Kieran Snaith & Lositika Berry & Katie Penner & Ryan Teasell & Alley Forbes & Ryan Sorley 55 min

Pipeline Power Hour: Sales, Fall '23


Buckle up for five masterclasses on sales strategies your team needs to be successful in this challenging market.



0:00

Welcome everyone to Pipeline Power Hour for Sales Leaders.

0:03

My name is Kieran Snaf,

0:05

I'm the VP of RevOps here at Qualified.

0:07

We hear so much about AI changing the game for sales teams,

0:10

but we don't often hear the nitty-gritty details on how teams are finding value

0:14

in AI,

0:15

and what's actually impacting their pipeline and deal cycles.

0:17

We have five great sales leaders here to give us a peek into what's really

0:21

working for them,

0:22

and what's just hype when it comes to AI.

0:25

Let's start with a foundational element of any good sales team.

0:29

Sales Enablement.

0:30

We're taking a look into how AlphaSense uses AI-powered tools to scale

0:34

their sales enablement and coaching strategies with their senior associate of

0:37

sales enablement,

0:38

Los Attica Berry.

0:40

Okay, so welcome everyone to the Pipeline Summit AI for Enablement Strategies

0:44

for Coaching at Scale.

0:45

By brief introduction, my name is Los Attica Berry.

0:49

I'm originally from St. George, Utah, and currently based out of New York City.

0:53

I'm over on the sales enablement team at AlphaSense,

0:57

and I primarily focus to support our sales and marketing teams,

1:01

specifically through onboarding, ramping, continual sales training, one-on-one

1:07

coaching,

1:08

and any type of continual support.

1:11

So I'll speak more into AlphaSense later, but to provide a high level,

1:16

we are an AI market intelligence research platform,

1:19

purpose-filled for financial and corporate professionals,

1:22

and we combine all of our premium and proprietary content, such as

1:26

worker research, company filings, trade journals, news, expert calls.

1:31

And what we do is we layer on a thematic search,

1:35

which allows our clients to search thematically through our across-the-business

1:39

content,

1:39

which detects various financial language,

1:42

and allowing our clients to be able to provide more insights and coverage

1:49

to make better investment decisions.

1:51

So again, I'll speak more on AlphaSense and our AI tech stack,

1:55

specifically on how we enable generative AI in our enablements.

1:59

When we think of AI, the narrative and common misconceptions

2:05

has changed a lot throughout the years, and now companies and teams are

2:09

thinking about

2:09

how we're going to use AI, how do we allow computers to work with said person

2:16

to make us

2:17

smarter? And so when it comes to sales enablement, we're always thinking

2:21

about ways to improve how we run our onboarding programs, ramping reps,

2:25

one-on-one coaching, continual sales training, building best practices,

2:29

and of course, driving pipeline.

2:31

And so sales enablement will continue to evolve when it comes to building sales

2:37

programs.

2:38

And so what does that change look like?

2:40

What are our essentials to better equip and coach our sales teams?

2:44

And then where can we see that growth for enablement teams in 2024?

2:50

So within three buckets of where I see the most changes in enablement this year

2:54

my initial challenge is always thinking about my training programs,

2:58

how do I create an effective training that impacts and improves how our reps

3:02

sell?

3:02

So done thing is perfect.

3:05

And without in mind, what is the goal for each training?

3:08

So by leveraging AI, we now have more insights more than ever before within

3:14

sales performance.

3:16

Documentation is a huge thing and I no longer need to join every live cold call

3:21

demo and instead of

3:22

get a glance of a rep and prospect interaction, I can build more content, sales

3:28

resources,

3:29

one-pagers, repositories for our sales team to then leverage in our

3:33

conversations.

3:35

And then especially when it comes to strategizing how to better understand our

3:38

key accounts,

3:39

verticals, personas, and then receive sales data on processes and patterns.

3:45

Within sales coaching, grading and phone video calls has changed a lot

3:48

throughout the year.

3:49

So summarizations of phone video conversations where I can now identify key

3:54

trends within specific

3:55

cold calls and demos where it picks up language recognition and buyer sentiment

4:01

So I can then go and ask questions and insights through generative AI, allowing

4:06

me to provide

4:07

real-time feedback and effective turnover one-on-one coaching.

4:12

When it comes to our goal to create a standardized sales process within AI,

4:17

I can then ensure time-sensitive actions are being met by each rep, like

4:22

response times,

4:23

touches per lead, effective outreach, and quick messaging from Gen AI tools.

4:28

I can now build a Holocene repository for onboarding reps and ramp faster and

4:33

build

4:34

a strong best-up behaviors that are backed up by data.

4:38

And then I can monitor conversation trends to then build future trainings and

4:42

drive urgency

4:43

within specific language. I've seen a 25% reduction in time spent onboarding

4:48

with new hires to get

4:49

them moved quickly to ramp because I can now identify top-performent behaviors,

4:54

highlight areas

4:55

improvement, provide actual feedback, and then use that data for new hires.

5:02

Although these are our current essentials and we are just tapping into

5:06

potential AI through

5:08

enablement, we are continually looking at AI tools to leverage in our day-to-

5:12

day,

5:13

like GONG, chat GBT, document tools, qualified alpha-sense, and then have all

5:19

enabled our

5:19

training to better provide support and insights in our enablement.

5:25

So a common pain point for enablements that we cannot be on every single live

5:29

cold call or demo.

5:31

And so we want to document how every call went based off of the reps notes

5:35

and be able to create some real insights. So we are looking for insights on

5:40

what was

5:40

talked about, how are reps handled each topic and what were the agreed next

5:45

steps.

5:45

With GONG, we can leverage through their generative AI to provide major

5:50

spotlight insights of what

5:51

was discussed in the call. I can then ask a question to have them generate a

5:57

summarize and

5:59

provide the specific topic that I wanted to pull from the reps call.

6:03

So then this allows me to better provide feedback and pinpoint the area of

6:07

interest.

6:07

And those topics can be filtered and transcribed for me so that I don't have to

6:11

listen to the full

6:12

call and leverage spotlight areas for in real-time coaching.

