A Day In The Life Of A Millennial Sales Rep: Why A.I. Is Causing A Sales Revolution

The workforce is changing. According to a White House report, 33% of the current workforce is a millennial and in 4 years time, millennials will make up over 50% of the entire U.S. workforce. I shadow a lot of sales reps in my job. I’ve done hundreds of ride-alongs and stakeholder interviews, many of them with millennials.

Millennials do things differently and they expect their work life to be like the rest of their life — supported by technology and A.I. The problem is, it’s not.

Work is the one area where sales reps do not get much support from A.I. and that trend is changing. A.I. in enterprise sales is at a tipping point and it’s a good thing because if you look at the day of a typical millennial sales rep, you’d be shocked at what happens. I know I was. Let’s look at Jared’s day:

5:00am

When Jared wakes up at 5am, his room temperature is being automatically adjusted to his liking by a technology called Nest. Jared bought the system four weeks ago. At first, Jared had to regulate the thermostat in order to provide data to Nest, but now it has learned his schedule and adjusts the temperature as needed. With its built-in sensors, it goes to energy-saving mode when it realizes nobody is at home.

 6:00am

As he quickly prepares for his morning run, his Fitbit uses its built-in GPS to show him the route map he needs to run and indicates his friends are already beating him on exercise for the day.

 7:00 am

Driving to work, Jared encounters an accident and without touching a button, Google Maps, using satellite technology, proprietary data, and crowdsourced information, gives him a heads up that traffic lies ahead and suggests that he’ll be stuck for an additional 15 minutes. It then presents the option to take alternate routes and includes an explanation as to why one is preferred over the other.

8:00 am

As themorning commute is coming to an end, Jared flips on Pandora and listens to one of his favorite songs. Jared created a station last week with his favorite band and he loves the suggestions that have been playing. Rather than use user connections or ratings to recommend personalized selections, Pandora relies on a Music Genome that consists of 400 musical attributes in the songs Jared likes so it can play other songs that possess similar musical traits.

9:00 am

Work starts and the fun ends. Jared is left to sell using his gut and intuition. At 9 am, he meets with a group of marketing and sales professionals to brainstorm what a target account should or should not be. The group leaves the meeting with some subjective characteristics, but nobody feels really satisfied.

10:00 am

Jared sits down at his computer to begin prospecting. Jared begins searching through his CRM to find his target accounts and identifies the ones he’ll focus on today. There are so many contacts in his target accounts he doesn’t know where to start. He finally chooses one account to focus on and by guessing he decides to label the head of sales as the decision maker, the head of operations as an influencer, and a director of sales as a champion. He’s been burned on subjectively choosing buyer roles so many times in the past, but he has no other choice so he continues on.

11:00 am

His peers keep saying cold calling is dead, so Jared doesn’t want to just place a random phone call. He opts to google each person and begins an exercise that lasts 15 minutes per contact of trying to learn about his prospects. Jared estimates he visits at least 10 different sites over a 45-minute period. Feeling more comfortable with his target accounts and contacts, Jared now begins to reach out. Jared doesn’t know if now is the optimal time and he doesn’t know the optimal method to prospect. All he knows is he prefers email over phone. Jared spends significant time typing two email messages trying to make them relevant and personalized and then decides to place one phone call only to find out that the CRM had the wrong number. Determined to find the right number, Jared spends the next 10 minutes visiting three different spots trying to find the right phone number. He finally gives up and settles on calling the company’s main number. It’s almost lunchtime so Jared manually logs his activities in the CRM and calls it a morning.

12:00 pm

Jared opens up a new website called Nara, a restaurant recommendation website that’s like Pandora and Yelp, combined. Nara works by learning your unique dining preferences to form a tailored list of restaurant recommendations and it gets smarter the more Jared uses it. Today it’s going to be Thai food and Jared is starving. He grabs a few of his buddies, orders an Uber and is on his way.

 1:00 pm

Just before he starts work again, Jared checks his Amazon account for a shipment he is expecting to receive today. Once done, one of the Amazon.com recommendations catches Jared’s eye. Amazon’s recommendation system is based on a number of simple elements such as what a user has bought in the past, which items they have in their shopping cart, items they’ve rated and liked, and what other customers have viewed and purchased who have similar behaviors. Jared, like most of us, is a sucker for those recommendations, so he takes the bait and makes the purchase.

2:00 pm

Jared has an appointment at 2 pm for a client demonstration. He prepares for the meeting by again spending time online trying to understand his audience and then he pulls together a few different marketing decks to present via a screen share tool the company has recently purchased. As he’s presenting, he wishes he could get better intelligence from this presentation, such as what people are actually doing during the presentation and what they are doing with the presentation that he sent across, but he knows that’s not possible so he does what he can with what he has.

3:00 pm

Jared has a meeting with his manager to review his performance. The manager sits down and reviews a paper copy of what they discussed two weeks ago and just as they are getting into it, a group of people knock on the door and say they reserved the room so Jared and his manager need to find a new one. The reservation system is a joke at Jared’s company so Jared and his manager simply admit defeat and go and find another room and complete their meeting.

4:00 pm

Jared spends the next hour entering and updating necessary items in his CRM and then prepares to leave for the day.

6:00 pm

On his way home, Jared feels hungry again so he pulls out his phone and opens up Yelp to find a recommended restaurant near him that has high ratings. He finds an Indian restaurant and orders takeout.

8:00 pm

Wanting to relax for a couple of hours, Jared opens Netflix and notices a new recommended show has appeared. It’s called Breaking Bad. His friends at work talked about it a lot a few months ago and he just never got around to it. He decided to give it a go. Jared leans back in his chair and begins his session.

11:00 pm

Jared gets ready for bed and wonders why everything in his life is easy except for work. Why can’t my work life be like the rest of my life?

• Why can’t the system recommend to me what accounts should be my target accounts and contacts?
• Why can’t my system bring me relevant information about my contacts?
• Why can’t the system find updated contact information?
• Why do I have to type every email individually and send them when I think it’s best?
• Why do I have to manually create my follow-up strategy and then manually log activities?

Frustrated, Jared closes his eyes and falls asleep.

Conclusion

If you don’t think most, if not all, of your salespeople feel this way, you’re mistaken. Millennials are not idiots. They know when something is broken and sales is broken. Welcome to the sales revolution where math + data + applications are fundamentally changing the way we sell. It’s here. It’s not tomorrow, it’s today and XANT is leading the charge.

If you found this interesting, check our research report on the State of A.I.

 

 

 

 

This post was originally posted on LinkedIn