Build the ultimate modern tech stack as we walk through the AI tools you need in 2024 to generate more pipeline. From driving intent to workflow management to closing the deal, the AI-powered platforms work together to supercharge your pipe gen strategies.
0:00
All right, everyone, I'm back and I'm excited about this session because I
0:03
think we can all agree that AI powered products sound great,
0:07
but it comes to actually understanding what technology is out there,
0:10
and more importantly, the use cases it solves for gets a little bit murkier.
0:14
There are new AI products hitting the market every day,
0:17
and it can feel overwhelming to figure out how it all hangs together.
0:20
So let's take a look at how to use AI powered martech to fuel your pipeline
0:25
generation strategy from the first touch
0:26
all the way through to closing that deal.
0:28
First, let's talk about something we're all familiar with because you're using
0:31
it right now to watch pipeline summit AI,
0:33
which is Goldcast.
0:34
Margaret has spent so much time planning and executing events to get in front
0:38
of our audiences,
0:40
and Goldcast's new content lab is making it easier than ever before to get the
0:43
most out of your event content.
0:46
Check it out.
0:47
All right, so I'm going to take you through the journey of an event,
0:52
the journey of a full end to end multi-channel campaign that was inspired by a
0:58
Goldcast event strategy.
1:00
We run a series here at Goldcast called Donuts and Demand,
1:05
targeted at our audience B2B marketers, really helping them connect with our
1:09
broader community,
1:10
learn best practices, et cetera.
1:12
Many of our customers also run these types of event series on Goldcast,
1:16
and this is what they look like.
1:18
And one of the common requests we get is how to tend the life of an event,
1:23
extend the campaign around that event.
1:26
I'm going to show you how we do it here at Goldcast.
1:28
This is our on demand content from that event that you just saw.
1:31
You can come in and watch the event.
1:33
You notice that it's 58 minutes.
1:35
So part of our whole strategy here is to give you those takeaways that you don
1:39
't have time to watch the event via a blog post.
1:42
It also will ultimately drive interest in watching that on demand event to see
1:46
some of the top quotes,
1:48
to see some of the top clips.
1:50
And so our team is hard at work generating this full end to end campaign,
1:54
the content to go along with it, the clips to go along with it, the clips even
1:57
to post on social,
1:58
to give you that snappable taste of what the webinar was like.
2:01
It could be there along with driving me back to the links to that blog posting
2:06
more on demand.
2:07
And so how did we get there?
2:09
We used the Content Lab.
2:11
We developed the content lab to sell the top pain point for B2B marketers
2:15
who generate really great content throughout their business,
2:18
but then have to collaborate across the team to get that snappable clip, to get
2:21
that blog post.
2:23
So on Goldcast, when you run an event, you have a video, you have the entire
2:26
trends for the event.
2:28
For anyone who's worked with Generated AI, you know that a lot can be done when
2:32
you have a lot of great language to work with.
2:35
So the two use cases we empower users where are creating video clips and
2:39
creating text summaries.
2:40
Here you can generate the top clips from the event or even highlight a really
2:44
snappy quote that you want to create a clip from.
2:48
If I want to just jump right in, I'll show you one of the clips we generated
2:51
here with Chris.
2:53
Part of the magic of the Goldcast Content Lab is that we pull the active
2:57
speaker feeds.
2:59
We pull all of those feeds.
3:01
We also pair them with your brand colors.
3:04
And we can give you lots of templates to work with right out the gate. You can
3:09
go back and forth.
3:10
You can really understand what's going to work best for your strategy with what
3:13
you have here.
3:14
You can also use audiograms.
3:16
So you highlight the caption, you highlight the speaker image if you didn't
3:21
think the video was not compelling,
3:23
or if you want to go with something different.
3:25
So all of that is built into the Content Lab when you have the clip that you
3:30
want to use.
3:31
You can download it and you can generate a summary to go along.
3:35
So you remember our blog post over here.
3:37
This is a great tool to generate a starting point.
3:41
You can generate a few different use cases.
3:43
What you're seeing here is a blog post outline developed from our Content Lab.
