While many in the go-to-market world focus on measuring revenue and closed-won targets, too many neglect pipeline creation. Pipeline predictions are a crucial step for revenue, but also impact future pipeline creation, coverage and more. Why do so many teams struggle to predict pipeline?
Challenges in Projecting Pipeline
Sales teams often have reliable methods to forecast revenue, but marketing teams struggle to project pipeline accurately. Lack of crucial data and insights, such as lead quality and conversion rates, makes it difficult for marketers to commit to specific numbers, impacting revenue targets.
There are additional complications, such as subjectivity in human interactions. Sales involves people on both sides, and predicting how individual sales representatives will perform can be uncertain. Salespeople's intuition, negotiation skills, and ability to build rapport can all play a significant role in influencing the pipeline. These factors are more difficult to quantify.
Understanding Funnel Metrics
To accurately project pipeline, marketers need to eliminate guesswork and use reliable data. Key metrics to analyze include conversion rates at each stage of the funnel. They also include average velocity of prospects moving through the stages, and identifying leakages where prospects drop out.
Sales pipelines can involve multiple stages and various decision-makers, making the process complex. Each prospect may have unique needs and timelines, and accurately gauging their progress through the pipeline requires a deep understanding of their individual circumstances.
It is harder to predict pipeline projections than revenue because of three key components: timing, value, and quantity. Marketing campaigns may take various amounts of time to create leads and qualify prospects for pipeline. However, each account may not be worth the same value to the company. Additionally, leads are rarely created evenly week over week and month after month, which can impact sales bandwidth and timing as well.
Analyzing Data and Metrics: By understanding the current composition and health of the pipeline, marketers can optimize their strategies to achieve targets. Monitoring bottlenecks and leakages helps identify potential issues and friction points, leading to better marketing-to-sales handoffs.
Pipeline prediction is harder when companies or industries have longer sales cycles. When it takes months or years to move a prospect from interest to closed deal, it's challenging to accurately predict pipeline creation in the short-term.
Analyzing Pipeline Composition: Examining regions, job titles, industries, and channels of leads and opportunities provides insights into the pipeline quality. This understanding helps refine Ideal Customer Profiles (ICPs) and target the right audiences.
It’s imperative to note that customer preferences and behavior can shift rapidly, driven by changes in technology, social factors, or market dynamics. These shifts can impact the sales pipeline, making it difficult to anticipate future outcomes.
Importance of Predictive Pipeline Intelligence: Stitching together reports and relying on guesswork is not reliable for pipeline projections. Integrating predictive intelligence, such as RevSure, allows marketers to turn more leads into opportunities and gain real-time pipeline projections. Predictive intelligence provides insights into lead behavior, roles, verticals, and segments most likely to convert, helping achieve revenue goals.
Overall, predicting the sales pipeline requires a combination of data analysis, sales expertise, an understanding of market dynamics, and the ability to adapt to changing circumstances. While advancements in technology, such as predictive analytics and AI-based solutions, can improve accuracy, complete certainty remains elusive due to the inherent complexity and human element in sales processes.
