Kevin Au

00:08 – 02:26

Alright. Well, welcome, everyone.

Welcome to our latest edition of the LeanData customer spotlight webinar. So if you’re new, this is your first time attending one of these, this is a series where we highlight real life LeanData admins like yourselves, sales, marketing, revenue operations professionals, and what they are doing to improve their go to market processes.

So these sessions are intended to give you, our LeanData users and admins, power users, a chance to learn from one another just to gain different ideas and inspiration so that the entire LeanData community can level up together. Now before I introduce our featured LeanData users for today, I do wanna cover a few housekeeping items.

So firstly, we do have some upcoming events. So including some webinars on wider industry topics, as well as some training opportunities.

So if you’re interested in any of the events on on the page now and you’d like to join one of our upcoming certification classes, please register for those. You should be able to find most of these events on our website, leandata.

com/events. So you can go ahead and visit that if you’d like to register for any of these.

Next, we will have a recording available. So, don’t worry for those of you who want may want to revisit something that you hear today.

You’ll be able to do that. And we also encourage you to interact with us.

So use the chat feature in your interface there to talk to us and let us know if something resonates with you. And then also, if you have any questions, if you could use the q and a panel to submit any questions.

And I can’t promise necessarily that we’ll be able to get to all of those questions today, but, if there are questions that we can follow-up with afterwards, we’ll be sure to do that. Alright.

So to kick things off with introductions, firstly, my name is Kevin. I’m head of training at LeanData, and I’ll be facilitating our discussion today.

And today, I’m happy to welcome Casey and Christian from Drata. So we’ll invite you guys to come on stage here.

Alright. So, Casey, Christian, I had not spoken to either of you before connecting to coordinate for this, webinar.

So if I can ask each of you to give a quick word of introduction about yourself and about Drouna, maybe we’ll start with Casey and then Christian.

 

Kacee Court

02:26 – 02:55

Sure. Sure.

Thanks for having us. Super excited.

I’m Casey Court. I’m head of marketing operations at Drata.

If you haven’t heard of Drata, we are the fastest, growing trust management platform. We have over 8,000 customers across the globe.

And then for a little bit of context as we go through today’s slides, we actually have 250 ish people, across go to market that the marketing ops team is actually serving. So, Christian, I will pass it off to you.

 

Christian Herlihy

02:55 – 03:13

Yep. Hi, everyone.

My name is Christian. I am a marketing operations specialist here at Drata.

I work directly with Casey, and I support many of our, you know, close to 250 go to market people on our team. I am an avid lean data lover.

I use it on the daily, so I’m very happy to be here.

 

Kevin Au

03:13 – 03:28

Great. Awesome.

I’m sure we have a lot of other LeanData lovers and, avid users on the call today as well. So the the inspiration for our webinar today is, a talk that you, Casey, you gave at a recent success conference, a breakthrough.

Is that correct?

 

Kacee Court

03:28 – 03:30

That’s correct. Yeah.

I’m super excited about it.

 

Kevin Au

03:30 – 03:53

Yeah. And it was from what I hear, I wasn’t there, but it was very well attended, but the time was limited.

I think we you only had, like, twenty or twenty five minutes, to really. flesh out the entirety of Drata’s story.

So, I wanna give you guys an opportunity to speak more about that because I’m sure that there’s a lot more to say and a lot more questions that people have. So we wanna give an opportunity to expand that conversation a little bit.

 

Kacee Court

03:53 – 03:56

Cool. Awesome.

Let’s. do it.

 

Kevin Au

03:56 – 04:46

So just a a detail for folks, what we’ll cover today. We’ll talk first about the the before state, what things were like before you started leveraging lean data and what problems you’re looking to solve.

Then we’ll talk about the lean data solution, and then we’ll talk about specific aspects of your setup like SLA enforcement and rapid response. Also things like audit logs, how you guys capture and measure attribution, and how that builds operational confidence.

And then we’ll talk about scaling. As your processes get complex, how do you use LeanData to really manage that complexity to scale up? So, firstly, a good place to start would be the before state.

So, Casey, could you tell us what the before state was, what things were like, and then you can transition into how you use LeanData to solve those.

 

Kacee Court

04:46 – 04:53

For sure. If you wanna just, go to the first slide.

Yeah. We can start there.

Cool. So before state,.

 

Kevin Au

04:53 – 04:53

things.

 

Kacee Court

04:53 – 06:25

if you were at breakthrough last year, you may have heard me speak a little bit about sales adoption of sales intelligence. So to give some additional context to this, the TLDR of that is we had launched sales intelligence, and we, basically taught our sales team how to, prospect more efficiently.

They were, teaching them to target the right accounts, better prioritize their time. And we did it by instilling a little bit of FOMO.

And so, essentially, we taught them how to go find their accounts and use this in their day to day workflow. Fast forward a little bit after that, we decided to start routing out the six QAs.

So the impetus for that, we were having a conversation with our CSM at 6¢, Ryan Birdsall. Shout out if he’s listening.

And he was telling us that we were only working 36% of our six QAs. And not only were we only working 36% of them, it was taking our sales team an average of seven days to get to them.

So we all know speed to lead is a really big deal here. In seven days, those accounts were going cold.

So So that was a huge problem for Drata, especially because we knew that our six QAs convert, almost seven times higher than non six QAs. And our strong fit accounts were converting into open opportunities, two times higher.