3:48
We also have key quotes.
3:51
So one of the custom use cases is to generate quotes.
3:54
That's one of the things that really saves Markner's time.
3:56
You can ask it to generate with context.
3:59
You can also go in and generate in any of these use cases.
4:02
You can see here a follow up email for people who couldn't attend with key take
4:06
aways.
4:07
There's another thing that you can have ready to go.
4:09
So in my conversation with many of our customers, we've noticed that really
4:14
helping with that first draft,
4:15
really helping with generating some of those clips, already getting them
4:18
branded.
4:19
It's going to take steps out of the workflow.
4:21
It's going to cut down for many of our beta customers from weeks of work up to
4:24
three weeks of work down to hours.
4:27
We use it in our own strategy as you saw, and I'm so excited for you to try it
4:30
out too.
4:32
We've launched all customers at the end of October, and I can't wait to hear
4:36
what use cases you've come up with.
4:38
I know my team is so excited to put Content Lab to the test after this event.
4:42
But what good is all this content if you aren't able to harness the engagement
4:46
and convert it into pipeline?
4:47
That's where the rest of our tech stack comes in.
4:50
Goldcast just helped you put a bunch of campaign content into market.
4:53
Now let's take a look at how to leverage six senses predictive model
4:56
to identify when accounts are most likely to convert and when to start reaching
4:59
out.
5:00
We've spent the better part of 10 years trying to help companies do what we
5:04
call light up their dark funnel.
5:06
So the dark funnel is a phrase we love so much we trademarked it.
5:10
It essentially represents kind of the research activity that prospects are
5:13
doing,
5:14
usually anonymously on websites you don't own.
5:18
So a company's interested in a chat solution, let's say, and before they go to
5:23
a qualified website,
5:24
they might be doing research on industry publications, blogs.
5:28
They might be going to technology review sites like a G2, TrustRadius, Gartner.
5:33
And we essentially have relationships with millions of different publishers
5:39
where we get all of that activity data
5:42
and then use our own matching technology, which is best in the industry,
5:47
to associate all of that activity back to accounts.
5:50
So not to individual people, but to the accounts that are doing that research.
5:54
So you can imagine for any single customer, we've got tens of millions of data
5:58
points,
5:59
about everything that's happening kind of leading up to when an opportunity is
6:03
open all the way through
6:05
till that opportunity is closed one or closed lost.
6:08
And so where the AI really starts to come, and by the way, there's a bunch of
6:11
AI involved in how we track
6:14
what the pages are about in the dark funnel. So we've got natural language
6:19
processing algorithms there.
6:20
One of the ways that you track your dark funnel activity is by entering
6:24
keywords.
6:25
We use AI, for example, to recommend keywords in addition to the keywords that
6:29
you as a customer might decide you want to put in.
6:33
But I think kind of the secret sauce that uses AI that we're most known for is
6:39
what we would call our predictive model
6:42
or our buying stage model. So with all of this data that we ingest, we actually
6:46
have five or six different ML models
6:49
that run on that data to produce different types of scores.
6:52
So we have an ICP model, for example, an account profile fit model. We have a
6:56
contact profile fit model.
6:59
So which personas are most involved right before an opportunity gets open? I'm
7:03
not going to get into all of those today.
7:05
This, the one that you're looking at right here is the one that we're probably
7:08
most well known for.
7:10
And by buying stage model, what it's basically doing is it's looking at all of
7:14
your historic historical opportunities
7:17
and what were those accounts doing right before the opportunity was open?
7:22
And it's then scoring every account in your CRM today based on where in that
7:27
buying journey we think they are relative to these other opportunities that
7:32
were open. So it is a predictive model. And you can see here, this is kind of what a
7:35
pretty healthy funnel would look like.
7:38
You know, Sixth Sense did not invent the concepts of awareness consideration
7:43
decision purchase marketers have been using those terms
7:46
for probably close to a hundred years now. But it is sort of central to what
7:50
our customer's revenue operating models look like,
7:54
which at its core is marketing should focus on awareness and consideration
7:58
accounts and moving them through the buying journey.
