How Funnel Volatility Effects Your Account Based Strategy

By Marko Savic

Volatility is my favorite way of looking at funnel metrics over time. It’s an immediate way to identity where your funnel is predictable and where you have blockage points. Volatility is easy to see. Plot any metric you want over time — conversion rates, deal velocity by campaign, size of deals by industry, or volume by rep.

Measuring volatility is a great way to see how new processes are improving your funnel. Moving from a lead-based model to an Account Based Marketing and Account Based Everything model is a great time to take stock of your metrics and evaluate how your new ABM/ABE strategy is improving the quality of your deal flow.

There are four types of volatility to look for:

  • High volatility
  • Seasonality
  • Decreasing volatility
  • Low volatility

True volatility represents chaos in your funnel: imagine this chart is about the average deal size for Closed Won opportunities over time — with such wild swings in deal size, you’d have a challenge predicting how many deals you need to hit a future bookings target.

The same could be true for conversion rates by opportunity stage. If you have a volatile stage, you’re not going to be able to rely on it for your forecast. Volatility is telling you there’s something you need to solve.

Volatility tells a story

There are three possible reasons for volatility: new segments are emerging in your funnel, there’s seasonality to your business, or there’s a real problem in your funnel.

Identifying where your funnel has a blockage point is imperative to optimizing your operations. When you see a volatile metric, your first step is to rule out if new segments or seasonality are the cause. If neither are the cause, drill in to figure out the problem. Below are some ways to look at the data to see what you’re dealing with.

1. New segments are emerging in your funnel

Volatility can tell you when your business has forked and you need to think about it differently. This requires you to break out each data point, such as plotting Closed Won opportunities by deal size. Box plots are a great tool that can help you visualize segments easily.

Imagine the illustration below is about price point — low MRR on the left, high MRR on the right. You can see a few different stories:

Data scientists: please forgive the visualization. This isn’t a real box plot.

You have distinct segments.
You can see distinct low-MRR and high-MRR segments, with a big gap between them. Your price point looks volatile because it oscillates between these two extremes, but really you have two main prices. This could be an SMB and Enterprise offering, a split by industry, or even approaches in discounting. You’ll need to explore the data to determine what causes the segmentation.

You have a niche.
This is great! You’re unlikely to see volatility unless there is a real problem, like the niche moves every month. In our pricing example, a niche could be a firmly mid-market deal.

You have no pattern.
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Source:: Business2Community