Clozd: Hey everybody, welcome to this session of win-loss week. Today you have me, Spencer Dent, one of the co-founders and co-CEOs here at Clozd, and I have the pleasure of speaking with Craig Clark, who is the CMO of Nitrogen. Welcome, Craig.

Craig: Happy to be here, Spencer.

This is going to be fun. Today we're going to talk about how Nitrogen and Craig in his role has used win-loss analysis to diagnose real revenue problems that aren't exactly ... the cool part about this, Craig, is they aren't exactly on the surface easily diagnosed, well, you have to have a level of intelligence to understand them, but then understand, diagnosing the problems and then coming up with awesome creative solutions, so super excited for this one.

All right, so let's get into it. First, before we talk about the story, maybe tell us about your self, your role at Nitrogen, how long you've been there, give us a little bit of background and context.

Sure thing. Myself, I've been a marketer in software as a service businesses for a little over 20 years now. That's pretty much all I've done in my working career, is been the lead marketing and in later years also sales development in software as a service companies. And I'm the CMO, as you mentioned of Nitrogen Wealth today, and I think it's a fairly typical CMO's remit with maybe a few exceptions.

All of product marketing rolls up to me including pricing and packaging, which I know we're going to talk a little bit about later. It doesn't always fall under the marketing remit, but certainly it does for me at the moment. And also sales development, so I carry a quota for pipeline creation, which not all marketers do, but I know it's becoming more common in recent years.

That's awesome. So you've been there for a couple of years, you came in, how did you get started at Nitrogen with win-loss? What was kind of the impetus for, we need to go do win-loss?

Well, I confess, I had worked with Clozd at two other businesses beforehand and it had been very enlightening at the time for me and I had a bias for win-loss before I even started at Nitrogen. But as soon as I arrived, I started to talk with some of the other members of the senior leadership team and our go-to-market team, and I started to detect these hunches and hypothesis for why certain things were happening. And they were different from the ones that I'd encountered in other companies, it wasn't at all about the win rate.

And actually, it was not about competition really either, which are two of the other things that had really come up a lot for me in previous roles. It was actually about product market fit, and we started to see little wisps of smoke around our pricing and in particular our packaging of our SaaS platform. And people had strongly held hunches about that and hypothesis about why certain things were happening, and I thought, this is a great opportunity to bring win-loss to bear and see if there's any merit to any of these hunches that people had.

I love the term hunches, because that's actually oftentimes how this gets started. Can you give me an example of what one of those hunches sounds like? What's one of the sound bites of the types of hunches that people were coming to you with?

A classic one at Nitrogen Wealth here, we build software for financial advisors and we have three quite distinct chunks of functionality in our platform. One is risk tolerance software, another is financial planning software, and then we also have investment research software, and up until recently, we bundled those all together. And one of the hunches that our chief product officer actually had was that customers were starting to get a bit anxious about paying for all three of those relatively distinct, tightly integrated for sure, but distinct value propositions in one bundle, and the price was starting to escalate for people.

And so he had a hunch, maybe we should break this thing up and just sell people what they are coming inbound to us or they're wanting to purchase from us and more willing to pay money for. And that was a hunch and it was a pretty strongly held hunch that he had at the time, that was two years ago.

Well, the part that I love about it is, the funny thing with win-loss I've found over the years, is a lot of times we don't tell you things that you don't have a hunch about already if you're a good leader and in tune with the business, we just help confirm them or disprove them or give you a relative weighting on what matters, so I love the term hunch. So you go and you start this and you get moving, tell me about the purpose, intent of the program, what you were trying to prove/disprove and how you got started and what insights emerged?

Sure. So I mentioned we suspected that we might have a problem with our product market fit, and one of the first avenues we went down was our brand. What do people want to buy from us, and what are they aware of? And are they hearing us when we're talking about certain chunks of our story? And the first thing we wanted to test was, are we perceived as a straight-up risk tolerance provider despite the fact that we had a couple of other big chunks of functionality in our platform?