So that was a ton of untapped white space where we had a lot of potential for additional revenue to bring in and scale. So that was the point that we decided to start routing out our six QAs.

And Kevin, if you’ll go to the next slide.

 

Kevin Au

06:25 – 06:48

Yeah. And just to kinda comment on that before we move on here, I think a lot of revenue leaders, maybe what keeps them up at night is just the fact that, you know, they’re they’re paying for all of this, these signals and this intent and not necessarily deriving actual.

pipeline format or not as much as they feel like they should be. And it’s.

not just a hypothetical. You guys actually measure that.

So,.

 

Kacee Court

06:48 – 06:49

Yeah.

 

Kevin Au

06:49 – 06:52

let’s hear a little bit more about, that situation.

 

Kacee Court

06:52 – 08:27

Yeah. Well, before we get into measuring that and, being able to scale out that additional revenue, I’ll give you the backstory of why we even decided to start using lean data.

So pre lean data, we had a $2,000,000 problem to go solve. So for anybody who’s talking about measuring, the importance of operations and operational efficiency, it’s $2,000,000 worth here.

So we had a routing tool in place, that we just couldn’t rely on. It constantly was breaking.

And in one situation alone, we found out that it didn’t route out 70 of our accounts, which totaled up to $2,000,000 in pipeline. For an ops person, really everyone involved, but definitely an ops person, that’s an absolute nightmare, because not only do you have to figure out, you know, which ones are still hot, which ones are cold, how do we nurture them, all the different, you know, complexities there.

You have to also explain the why behind that. Why did our routing not work the way it was supposed to? Typically, when I go to present, you know, the problem and the solution to it, it’s like, this is what happened.

This is why it happened. This is what we did to remediate it and future proof so that it doesn’t happen again.

In this situation, I just I didn’t have the why. So it was really challenging.

And at that point, that was our breaking point, no pun intended, to actually decide to migrate off of, the previous routing tool to lean data.

 

Kevin Au

08:27 – 08:56

Got it. So, yeah, there’s it’s I’m glad that you’re able to identify, you know, this is the exact impact, you know, that missing out on these things had because that really, you know, lights a fire under the people to get something fixed.

So I’m glad that you’re able to to grab those metrics. And, you know, in in a sense, it’s, once it’s gone, it’s gone.

Like, if there is a six QA or if there’s a hot lead or hot account, then you can’t necessarily recapture that. Hopefully, you can.

It’s you know, that that’s, time and pipeline lost.

 

Kacee Court

08:56 – 09:15

Yeah. Yeah.

And then it’s, additional work too. You know, you’re taking away from the regular day to day, operations work because you’re actually having to go, you know, spend time digging in, figuring out what went wrong, how do we fix it, all that kind of stuff.

It’s just additional time added, and so it’s just not efficient for us.

 

Kevin Au

09:15 – 09:22

Yeah. Absolutely.

And like you said, not having answers is a terrifying, proposition.

 

Kacee Court

09:22 – 09:24

Yeah. Yes.

Very much so.

 

Kevin Au

09:24 – 09:35

Yep. Alright.

So let’s, talk about then unless you have more to talk about, sort of the circumstances around that. What did you set up to solve for this problem?

 

Kacee Court

09:35 – 12:30

Yeah. So, we basically migrated.

It was an amazing it I say it was an amazing migration. It’s a lot of plumbing.

But for us, the migration was really smooth. We had an amazing onboarding team with LeanData that really held our hands in a lot of ways and was very patient with us.

And so after that migration happened, that’s when we were starting to kind of build net new things, which kind of leads us to our six QA routing. If you wanna go to the next slide.

So, fast forward, we set up, all of our regular routing and then we decided to add on to that. So we were able to start routing out our six QAs, and getting them in the right hands at the right time.

So, essentially, what we do at Drata is, we’ve got a flow or a workflow that’ll essentially route out the six QA via lean data. We add them to a Salesforce campaign.

So going back to, the conversation about attribution and tagging and being able to prove that value, Drata really leverages Salesforce campaigns in that way. So our tier one accounts, our hot strategic accounts, those will go, directly into an outreach sequence.

The, AE will get a notification, the AE or the SDR depending on flow. They’ll get a notification about the account being put in their name with some additional information, and then it’s automatically dropped into an outreach sequence.

Our tier one or top strategic accounts, we also can layer in we use postal, so for gifting. Gifting.

So if we want to send a gift, to hyper personalize their outreach, they can do that. The ones that are medium priority is what we’ll call them, like, our tier two.

They just go through the standard outreach sequence. It’s very personalized.

They have two that they use specifically, and that will automatically start their outreach. The ones that we don’t route out to the sales team because they’re, considered maybe, like, our tier three.

By the way, we’re using Salesforce fields, to be able to distinguish their tiers. We have done a lot of experimentation with conversational email.

Sorry. They were calling it AI email and 6¢ now.

I keep doing that. I guess I’m just an OG.

But we have done a lot of experimentation with this to figure out how we can actually scale. We don’t want our sales team to be focused or getting a lot of noise.

We want them to be focused. And if the account is not the best fit, then let the AI agent take it and run.

Lots of learnings there for that. And then anything else that’s not really in our top accounts that we wanna focus on, we actually don’t route them out or prioritize them.

I don’t think it makes sense to try to touch a 100% of six QAs, because they’re not all going to be the best fit. However, they are, you know, an account that could be potential.

We just don’t prioritize those right now.