6:16

When it comes to building programs and revamping our framework and language,

6:23

leveraging AI can help with gathering insights on suggestions, methodologies,

6:27

framework and coaching skills and language. For example, training and building,

6:32

I was curious

6:32

on what CHAT-GBT would pull for cold call methodology versus structure and see

6:38

the benefits

6:38

and differences and approaches and how to better build rapport effectively,

6:43

engage and

6:44

understanding different aspects. Very similar to how I can see strategies and

6:48

free work on how to better improve my sales training and ensuring that each

6:53

session,

6:53

there's a goal and it's truly impactful for our sales team. On a sales reps

6:58

perspective,

6:58

they can leverage the tool with suggestions and better understanding their

7:01

prospects.

7:02

For example, what is the day in the life for a hedge fund manager? This is

7:06

something that all

7:07

of our reps have to be trained on, is value and why should they care? What is

7:11

their day in the life?

7:13

So we are also looking at auto-pouncing to help drive engagement numbers, limit

7:19

the amount of

7:20

touches and sales cycle and not go straight to demo book with AES. So with the

7:26

growth of AI tools,

7:28

documentation is more available than ever. So enablement teams and marketing

7:32

segment are now

7:33

creating more internal and external content. Our sales team can leverage these

7:38

one-peters,

7:40

battle cards for their messaging, knowledge and training that are all being

7:45

generated by AI.

7:46

So all marketing collateral, sales battle cards can be found and shared

7:50

internally or externally.

7:53

For example, all updated resources and battle cards can be searched across

7:57

through our generative

7:58

AI by question and insight. So if I wanted to look up information for my own

8:02

knowledge as a rep

8:04

or share one-peters to potential prospects, I can search through questions and

8:09

insights.

8:10

For example, how to competitive intelligence teams use Alsescents. I can share

8:14

this with my

8:15

prospects. I can also use this for my own knowledge and training and then be

8:19

able to

8:20

leverage sharing and tracking type links and touches for engagement.

8:25

Our inbound team manages the many channels of incoming leads. So when it comes

8:31

to boosting

8:32

productivity and leveraging AI for messaging and enabling personalization, we

8:37

utilize qualified

8:38

AI when responding in real time to potential prospects like face-to-face

8:43

experience. And

8:44

then within their AI, we can pull information quicker so we can respond using

8:47

the same language

8:48

across the whole org on Alsescents questions. We have to match a very similar

8:53

type of language

8:54

across the org when it comes to financial language, corporate markets. And so I

9:01

can,

9:01

for this example, I can leverage their AI by pulling suggested public

9:06

information on broker

9:07

partners and include tone and sentiment and elaboration in addition with rep

9:13

personalization

9:14

to their messaging. And this is allowing them to receive that real-time

9:19

response from direct sales

9:21

reps. And then we can do this in the questions when it comes to our content

9:26

sets and where that

9:27

would take us to create any type of draft on our own, all that time that would

9:32

take. We can now

9:33

leverage that into our specific messaging. So we are always treating our sales

9:40

reps on the value

9:41

and building rapport with our prospects. Our generative AI is a purpose-built

9:46

and fine-tuned

9:47

through our vertical LLM. In addition to our already set-in-place AI tech stack

9:53

, like our Slurm

9:54

Search. And so specifically with our generative AI, our clients can go in and

10:01

find company

10:02

recognition, sentiment, topic extraction, smart synonyms, and smart summaries.

10:07

And then this is

10:08

enabling our clients to deliver, insert, and accurate and secure summarizations

10:12

of both premium,

10:14

external, and proprietary internal content. So when it comes to our sales teams

10:19

and how we train

10:20

them, we're basing off of value-selling. So we're understanding specific person

10:24

as day to day

10:25

and better understanding what does that look like for them when it comes to

10:29

utilizing

10:31

alpha sense and conducting their research. By using alpha sense JNI, the sales

10:38

rep can leverage

10:38

sentiment topics, market trends, summaries at scale, and their cold calls and

10:43

demos through

10:44

their specific vertical focus or to better leverage value and use case and

10:49

their messaging,

10:50

cold calling, or demos. Some predictions that I see for AI powered enablement,

10:58

I truly see

11:00

chatbox training being more part of onboarding. A common onboarding cadence

11:04

right now is cold

11:06

calling email, LinkedIn outreach, best practices. And so by prospect behavior,

11:13

a lot of that I can

11:14

see will change when it comes to the sales cycle. Buyer behavior will evolve

11:19

and rely more on

11:21

getting straight to a demo. So this will reduce that sales cycle with a benefit

11:26

of immediate

11:27

support and sales contact. And then personalization tools and content, we will

11:32

generate more personalized

11:34

content from prospect behavior tracking, which will increase the demand of

11:38

collateral tracking

11:40

and suggestions through automation. And then within our sales rep productivity,

11:45

I think

11:46

a lot of productivity tools, I know that's something that we're currently

11:51

looking into.

11:54

Obviously, we shown a few that we're currently using, but there's always a lot

11:57

of growth as a

11:58

lot of companies are looking into generative AI call transcripts, polling

12:04

specific topics,

12:05

trends are happening in calls, lead prioritization, and deal conversions are

12:10

going to be the biggest

12:11

ones that I think will be focusing on for next year. And then within grading

12:16

and learning management,

12:18

I'm constantly grading, I'm constantly working with new hires and in ramp. Our

12:24

ramp period is

12:25

a longer period of time, which makes sense for our sales cycle. But with that,

12:32

we want to look

12:32

at how we can be more effective and efficient with our new hires. So having a

12:37

faster ramp period for

12:39

new sales reps, increase of data on performance and be able to push on increase

12:44

on any rep productivity,

12:46

that's always something that's going to be important for us. And then I can see

12:49

in the future. And so

12:51

when it comes to AI, we're truly excited to see the potential. We're really

12:56

only tapping into

12:57

limited or what we've seen so far. So when it comes to 2024, I think this is

13:05

probably the most

13:05

exciting part of being able to make my job be more effective, see how many

13:10

teams are going to be

13:11

strategizing ways to leverage AI when it comes to running sales team and

13:16

driving pipeline. So

13:18

really looking forward to AI in 2024. Thanks so much, Losetica. All of the work

13:24

that goes into

13:25

enabling your sales team is meaningless if you can't rise above the noise and

13:28

get in front of your

13:29

buyers. AI generated outreach has its place, but when done poorly, it creates a

13:33

lot of noise in

13:34

your prospects inboxes. But AI isn't just limited to email writing. Next, we'll

13:39

hear from Katie Penner,

13:41

head of sender relations at Sendoso about how they're using AI to power their

13:45

direct mail platform

13:46

and get your company in front of buyers in creative ways that make a big

13:49

statement. Take it away, Katie.

