How to Accurately Calculate Sales Cycle Length
The true sales cycle length is one of the most important metrics in a sales organization. Sales operations professionals pore over sales cycle statistics, looking for the points in which deals slow down or speed through, hoping to find ways to shorten the cycle. The shorter a company’s sales cycle, the faster they earn money. By applying insights gleaned from examination of the sales cycle to various elements of their sales process, a company can increase the efficiency and effectiveness of their sales team. There are a few ways to look at the sales cycle, each with its own pros and cons:
Lead Creation Date
The most obvious way to track a sales cycle length is to start with when leads are created in CRM, and end with when the deal is closed. This method gives sales operations managers the most comprehensive view of a customer’s journey from entry into their sales funnel through to the close of the deal. By examining a sales cycle length from the very first touch of a customer, sales teams can learn ways to improve their top-of-funnel activities like prospecting and marketing. Excelling at these early stages is essential to propelling customers through the sales cycle quickly and ensuring a strong pipeline.
The trouble here is that leads can be created at any time. Most companies that sell highly complex technologies and services usually want customers to have an understanding of the offering before a salesperson contacts them, so they’ll employ a variety of marketing and lead development tactics. A company could buy a set of leads and let them sit unworked in CRM for months or years. One of these leads could download a marketing eBook, which potentially creates a duplicate lead in CRM, and then months later request a demo, creating another lead and triggering a salesperson to actually pursue a deal. Measuring this sales cycle length according to the lead genesis becomes problematic; there are three leads attached to the actual opportunity. Deciding which to peg as the start of the sales cycle is difficult, because while each lead-generating event played a role pushing the customer through the funnel, it’s hard to say which was the actual “start”.
The variability of when leads are created and when they are actually worked, combined with the likelihood that many leads are likely duplicates, tends to skew analysis. This means sales operations managers have to constantly spend time checking in with their reps to determine whether leads are duplicates, and cleaning out their CRM. Then when they come to find a duplicate, they have to decide which to use for their analysis on a case-by-case basis. Though this gives them the accurate view of when a customer first came into the system and when it was worked, it creates a massive time sink and relies on subjective judgement, often resulting in inconsistent data and unreliable analysis.
Opportunity Creation Date
Some companies attempt to fix the problems that come with deduping leads by choosing to consider the beginning of the sales cycle as the time when a lead is converted into an opportunity. This reduces the amount of time the sales operations manager has to spend cleaning the data, and lets them keep more contextual information on deals in their CRM. This is a useful approach for some: it removes the inherent difficulty with lead-based sales cycle measurement and allows for the inclusion of richer data.
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However, this method limits the focus of analysis on deals that have already reached a certain level of velocity, and ignores the entire top of the funnel. It streamlines analysis by sacrificing comprehensiveness. This may be enough for companies that have a powerful marketing apparatus and maintain a strong flow of customers into the funnel, and want to focus on optimizing close rates for customers that are already in the pipeline. But for companies still building out their sales and marketing, who aren’t satisfied with their inbound lead flow, they need a process that allows them to efficiently study and iterate on their sales cycle from the first point that potential customers touch their system.
The Opportunity Creation method also falls short without hard standards set around when a lead is converted to an opportunity. A redeeming factor of leads is that despite the wide array of sources, they are all created through concrete events. But because Opportunities rely on salespeople to manually change the deal status in CRM, there’s never a guarantee that they’re created along consistent criteria. Experienced sales managers will implement strict rules around when leads must be converted to opportunities, but this still doesn’t assure the whole team will properly edit each deal every time. It’s very common for deals to be converted to opportunities right before they close, thanks to pessimism or simply lack of diligence. And without consistent data, analysis becomes unreliable.
Conversation Start Date
The third way companies are calculating their sales cycle is by when the sales conversation actually takes place. This is difficult to do while relying on manual CRM updates – no one wants to update CRM for every email they send to every prospect they target, especially the ones that get qualified out. It could take three or four emails and a call before a sales rep decides a lead is an opportunity, and the email and call data for leads that get qualified out is largely irrelevant. But for the deals that do close, it’s some of the most important data in the sales cycle, and measuring actual conversation length is the most accurate gauge of how long it takes deals to close.
This creates a conundrum for sales teams. Measuring by opportunity creation date ignores highly valuable early-stage information and relies on subjective qualification. Measuring by lead creation takes forever, is much more difficult and still doesn’t create totally reliable analysis. And measuring by conversation length places a huge burden on sales reps if relying on manual data entry.
The solution many are finding is to automate the entire process. Modern sales software can take on the entire burden of sales cycle analysis by automating CRM data entry, analyzing conversation length, and creating reports by deal, rep, team or company. This gives sales operations teams instant reports based on objective data, and frees sales reps from spending their day in CRM.