 

Kevin Au

12:30 – 12:45

Yeah. Absolutely.

A few things that you mentioned there that I think I’d like to circle back and just highlight again. So you’re not just making sure that all these signals are getting captured.

You’re taking the subsequent action from that in terms of getting into the right people. But even not only that,.

 

Kacee Court

12:45 – 12:45

Yeah.

 

Kevin Au

12:45 – 12:58

there’s a layer beneath that where you are segmenting and prioritizing these. And what that does is you mentioned it allows for some experimentation.

Right?

 

Kacee Court

12:58 – 12:58

Yeah.

 

Kevin Au

12:58 – 13:20

You don’t get. to yeah.

You don’t wanna mess with, you know, tier one to six QAs because you have a process for those. Those close at a high rate or whatever it may be.

But then by tiering out the different, segments there, you’re able to test different things out, see if they work better. So I’m sure that there’s gonna be a lot more experimentation that you guys will wanna do with that.

 

Kacee Court

13:20 – 13:53

Yeah. And a lot of the experimentation too is, like I mean, we’ve got a massive tech stack.

We’ve got a lot of different intent signals. We have a lot of enrichment providers that we’ve tested.

And so for us, like, we have the ability to get really creative with that. And we’ve got learnings.

I mean, it’s not all worked out for us, but we also have figured out how to best integrate and kind of, synthesize those signals so that we can action on them appropriately versus, like, a bunch of accounts just popping up and not really knowing where to start. So.

 

Kevin Au

13:53 – 14:02

Yeah. And it gives you the flexibility as you get those learnings, as you learn what works, what doesn’t, what may be a better fit for certain segments.

You can easily make those changes.

 

Kacee Court

14:02 – 14:04

yeah. Yeah.

 

Kevin Au

14:04 – 14:30

And I think something else you mentioned, I think, is important note to highlight is that, you said that not all of these would necessarily require to be prioritized or looked at. So just having I I I think the the the confidence, to be able to say, like, hey.

We wanna be able to focus. We wanna focus on the the things that matter, but that means necessarily sort of deprioritizing other things.

I think that’s a key takeaway as well.

 

Kacee Court

14:30 – 14:48

Yeah. And the other part for, like, go to market that’s not just, sitting on this slide is, like, the legwork behind that and the ICP work that you have doing getting the alignment across go to market.

That’s gonna be really important because you wanna make sure you’re actioning on the right things. And, so you have to have that tight too.

 

Kevin Au

14:48 – 15:02

Yeah. Absolutely.

Great. Thanks for sharing that.

So we talked about kind of where things were. We’ve talked about what you guys set up to address those things.

Now let’s talk about the results. Where have you guys ended up because of this?

 

Kacee Court

15:02 – 16:16

Yeah. So, at the beginning, I had mentioned it was taking us an average of seven days to get to these accounts.

It now takes us fifteen minutes, and we’re able to actually measure this with LeanData’s SLAs so we can figure out if the SLA was met. We’ve got notifications that go out.

I won’t steal all of Christian’s thunder, but we’re able to actually track and measure this. The second point was then we were working 25% more of the six QA benchmark that 6¢ has given, just because we were able to immediately route things out and scale it that way.

And then also looking at our pipeline that we create on a monthly basis, we could see that a roughly 12,000,000 of that pipeline was a six QA at that point. And then last but not least, definitely not least for me, the nightmares are gone.

We can sleep again at night. We have a 110 confidence in our routing, just because of our notifications and SLA management.

We can see exactly why something happened, where it went, etcetera, which is incredibly helpful for us, as ops leaders and trying to explain why things happen when we have these layers of complexity across the globe, essentially. So.

 

Kevin Au

16:16 – 16:22

Yeah. I mean, I’m glad you included that last metric.

I think it’s important for, a lot of folks on this call here.

 

Kacee Court

16:22 – 16:23

yep.

 

Kevin Au

16:23 – 16:42

1. So seven days to fifteen minutes, that’s not just an improvement.

That that’s like an an order of magnitude transformation there. So has that really affected how your sales team works? And, do they tell you guys about how that impacts what they do on a day to day basis?

 

Kacee Court

16:42 – 17:18

Yes. So and it’s not all rainbows and butterflies.

Like, we’ve had to work through a lot too to get that alignment, getting feedback from the sales team, making sure that we are making tweaks to kind of help, focus a little bit more. So it took us some time to get in the groove for that, but just making sure that we’re having those weekly conversations.

And Christian will talk a little bit more about it. He can talk about the dashboard he created, but, it was definitely a process.

But after the change management happened, now we’re able to, like, help them bring in more pipeline. And, yeah, everybody loves more pipeline.

So.

 

Kevin Au

17:18 – 17:27

Yeah. Absolutely.

And especially those in sales management. So I think you you provided a quote, for us, from your sales development manager.

Would you like. to cover that?

 

Kacee Court

17:27 – 18:12

Yes. I would love to cover it.

So if you think that I might just be an ops person touting lean data because I love it. It makes my life easier.

It makes everybody else’s lives easier easier too. So, Nick is our senior director of sales development, and he also was speaking highly about lean data.

It really is an integral part, he says here, to how his org operates. It’s not only just making sure that their their accounts are being routed out to the right rep in that moment.

It also helps with other channels like event follow ups and that kind of stuff. So we can actually see if something was routed, why it was routed, and then it helps them, with their outreach as they start to work those accounts too.