13:51

Hello, my name is Katie Penner. And today we're going to talk about the gift of

13:57

AI and using AI

13:59

to blow your buyers away. Now, I am the head of sender relations at Sendoso,

14:05

where we make it

14:05

possible for you to send virtually anything to anyone anywhere. Now, with that

14:11

being said,

14:12

let's go ahead and dive in. So I first want to share my opinions about the

14:18

future of AI and how

14:20

it will affect sales organizations. Now, I'm sure we've all heard the narrative

14:26

that AI is going

14:27

to replace all salespeople. However, human to human connection is actually more

14:33

important than ever.

14:35

So AI should be leveraged by revenue teams to make their efforts more efficient

14:39

, but not to

14:40

replace them. That being said, humans that leverage AI will probably end up

14:45

outperforming those that

14:47

don't people in AI bring different strengths to the table. AI tools are

14:53

incredibly fast and

14:55

accurate, but they aren't empathetic, sensitive, intuitive. And that human to

15:01

human personalization

15:03

is actually key to standing out today. A study by Gartner reported on the

15:09

percentage of customers

15:10

that expect companies to be well informed about their personalized information

15:16

during an interaction.

15:17

That number is 71% for B2C and 86% for B2B. Customers don't just want personal

15:26

ization,

15:27

they're demanding it. And technology plays a significant role in modern sales,

15:32

but it should

15:33

never overshadow that human element. So using tools like Sixth Sense Intent

15:39

Data,

15:40

Qualified Chatbot, and AI with tools like BARD to streamline processes, gather

15:46

insights,

15:47

and personalize communication is necessary. However, always remember to infuse

15:53

that personal

15:54

touch in your interactions, to balance that efficiency with authentic human

15:59

connections,

16:00

to create a seamless and memorable experience for your prospects, clients, and

16:04

customers.

16:05

In today's world where AI is taking a front seat and buyers are experiencing

16:11

buyer fatigue,

16:12

physical touchpoints with Sindoso can help you foster these relationships

16:17

faster.

16:17

Now that being said, how are we leveraging AI to create these more delightful

16:24

experiences for

16:25

our customers? In the future, AI is going to be leveraged to provide a more

16:32

intuitive user

16:33

experience for our customers, guiding them through the process of selecting,

16:38

customizing,

16:39

and even sending gifts on behalf of the sender. Our engineering team is

16:45

utilizing an OP stack.

16:47

So an AI plus a vector database. For those of you unfamiliar with an OP stack,

16:54

OpenAI has this huge information database as it's essentially trained with the

16:59

entire internet.

17:00

Therefore, when you ask a question, it sometimes has a tendency to hallucinate.

17:06

An adding a vector database with a tool like Pinecone gives AI a memory layer

17:13

to avoid hallucinations.

17:15

In preparation for this presentation, I had the honor of chatting with one of

17:20

our brilliant

17:21

engineers, Cheema. He began to show me this chat bot that he and his team are

17:26

developing.

17:27

And he also showed me a chat bot that another company in the gifting space has.

17:32

We gave that chat bot a simple prompt. What should I send to someone in college

17:37

And the chat bot narrowed down to categories that it believed to be relevant,

17:43

such as education

17:44

and technology. Of course, any narrowing down of options is helpful. However,

17:51

as we scrolled

17:52

through the options, we saw things like educational toys made for children, not

17:56

college students.

17:57

The gifting assistant bot that our teammates in DOSO is building is much more

18:02

intuitive in

18:03

comparison. You can give it a prompt like, what's a good gift for my calorie

18:08

conscious friend who

18:10

loves cheesecake. And the bot will suggest a cheesecake sampler so that they

18:15

can indulge

18:16

in a portion controlled manner. But that's not all. You can also give this bot

18:22

the prompt,

18:23

send name at company.com, a gift meant for someone who's calorie conscious and

18:28

loves cheesecake.

18:29

Then this gifting assistant bot will find that cheesecake sampler gift,

18:35

compose a note card for you, and complete the send. It will complete the entire

18:42

send process

18:42

for you after being given a simple prompt. This kind of thing is going to be

18:48

absolutely game

18:49

changing for our prospects and our customers. A smart AI tool that they can

18:54

trust to not only

18:55

select a highly curated gift, but to also complete the entire send process. I

19:01

mean, it's pretty

19:02

pretty incredible. So by communicating with our engineering department more

19:07

regularly,

19:08

our revenue org is becoming more empowered to speak to the product roadmap and

19:13

to what customers

19:14

can expect in the future. This has enabled our revenue team to close more deals

19:19

with more confidence

19:20

than ever before. In the future, we can also utilize AI to optimize operations

19:27

in our SFC,

19:29

our warehouse. Things like inventory management, shipping logistics, and other

19:34

operational

19:34

aspects to ensure timely deliveries and to minimize cost for our customers. We

19:40

currently

19:41

utilize AI for order waving, so attaching inventory to orders based on shipping

19:46

timelines

19:47

for rate shopping, finding the Sindoso optimized fulfillment options that

19:54

ensure the lowest cost

19:55

for our clients, and performing quality audits. But in the future, we can see

20:02

Sindoso utilizing

20:03

AI to help route orders to the most optimal fulfillment center based on

20:08

capacity, time,

20:09

labor cost, inventory availability, outbound connections, using AI to track

20:15

inventory and

20:16

consumption levels, generate recommendations on send trigger dates while fact

20:21

oring in shipping

20:23

methods and costs predicted by AI, and finally, utilizing AI to analyze

20:28

transactions to prevent

20:30

fraud. As Sindoso looks to expand, AI will become this integral part of our

20:35

fulfillment

20:36

optimization on behalf of our clients, and ensuring that our revenue org has a

20:41

deep understanding

20:42

of what our engineering team is developing with AI is critical to communicating

20:47

these things effectively.