And it was just an absolutely smoking gun, as soon as we brought Clozd to bear on it, we learned that our existing customers that we had been marketing and selling to for many years strongly believed that we were a purebred risk tolerance software provider. And again, that's like a third of our value proposition, so that led to a pretty big change at the company, we actually rebranded the whole company. We were originally called Riskalyze, which was very descriptive, and it immediately brought the concept of risk tolerance to mind and it was very appropriate when the company was first founded. But that was one of the first things we proved out with win-loss analysis, and then we made a very substantial corporate change as a response.

That's a big change. This is the name of the company, it's what we've been doing forever and it's interesting how sometimes the floor can move underneath you as a business and times change and your offering changes and things like that.

Absolutely.

How did you get people to buy into that? Because that's not just like a, let's change the name on the building, and there's a whole bunch of things and trickle through, how did you get people to buy in and do it?

Well, Clozd was a big part of that, win-loss was a big part of that, data is very influential when you're trying to convince a board of directors that they need to invest in rebranding the company and building up a new name. So I would say win-loss was very important, and the fact that we had third party evidence of this being the case rather than a hunch that maybe me as the new marketing leader wants to rebrand the company, it's a vanity exercise. Not like that, it was definitively a pattern that existed in real life. And we matched up win-loss with surveying of our customer base and our target market, our TAM, to prove that out from many directions, but the data, it spoke for itself.

That's awesome, I love it. A lot of times when people go through these branding exercises, it's more like, what colors do we like? Versus the who are we, who are trying to sell to, what are we trying to sell to them, and do those things match up? And it's cool how win-loss can play a game in that or play a big part in that. Are there any other things from that initial rollout of the program that stood out that you felt like had a big impact on the business?

I would say the other one that was surprising to me, Spencer, and actually I think to the rest of the company, was that it didn't seem like our sellers had any impact on the outcome. And actually, our program manager from Clozd, his name is Spencer as well, he brought that to us and went, "I don't see this very often, but it seems like your sellers actually have no impact on the outcome of your deals." And I've never seen that before myself either, there's usually something in your sales process that isn't quite right and maybe you can make a slight change and affect the outcome. But that was quite a big learning for us and that led us to phase two, I would say, of our win-loss program, which was further improving our product market fit.

Now we've fixed our brand, so phase two was, people still aren't hearing us when we say we're a financial planning software company. And so that led to testing that hypothesis with win-loss and led up to repackaging our entire platform and selling it and pricing it in a very different way to back up this path we had started down by changing the name of the company.

Yeah, that's awesome. What's so interesting is, sometimes people think, there's a silver bullet, we'll just rebrand or we'll just train our sales reps better or we'll just repackage. And sometimes it's a multi-year journey, but there are results, what were the results? What did you guys see after making these changes?

When we first changed the name, it was very interesting to start looking in our win-loss data. Existing customers hated it, they just straight up hated it, they had a lot of affinity for the old brand and so that was something that we could detect and we could take advantage of. But as time has gone on here, we've been able to adapt and we released a low cost, low functionality piece of packaging, like a piece of our software that we could carve off and sell for a low platform entry price point.

And it's one of those times where you really strike it, from a product fit, we clearly struck a chord there and the volume of that product is just way up over our previous packaging and pricing scheme. So almost instant impact on that, it was less than two months ago we did that.

That's awesome. So you change the brand, you change the pricing, you change how you're messaging and how you're selling it, you roll it out, you start to see this lift, in the process of doing that, you realize you can actually create a lower tier solution and segment your business that way. So this is a great story, I'd love for you to share this.

The original approach is the traditional win-loss approach of, let's go out and interview buyers, do very probing adaptive interviews to understand what they think, how they feel, what's different about these two segments of your business now? And maybe it'd be great to hear about how you've thought about attacking the traditional larger enterprise style sell versus the lower end SMB style sell from a win-loss perspective?

It's so unique, I haven't really encountered it before in my career. We have essentially two ideal customer profiles, we have an individual financial advisor and our packaging and pricing for that segment starts at a thousand dollars a year ranging up to about 6,000. And then we have this completely separate, it's literally the same software, but we package and price it totally differently, enterprise segment where our dealers might average $15,000 and up to well over a million, and these are two radically different things.