So it’s had an impact across all of go to market.

 

Kevin Au

18:12 – 18:50

Yeah. Excellent.

Yeah. I think one of the theme that we’re going to dig into a little bit more is just this idea of organizational confidence, not just for yourselves as operations people, but kind of expanding outward through the sales team, different marketing team members, sales leadership, all of that.

So we’ll definitely continue to to touch on that as we go on. So, you know, we’re we’re in a room full of, LeanData admins and and operators.

So I’m sure they’re seeing all of this, and they wanna know what do I do? How do I set this up for myself? So, Christian, I’m gonna turn to you to kind of fill in some of those details for us as far as configuration wise, what you set up, and how you set that up.

 

Christian Herlihy

18:50 – 21:54

Of course. Yeah.

So, you know, as Casey has mentioned, six QAs are incredibly important to our go to market motion here at Drata. And speed to lean, 46 QAs as she showed, is absolutely critical.

And so there’s really that is why lean data has become such, like, an integral part of our go to market motion. It’s really helping to ensure that we can get these six QA accounts to the correct rep all within that, you know, fifteen minute SLA period and that they can follow-up, work those, or tag to the correct sequences, etcetera.

So, essentially, looking here, with lean data, we are taking these accounts as soon as they six QA. We’re looking at our account data, and then we’re following our internal routing logic to assign that correct rep almost instantly.

So this is a, you know, distilled slash simple version of our, you know, graph that we use on day to day basis. But, basically, once they come in, we’re able to filter out exactly what we want.

So we have, you know, customers, partner accounts. We filter out, you know, certain closed loss opportunities, and then we’re signing those accounts into a campaign.

As I’ll touch, you know, on a bit more later, campaign and campaign reporting is huge to our organization here at Drata. So being able to assign these six two a accounts to a campaign, we’re really able to use our already in place campaign reporting reporting framework and make sure that we’re actively tracking sort of that ROI, making sure that these accounts are being followed up upon.

So as we continue down here, LeanData is essentially handling all of our routing. And it is pretty complex here at Drata.

We have a lot of different teams. We are a global organization.

We are constantly growing, and expanding our SDR team, so this is constantly evolving. But, yeah, as you can see here, we, you know, we route by a region.

So headquarters, EMEA, APAC, AMER, as well as sort of that market segment size for the accounts, you know, enterprise, mid market, emerging, etcetera. And what’s also really great, and I didn’t emphasize in the notes here, but as soon as they’re assigned, the rep and their manager are notified from LeanData when the six QA account is in their name.

So it really helps make sure that everyone is aligned. The manager knows there’s a new six QA account.

The rep knows that there’s a new six QA account. So it really helps to make sure that there is that confidence that, hey.

You should be working this account, and let’s get going on it. And what’s also really great about this is that it’s really easily adjustable.

That second node there at the top for closed loss opportunities, that was a very recent request to be implemented. They wanted to filter out those closed loss opportunities from the last four months.

I took that data, the information. I create a new node.

I tested it and deployed it, and that took me, you know, probably less than five minutes. So as we’ve scaled, as we’ve adjusted our parameters, lean data has been, you know, integral on that.

 

Kevin Au

21:54 – 22:28

Yeah. I’m sure that’s a a really empowering thing for someone who’s kind of in the weeds and building this stuff out on the ground level like you are, Christian.

And I think that’s something we’ve heard from a lot of our lean data admins, just the flexibility and the quickness at which you’re able to iterate because your business is not static. There are certain things that come up as people notice them, and that experimentation, as Casey talked about, hey.

If something’s working or something’s not working, you want to be able to respond to that in a rapid manner. So lead data allows for that.

And remind me again, Christian, how often are you in here, you know, making changes to to the graph?

 

Christian Herlihy

22:28 – 22:43

I mean, I’ve Clean Data is probably the first tool I open up on a day to day basis. So adjusting it, you know, maybe once a week, couple times a week, it depends.

But, yeah, it’s it’s probably the second tool I open or if not the first every day.

 

Kevin Au

22:43 – 22:51

Yeah. Yeah.

Absolutely. Makes a lot of sense.

Is there anything else that you wanna comment on from this particular graph setup?

 

Christian Herlihy

22:51 – 23:08

I mean, all I just wanna say is that, you know, there’s always a lot of room for improvement here, as we’ll touch on later. You know, talk about data tables.

You know, there’s a lot of room to clean this up and even make this even more efficient and effective than how it is, and I think that’s just why it’s been so great so far.

 

Kevin Au

23:08 – 23:41

Yeah. Absolutely.

Well, I think then we can transition and kind of talk about this idea of speed and SLA enforcement and rapid response. You mentioned, so the the technology itself can action your records as those signals come into your Salesforce and get to the right people.

But you mentioned a critical piece as far as the visibility of that through notifications. Do you also use any other features to, ensure that there’s a follow-up in the time frame that you want? Is there an enforcement of that? How do you have that accountability?

 

Christian Herlihy

23:41 – 26:04

Yeah. So notifications are huge, and that leads into SLAs.

So yeah. So just, you know, high level from beginning, we have notifications.

We have dashboards and reports that all focus on, you know, the SLAs that we implement. So, yeah, so, really, as you made the point, SLAs are very critical to what we do here.

