GTM AI Tech Tour

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.

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There are new AI products hitting the market every day,

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and it can feel overwhelming to figure out how it all hangs together.

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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

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all the way through to closing that deal.

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First, let's talk about something we're all familiar with because you're using

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it right now to watch pipeline summit AI,

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which is Goldcast.

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Margaret has spent so much time planning and executing events to get in front

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of our audiences,

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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,

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the journey of a full end to end multi-channel campaign that was inspired by a

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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,

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and this is what they look like.

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And one of the common requests we get is how to tend the life of an event,

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extend the campaign around that event.

1:26

I'm going to show you how we do it here at Goldcast.

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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.

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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.

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It also will ultimately drive interest in watching that on demand event to see

1:46

some of the top quotes,

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to see some of the top clips.

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And so our team is hard at work generating this full end to end campaign,

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the content to go along with it, the clips to go along with it, the clips even

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to post on social,

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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?

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We used the Content Lab.

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We developed the content lab to sell the top pain point for B2B marketers

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who generate really great content throughout their business,

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but then have to collaborate across the team to get that snappable clip, to get

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that blog post.

2:23

So on Goldcast, when you run an event, you have a video, you have the entire

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trends for the event.

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For anyone who's worked with Generated AI, you know that a lot can be done when

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you have a lot of great language to work with.

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So the two use cases we empower users where are creating video clips and

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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.

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If I want to just jump right in, I'll show you one of the clips we generated

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here with Chris.

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Part of the magic of the Goldcast Content Lab is that we pull the active

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speaker feeds.

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We pull all of those feeds.

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We also pair them with your brand colors.

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And we can give you lots of templates to work with right out the gate. You can

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go back and forth.

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You can really understand what's going to work best for your strategy with what

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you have here.

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You can also use audiograms.

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So you highlight the caption, you highlight the speaker image if you didn't

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think the video was not compelling,

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or if you want to go with something different.

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So all of that is built into the Content Lab when you have the clip that you

3:30

want to use.

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You can download it and you can generate a summary to go along.

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So you remember our blog post over here.

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This is a great tool to generate a starting point.

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You can generate a few different use cases.

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What you're seeing here is a blog post outline developed from our Content Lab.

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We also have key quotes.

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So one of the custom use cases is to generate quotes.

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That's one of the things that really saves Markner's time.

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You can ask it to generate with context.

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You can also go in and generate in any of these use cases.

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You can see here a follow up email for people who couldn't attend with key take

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aways.

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There's another thing that you can have ready to go.

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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.

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It's going to take steps out of the workflow.

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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.

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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?

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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

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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

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call light up their dark funnel.

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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

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doing,

5:14

usually anonymously on websites you don't own.

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So a company's interested in a chat solution, let's say, and before they go to

5:23

a qualified website,

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they might be doing research on industry publications, blogs.

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They might be going to technology review sites like a G2, TrustRadius, Gartner.

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And we essentially have relationships with millions of different publishers

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where we get all of that activity data

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and then use our own matching technology, which is best in the industry,

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to associate all of that activity back to accounts.

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So not to individual people, but to the accounts that are doing that research.

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So you can imagine for any single customer, we've got tens of millions of data

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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.

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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

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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

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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

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subscribe.

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Thank you again so much for joining us today at pipeline summit AI, and we will

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see you

22:49

next time.

22:49

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