The Enterprise Software Salespeople of The Future
If you sell software for a living, odds are you sell business-to-business software (also referred to as enterprise software). It’s a viciously competitive industry because there are billions of dollars you can rake in per year selling your SaaS (Software as a Service) solution to firms by convincing a small pool of decision makers to give millions of dollars per year to you instead of someone else.
Over the years these sales cultures haven’t changed much, and the environments are so competitive that even the most primitive advantages are often exploited ruthlessly. Attractive young people fare well because of something called the process of natural selection, a phenomenon which also happens to be industry and function agnostic. When it comes to the lads, they’re usually a bunch of charismatic jerks, all vying to be the alpha salesman of the bunch. Often referred to as BSDs (look it up), they’re likely to spend as much time selling as they do making themselves look good in the eyes of their VP of Sales – a person who spends all their time wondering what the sales team actually does every day.
What Enterprise Software Salespeople Do All Day
One person who can relate to the pain points of today’s enterprise software salesperson is Kimon Cambouroglou, co-founder of Quarterly.ai, a startup that’s been talking to sales teams over the past four years to find out what salespeople could do better with technologies like AI (artificial intelligence). His search began with a simple question – what is it that salespeople actually do? It’s the same question asked by every single sales manager Kimon’s team has ever talked to. And the answer isn’t what anyone wants to hear:
Incredibly, only 34% of a salesperson’s time is actually spent selling – what you hired (and are paying!) them to do. This might be a good time to briefly explain the sales cycle for people who may not know how B2B software sales work.
The Enterprise Software Sales Cycle
It all starts with a marketing team that generates leads from visitors to the company website, attendees of a conference the company hosts which tries to mask a sales pitch with some industry-relevant research, readers of the company’s white papers, etc. These leads are then “scored” based on the number of “touches” the company has had with each lead. The resulting leads are called MQLs (Market Qualified Leads). These MQLs are then turned over to BDRs (business development representatives) who will then try to turn MQLs into SQLs (Sales Qualified Leads.) An SQL is a lead for which there is a definite “opportunity” which is then weighted and becomes part of the sales “pipeline”.
At this point, the BSDs come in pounding the table in front of the small circle of decision-makers who can sign that purchase order on the dotted line and increase their run rate by millions of dollars.
Great sales executives (BSDs) have an almost intuitive feel for which opportunities will convert into closed sales and which ones will drag on forever, but most field sales reps don’t have a clue and usually just guesstimate the probability of success. This is why forecasting is such a dark-art for the VP of Sales – factoring in the experience of the sales rep, their prior success rate, the state of the account, any ‘sandbagging’ they may be doing, and the list goes on.
In addition to the sales funnel system described above, BSDs have their own networks numbering into the thousands. They carry these from company to company and hide them from their VPs, only adding a contact to the CRM when a deal with that contact is fully baked. This drives VPs nuts and throws sales forecasts out of whack. BSDs often manage these personal networks on paper and spreadsheets and by researching online from time to time to try to keep up. It’s the classic mess of different technologies, systems and processes which should be unified.
Top enterprise software salespeople can pull million dollar bonuses by accurately forecasting and then beating their quotas. That money comes from their ability to competently preach the merits of a complex software product while drawing from other functional areas of the business to support their case. As objections are raised, evidence is procured to stifle objections. The salesman who sells the most is likely to be the one who spends a great deal of time in face-to-face meetings with decision makers getting them to close the deal. That’s why the VP will look out on the sales floor and ask why half the sales team is sitting at their desks instead of out in the field. Let’s take a look at what technology solutions are available to get our BSDs in front of other BSDs so we can close some deals.
Writing Emails (21% of time spent)
We’ve talked extensively about how natural language processing/generation (NLP and NLG) tools can be used to read emails and suggest responses. That stuff is so 2017. Today, we expect the AI algorithms to tell us who needs to be emailed next based on some predetermined prioritization process (Gmail has actually started doing this now.) When it comes to email introductions, the AI algorithms can parse through a BSD’s social network and past interactions and answer questions like:
- When is the best time to reach out to someone in my network based on their social media, company news and other online activities?