20:50

Now, predictive analytics will also be huge for us. Sindoso will be able to

20:55

feed historical data

20:56

to AI so that AI can make recommendations to our customers based on what other

21:02

companies

21:03

similar to them are sending. What sends are the most successful for what stage

21:08

of the sales cycle

21:09

they're in and more. We will also be able to provide personalized trend data

21:14

for individual users

21:16

that will add a more detailed layer of tracking and understanding success of

21:21

various direct mail

21:22

campaigns. Our first AI release was Punpal. Now, Punpal provides AI generated

21:31

messages

21:32

that correlate with the gift being sent, and it's also just a lot of fun. Our

21:37

customers are

21:38

seeing that the time spent on ideating messages for note cards that go along

21:43

with e-gifts and

21:44

physical gifts is being cut down tremendously when they utilize this tool, and

21:49

this is just the beginning.

21:50

Now, I hope that this presentation was interesting and that at the very least,

21:57

it sparks some ideas

21:58

for how you can leverage AI at your organization, but if you walk away with

22:03

nothing else from this

22:04

presentation, I'd like you to walk away with this. The time to take a deep dive

22:09

into AI is now.

22:10

Educate yourself, ask your engineering team questions about how AI is currently

22:15

being

22:16

leveraged at your company, continue to learn by attending events like this, and

22:21

like I mentioned

22:22

earlier, people who leverage AI will begin to outperform those that don't. So

22:27

make sure that

22:28

you begin leveraging AI and exploring AI tools and offerings to ensure that you

22:33

and or your team

22:34

become more efficient so that you can focus more on things like building

22:38

relationships with your

22:39

prospects and customers. Thanks, Katie. AI is powering all of these crucial

22:44

channels that support sellers

22:45

and getting the most out of their outreach and meetings. But how much of these

22:49

AI tools are

22:50

actually helping sales teams hit their quota and what's more hyped than help?

22:54

Our very own Ryan

22:55

Teasle, enterprise sales and partnerships here at Qualified is ready to

22:58

highlight where AI really

23:00

shines for sellers and where it still needs a lot of human interaction to make

23:03

the most of the

23:04

technology. Let's hear it, Ryan. Hey, everyone. My name is Brian Teasle. I work

23:10

on the sales team

23:10

here at Qualified. We're going to talk about how most successful go-to-market

23:15

teams are balancing

23:16

meeting AI in the middle while still standing out as humans in their processes.

23:21

So the kick things off.

23:23

I took this quote from one of my favorite podcasters, the name is Lex Friedman.

23:30

I have

23:30

he's an AI researcher with millions of subscribers and followers, but more

23:36

importantly, he's an

23:37

optimistic and romantic human being. He believes that we will eventually become

23:43

more AI than men

23:44

when we integrate with AI, but even integration with AI is ultimately becoming

23:50

better human being

23:51

in our day-to-day lives. So we can focus on the core interactions and

23:54

everything that means the most

23:56

to us. I believe that the most successful salespeople right now are already

24:01

taking this approach,

24:02

meeting AI in the middle for suggestions, sometimes taking them into account,

24:07

and then

24:07

sometimes saying like, eh, thanks, but I think I got this one. So as we move

24:12

forward to this

24:13

presentation, I hope this prompts you to think about what AI can help you to do

24:19

to streamline

24:19

your processes and then what you can double down your human efforts on in your

24:24

everyday

24:25

single processes. So looking into quick data of AI in 2023 and business

24:32

business sales,

24:33

that may present a BDB sales theme for already being AI. So we're all using it.

24:39

71% of sales

24:41

leaders say that AI is going to make their teams more productive, but 61% of

24:46

employees are

24:47

skeptical about how useful AI actually is in their work long term. So we're all

24:53

using it.

24:54

We all say it's going to make us more productive. Why are we all still

24:58

skeptical? AI has rounded

25:01

us for years already, even if we haven't truly acknowledged that it is, the on

25:05

social media,

25:05

our algorithms, the music we listen to on Spotify, the movies we watch on

25:10

Netflix are served up to us

25:12

by AI, the meetings we book in sales, the Zoom call if we record and listen

25:16

back to the data we

25:18

use to build account lists and target prospects that accounts. This list goes

25:22

on and on. We're

25:23

already surrounded by it. We're all selling it. So why would we still be

25:26

skeptical? I'm going to

25:27

pull from my personal experience using AI every single day and just give my

25:33

take on whether something

25:34

is helpful or maybe it's a little too hyped up right now. And so there are many

25:39

different areas

25:41

about how go to barcode teams specifically use AI and drive productivity. But I

25:45

'm going to focus

25:46

on a couple here that are likely top of mind for all reps and me especially.

25:51

Generative is the first

25:53

researching accounts, generating emails to send insight looking for insights on

25:58

public information,

25:59

10k interviews, podcasts, whatever might be out there for your accounts. It's

26:03

going to help

26:03

and stay relevant. Then I'm also going to dig into sales coaching tools and how

26:08

AI is helping you

26:09

take a look at your calls, give you some coaching, give you some feedback and

26:13

how you can improve

26:14

on your identity processes and become the best rep that you can be. Then we'll

26:19

start

26:20

with generative AI. And two of the main ways I'm using generative right now are

26:24

to research

26:25

accounts and find information and also for writing. So we'll start with

26:28

research. Being relevant

26:30

is the key to any outbound approach. What used to take hours and hours to find

26:36

any kind of

26:36

kind of key insights on your accounts and prospects and now really take just

26:40

seconds.

26:41

Whether you're about to start a prospecting account, hop on a first call or

26:46

deepen a cycle and trying

26:47

to validate your solution with above the line leaders. There's a number of

26:50

tools to help you

26:51

find what you need, build relevancy and trust with whoever you're selling to. I

26:57

prompted to dig

26:58

into 10k's, summarize earning calls, look into podcasts, pull snippets from job

27:04

posting with

27:05

one of my favorites and look into the company ebooks that you can dig into. Hey

27:10

, maybe their

27:11

ebook is going to give me some insight as to how this company is writing their

27:14

business. Anything

27:16

that's going to help you shape your approaches or rep is certainly an help you

27:19

win. And as you

27:20

familiarize yourself with your buyer persona as in constant trends in the

27:24

market, this quick research

27:26

is also going to be useful when trying to be creative and experiment with new

27:30

value props.

27:30

And this is where writing comes into play. Generative and writing emails has

27:34

come a super long way.