8:01
Sales should focus on decision and purchase stage accounts and closing business
8:06
with them.
8:07
And so it's a very easy way for both marketing and sales organizations to work
8:11
from the same set of data to have a very clear sort of division of labor as to,
8:17
you know, who's responsible for what and when.
8:20
And as you can imagine, one of the things that I think is powerful about this
8:25
is in addition to allowing marketers to run different plays and tactics at
8:30
accounts with at least an educated guess as to where they are in the buying
8:33
journey.
8:34
It also gives sellers a wealth of information about exactly what those accounts
8:39
are doing.
8:40
Incredible.
8:41
You've used AI built content to drive demand with your target accounts,
8:45
identified which accounts are in purchase mode and most likely to convert.
8:48
And now it's time to start reaching out.
8:50
But the album process can be a little overwhelming to manage sales loss latest
8:54
AI release rhythm uses AI to help you manage your entire out on motion from the
8:59
first email all the way through the entire buying cycle.
9:02
So let's see how it works.
9:04
So this screen may look very familiar to you as far as what your team's day to
9:09
day looks like.
9:11
2023 studies show that only 28% of a seller's time is actually spent selling.
9:17
And only about 25% of sellers are on track to hit quota.
9:22
And what a lot of companies have done is they've spent more money on tech stack
9:26
to help with this with the average being about 120 applications.
9:31
And so while the goal was to create efficiency and productivity, what a lot of
9:34
that has done is is created more of a distraction swivel chairing and kind of
9:39
organizing that chaos.
9:41
So this is where we have rhythm come into play to really help with this.
9:45
So while we do have various different focus souls to kind of meet the seller
9:48
where they want to live, you know, the more the structured ones with our cad
9:52
ence, the proactive, multi channel approach to get to some sort of end goal, as
9:58
well as our clothes, which is more of that opportunity
10:00
management.
10:01
And then we have our unstructured workflow, which is rhythm.
10:04
So I want to dive a little bit deeper into rhythm with you.
10:06
And what rhythm is is it's using our conductor AI to turn the buyer behavior
10:11
from across your ecosystem into seller actions.
10:15
So it's allowing teams to prioritize actions that drive to their outcomes
10:20
quicker.
10:21
So let's head on a couple of things that pull into here.
10:23
So one of the first things that has been something that our clients are really
10:26
excited about is having the ability to pull in their third party integration.
10:31
So we have some to highlight such as DocuSign, G2, Vidyard, the same kind of
10:35
sprinkled throughout, but we do have more and more that we're adding to the
10:39
platform, the capabilities.
10:41
We're also going to be looking at CR and the data when it comes to opportunity
10:45
and the buyer engagement that the sellers having.
10:48
And also the seller's activity that they have a meeting, do they have one
10:51
coming up and having problems for that.
10:53
And really what the AI is doing is it's looking at our opportunity information
10:58
and it's looking at our buyer engagement and it's breaking those actions based
11:03
off of the immediacy and the impact and prioritizing them based on the
11:07
likelihood to lead to a book to
11:09
a book to needy or an open opportunity and it's looking at that deal importance
11:20
So one thing that says I've really prides ourselves in is explainability with
11:24
our AI.
11:25
So you'll see it sprinkled throughout, but just to call it out here as I hover
11:28
over the opportunity specific data, you'll see it's already indicating why the
11:30
conductor AI has prioritized as the way that it has. So you'll see that one thing in particular is our deal engagement score. And
11:40
what our deal engagement score is is it's using that AI to provide insight of
11:42
the likelihood for this deal to end as a closed one based off of recency,
11:44
frequency, progression and engagement we've had with our buying committee
11:48
and really ultimately removing the subject to me of the deal.
11:52
But I also have that same insight from the buyer engagement perspective. So you
11:56
can see the key factors that are impacting this for my email sent, clicked, and
12:00
those call connects that I made.
12:03
So let's take a further look into the workflow of rhythm. And let's say I've
12:06
already booked a meeting or I've done a meeting and I want to provide a follow
12:10
up here.