It really helps to make sure that there is that alignment between what we’re expecting the reps to do and actually what is actioned on. So here at Drata, we have incredibly strict SLAs, and it’s really not just for our team to adhere to, but it really helps us, you know, from a marketing ops side, from a sales ops side, to understand, you know, what is the actual efficacy of these actions.

If we’re being able to reach out within fifteen minutes or one day, is that, you know, more effective or less effective than, you know, one day, three day, etcetera? And so I think that’s why we’ve implemented these sort of SLAs across our various graphs, whether it’s opportunity, account, or contact. So just touching on this a little bit, this is a, you know, relatively still down version of one of our inbound SLA sort of flows.

And we really want these SDRs to work these leads as soon as possible. So as you can see here, there’s three SLAs in this one sort of SLA workflow.

And within one minute after the the, you know, record is assigned, we have this fifteen minute SLA. We’re then capturing that data.

We have it in our own reports, in our dashboards. And then if they meet it, we can report on that.

And then we have that one day SLA. And then we have this hold until SLA period for twenty one days to make sure that that inbound rep can qualify that record and hopefully create it or convert it into a qualified opportunity.

What’s not showing here is, you know, after this, if they don’t really qualify or convert it, is that we also use LeanData to reassign that contact into a different rep. So it’s not just, you know, sitting in stale pipelines, not just being, you know, never worked.

It’s constantly being recycled. You know? So really from this, this relatively simple SLA sort of workflow is helping us capture the efficacy of how our inbound SDR team is working these leads, how well they are being worked, and it also helps to sort of recycle constantly and make sure that these leads are being followed upon.

 

Kevin Au

26:04 – 26:34

Mhmm. Yeah.

Absolutely. A question and maybe either of you can can speak to this, but you’re setting up all these SLAs, these hold until nodes, just to ensure that folks are working things in a timely manner and the time frame that you want.

How do you surface this or make this visible, to the decision makers, sales leadership, marketing leadership, executive level? You know, do does this make it up to that level, and how do they know that things are working as they should?

 

Christian Herlihy

26:34 – 27:33

Yeah. That’s a great question.

And so one of the first things that we did when we implemented SLAs was creating this dashboard, in Salesforce that, you know, it was very difficult, but, you know, we look at that on a weekly basis. You know, it’s one of those, you know, pin tabs, in my in my Chrome to to always be looking at and making sure that those the marketing leaders and the SDRs leaders are looking at.

So it really is just a a large dashboard that we look at and follow. You know? Are these SLAs being met? What is the efficacy of converting these leads into opportunities? And everyone from the marketing opsides, myself and Casey, to, you know, know, Nick on our SDR leadership side to, you know, the individual contributors in marketing, they can all see that.

They can all see how their SLAs are being adhered to from campaigns to demo requests, etcetera, and seeing how those up or those contacts are sort of converting.

 

Kevin Au

27:33 – 27:42

Yeah. Casey, do you have any comments on, you know, those dashboards and sort of how they’ve been received by your the wider teams at Drata?

 

Kacee Court

27:42 – 28:39

Yeah. So we went through a couple we went through a couple iterations of the dashboard to get it right.

But it was something that we’ve got a biweekly sync as well. That’s really where we all get together and talk about, just different things that are happening between marketing and sales.

And so this it took a little bit to get, you know, true adoption of it, but I feel like that’s of everything is, you know, whenever you launch something new. But it was something we were able to, like, sit around and have a conversation about, and it was driven by data.

So there wasn’t any anecdotes of, like, you gave me a garbage lead, and that’s, you know, whatever. The the tale is all this time.

But we were able to actually say, hey. This amount met.

This amount didn’t. What are we gonna do about these leads? And we need to make sure that we’re jumping on them because to the point earlier, like, speed delete is so critical.

And so it was able we were able to kind of centralize the conversation around that information.

 

Kevin Au

28:39 – 29:05

Mhmm. Yeah.

Well, thanks for sharing that. Question, maybe you can talk a little bit more about this idea of how things get recycled.

Right? So if things aren’t worked in a particularly, you know, expedient way, is there an aspect of recycling the that back to a different user? Or how do you guys handle, that type of situation where you need to recycle or reassign a record?

 

Christian Herlihy

29:05 – 29:42

Yeah. I mean, there are definitely a lot of opportunities with LeanData in this sort of specific scenario.

Downstream, we’re we’re using data tables a lot to look at specific data, whether it’s the account region and employee size, where’s the HQ location. We’re able to pull in those fields, and then we, of course, we have our, round robin pools and our specific reps.

But all of that is managed in sort of data tables, so it’s not just going to a random rep. We know that, you know, this contact or this account with this data is going to this person, and that is who it matches.

to.

 

Kacee Court

29:42 – 29:43

Yeah.

 

Kevin Au

29:43 – 29:43

And.

 

Kacee Court

29:43 – 30:38

think oh, sorry. I was just gonna add to that.

We have, like, internal ROE. So when we talk about, like, recycling something, we call our SDRs all SDRs, but they’re inbound and outbound.

And so what Christian was talking about specifically earlier was, we give the inbound SDRs fifteen business days. So it’s like twenty one days.

And we give them the opportunity to actually get a meeting booked. If that doesn’t happen, it goes to the outbound STRs.

And so lean data is, like, automating all of this, which is why there’s a hold for twenty one days. And so after that, then we’re actually talking through now.

How do we then automate notifications to make sure that we’re closing things out? So when they close out the opportunity, it can automatically then be put into a nurture, and we’re recycling it that way. So recycle.

can feel like a loose a loose term here. We use it inter interchangeably, but, a.

couple different things.

