Many years ago, at a SKO (sales kickoff), I remember a revenue leader walked into a room full of sellers and asked who had lost a deal because of price. Many hands went up. He then asked the same group who had won a deal because of price. Not a single hand went up. And just like that, he taught a very valuable lesson to all of us. Buying decisions are made based on perceived value by the customer. Value is also hugely context sensitive.  A seller’s success is directly proportional to her/his ability to articulate the right value in the given context. Yet the ability to position value effectively has always depended on the seller’s ability, beyond what generic marketing and sales enablement materials provide. The top 20% have mastered this skill. The rest, especially new hires, struggle. This gap is where deals are lost.    

Is this a talent problem? Are some people born with an ability to position better than others? Perhaps. Or could it be that at least part of it, if not all, is a systems problem? That there are solutions that can be put into place which could reduce the gap between the best and the rest? 

There is a good reason why teams haven’t been able to elevate and standardize this ability at scale. Actually, there are three. 

The first is collecting the data which is foundational. Raw data is scattered across multiple places, including people’s heads. It lives in your CRM, your call recordings, emails and Slack threads, the head of your coworker who has worked at a competitor and successful rep who left the company two years ago. How do you systematically collect and organize all this unstructured data siloed and locked up in tools and people?

The second, and arguably the most important, is the ability to synthesize that data into applied insights. Synthesis is a cognitive skill. It is built over years of experience, being in different situations, testing different approaches. This is what sets your top performers apart. They have been there, done that. They apply pattern recognition in a context instinctively, and it looks like magical talent.

The third is the challenge to keep your positioning up to date, especially in this AI age, where the whole ecosystem around us changes as we sleep. A prospect’s priorities change, markets get disrupted causing shifts in whole industries, your competitors release products and change commercial models overnight. Recently, a $400 million ARR company reduced its SDR team from 15 to 1. If you are a recruiting agency that specializes in supplying sales talent to customers, you couldn’t use the playbook today that earned you business last week.

All three of these problems are solvable today, at a scale and speed that was unthinkable even a few months ago. 

When it comes to data, storage and access is not the problem. Sales teams have been recording data forever. New AI tools like Gong have enabled the digital capture of conversational data. And we’ve had API and integrations for years. What has changed is the ability to read that unstructured data. Today, you can build a system that interacts with this highly scattered data, internally organizes it and comprehends it as a human would do. 

Synthesis, as I mentioned above, is a pattern recognition and application problem. But instead of it living in the heads of a few, you can now externalize it, encode it, and make it accessible to everyone. Even to a new hire. On Day 1. That’s your company’s institutional wisdom, systemized and democratized. When the new hire gets handed the Shell account, he can immediately apply the playbook that someone else applied to win the Chevron account, for example, even if that person no longer works for the company.

Keeping it current is humanly impossible. You need to monitor existing competitors’ activities, track new ones that are emerging faster than ever before, be deeply aware of prospect’s business and moves, keep up with industry changes, stay up to date with what’s changing in the buyer’s lives amongst others. It’s not just external, but also internal changes such as feature releases and pricing changes. Then you need to distill that information, figure out what's relevant, and update accordingly. When everything is moving at AI speed, an individual seller or even an entire marketing team simply can’t keep up. Instead, you need a system that does this automatically. And not just at a pre-scheduled time. But in real-time, dynamically, as things shift.

Beyond the ability to address each of these problems in isolation, what’s really transformative is that they can all work together as a single system, connected, continuous and contextual. It will totally change the way you define success and operationalize sales.       

If you are a revenue leader, the next time you are in that room and hands go up saying they lost on price, notice if those are your new hires and average players. If they are, ask your best folks what they would have done differently in that situation. And then ask yourself, what are you waiting for when you can make your entire team operate at that level all the time.