12:11
So I can go ahead and action this and having my sidebar that follows me along
12:14
here, making it super easy to be efficient in my day. And then you'll see that
12:18
it's already pulled in this template and it's ready to go to where I can add
12:21
personalization or leave it as is.
12:24
One thing I want to call out that will introduce our conversations AI is these
12:28
next steps and action items.
12:31
So I'm going to take a glimpse into our conversations and show you where we're
12:34
pulling this information as well as other AI insight that's available.
12:38
So tapping this down, we do have a recap tab that's going to give us two pieces
12:42
of media in conversations.
12:45
First, it's going to look at the summary. This is going to provide, hence the
12:48
name, a summarized view into what occurred during this meeting.
12:52
And then it's also going to have those action items laid out that as you see,
12:56
we set up automation to automatically pull that into an email.
12:59
So what I'm getting here is not only am I getting efficiency with those meeting
13:03
follow ups and those action items.
13:05
I'm ensuring nothing falls through the cracks with those deliverables.
13:08
And then the other thing is, is we're thinking about a collaboration or a
13:11
coaching perspective.
13:13
This really allows us collaborating teams or those managers to understand at a
13:16
glance what happened and what is coming up and what do we need to drive towards
13:21
as an outcome from this meeting.
13:23
So as we wrap this up, you'll see that AI is critical to sales off and it's we
13:28
through our platform to really make sure that we're focusing our teams on the
13:34
right actions to get them to those outcomes that they're after quicker.
13:39
It's so cool to see how AI actually helps us spend more time marketing and
13:43
selling and less time in the operational weeds.
13:46
So you have your outbound plan, but does it mean anything if you aren't getting
13:49
a response from your buyers.
13:51
Lavender uses AI to score your email communications and identify areas where
13:54
you can make tweaks to optimize your outreach for engagement and response.
13:59
Check it out.
14:00
Hey everybody, Chad here from Lavender.
14:03
I'm going to show you an email intelligence platform.
14:06
And basically what that means is we're going to sit on top of your existing
14:09
email providers and show you how likely is your email to get a reply using your
14:13
best practice data.
14:15
So using personalized data from emails that you've sent historically to tell
14:19
you how do you perform the absolute best.
14:22
What it's going to look like this email right here.
14:25
You might think, great, right?
14:26
This is a perfect email.
14:27
Well, Lavender not going to tell you that.
14:29
We're going to tell you it's a decent email.
14:32
But really where we want to see this is at a 90 score.
14:35
This is where we're going to see the biggest improvement in terms of reply
14:37
rates.
14:38
So what do we want to do?
14:40
Want to get this up into the 90 range.
14:42
How do we do it?
14:43
Go through the steps, right?
14:44
Very first thing I'm telling you, subject length.
14:46
Make it shorter.
14:47
Don't use title or use title case.
14:49
Make it shorter.
14:50
Exclude numbers.
14:51
So let's make it shorter and exclude some numbers.
14:54
It's shorter.
14:55
My score is going to go up.
14:56
Subject length goes away.
14:57
Mobile issues.
14:58
We're looking at this.
14:59
Right here.
15:00
This is what it's going to look like when somebody gets it on a mobile phone.
15:03
Make it mobile friendly.
15:04
83% more likely to get a reply.
15:07
If you make your emails mobile friendly.
15:09
It's really quite simple.
15:10
You should do it on everything.
15:11
LinkedIn messaging, emailing, wherever you're writing, make it mobile friendly.
15:16
Now, this is if we're doing a sequence, a template step, right?
15:19
We've already got it written out.
15:21
Perhaps we don't have this.
15:22
Come over here.
15:23
We can actually do chat GPT.
15:25
This will show you.
15:26
You can use it to write an email, of course.
15:29
But what I'm going to recommend is initiatives and pain points.
15:31
What are some initiatives and some pain points that a CEO may be experiencing
15:35
right now, right?
15:36
And you can find that in the personalization.
15:39
This will give you all the information that we're able to find on Mr.
15:42
William Balance up here.
15:44
Use this.
