How LogMeIn Nailed 39 Straight Quarters of Sales Forecasting
Lessons for improving your forecast accuracy
Accurately forecasting sales is an incredibly complex process. But LogMeIn, one of the world’s top 10 SaaS companies, has perfected the process. The company does roughly $1.3B in business each year and has three unique business units that are selling approximately 20 products with multiple revenue channels.
“We’ve accurately forecasted our numbers for 39 quarters in a row. In 38 of those, we beat the high end of guidance.”
Despite doing millions of transactions a year, the company has managed to consolidate sales information, create a finely tuned forecasting process and hit forecasted numbers for 39 quarters in a row. In 38 of those quarters, they beat the high end of their guidance across all the metrics, and in one quarter, they hit the high end.
Chief Sales Officer of LogMeIn, Larry D’Angelo, shared his formula for success at our annual Sales Summit.
The art and science of forecasting
Regardless of size, every sales organization needs to be able to forecast their sales numbers well. Public companies need to equip the CEO and CFO with numbers to give shareholders and startups need to be able to accurately forecast sales and share them with potential investors. And yet, many sales leaders fail to do this accurately.
“Most companies miss their forecast by quite a lot,” says D’Angelo. “Because you have two deals that look exactly the same, one of which you win and the other you lose, but you don’t know why. And there’s probably two fundamental reasons: One is, you’re asking the wrong questions to drive the activity and the other is that managers are asking the wrong questions during deal reviews.”
Prior to the use of predictive analytics, machine learning & AI, forecasting was primarily an art. Now, many companies rely too heavily on the science of forecasting. In reality, the most successful companies will use a combination of the two.
“You should use science and analytics to try to normalize all your deals so they look the same,” explains D’Angelo. “It creates uniformity, and uniformity creates predictability, which allows you to craft a repeatable process. The art comes into play when the manager and the sales rep converse about certain accounts to enhance the given data.”
Start with the science
Forecasting should start with the science and there are three steps to take during this stage. The first is to establish a consistent questioning methodology. Equip sales reps with a set of standardized questions that need to be answered on a sales call or at a meeting.
“At LogMeIn, we have six categories of questions for classic pipeline deals,” notes D’Angelo. “We need to know the customer’s pain point, who the decision maker is, what the budget is, what the purchase timeframe is, where we stand among the competition and what the buying process is.”
The next step is to take the questions and embed them in Salesforce. This allows the rep to be on the phone with a client and have all the questions in front of them, and record answers directly into the software where the information needs to be stored. Adding questions to Salesforce should also help with adoption.
“If a sales rep is typing notes into an open field in Salesforce, that becomes a lot of work to manage while on a call,” states D’Angelo. “But if they’re checking boxes and typing quick responses in individual fields, it adds value to their process.”
The Salesforce integration will also be beneficial when managers are conducting deal reviews. Instead of combing through a long list of comments or trying to find the information in Salesforce, they can quickly find the segmented information that’s needed.
The last step is to remove rep variability by automatically adding classifications to stages in the sales cycle. The three classifications recommended by D’Angelo are Early Stage, Best Case and Commit.
“What you end up with are deals that are all classified in the same way,” notes D'Angelo. “The idea was that as our reps matriculate the customer through the sales process, they know how the deal is classified, which gives us a more accurate picture of our pipeline state.”
Apply the art
Once the science is in place, it’s time to layer on the art. D’Angelo recommends coming up with three to four questions that reps and managers should ask to justify whether or not the deal is forecastable.
“When you have all these deals coming in and you have millions of transactions, if you’re off by a small degree at the rep level you’ll be off by a mile by the time it gets to my level,” warns D’Angelo.
At LogMeIn, managers start every forecast call and every deal review with three questions. The first is: Is the deal in or out? Outside of the questions answered about budgets, timing, decision-makers, etc., what is the sales rep’s gut feeling about whether or not the deal will close by the end of the month or quarter? That will help you determine if it’s worth pursuing at the moment. The second question is: What differentiates your product from others in the customer’s eyes? And finally: Why now?
“One thing that’s very important at this stage is: if no one tells you you’re winning a deal, you must assume you’re losing,” stresses D’Angelo. “This has been the best predictor of whether or not a deal will close. If a rep isn’t sure where the client’s head is at, we have him or her call the client to ask. They say, ‘At this point in the process, you’re likely leaning towards one product or the other, and it would help if we knew our position.’ If the client responds that we’re leading, we ask how soon we can close the deal. If it’s clear that we’re not in the leadership position, we ask that they let us know what we can do to better our outcome. If the customer won’t disclose new information or provide guidance, we tell the customer we have to assume we are losing, and it sounds like you (the customer) have made your decision. In this case — we see how the customer reacts and adjust our strategy accordingly. If we are going to lose, we are better off knowing right then before we continue to invest additional resources and emotion into the deal.
D’Angelo emphasizes that companies need to challenge their reps to eliminate any uncertainty and get a clear answer from the client. They should also feel empowered to predict whether or not a sale will close soon. As the person closest to the deal, they need to be able to say where the deal stands regardless of where it is in the sales funnel.
If a deal does end up stuck in a certain stage, D’Angelo admits there’s no magic formula for moving it. It often comes down to the fact that there’s no compelling event on the client’s end or the product isn’t the right fit. This is where his team cleans up the pipeline. The manager and rep thoughtfully discuss every deal and move it to a different stage if necessary.
“This prosecution of the opportunity with those questions is really what put us over the hump on accurately forecasting transactions that have to go through a pipeline process,” says D’Angelo. “We found that our pipeline roll-up for every rep was much more accurate with this new process in place.”
Adjusting for a high-velocity inside sales model
While the process laid out by D’Angelo works for pipeline deals, roughly one-third of LogMeIn’s deals are not through pipeline. Companies with a freemium eCommerce or high-velocity inside sales model can’t necessarily see all the transactions that come in and close within a quarter. The challenge becomes: How do we forecast business we can’t see?
“We had developed what we called run rate at LogMeIn,” explains D'Angelo. “With all these transactions coming in, we had to create a methodology that made deals repeatable and predictable, so we introduced a lot of machine learning and analytics.”
Machine learning and AI will be able to better predict the run rate for high-velocity sales businesses. Even in surprising cases, AI should provide enough leading indicators that you can see the change coming a few weeks out.
“We determined that when we go into a quarter, we can’t see 50 percent of our deals,” says D’Angelo. “So we developed what we call burn down. Using a lot of data and regression testing, we found that each quarter we will close about 50% of deals that we can’t see at the start of the quarter, provided our marketing activities and sales calls remain the same.”
Though forecasting will always be a delicate balance of art and science, D’Angelo’s advice should help narrow the margin of error for many companies.
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