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,
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but we don't often hear the nitty-gritty details on how teams are finding value
0:14
in AI,
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and what's actually impacting their pipeline and deal cycles.
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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.
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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
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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
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listen to the full
6:12
call and leverage spotlight areas for in real-time coaching.
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When it comes to building programs and revamping our framework and language,
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leveraging AI can help with gathering insights on suggestions, methodologies,
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framework and coaching skills and language. For example, training and building,
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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,
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battle cards for their messaging, knowledge and training that are all being
7:45
generated by AI.
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So all marketing collateral, sales battle cards can be found and shared
7:50
internally or externally.
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For example, all updated resources and battle cards can be searched across
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through our generative
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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]