimentation and continuous improvement within the RevOps team.
Encourage feedback from stakeholders and incorporate it into future initiatives.
Stay current with industry trends and adopt new technologies to maintain a competitive edge.
Measuring Success: Key Metrics for RevOps Transformation
To ensure the success of the RevOps transformation initiative, it's crucial to establish a comprehensive set of metrics that align with the overall business goals and provide insights into the effectiveness of each phase. These metrics will be tracked and analyzed regularly to identify areas for improvement and demonstrate the value of the RevOps function.
There are many families of metrics you can measure.
Stats about the data (volume, velocity, quality, etc..) are useful. In some organizations they have metrics on their processes themselves, their technology stack maturity, etc..
Here are a few examples:
Data Quality Metrics:
Percentage of duplicate records in Salesforce and Hubspot.
Percentage of missing or incomplete data fields in Salesforce and Hubspot.
Data accuracy rate after cleaning and standardization.
Time taken to complete data pipelines and refresh the data warehouse.
Process Metrics:
Number of documented processes.
Number of identified bottlenecks and inefficiencies.
Time taken to complete process mapping and documentation.
Technology Metrics:
Number of identified technology gaps and redundancies.
Time taken to complete technology evaluation and develop a roadmap.
My favorite metrics are related to the power, efficiency, consistency and reliability of the revenue engine. These can look at the sales performance, marketing volumes and conversions, and of course the CS vitals as well.
These statistics and analytics provide health and performance readings for the revenue engine. Here is a short list for you to evaluate:
Sales Metrics:
Lead conversion rate from MQL to SQL
Opportunity win rate
Average sales cycle length
Sales quota attainment
Revenue growth rate
Marketing Metrics:
Marketing qualified lead (MQL) generation rate
Return on investment (ROI) for marketing campaigns
Website traffic and conversion rates
Customer acquisition cost (CAC)
Customer Success Metrics:
Customer satisfaction scores
Net promoter score (NPS)
Customer retention rate
Customer lifetime value (CLTV)
Operational Metrics:
Percentage of automated processes
Time saved due to automation
Data accuracy rate for lead scoring and routing
Number of leads touched by marketing campaigns
Once things start to work well then you can focus on engineering improvements.
These can be improvements to your forecasting methods, or to the processes themselves.
Predictive Modeling Metrics:
Accuracy of lead scoring models.
Accuracy of revenue forecasting models.
Lift in conversion rates due to predictive modeling.
Continuous Improvement Metrics:
Number of experiments conducted.
Success rate of experiments.
Adoption rate of new technologies and processes.
By tracking these metrics, we can gain a comprehensive understanding of the impact of the RevOps transformation initiative on the organization's performance. This data-driven approach will enable us to make informed decisions, identify areas for improvement, and ultimately drive revenue growth and customer satisfaction.
There are many experiments that RevOps can run to further improve the revenue engine. Here are experiment frameworks that I’ve used previously & encountered when I interviewed other operations professionals and revenue leaders.
Experiment 1: Lead Scoring Model Optimization
Hypothesis: Adjusting the lead scoring model to prioritize specific engagement behaviors (e.g., website visits, content downloads, demo requests) will increase the conversion rate of Marketing Qualified Leads (MQLs) to Sales Qualified Leads (SQLs).
Experiment: Create two groups of MQLs: one scored using the existing model and another scored using the adjusted model. Track the conversion rates of each group to SQLs over a set period.
Metrics: MQL to SQL conversion rate, sales cycle length, win rate.
Experiment 2: Personalized Lead Nurturing Campaigns
Hypothesis: Tailoring lead nurturing campaigns based on industry, company size, or job title will result in higher engagement and faster lead progression through the funnel.
Experiment: Segment your lead database based on relevant criteria and create targeted nurturing campaigns for each segment. Compare engagement metrics (open rates, click-through rates, conversion rates) across segments.
Metrics: Email open rates, click-through rates, conversion rates, time to MQL.
Experiment 3: Sales Playbook Effectiveness
Hypothesis: Implementing a standardized sales playbook with tailored messaging and objection handling techniques will improve win rates and shorten sales cycles.
Experiment: Divide your sales team into two groups: one using the new playbook and one using the existing process. Track win rates, average deal size, and sales cycle length for each group.
Metrics: Win rate, average deal size, sales cycle length.
Experiment 5: Account-Based Marketing Pilot
Hypothesis: Targeting high-value accounts with personalized ABM campaigns will result in higher engagement, faster deal progression, and increased revenue from these accounts.
Experiment: Identify a set of target accounts and develop personalized campaigns across multiple channels (e.g., email, social media, direct mail). Track engagement and revenue metrics for these accounts compared to a control group.
Metrics: Engagement rate, pipeline velocity, average deal size, revenue from target accounts.
Experiment 6: Sales Enablement Content Optimization
Hypothesis: Providing sales reps with more relevant, up-to-date, and easily accessible content will improve their ability to engage prospects and close deals.
Experiment: Create a new sales enablement content library with curated resources tailored to different stages of the buyer's journey. Track content usage, sales rep feedback, and deal outcomes compared to a control group using the existing content.
Metrics: Content usage, sales rep feedback, win rate, average deal size.
This is a lot — you will need to focus on communication and project management to succeed in revenue operations. Regular communication with stakeholders on progress and challenges are key.
Change management initiatives ensure buy-in and adoption. Pair these with training and support for team members on new processes and technologies — that is the most effective route to high-performance operations.
By following this comprehensive plan, you can transform the revenue engine into a world-class device that drives sustainable growth and profitability.
Just like the job description calls for!
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