As a student of my profession, I’ve probably read about 100 sales books. Of these, there are only a few that I would read more than once and even fewer that I would enthusiastically recommend. To qualify, the book must teach something new, be backed up by hard data, and be well-written. I’m happy to say that The JOLT Effect: How High Performers Overcome Customer Indecision, by Matt Dixon and Ted McKenna, easily meets all those criteria.
Here’s the gist of the book in one paragraph. The single biggest reason sales are lost is because customers can’t or won’t make a decision. The way that most salespeople have been taught to sell doesn’t’ work against indecision, and actually makes things worse. Using the counterintuitive approaches described by the acronym JOLT can more than double your chances of winning deals.
Let’s take these one by one.
Your biggest competitor
For any sales opportunity to succeed, the customer must take action to buy from you. That means that they must intend to change, select your offer, and follow through with their intent. In other words, your three competitors are status quo, competitive vendors, and indecision. The first surprising insight from this book is that indecision is the most common reason that deals don’t close, comprising 40-60% of losses. Indecision is not the same as deciding to stick with status quo; it occurs when the customer has expressed an intent to change, but is either unwilling or unable to actually pull the trigger on the decision. Amazingly, even after customers have said they’re willing to buy, conversion rates are only 26%!
You can’t fight fear with fear
Since sales is about change, most sales approaches are designed to overcome status quo bias. In this battle, fear is the salesperson’s friend. Because change is hard, salespeople have learned to bring out the fear of loss—to make the cost or pain of not changing greater than the cost or risk of changing. It’s extremely effective in getting the customer to agree that they need to change.
But there’s a problem. Once the customer has decided that change is necessary, another more powerful fear kicks in, called commission bias. We are more afraid of making a mistake through action than inaction. Especially in a large organization with a lot of people involved in the decision process, it’s easier and safer not to decide. Fear of missing out is not as strong as fear of messing up.
When the customer delays or dithers, the average salesperson assumes they haven’t done a good enough job on making their case for change, so they double down on the fear. But this just injects more fear into the customer’s mind and actually backfires. Statistics gleaned from literally millions of sales conversations show that while dialing up fear works 16% of the time, it does not work 84% of the time.
So, to combat indecision, the trick is to flip the switch—from fear to reassurance. You have to lower the fear of deciding. Every business book needs an acronym and that’s where JOLT comes in.
JOLT them into action
Judge the indecision. The best sales reps qualify not only ability to buy, but ability to decide. This is probably the hardest part: being able to detect the presence and depth of indecision. Their research has shown that indecision is present in 84% percent of sales opportunities. It comes from three sources: valuation problems, which means they have trouble comparing options; incomplete information; outcome uncertainty, which is the risk of not getting the results they expect. This chapter explains how to gauge the source and depth of indecision through things the customer does and says during the sales cycle.
Offer recommendations. Another “aha! moment” for me. I’m a huge proponent of asking questions and talking less during sales conversations, but that’s not the best approach at this stage of the sale. Their research showed that the most effective reps actually talked more rather than less, telling more than asking. Too much choice and resulting complexity make it harder to decide, so the salesperson who offers proactive guidance and expert personal opinion makes it easier, boosting conversion rates from 13% to 48%. (I note that for this to be effective, the rep must have established credibility and trust, and asking a lot of questions earlier in the sales cycle is still one of the best ways to demonstrate customer orientation and to get the information needed to make credible recommendations.)
Limit the exploration. Every salesperson knows the frustration of analysis paralysis, where the customer is always asking for just a little more information. High performing reps learn to own the flow of information in three ways. First, they establish their own expertise. One of the ways they do this is by actually limiting the participation of subject matter experts like sales engineers. Another way is to anticipate objections or concerns the customer is likely to have, and bring them up before the customer does. This strategy of “pre-buttal” is extremely effective, as shown by a 45% increase in win rate when it’s used. Third, they are not afraid to challenge the customer’s request for more information, and follow up with questions to probe for exactly what uncertainty is driving the request.
Take risk off the table. When the book first came out, I texted Dave Brock to ask if he thought it was worth investing the $29 price. He responded by saying that it was well worth it, and if I did not agree, he would personally reimburse me. He demonstrated the effectiveness of finding ways to lower the customer’s downside risk and make it easier for them to decide.
Will adopting the JOLT approach pay off for you? Let me try my hand at taking risk off the table[1]. First, using JOLT does not mean you throw out everything you’ve learned to date about changing the status quo. That is still necessary. It’s an addition, not a replacement, for your sales playbook.
Second, I can’t totally reduce your outcome uncertainty, but let me stress what I said at the beginning about hard data. Dixon and McKenna did not make up the JOLT techniques; they discovered them in the patterns from the data. They have taken advantage of the explosion of virtual sales conversations caused by the pandemic, using machine learning to analyze 2.5 million sales conversations and uncover patterns of what separates the high performers from the average. As you can see from the liberal use of statistics in this review, they’ve measured what works and how well. If it worked for them, it will work for you.
It’s an easy decision: buy it, read it, apply it.
[1] I don’t have the resources to make the same offer Dave did to me.