15:45
Populate an email for you.
15:46
Biggest thing.
15:47
Make sure you run it through lavender and get that lavender score.
15:50
Once you click the send button, if you want to see how you're performing, if
15:53
you go into
15:54
your dashboard right here, the center column is going to show you everything
15:57
that we're
15:58
measuring.
15:59
You can click into any of them and see what is this actually doing to my data,
16:01
right?
16:02
What is long sentences doing to my data?
16:04
You can filter it by email type, teams, team member, specific domains, whatever
16:08
you need to see, it's all here.
16:10
If you need help with anything, as always, support 11 or .ai.
16:13
Reach out.
16:14
Let us know what you need help with.
16:16
We're always happy to help.
16:17
Thanks, everybody.
16:18
All right.
16:19
We've engaged buyers with our content.
16:21
We've identified the accounts that are ready to buy.
16:23
We've optimized our outbound workflow to be as efficient as possible.
16:26
And we've tailored our outreach to be succinct and impactful, all with the
16:29
power of AI.
16:31
But here is where it's all going to come together.
16:34
With the pipeline cloud powered by qualified AI, the outbound message we sent
16:38
at the exact
16:39
right moment is about to pack a major punch when our buyer clicks the link and
16:43
lands on
16:43
the website where an AI powered chatbot is ready to convert them into pipeline.
16:48
Watch this.
16:49
Thanks, Sarah.
16:50
Let's get into it.
16:51
So here on the qualified website, we have one of our target accounts, CARTA,
16:55
browsing
16:56
around.
16:57
CARTA can engage with the qualified team in multiple ways.
17:00
Things like chat, but also things like qualified meetings.
17:03
Simply by clicking on one of these calls to actions, our target account visitor
17:07
can get
17:08
a VIP access to the appropriate representatives calendar.
17:12
They pick the time that works for them and off they go, meeting booked.
17:16
But there may be some situations where this visitor is browsing around and
17:20
maybe looks at
17:21
a few things instead of just to have, hey, I have some questions about this
17:24
particular
17:25
product.
17:26
Rather than jumping right into a meeting, let's start to use qualified AI to
17:30
hopefully engage
17:31
and ask, answer some questions for this visitor.
17:34
Now, in this case, start to ask about things like qualified meetings.
17:40
What qualified is going to do is start to look through all of the content and
17:44
upload it to
17:45
our servers, everything from pricing sheets, product pages to the information
17:50
about the
17:51
account that's on the website right now.
17:53
Aggregate all that information to hopefully provide a sufficient response that
17:56
gets them
17:58
advanced to the conversation and generates some pipeline for your team.
18:01
Now, in this case, asking for a next step, yes, I would love to chat with
18:07
someone on the
18:10
team now.
18:13
Now, this is where we leverage qualified's unique intelligent routing
18:16
capabilities.
18:18
Qualified's going to use AI to figure out who's the accurate person to bring
18:21
into the
18:22
conversation and hopefully queue up our team with the right type of intel to
18:27
have a good
18:28
chat.
18:29
No, that's it for now.
18:32
It is it for now.
18:35
And let's jump over to qualified to continue this conversation.
18:38
Here inside of qualifying, I can see that Anna from CARTA has been prioritized
18:43
for our sales
18:44
representative alongside all of our other visitors here on the website.
18:48
Now, let's jump into this conversation with Anna and pick it up.
18:52
Now, before we actually start to send Anna a message over here, let's take a
18:56
quick look at all the information that we get about this visitor.
18:59
We can see their visit history, their account signal intent, all of the data
19:03
that we, at
19:04
times, will we've offered our book meetings with that team or that specific
19:08
individual.
19:09
We even get a wealth of information about that specific contact in that account
19:12
enriched by
19:14
other data providers, marketing automation, or data enrichment services.
19:18
But it doesn't end there because we actually can get an insight to what
19:21
specifically this
19:22
visitor is looking at right here on the website.
19:25
So as they browse around, this becomes a co-buying journey and we can help them
19:29
along in their
19:31
evaluation.