27:36

Nine to 12 months ago, I wouldn't have trusted any AI tool to write an entire

27:41

email for me

27:42

that converts into pipeline or an opportunity. That still hasn't changed for me

27:47

to a certain

27:47

degree, but there's still have been some major improvements in this field. If I

27:52

'm stuck,

27:53

it gives me a really great starting point to help me shape my message and get

27:56

the creative

27:57

agents flowing. I'll get into this a couple slides from now, but I'd much

28:01

prefer starting and writing

28:03

my own email and using AI to coach me on my grammar, cutting fluff, rewording

28:08

anything that

28:09

sounds off rather than the reverse. So if you do have writer block or need a

28:13

good reference point,

28:14

you can always just generate a few email examples, picking two of the few

28:18

sentences that look great

28:19

and go from there. The medicinal use cases, leveraging JAREDA.I can be sending

28:26

out a post

28:26

call recap email. It's really great for just remembering what prospects ask for

28:32

on calls.

28:33

But again, I'm typically going in and editing most of what that follow up email

28:37

is going to look

28:38

like. Like in come off as Ryan and not just an AI sending an email. For me, I'd

28:45

put generative

28:45

about 60% height and 40% helpful review right now. I'm almost to the point

28:50

where it's 50-50.

28:52

It can be helpful in the right context and situation, but it still takes a lot

28:57

of human effort to get

28:58

this right. And so a few generative tools I love to use on a daily basis are

29:05

some of the big names

29:06

that everybody's probably heard of, chat, hibt, google bar, or perplexity. And

29:10

I'll usually prompt

29:11

all three of these to see what insights each of them will gather. For this

29:16

example, if I was

29:17

prospecting or have a first call with my VP of wrap ups here at Qualified, this

29:21

is the prompt I'd

29:22

start with. Can you pull some insights from Qualified's website? Tell me what

29:26

their goals might be.

29:27

You can go as far down the rabbit holes you'd like, but I always like to dig

29:31

until it breaks

29:32

because you never know what valuable information it's going to give you. I go

29:36

in, I ask him how

29:39

it's going to be relevant to Karen's role. I try and find any hobbies or

29:44

interests that

29:45

Karen actually likes to do outside of work to try and personalize a little bit.

29:50

And then I can

29:51

give it a prompt that relates what Karen's into, his golf game, improving it to

29:57

how Qualified

29:58

can help him improve his website conversion, and so on and so forth.

30:04

Moving into more some of the coaching side of things, I think this is where AI

30:10

shined the most.

30:11

For me, just as a rep in my day to day life, I use tools like Lavender and Gong

30:16

every single day

30:16

to iterate and make myself a better seller. These tools provide scalable team

30:21

insights so that

30:22

leadership doesn't miss any bad habits that need to be stopped right in their

30:26

tracks. And the data

30:27

is backed by actions and actual reality, things that reps are doing every

30:30

single day. The reps who

30:33

are open to this coaching, no matter the situation, start to pile up wins, and

30:38

the reps who stay stuck

30:39

in their ways will start to fall short. I do find that sometimes AI can miss

30:43

some of the contacts.

30:45

For example, a prospect mentions a competitor on a call once. They aren't using

30:51

them, but the AI

30:52

now alerts my team and my manager that this is a competitive deal when we just

30:56

talked about a

30:57

competitor once. Humans are still needed to implement action on this coaching,

31:03

and I'm currently

31:04

all the way in on how AI can constantly make me better as a seller every single

31:08

day.

31:09

Couple examples here. We'll talk about writing coaches. I use Lavender and Gram

31:16

marly on pretty

31:17

much every single email that I sent. There's a couple examples here, but there

31:21

's hundreds of

31:22

different ways to write an email from what I've seen, both in getting prospect

31:27

ing emails sent to

31:29

meet personally and using AI myself. There's generally three schools of thought

31:35

. There's the

31:36

automation school letting AI do most of the work. It looks fine. You copy and

31:41

paste it and send it

31:42

off. But in a world where your prospects inbox has hundreds of prospecting

31:47

emails in it every

31:48

single morning, a year for now when the percentage of people using AI grows

31:52

from 70 to 80 to 90 percent.

31:54

How many more emails do you think your prospects are in the beginning? You have

31:58

to stand out.

31:59

Automating completely everything will get you a couple places, and that's a

32:03

spam folder or

32:04

a trash folder. The second way is automation with a little bit of flair. You

32:09

did your personalization

32:10

in your research. You give the specifics of the prospect and the personal

32:13

ization that you found

32:15

through the AI and ask it to relate to your value crop. You edit the email, you

32:20

send it off.

32:20

This method has gotten me some meetings every now and again. If you're smart

32:24

about how you scale

32:25

this, but I'm skeptical about how this method scales over time. The third way,

32:32

and I've already

32:33

alluded to this early on in presentation, is handwriting your email, full email

32:38

and copy,

32:39

looking at it and letting the AI coach you and edit it for you. It'll prompt

32:46

you for suggestions.

32:48

It'll give you some edits that you can make to edit it down. You can see I went

32:52

from a 77 on this

32:53

first email here to a 90 within 14 minutes. It's a long time, but I usually don

32:59

't spend that much

33:00

time on an email and send it off. This is my number one method, and we'll lead

33:06

us into our next session,

33:07

where AI can help you help coach you and make your own work just a little bit

33:11

better.

33:11

Recording calls has been ubiquitous for years now, but it's only become more

33:19

powerful and useful.

33:21

It was like gone, chorus, sales, love, outreach, record your conversations, and

33:28

they provide you

33:28

with actual items to send post call, e-topics, and keywords and problem

33:33

statements that were

33:34

discussed and showing the call, that you can discuss with your manager, and

33:38

then also will give your

33:40

leadership in your manager an idea of what deals could be at risk or more

33:44

accurate forecasting based

33:45

upon how the conversation is going and how the deal stages are moving along.

33:50

Reps are held accountable

33:51

at all times during cycles, whether we may like it or not, and having a coach

33:56

who's only there to

33:57

make you better is going to significantly improve your weaknesses and only make

34:01

your strength better.

