I’ll lay out a step-by-step process for defining the sales cycle and building an accurate, actionable sales forecast that drives more informed decisions.
The sales pipeline impacts every single decision the company makes, from hiring to expansion to the resources allocated for product and service delivery. But when the pipeline isn’t predictable and the data that defines it isn’t reliable, those decisions can be disastrous—especially for high-growth companies. Yet too many are playing fast and loose with the sales forecasting process.
I touched on the topic in Sales Pipeline Definitions Matter: No Decisions vs. Lost Deals, demonstrating the dangers of leaving the “no decision” stage poorly defined. This time, I’ll lay out a step-by-step process for defining the sales cycle and using those definitions to build an accurate, actionable sales forecast that drives better, more informed decisions.
STEP 1: Align the sales process with your customer’s buying process.
The buying process is different for every organization, but what’s important is to develop an understanding of your specific customer’s journey and ensure that your sales process mirrors that buyer.
Start by asking your prospect these questions:
- Why is your organization even buying?
- What’s the need, and how does it align to your organization’s goals?
- What urgency is driving it now?
- Do you have a budget established?
- Who influences the purchasing decision? (Get names and roles.)
Think about how the sales process might end at every phase—will they purchase, go to a competitor, solve the problem in-house or do nothing? I have seen more than 65% of all sales opportunities end in “no decision,” so figure out if that is a possibility as early as you can. If the buyer is not able to clearly articulate answers to the questions above and to walk you around the organization to ask each person involved in the decision, then you are most surely going to end in that dreaded “no decision.”
My main point is that unless the sales process reflects the buyer’s reality, the stages assigned to your pipeline and forecast won’t provide consistent win/loss/no decision percentages by stage.
Much of the value of these steps is not in the actions you take. Rather, it’s how they help you learn more about WHY the prospect will buy.
STEP 2: Define each stage of the sales process.
Every buyer needs to go through a series of stages from prospect to customer, and those stages must be clearly defined. In No Decisions vs. Lost Deals, we sketched out a six-stage process that began with prospect qualification and ended with contract negotiation.
Most organizations define the stages of their sales process, but many are missing these two key ingredients:
Are you just slapping a label on those pipeline stages, or are you providing a detailed definition? Each stage can mean different things to different people. Unless the definition is spelled out in a way that requires you to accomplish a series of objectives before you can move the prospect to the next stage, the data in your system and the input from your team won’t add up to a coherent and trustworthy story. If you define each stage as a step, you’re not going deep enough; each stage should be broken down into a series of steps or a checklist. Only after that checklist is complete can the prospect move to the next stage. Much of the value of these steps is not in the actions you take. Rather, it’s how they help you learn more about WHY the prospect will buy.
Many software companies start a sale with a demo of the product—WRONG. In the first phase, you should ask as many sales qualification questions as possible before you show the product. It’s a tricky dance because you do not want to irritate the prospect, but you have needs, too, and your time is equally as important as the buyer’s.
Every stage in your pipeline should have an outcome assigned to it, whether that means the buyer progresses successfully to the next stage, is reinserted into an earlier stage or is removed from the system as a “no decision.” When stages don’t culminate in a decisive outcome, buyers get stuck in places they no longer belong, which inflates the numbers and throws off the sales forecast.
For example, if a prospect stalls, move them back to the stage where the initial questions were likely discussed and ask them again. Remember, we are driving toward a sales forecast, so if a prospect sits in a more advanced stage, but in reality, they should not be there, then the forecast is inaccurate. The role of sales manager is critical here to ensure that all prospects are in their appropriate stages.
Once the sales team learns “gut feel” isn’t acceptable and adhering to the process earns praise and drives results, your pipeline will course-correct and start generating credible data.
STEP 3: Train your sales team.
Defining each stage in the sales pipeline is one thing. Adhering to those stages is another. Without discipline and accountability across the sales team, the most well-defined pipeline won’t produce reliable sales data.
Every salesperson needs to learn the stages of the pipeline, understand their potential outcomes, and be disciplined about checking the boxes before progressing the customer to the next phase. Salespeople are natural optimists, and they’ll always believe the sale is imminent. But while moving a lead from one stage to the next in the CRM may create impressive reporting numbers in the short term, it won’t actually bring you closer to the sale.
The sales team needs to understand that unless they confirm that the prospect has checked the boxes for that phase—setting aside budget, going through the internal approvals process and articulating why they are buying, for example—that lead stays put. Once the sales team learns that “gut feel” isn’t acceptable and that adhering to the process earns them praise and drives results, your pipeline will course-correct and start generating credible data.
STEP 4: Analyze the pipeline.
Now that you have a well-defined process and a well-trained sales team, you’re ready to begin forecasting by collecting and analyzing six key data points. However, forecasting with confidence takes time. Many organizations base their forecasts on the data collected over a period of time equivalent to the average sales cycle, but that won’t yield results with enough statistical relevance. Plan to collect data over a period roughly 2.5 times as long as your average sales cycle.
For example, if it takes 3 months for a customer to progress from first stage to close, wait for at least 7.5 months of pipeline data to accumulate; if it’s an 8-month sales cycle, collect the data for 20 months. That doesn’t mean you can’t run a forecast until then—of course you’ll need to start looking ahead sooner than that—but the point is that your forecast will be more accurate when you have been tracking it consistently for 20 months.
Once you have enough historical data, the final stage of the sales forecast process is to use these six data points to predict your revenue:
- Win rates by stage. Calculate the percentage of buyers at each stage of the sales cycle who ended up deciding against a purchase (“no decision”), going to a competitor (“loss”) or becoming a customer (“win”). This enables you to look at the number of buyers in the sales cycle and forecast the number of sales you can expect to close.
- Sales cycle. Determine the average duration from first interaction to close. This enables you to cross-reference with the percentage of anticipated “wins” in each stage and determine how soon you can expect to see those sales come through.
- Bookings target (annual). Look at the total number of bookings you expected to make for the year. This enables you to compare the forecast to the goal and see whether you’re on track to attain it.
- Average contract value (annual). Calculate the average contract value per deal. This enables you to determine how much revenue the organization can expect to see from those sales.
- Total closed bookings (annual). Consider the bookings you’ve closed year to date.
- Months remaining. This is a simple but critical part of the equation, because you need to be able to see how much time you have left until year end and compare that variable to the number of deals in the pipeline and the anticipated time-to-close on each of those deals by stage.
Here’s the bottom line.
Being able to forecast revenue is an essential capability. For the sales team, it’s the only way to determine whether sales are on track or in trouble. For the wider organization, it’s the only way to identify the resources required to support growth opportunities and avoid wasteful spending. That’s important for organizations at every maturity stage, but for high-growth companies, it can be a make-or-break situation. By using the sales forecast process outlined above, sales leaders can accurately and reliably anticipate sales and revenue.
LLR Partners believes in sharing the wealth of experience and expertise within our portfolio companies, network and teams in order to inspire and help accelerate growth for a wider community of business leaders. We hope you find these GrowthBits helpful and share them with your network. Read more growth insights here.