 

Kevin Au

30:38 – 30:48

Yeah. Absolutely.

You you have an internal system set up for where things go at a certain point in time, and lean data just facilitates movement between those. different buckets.

 

Kacee Court

30:48 – 30:48

Correct.

 

Kevin Au

30:48 – 30:48

Mhmm.

 

Kacee Court

30:48 – 30:49

Yeah.

 

Kevin Au

30:49 – 31:22

Excellent. Excellent.

So I wanna kind of stay on this idea of sort of accountability. We talked about it from a SLA speed to lead type of, perspective, but there are also a few other ways that we really, allow for accountability when it comes to your different processes.

So one of those is audit logs, which allow you guys to speak to just how impactful that’s been in your organization. But we’ll also wanna get into, attribution, after that as well and talk a little bit more about that.

But maybe we can start off with audit logs and how that’s been impactful for your business.

 

Christian Herlihy

31:22 – 32:58

Yes. Audit logs may they may be my favorite feature in LeanData, to be honest.

I I find them to be very underrated. But I am quite literally in audit logs on the daily.

What’s really great about them is, you know, first of all, it it helps me see what went wrong. We’ve talked about, you know, experimenting and updating graphs, and I do that constantly.

I’m human. I make a lot of mistakes.

And so if I implement a new change and I get an error notification, I can see exactly where that went wrong and then, you know, remediate that quickly. So that that is you know, audit logs have been huge for that.

The other great thing, that I love about audit logs is that you can see where in sort of in the routing logics something went wrong, and it helps, you know, believe it or not, helps keeps the teams aligned and up to date on what’s going on. So this actually happened relatively recently, but with, you know, new reps joining, new or reps leaving, if we have a round robin pool or we have owner mappings that are out of date, we can see exactly that issue and then update that very quickly.

So that happened the other day. It would go and update our owner mappings, and just like that, it was working as good as new.

So I probably would never have seen that without audit logs. It probably would have been something that would have gone unnoticed for three weeks or something.

So, yeah, that’s you know, it just helps us keep aligned in where where things are going. And.

 

Kacee Court

32:58 – 32:58

Oh,.

 

Christian Herlihy

32:58 – 32:58

oh,.

 

Kacee Court

32:58 – 32:58

sorry,.

 

Christian Herlihy

32:58 – 32:59

you sound crazy?

 

Kacee Court

32:59 – 33:44

Krishna. I.

was gonna say I don’t think you’re giving yourself enough credit, because it’s not Christian making a lot of mistakes. There’s a lot of complexity.

Like, when you think about an enterprise tech stack and, all the nuances of, like, we’ve got global teams, we have different segments, we have different subsegments that sometimes we wanna focus on and have different rules for. There’s a lot of complexity with that.

And so for Christian to be able to, like, go in and quickly diagnose what the problem is instead of digging around, It, like, speeds the process up, and then we have the visual here to say this is exactly what happened. And it it helps when you’re communicating to people who are not in the weeds are very technical.

Like, you’re giving them something to look at and digest, and it just kind of helps the conversation.

 

Christian Herlihy

33:44 – 34:14

Yeah. And and to that point, I will sometimes just screenshot our audit logs and send it to a sales manager, SDR manager, or marketing person and be like, this is exactly what happened if they have a question.

And you’re like, oh, okay. I I remember that now.

And then so it gives them that confidence that, alright. This is working how it is intended, and then we don’t get, you know, dozens of questions.

Why to do this? Why isn’t it doing that? Etcetera. So Ops, we love it, and these audit logs help helps keep everyone on the same page.

 

Kevin Au

34:14 – 35:21

Yeah. Yeah.

I think for folks in your role, you understand the power of the audit logs, and you say that it’s like a maybe overlooked type of feature. But, you know, for all all of our folks here who usually need it on the daily, they they know, like, hey.

This is a really powerful feature because, you know, the the problems and the issues, they’re always going to be there. To your point, Casey, there’s always complexity that you need to manage, and there’s always things that you need to iterate on.

But, those problems stay small because you catch them and any gaps that there might be early, and you want to surface the problems. Right? You want to surface the problems as soon as possible so they don’t become larger problems.

Yeah. And I think a lot of folks who may not work with LeanData on a daily basis, they see this is this is a little kind of overkill.

There’s so much data here. Do we really need this? But you don’t really need it until you need it.

When you get those questions as far as what happened here, you know, 90% of the audit logs, you may never look at. But for those one or two records or three records that you do, you’re definitely glad you have that.

So you going back to your point, Casey, you have an answer when someone. asks you a question.

about it.

 

Kacee Court

35:21 – 35:23

Yeah.

 

Kevin Au

35:23 – 35:50

Okay. So, let’s transition a little bit into this idea of attribution.

I think you mentioned earlier forgot if it was you, Casey, or you, Christian, but maybe both of you. You talked about being able to, tie the opportunities and what you’re doing or the different contacts with the campaign, that essentially flipped it.

Right? So how do you do that? How do you set that up in lean data?

 

Christian Herlihy

35:50 – 37:17

Yeah. So yeah.

I mean, that’s a really good point. I mean, campaigns really are sort of the backbone of what we do here at Drata from, like, an operational standpoint.