19:32
Now, I here have said I want to jump in based on everything that I now know
19:38
about Anna and
19:39
the team.
19:40
So here, I'm going to say, hey, you know what, I can talk about qualified
19:43
meetings.
19:44
Did you have any questions or specifically about pricing?
19:47
You know what?
19:48
Yes, I do have questions about pricing.
19:54
And let's say, great.
19:55
You know what?
19:56
Let's see if Anna wants to hop on a video call right here and now.
20:00
And it looks like, yes, she does.
20:02
And without ever leaving the qualified platform, I can turn this immediately
20:06
into a real-time
20:07
conversation right here on the website.
20:10
All things go well.
20:11
I end the conversation by simply putting in my calendar, selecting the people
20:16
that I need
20:17
to, and sending over this next step for us into our wonderful pipeline.
20:25
So just like that, we've taken a conversation, an interaction on the website,
20:29
turned it into
20:30
multiple touch points for generating pipeline and gotten that next meeting
20:34
booked with the
20:34
appropriate person on their team.
20:37
Sarah, back to you.
20:39
And there you have it, a modern tech stack powered by AI, taking an event just
20:44
like this
20:45
one and turning into engaging content, optimizing every step of the outbound
20:49
sales motion, crafting
20:50
pitch-perfect emails, and most importantly, generating more pipeline.
20:55
The future of pipeline generation is here, and it's powered by AI.
20:58
[MUSIC]
21:18
Okay, everyone.
21:19
That is a wrap on Pipeline Summit AI and on all of our pipeline summits for 20
21:24
23.
21:25
It's hard to believe that we're coming to the end of the year, but we hope that
21:28
you learned
21:29
a ton today and that you're heading into 2024 feeling more confident about your
21:34
AI powered
21:35
pipeline generation strategies.
21:37
We heard from so many incredible thought leaders today about how AI is changing
21:42
our
21:42
sales and marketing games.
21:44
I know I learned a ton from our lineup, and I just want to say thank you to all
21:47
of our
21:47
speakers who took the time to join us today.
21:50
And if you missed a segment, do not fret, all of this content will be available
21:54
on demand
21:55
just later today.
21:56
We'll be emailing the recordings to everybody, so hopefully you can reference
21:59
them as you
21:59
begin your 2024 planning, share them with a friend, whatever it may be.
22:04
We're going to be back in the spring with another fresh pipeline summit.
22:08
So if you want to know about that event, once we get closer to it, you can just
22:11
hit
22:11
the button in the top right, let us know if you're interested, and we'll keep
22:14
you in
22:15
the loop once we get closer.
22:17
And if you have just not gotten enough AI content, do not worry.
22:21
We mentioned that we launched our new show GTM AI, where every week our BP of
22:25
demand
22:26
gen Sarah McConnell sits down, and she takes a look at real product
22:30
demonstrations of
22:31
GTM AI technology to help demystify all things AI.
22:36
And we're going to be dropping new episodes of GTM AI every single week.
22:41
So just click the link below if you want to know more about that show and
22:44
subscribe.
22:45
Thank you again so much for joining us today at pipeline summit AI, and we will
22:48
see you
22:49
next time.
22:49
[MUSIC]
22:59
[MUSIC]
23:09
[MUSIC]
23:19
[MUSIC]
23:29
[MUSIC]
23:39
[MUSIC]
23:49
[MUSIC]
23:59
[MUSIC]
24:09
[MUSIC]
24:19
[MUSIC]
24:29
[MUSIC]
24:39
[MUSIC]
24:49
[MUSIC]
24:59
[MUSIC]
25:09
[MUSIC]
25:19
[MUSIC]
25:29
[MUSIC]
25:39
[MUSIC]
25:49
[MUSIC]
25:59
[MUSIC]
26:09
[MUSIC]
26:19
[MUSIC]
26:29
[MUSIC]
26:39
[MUSIC]
26:49
[MUSIC]
26:59
[MUSIC]
27:09
[MUSIC]
27:19
[MUSIC]
27:29
[MUSIC]
27:39
[MUSIC]
27:49
[MUSIC]