34:02

Reps who take this feedback and stride will have a serious leg up, and the rest

34:08

who ignore this

34:09

will start to fall right away. To finish up, a few thoughts and predictions for

34:15

2024 and how

34:16

sales teams will adapt to this new world we're selling in. The first is that

34:21

teams will adopt

34:22

this idea of AI in automation, and that it's going to become more relevant, and

34:30

teams are going to

34:30

learn their lesson that this is not going to work for them. Sales reps, AI is

34:34

not going to do your

34:35

job for you, but it will help you do your job extremely efficiently. If you're

34:39

using it for

34:40

nominal tasks already, you're ahead of the game. Reps will look at their

34:44

weaknesses and use AI to

34:46

improve them and double down on their strengths and they'll have the upper hand

34:49

on reps you don't.

34:51

I say we're at the peak of AI that's in the industry right now. I think there's

34:56

going to be some AI

34:57

coming up here in 2024. Tools that don't meet buyer's expectations are going to

35:02

fall by the

35:03

wayside, and tools that exceed expectations will only get better as time goes

35:07

on. And after the

35:08

facts, I think it will be in a much better position to become market leaders.

35:12

Last but certainly not

35:14

least, people buy from people. Humans trust other humans that they connect with

35:19

, and AI is going to

35:20

help reps and managers move deals along, but deals will get done at the human

35:23

level.

35:24

I'll leave you with that. I hope this session was helpful, and that's all crush

35:29

our numbers and

35:29

the year. Thanks everyone. Thanks for that deep dive, Ryan. I'm curious what

35:34

Chatch EPT told you

35:35

about my golf game. One of the ways we know AI is helping both marketing and

35:39

sales leaders is

35:40

taking over some of the more mundane tasks to free us up to get more creative,

35:44

but VDAR is taking

35:45

that to a whole new level by using AI to help sellers make more creative,

35:49

engaging content for

35:50

their buyers. Ali Forbes, Sales Manager at Vidyard, is here to show us how to

35:56

think outside the box

35:57

with the help of AI. Hello, everybody. My name is Ali Forbes. I'm a Sales

36:03

Manager at Vidyard.

36:04

I've been selling Vidyard since June 2020. It feels like forever ago and just

36:10

like

36:11

yesterday as well. I've been worked way way up as a top performer and I've been

36:16

a Sales Manager

36:17

here since March 2022. I'm almost two years as a manager. I finally know what I

36:27

'm doing as a

36:28

manager. I'm really excited to chat with you all today about leveraging the

36:32

power of AI to cut

36:33

through inbox noise. We're going to chat a little bit about video, AI, and the

36:39

humanization piece

36:40

as well, really just marrying the two in order to be successful and building

36:47

pipeline, whether that's

36:48

marketing sourced or sales sourced at the end of the day, as long as the

36:52

pipeline's there, who

36:53

really cares where it comes from here. So I'll jump to the next slide here and

37:01

sit.

37:05

There we go. You'll notice here from the title, it's as virtual as the normal

37:12

for sellers and buyers.

37:13

I've presented on similar topics in the past and virtual previously was the new

37:20

normal, but at this

37:21

point, it's here to stay, whether you're selling virtually from home or

37:26

virtually on your laptop

37:28

in an office. 76% of sales managers believe remote sales is the most effective,

37:35

but most

37:35

importantly, our buyers, 80% of buyers say they prefer remote sales interaction

37:42

. So we really do

37:44

need to meet our buyers where they're at. Obviously, we have our sales

37:48

processes and

37:48

things that we know that work. But buyers at the end of the day are the ones

37:54

that keep us going.

37:55

So we really need to, again, meet them where they're at and sell to them how

37:59

they prefer to buy here.

38:01

So there's a number of aspects that go into by behavior in terms of building

38:07

pipeline, obviously,

38:09

and closing revenue. So just studying the stage here before we get into the fun

38:13

stuff with AI

38:14

and humanization. But typically, the top three that I've noticed that my team

38:21

is known as as

38:21

a sales org. The industry is buyers prefer like self education. So whether that

38:28

's

38:28

easily digesting content on a website or, you know, their own third party

38:34

research, things that

38:35

they can do on their own in their own time. I think a lot of folks are

38:40

experiencing this,

38:42

like buyers prospects don't want to talk to sales unless it's absolutely

38:46

necessary.

38:48

You know, and they're in the stage where they're in that action or desire phase

38:52

where they

38:53

they finally do want to purchase. And then, of course, asynchronous decision

38:57

making. And if anyone

38:58

is wondering if I spelled behavior wrong or right, I was second guessing myself

39:03

, but I'm Canadian.

39:04

So in my mind, I have spelled it right. I did do a quick Google search prior to

39:09

this.

39:10

So I'm just going to jump to the next slide here. So just something that we've

39:16

noticed from like an

39:16

IC, like a rep perspective in terms of a problem that they're looking to solve

39:21

is that 40% of sales

39:23

reps according to Forester are looking for new ways of selling in this remote

39:30

environment,

39:31

especially now the market has never been tougher to sell. It's not only harder

39:36

to catch our ICP's

39:37

attention, but rather like earn their time, like given the budgets and how long

39:41

it takes to make

39:42

decision make decision. So our prospects need to know that you're going to show

39:47

them value,

39:47

whether or not they buy from you or not, that at least is half an hour or 45

39:50

minutes spent with you

39:51

has been valuable to them in their mind here. So what are we doing at Vidyard

39:57

to help mitigate

39:57

this? And how can we find the balance between AI and humanization or personal

40:03

ization, ideally

40:04

humanization? A lot of folks are looking for a silver bullet to solve all their

40:10

problems.