And like like you mentioned, like, we use it for tagging, we use it for reporting, and we use it for sort of, like, what’s lead should be worked or not. But for the point about attribution, we we use LeanData for not just account, sort of campaign tagging, but for contact tagging as well.

So this is just sort of a, again, distilled version of what we do and sort of certain place that we do at Drata. But, really, like, what is happening is when a record changes, whether a contact or lead changes, we’re we’re taking that and we are signing that record all in this one flow and then adding it to the campaign.

And then once certain a certain action happens, whether it’s it’s worked or it’s a, you know, a connection via an SDR, AE, we’re able to update the status automatically and then able to tag that record with specific fields. As I mentioned about, you know, campaign reporting, we have sort of, the primary campaign source attribution turned on in Salesforce, and this is essentially what drives all that operational sort of cadence for that campaign reporting.

And so LeanData, it empowers all of that essentially from tagging to adding campaign members to attributing sort of, sort of those opportunities to different campaigns.

 

Kacee Court

37:17 – 38:18

Yeah. I’ll I’ll tag on here too a little bit.

When we were talking about this at breakthrough, specifically, one of the questions that had come up was around being able to, report on the performance of all of your campaign activities, improve the value of, like, the operations behind it. So what you’re seeing here is it’s adding it to a campaign, but then we pull all of that campaign information into what we call, like, our PROI framework, your pipeline ROI.

And we we can use it in Salesforce. We have Salesforce, reporting set up primarily for the day to day people who are looking at that.

But then here, we also pull it into a spreadsheet, and it gives you by campaign, whether it’s an operations campaign or, like, a real true integrated campaign, etcetera. You can see the pipeline that is returned, against a target at that expected time, and then it rolls all the way down to revenue.

And so that’s how we’re able to actually prove the value as using that Salesforce campaign as the backbone behind it.

 

Kevin Au

38:18 – 38:38

Yeah. Absolutely.

So we’re we’re talking about this idea of trust and confidence, and a lot of what builds that is the visibility into these things and your ability to tag and mark certain campaigns, as part of your process really gives that visibility in a reportable way so that you can make confident decisions moving forward.

 

Kacee Court

38:38 – 38:40

Yep. And be proactive.

 

Kevin Au

38:40 – 39:04

Yeah. Absolutely.

So, yeah, I just really wanna drive home that point of just getting that trust and getting that confidence that’s so important and not just for your own team, but making sure that that trust. sort of expands outwards to other teams because that just makes things easier for you.

When you wanna make sure it is or make a case for something that seems to be working or not working, you have all of that at your fingertips.

 

Kacee Court

39:04 – 39:04

Yeah.

 

Kevin Au

39:04 – 39:29

1. Alright.

Let’s, move on then to our next topic. So you’ve described a lot of the different pieces of your overall setup.

And I don’t know if things started off complex for you guys or it started off simple and it grew in complexity. But what are some of the ways that you sort of approach and manage the complexity in your processes?

 

Kacee Court

39:29 – 39:30

Oh,.

 

Christian Herlihy

39:30 – 39:30

Experimenting.

 

Kacee Court

39:30 – 39:33

if you’re in India.

 

Christian Herlihy

39:33 – 41:27

Yeah. Data tables, they’ve been a game changer for me.

Yeah, like I’ve alluded to multiple times so far, we have incredibly complex routing rules. We have a growing team.

You know, SDRs have grown probably double since I joined the sales team, double as well, CSMs. And just being able to account for all of that logic in a simple, you know, CSV file that I didn’t upload is is incredible.

So just looking at this example here, these are just three data tables that we use in some of our MQL and campaign routing. But just to give a little bit of insight, that single node route to EMEA SCRs, that probably replaced five nodes itself, when I started to implement data tables more and more.

And it’s really great because, you know, I’m able to, one, use all the data points that we want to route, but also, two, account for the variations in data not being filled or either mismatched data and still route to the correct person or round robin pool. You know? So maybe it says, you know, the the country is, is France but doesn’t have an employee size.

I can still account for that in the logic, and it still routes to that correct pool that I wanted it to. Otherwise, it would be four different nodes with a if this doesn’t happen, then route to this person.

And at the end of the day, it just helps clean it up. And like I mentioned, because it’s server CSV file that upload, it can be in a Google Sheet or Excel file beforehand.

I can have other stakeholders update it, as needed and then upload it, and then it’s good to go. It’s across our our different graphs we use, and I’m confident in where those leads are going and how they’re being routed.

So thank you for data tables.

 

Kacee Court

41:27 – 42:02

And, Kevin, to your question about, like, did it start off complex? Did it grow into more complexity? It it grew very quickly into more complexity. Again, you know, Drata, we’ve scaled past a 100,000,000 three and a half years.

Like, when you talk about the number of customers that we’ve onboarded, like, our team has also grown. So for us, like, this is a visual of scale.

We can update it in one place. It updates across everything that we have, and then we are able to actually build this tech foundation that will scale with us as we grow with our.

customers. So.

 

Kevin Au

42:02 – 42:37

Absolutely. You know, I’m I’m glad, I I’m thankful for the simple answer, data tables, you know, two word answer to how complexity with needs.

And I’m glad someone else is kind of, you know, beating that drum because I often do that. It it is I I will say that for someone kind of approaching a new, it can be a little bit of intimidating.

Right? They have their graph set up a certain way. It seems to be working.

Things are going to the right places. So why should they introduce data tables? And do you have any comments for you know, to encourage folks to explore this particular functionality more?