- What should I write to them based on our interactions across emails/meetings/deals/calls/social media?
- When is the best time to email them? Or should I call? When should I call?
Just ask Dataminr how valuable it is to mine social media data for insights.
Data entry (17% of time spent)
What we’re talking about here are mundane tasks like logging phone calls or meeting notes into the CRM. Doing the math, 17% of an 8-hour day is 82 minutes – almost 7 hours a week. Because of CRM data entry, a 6-person sales team becomes a 5-person sales team and one highly-paid data entry admin. Newer tools like ProsperWorks automate much of the data entry provided you are using all of Google’s Apps.
Prospecting Leads (17% of time spent)
Many high-scoring MQLs are ‘kick-the-tires’ types who have no intention of buying, while a low-scoring (or even absent) MQL may be the decision-maker at a company going incognito by using their Yahoo or Gmail address. BSDs can ‘sniff’ the wheat from the chaff, but the rest of us need on-point coaching to help distinguish a real lead from a wannabe. This is where the AI algorithms can start linking external data sets from social networks to the CRM system to find the most influential people for the BSDs to get in front of.
Attending Internal Meetings – Check-ins (12% of time spent)
This isn’t on our list of “things that salespeople spend their time doing” because nobody would actually admit to doing it. What we’re talking about is something we all do, whether consciously or not. Call it kissing up, call it brown-nosing, it’s the process of making sure that the boss thinks you’re not like all those other tools on the sales floor who think they’re the next Steve Jobs. Apart from the politics, most internal meetings are wasted gathering data. “Sales managers always tell us that they spend most of the meeting bugging their salespeople to make and log their calls/emails/meetings and trying to find out what’s going on with the deals, rather than actually helping the salesperson advance their deals,” says Kimon. Quarterly.ai does the bugging (in a nice way) and logs everything, while coaching salespeople along the way. The managers get real-time insights into the salesperson’s activities, so they can have a short data-driven meeting focused entirely on getting the salesperson over bumps in their deals. An hour meeting turns into 10 minutes.
Scheduling Meetings (12% of time spent)
Maybe you saw the recent news that Google now has an AI-powered “voice assistant” that sounds so real that it can call an actual restaurant and make a real reservation. The simple process of scheduling meetings with executive assistants can easily be automated with such technology. According to the National Sales Executive Association, getting lots of meetings means closing lots of sales:
While automating the scheduling of sales meetings is an obvious application, there’s room to be much more sophisticated. A BSD’s personal schedule might start to become part of their overall day. Picking the kids up from soccer practice tomorrow night? Maybe the AI will schedule a meeting with a client whose office building is across the street from the soccer field. During the drive there, the AI has also scheduled a voice call introduction which the BSD can make using a hands-free phone while driving, and then prompt him for a quick (voice-recognition) meeting note as he’s walking to the car – on his way to the next meeting of course. It’s the “traveling salesman problem” finally being addressed.
Training and Industry Meetings (22% of time spent)
In-person Selling (Ideally, > 90%)
We’ve looked at some clever technologies like call ‘listening’ from Chorus.ai which enables the salesperson to push the deal along. However, for complex enterprise sales, it’s usually more important to get to the face-to-face meeting. BSDs use their Jedi mind-tricks to close the prospect over breakfast, lunch or dinner, not over the phone. There is a simpler AI concept here: “am I talking to the right person at the right time with the right message?” The end result is a daily directive to the BSD:
CRMs took all the joy out of sales, turning masters of psychology with strong personal networks into mindless desk-jockeys entering data for their managers without seeing an iota of value. High-performing BSDs excel at the art of relationships, and would rather leave everything else (cold-calling, lead qualification, opportunity scoring etc.) to a personal assistant – or an AI algorithm in this case. New initiates into the enterprise sales dark-arts require on-point coaching at each stage of the engagement with the customer, something existing CRMs do not provide. In today’s always-on, mobile, digital-nomad lifestyle, business exists beyond (way beyond) the CRM.
Tech investing is extremely risky. Minimize your risk with The Nanalyze Disruptive Tech Portfolio Report to find out which tech stocks you should avoid. Become a Nanalyze Premium member and find out today!