40:10

Even when prospects come to Vidyard, they're like, well, how can we make this

40:13

more efficient and

40:14

not actually record videos for every single prospect? And like, I think it's

40:20

really important to define

40:21

what does efficient mean for you. I think if you didn't have to record a video,

40:25

if you wanted to

40:26

make things human and personalization, you'd be selling Vidyard for a million

40:29

dollars. And

40:30

that's not the case. But you can absolutely marry the two here. So just taking

40:35

a step back

40:36

in terms of what how like what Vidyard actually does for those who don't know,

40:40

we're a full suite,

40:41

go to market tool for driving leads, pipeline, revenue, of course, like on the

40:46

marketing side,

40:47

overall sales efforts and host sale as well. As we can see here, there's a

40:52

number of pros

40:54

in terms of leveraging AI and the humanization piece and like with your sales

40:59

process. So we

41:00

won't get into absolutely everything here today. But really what I've done, I

41:03

've selected like the

41:04

top four that we focus on at Vidyard for ourselves and then potentially

41:09

customers as well. And

41:11

hopefully you do see some sort of value in this to help build your own pipeline

41:15

. So first of all,

41:17

leveraging like hosting video as well in combination with your CRM, whatever

41:24

that may be like a sales

41:25

force or hub spot, marketing automated platform like Mark Keto and using AI to

41:32

identify leads

41:33

and qualify leads. So just using the database that you have the AI,

41:38

technicality part is above my pay grade, but it's something that we're doing

41:42

here. Not only to

41:44

again, just identify leads, but create at minimum 30 to 50% more qualified

41:50

leads for our teams. So

41:51

we're spending time and personalizing our outreach to the right folks and we're

41:55

spending our time

41:56

efficiently here. So that's one aspect that we're doing here. Secondly, when it

42:02

comes to research

42:04

and generating sales pipeline, like just what my team is doing, what we

42:07

recently been doing is

42:08

using chat TPT as soon as we sign on a customer. I just use Shopify as an

42:13

example. We'll pop in.

42:15

Hey, let's say we sign on Shopify. I don't know if we have to, but like give me

42:22

the top five

42:23

Shopify competitors. And then from there, we'll tailorize our outreach. We

42:29

already have like a

42:29

cadence setup for competitive prospecting. I have an example here that you can

42:34

see where you'll just

42:35

like pop in the competitive organization and Dolly prop and so forth there. So

42:42

really just using

42:43

AI just to help you do overall research. I've been doing it as well. This is

42:48

not meant to be like

42:49

a video art pitch. We have a two platform called prospector where you can

42:55

basically set up your

42:57

territory and then AI grab all the accounts, all the prospects that you'd want

43:02

to be reaching out to.

43:03

You can create a quick general video that's included in this email outreach and

43:09

then like the AI will

43:10

also spit out the messaging. So it's very general, but the results you get from

43:15

that, our team will

43:16

personally do their outreach to the folks who are the most engaged as well. And

43:22

then lastly,

43:23

video messaging, right? Video is new to a lot of folks. We use chat GBT to help

43:28

create video scripts,

43:30

just making these video a lot easier and decrease that learning curve like cold

43:34

calling,

43:35

write an email poppy. That's all new for a salesperson. So at the end of the

43:38

day, this is just a new

43:40

tool to your tool belt, but use a technology for you to be more human and

43:45

ultimately see

43:46

more success there. So rounding out here, these are the four things that we

43:50

focus on right now with

43:51

AI and humanization, lead identification, research, prospecting, and then

43:56

overall video messaging. So

43:58

thank you very much for listening to my chat regarding AI and humanization to

44:05

help drive pipeline.

44:07

Feel free to connect with me on LinkedIn and happy to answer any questions.

44:11

Thank you so much,

44:11

the qualified team for having me. That was great, Ali. We've talked about

44:16

enablement. We've talked

44:18

about how to engage your buyers in new ways. And now we're bringing it all home

44:21

and learning how

44:22

to use AI to better build and scale your win loss program with Ryan Sorley VP

44:27

of win loss at Clue.

44:28

Hey, everybody. My name's Ryan Sorley and I'm the vice president of win loss

44:32

over at Clue. I'm

44:33

super excited to be here with you today to talk about something that's really

44:37

near and dear to my

44:38

heart, the use of generative AI technology to launch your win loss program.

44:44

Just to set the stage,

44:46

when I think about win loss and when we think about win loss at Clue, we really

44:51

think about it

44:52

in the form of building blocks. We'd like have to identify the program type

44:56

that we're launching.

44:57

Is it focused on channel partners or direct sales motions? We have to narrow

45:03

down the objectives.

45:05

We have to think about is this a effort to collect data on competitors or maybe

45:10

it's a

45:10

effort to understand how people perceive our product. And then we have to get

45:16

into the segmentation

45:17

of opportunities. So when we're collecting data, we want to end up with enough

45:22

of a sample size of

45:24

anything to be able to start to do trend analysis. So that might be looking at

45:28

our enterprise business

45:30

versus our SMB business, maybe looking at our European market versus our North

45:35

American market.

45:36

We want to isolate those. So we do go through a segmentation process to

45:40

typically help

45:41

get things going. And that's what we would recommend to you. Then we want to

45:45

start to

45:45

figure out, well, what questions are we going to ask in these win loss

45:49

interviews? And those

45:51

should definitely align back to those objectives that you created with your

45:55

team as you were

45:56

launching the program. Then you get into the outreach, which is often a

46:01

problematic area for

46:02

a lot of people getting folks to actually respond yes to an interview. Then we

46:06

actually hold the

46:07

interviews and think through like, what is the strategy that we're going to

46:11

take when we're

46:13

speaking to somebody to get them to really open up to us? And how are we going

46:17

to summarize

46:18

our conversations? And then finally, how are we going to identify themes that

46:23

are emerging from

46:24

across all of these interviews? So traditional win loss looks like this. But

46:30

when we're thinking

46:31

about AI for the purpose of this conversation, because I only have 10 minutes,

46:36

I'm going to focus

46:37

on these last three areas, which is the generating the outreach plan holding

46:42

interviews and thematic

46:44

analysis. So let's start with the first area. And let's talk about the

46:50

challenge. So more times

46:52

than not, I hear from salespeople, product marketers, leaders that they have a

46:59

really difficult time

47:00

getting people to respond to requests for interviews. People are too busy. They

47:06

've moved on if it's a

47:08

loss. And that is an area that I want to focus on here, because I think there

47:13

is a way that we

47:14

can leverage AI technology, generative, generative AI technology to help here.