 

Christian Herlihy

42:37 – 43:59

I would say it is daunting at first, but once you, I think, just experiment and try with it, it’s it’s simple. I mean, the way we started with it is we had a Google Sheet, and then we just copied and pasted all of the countries that we potentially wanna route to as as a test.

We did it in a small little, you know, sort of flow at first, and it worked. And it seems kind of just crazy to think that, you know, you can just copy and paste your data points and put it in there, upload it, and it works.

But that’s really how it is. As we have grown and scaled, I’d say our data tables have grown a lot more complex.

We’re adding new columns or data points of, you know, use, postal code, for example, and route via that. Or, the one on the right there for campaign region.

You don’t and it’s not just contact, account, or opportunity objects. We’re using it on the campaign object as well.

You know, so, like, if my advice, it would just be to try it with something small and then slowly iterate over time, and then you’ll get to a point where one node can replace five to six nodes itself. And you’ll feel a lot better about it when you’re looking at your graphs, and it’s not a huge spiderweb of a of a mess.

 

Kevin Au

43:59 – 44:29

Yeah. Absolutely.

I can definitely concur with that that starting off small, maybe pick one piece of your graph that you would like to experiment with the data table, see if that works. And, you know, as you, you know, grow in your, confidence in using it and how it works, you can add more into that either that same data table or you can use multiple ones.

As you’ve shown here, you have three different data tables that are doing different things in one screenshot here. So all of that is doable and is flexible enough to allow for that.

 

Christian Herlihy

44:29 – 44:29

Absolutely.

 

Kevin Au

44:29 – 44:45

1. Alright.

We are running a little short on time, so but I do wanna get to these key takeaways. So, Casey, I’ll I’ll get handed back to you just to cover maybe some of the key takeaways from your journey, using lean data.

 

Kacee Court

44:45 – 45:47

Yeah. So to kinda bring it all back, we’ve thrown a lot at you.

Three key things that I would say to take away from today would be number one is scale. Because of lean data, we were able to actually scale our coverage and ultimately our revenue, and Christian just gave a great example of how that can be helpful.

And then number two would be lead management. So we have stronger lead management.

We can ensure our accounts are being worked, and we can manage, the complexity of our routing. Dreda Dreda has incredibly complex routing.

So the rules can span across regions, segments, GTM teams, everything that Christian has discussed, and it gives us more, more clarity into that, which leads me to the next point of complexity management. So we can actually, you know, manage this, have it kind of be small problems that don’t turn into bigger problems.

And this has really given back the confidence to us, and our go to market partners, that we need it back in our routing. So.

 

Kevin Au

45:47 – 46:02

Thanks for these key takeaways. I think, we’re we’re out of time, but I do wanna just maybe quickly ask, what’s next? You we mentioned how LeanData is flexible.

You guys are doing a lot of experimentation. Could you share what you’re looking to build next or what you’re thinking about doing with LeanData?

 

Kacee Court

46:02 – 46:42

before, Christian, you go, I just have to say there’s one thing that we didn’t talk about on here. So it’s not next.

It’s something that we did. It was really helpful for us.

It was actually the list analyzer. So we acquired a company back earlier this year called Safe Base, and we were tasked with doing an incredibly quick MarTech migration.

We did it in four weeks. And a lot of the reason we were able to speed that up is because we had confidence in the data that we were migrating over because of the list analyzer, which helped us proactively get ahead of the different impacts that we might see when we did that migration.

So just wanted to call that out. And, Christian, I’ll give it to you to talk about what’s next for you.

 

Christian Herlihy

46:42 – 47:36

There’s always a lot of what’s next. Honestly, it’s just at a point of improving and iterating on it.

Like I’ve mentioned, I’m constantly in it. And as we’re preparing for next year, there’s new campaigns.

I’m sure they’re gonna be coming up. It’s just making sure that what is in our graphs is scaling with what we’re doing, whether that’s implementing more data tables, whether that’s making sure that we’re properly enriching our accounts, whether it’s getting even more complex with our routing, you know, connecting opportunities to campaign members using those sort of nodes.

There’s a lot of opportunities. There’s a lot of requests that I would say I get on a day to day basis.

And so it’s really just making sure that what is live is, you know, still working, and, luckily, it is working, but there’s always room for improvement. And I love tinkering.

So.

 

Kevin Au

47:36 – 47:53

Nice. Well, thanks for that.

And, Casey, thanks for the, promoting the list analyzer tool. That’s probably, like, number two after data tables of, overlooked features that I want to to plug more.

So thank you for bringing that up. Alright.

So we are at time now. We’re past time.

 

Kacee Court

47:53 – 47:53

Yep.

 

Kevin Au

47:53 – 48:35

So thank you, Casey, Christian, for for your time to share these things with us. And I’m sure there are many things that all of our attendees, picked up today and learned from you, and I hope that you’ll continue to share as you make their further iterations and improve and refine your processes.

And for everyone on the call, thanks for attending. Apologies that we may not have been able to get to all the questions here, but we’ll take a look at what we weren’t able to get to and follow-up if appropriate.

So just be on the lookout for a follow-up email from us so that we can, share today’s recording and, any follow ups that we would want to do with you. So, again, thanks again for your time.

We’ll be signing off now, but I hope you have the great rest of your day.

 

Kacee Court

48:35 – 48:37

Thanks, guys.

 

Kevin Au

48:37 – 48:37

Bye.