Categories Articles, Sales and Marketing

The sales cycle has long been one of the most fundamental principles in sales. It’s a core part of Sandler’s techniques for closing more deals in the same amount of time. It’s held up by Salesforce.com as an example of how the most efficient sales teams set themselves apart. And Inc. believes it’s so critical to a company’s success that it should never be far from the minds of CEOs.

The only problem is that, in almost every real-world application, average sales cycle is meaningless.

The Myth of the “Average Sales Cycle”

Let me back up for a second. A few months ago, during the worst of Boston’s historically bad winter, I overheard a conversation on the T between a couple of tourists. I may be exaggerating it a bit in my memory, but I really think it went something like this:

Tourist #1: “This is unbelievable. I knew Boston got cold, but I had no idea it would be this cold.”

Tourist #2: “I know! I didn’t even bring my gloves!”

Tourist #1: “Me neither! Before we left, I looked up Boston’s average temperature, and it said it was 50 degrees! This is not 50 degrees!”

It’s easy to see where these tourists went wrong. Boston in February is completely unlike Boston in July, and to group them together is just foolish. These tourists made a mistake I never even considered, and it could very well have ruined their trip.

The amazing part, though, is that this rookie mistake is exactly like an error that sales leaders make all the time: They think of (and report) their sales cycle as a single number.

And this mistake has tangible, real-world repercussions. Just as thinking of Boston as having a year-round average temperature makes it hard to pack, plan and prepare for a vacation, boiling your sales cycle down to a single “average” makes it impossible to take the specific steps you need to in order to optimize your sales process and win more deals.

What’s the remedy? Sales leaders need to think of their sales cycle as a collection of meaningful numbers that must be sliced up and analyzed individually to offer any real insights.

Learn More About Measuring Sales Cycles»

All the World’s a Stage

The first step is to get granular when you think about your sales process.

Your sales process is not a monolith. Every team’s process is broken into distinct stages, which are necessary for forecasting accurately, prioritizing activities, and determining the next right step for each opportunity in your pipeline.

It’s also necessary for understanding your sales cycle.

WIthout stages, your sales cycle offers almost nothing insightful. What good is it to know that your average sales cycle is 120 days? What can you do with this information? Sure, you can say that it would be better if it were shorter, but how can you actually make it shorter. In this scenario, you’d be just as well off throwing spaghetti at a wall and seeing what sticks. (Full disclosure: This trap is so common, we’ve been known to fall into it ourselves.)

But if you slice your sales cycle up by stage, it starts to reveal some pretty interesting (and actionable) insights.

Look at the image above. It doesn’t take long to see which part of this team’s sales cycle is contributing the most to its length. This level of granularity makes it much easier for the Sales VP to institute changes that actually move the needle.

For example, if you see that your demo stage is eating up the bulk of your sales cycle, it may be time to take action by coaching your reps to deliver demos more compellingly or work with your product team to streamline the demo process.

But the truth is that even breaking your sales cycle into stages isn’t enough. Unless your company sells a single product to a uniform customer base, you also need to break your sales cycle down by deal size, product line and lead source.

Wearing a Sweater in August

Deal size can have a huge impact on sales cycle. More stakeholders, more organizational red tape, more need for budget approval ‒ these are all things that slow down the velocity large deals.

They also mean that your assumptions about how long a certain deal will take to close (or how likely it is to close at all) need to account for deal size. If your team’s “average” sales cycle is 30 days and you see an opportunity lingering in the pipeline for 80 days, it may lead you to believe that the deal is unlikely to close. But what if that opportunity is 4x bigger than your average opportunity? In this case, you would want to analyze your average sales cycle for deals in that size range to get an accurate estimate of how long you can expect this one to stay in the funnel before it closes. Otherwise, you run the risk of relying on overly general data to make specific decisions. In other words, you wind up wearing a sweater in August.

Knowing your sales cycle for different deal-size buckets ‒ such as SMB, mid-market and enterprise ‒ is not only important for making tactical decisions (like whether to closed-lost a specific opportunity), but also for developing your team’s overall strategy. For example, if you realize that enterprise deals take 10x as long to close as mid-market deals, and that they have a much lower win rate, you might decide to de-emphasize enterprise deals and instead focus on pushing a swarm of smaller deals past the finish line. (And, of course, this principle applies in the reverse as well.)

What Are Your Sales Cycles?

The bottom line is that it’s not about your sales cycle, it’s about your sales cycles. The most effective sales teams are the ones that go way beyond broad generalizations ‒ like average sales cycle and average sales price ‒ and start looking at their sales results on a much more granular level. Just as baseball teams are beginning to look well beyond batting average to evaluate players, the best sales teams need to look at a larger variety of narrower metrics.

Sales cycle is the perfect place to start. It’s a metric that is used (okay, misused) by almost every sales team, and one that has a huge impact on your company’s bottom line.

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Mike Baker
Mike Baker is the Content Strategy Manager at InsightSquared, where he helps distribute original eBooks, articles and guides about data-driven sales and marketing. He has a BA in English and Journalism from Oberlin College.
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