47:19

So at a basic level,

47:22

what organizations should be thinking about when looking to schedule interviews

47:27

is asking earlier

47:29

in the process for that interview. So if you're a seller, and you're maybe at

47:34

the demo phase,

47:35

maybe you're at the price or negotiation phase, that's the time when you should

47:41

ask if that particular

47:42

buyer champion would be open to speaking to you again, or speaking to somebody

47:47

within your

47:48

organization after they've made their final selection simply because you're

47:53

eager to understand

47:54

what their experience was like and learn from it. By asking when you're still

47:58

engaged,

47:59

your chances of getting that person to respond favorably are significantly

48:03

higher. So that's

48:04

the first step. I know it's not gen AI related, but I'll get there. The next

48:09

area is to schedule

48:11

those interviews once that you'll close this in your CRM. So you're automating

48:16

that request

48:17

earlier on. Now you're automating the request to follow up on that person with

48:21

that person who

48:22

agreed to the interview. And then you can get that interview schedule. However,

48:26

if you are unable

48:28

to do these things, there is a new technology area that we're really doing a

48:34

lot of experimenting with,

48:35

which is actually using voice bots. And before you kind of roll your eyes or

48:40

laugh, there are

48:41

technologies out there that are quite advanced. They can actually use your own

48:45

voice. And you can

48:47

build a generative AI workflow in the discussion field within these platforms

48:52

to be able to

48:54

have a really natural conversation with folks. So think about using AI

48:59

technology and generative

49:01

AI technology for phone calls, actually reaching out to people following up on

49:05

those emails that

49:06

you sent and trying to schedule them. These tools are super advanced. And if

49:11

you spent a little time

49:12

looking at some of them, I think you'd be quite surprised at how advanced they

49:16

are. And they can

49:16

actually, a single bot can make up to 3000 calls a day. So super good use of

49:21

the hub of their time

49:23

to do that work for you. Now let's move on to the next challenge, which is

49:28

really focused on

49:29

summarizing those interviews. See, if I had a great conversation with somebody,

49:34

maybe you've

49:35

taken some notes, maybe it's chicken scratch, maybe you have a stronger process

49:39

for doing it.

49:40

But I think that it's been a challenge historically for people to take those

49:46

conversations and turn

49:47

them into some sort of a deliverable for the rest of their team. So what we're

49:51

going to do here is

49:53

we're going to touch on a tool that we use every day, which is called Rev. It's

49:58

a transcription tool.

50:00

And there's plenty of transcription tools out there, different levels of

50:04

quality, of course.

50:05

But that first step is having some sort of automated transcription of your

50:10

conversation. And that may

50:11

require you getting consent from the person you're interviewing, especially if

50:15

they're in the European

50:16

Union and GDPR compliance is an issue for you. But we recommend asking for

50:22

their permission

50:22

to record the conversations and 9.9 times that of 10, they'll agree to it. So

50:28

this is basic,

50:29

right? A summarization or sorry, transcription has been around for years. But

50:33

what's new is this

50:35

whole idea of summarizing the conversations. And a lot of these tools today,

50:42

based on chat,

50:43

GPT coming into popularity late last year in November or so about a year ago,

50:49

we can actually

50:50

summarize those conversations into something meaningful. It might be a 15 page

50:54

transcript,

50:55

but you can narrow that down into a paragraph of three or four sentences that

50:59

do a pretty good

51:00

job of describing what happened in that interview. And that might be good for

51:04

some, especially if

51:06

you're conducting win loss interviews at scale. However, a lot of folks need to

51:11

go deeper. So

51:13

what they are looking for is the ability to ask questions about that particular

51:19

interview.

51:20

And those questions might be related to, you know, how was the sales experience

51:24

or what were the

51:25

business drivers that led you to look at our solution as compared to others and

51:29

what solutions

51:31

did you look at? Which of our competitors did you evaluate and what did you

51:34

think of them?

51:35

And there's a lot of wonky technology out there today that will do this. And

51:39

then there's some

51:40

really good technology. And going back to Rev, I'm not paid to promote Rev, we

51:45

just have been

51:46

using them for years. But they have also come out with a really interesting on

51:50

capability where

51:51

you can just ask those questions. And those questions, if they're consistent

51:56

from one

51:57

interview to the next can start to build a really interesting database of

52:01

insight about

52:03

key learning objective areas. Like, why were they looking? What were key

52:07

selection criteria?

52:08

What resources did they leverage? What competitors did they look at? How did

52:13

they feel about your

52:14

price, your sales experience? So there's a whole list of common areas that you

52:19

can use with the

52:21

capability like this to kind of start to string data together. So now you have

52:26

this view into

52:27

what happened in a deal and you're starting to farm data from an individual

52:33

interview. But the

52:34

next challenge is how do you look across interviews and start to summarize this

52:40

data in a way that's

52:41

meaningful that identifies trends, which is the next challenge here. Now what?

52:44

What do I do?

52:45

So the way that we think about that is using generative AI technology to dip

52:52

into all of

52:53

this unstructured data using prompts to be able to tell a really cohesive and

52:59

comprehensive story.

53:01

One of the things that we've rolled out recently at Clue is focused on looking

53:06

at GT reviews,

53:08

trust radius, Gargner, Pure Connect, resources like that, where there's actual

53:13

real buyer and

53:14

customer feedback, pulling all of that data together through generative AI

53:20

technology and machine

53:21

learning to spit out what are those core strengths and weaknesses? What are the

53:26

key areas that people

53:28

talked about most that they really liked about each solution in dislike? So

53:33

when you're looking at

53:33

this type of data from a win loss perspective, competitive intelligence

53:37

perspective, leveraging

53:39

various tools to get to this point are going to be super critical in the future

53:44

and more and more

53:45

companies are coming out with these types of capabilities. So in the 10 minutes

53:50

, I have 32 seconds left,

53:52

I just wanted to wrap up that these are three immediate areas that you can

53:57

focus on to really

53:59

get your win loss program rolling. There's a lot of other areas that still

54:04

require some manual

54:05

intervention, but our vision is over the next few years to have all of this

54:10

stuff be fully

54:11

automated borderless, which would be in any language and always on collecting

54:18

data at scale as you go.

54:20

So I hope you found this information to be valuable. If you have any questions

54:24

and would like to go

54:25

deeper in any of these areas, feel free to shoot me a note. I'd be happy to

54:29

chat.

54:29

Thanks, Ryan. That does it for our sales pipeline power hour here at Pipeline

54:34

Summit AI.

54:35

Thank you so much to all of our speakers. It's great hearing how other teams

54:39

are leveraging AI

54:39

within their sales strategies. And we definitely learned a few things to take

54:43

into 2024 with us.

54:44

We'll see you next time.

54:50

[Music]