And I mentioned earlier that we had detected this trouble we had with product market fit and these financial advisors feeling like they were paying for product they weren't using. So one of the things that we did, was we realized in that small segment, in that individual financial advisor paying us very little money segment, we had an opportunity to run a bunch of our renewals we had lost through Flex interviews from Clozd. And it was just this perfect fit because we could get direct feedback from this cohort of renewals about why they had canceled, why they'd gone with a competing solution and so on in this form factor where we could get their actual messaging, the words they used to describe it as well as the kind of data around why they left in this one concise little package.

And it was just perfectly sized for a fairly small ARR segment of our business where it just didn't make a ton of sense to have Spencer, our program manager do a straight-up interview with them and granularly go into their feedback and take a lot of time out of their day. So Flex interviews was actually very influential for us when we did that renewal cohort that we ran through Flex interviews. And that led up to our decision to decouple the platform and offer that very low functionality, low entry point pricing and packaging. And we just never could have got at that if we tried to do interviewing with individual customers or even if we brought Clozd to bear on it and done full-blown interviews, I don't know if we would've got enough volume.

Volume to feel good about it?

Yeah, to make a confident decision on that. So it was actually a perfect fit for us at the time, and that was just a few months ago.

Craig, you're running a pretty robust program right now at Nitrogen, and I think it might be helpful for people to hear about the different ways that you approach it. So there's one part of your program to really go understand the rebranding was doing live interviews and actually talking to customers and understanding how they felt about things and doing that probing adaptive conversation.

Another part of it is more of like an asynchronous video-based interviews that we at Clozd called Flex interviews. And the difference between these two are, one is very hands-on, you have a person doing it, the other one is more scalable, but the questions are not adaptive, they're not going to change interview to interview, but people will share their feedback. So maybe tell folks that are listening in, how do you view these two different methods, and what do you think are the strengths and weaknesses of each?

Such a great question. And they both have very strong applications within our business here at Nitrogen Wealth. Number one, the offering that most people are used to would be the granular interview. We bring that to bear on the enterprise segment of our business where we're trying to learn in great detail from a fairly high ARR deal why they bought, why they canceled their subscription. We want to learn in a lot of detail and we want to hear it in their words and we want to look at the full robust interview there, but we also have this segment of our business, which is a small ARR deal at a very, very high volume.

And I personally feel like you get a lot of value out of the sensation of an interview over something more like a quantitative survey, put a lot of stock in hearing things in the customer's own words. And so we use Flex interviews from Clozd and we did run a cohort of our renewals through that to learn about why they canceled their subscription. And it just proved to be a perfect fit because we couldn't ask someone who only pays us $1,200 a year to sit down for a 45-minute interview, it doesn't make a ton of sense for them or for us frankly. But Flex interviews allows us to get the very qualitative, in their own words, sensation of an interview, but at a much higher volume that just really fits with that lower ARR segment of our business. It's just perfect to have both of them.

One thing that's been interesting for us at Clozd is, over the years as we've run these programs, the traditional two ways that companies will go after this is, I'm going to do a super high in depth interview, or I'm going to do a really brief quant survey. And this is great if you have thousands and thousands and thousands of deals and you're just going to skim the surface to understand. But even if you have a whole bunch of questions that you're getting a lot of quantitative feedback on, you still don't get the color around it, you still don't get the, but the reason I told you your pricing wasn't great was because of all of these things. I'm trying to translate my feelings into a radio button and that doesn't always get retranslated back so that you can do something about it.

The challenge with the interviews is because they're so costly, and they take time and there is a bigger heavier investment there. You're going to get deeper feedback, but can you apply that at a point where the economics break on this side? So we introduced Flex interviews to try to goldilocks this thing a little bit and meet people right in the middle of not too small, not too big, kind of just right, and this is a great story of how that can work out.

It's perfect fit for us, Spencer. And I would say it's not just about the price point in terms of how much that offering costs, I think it's also about the volume of data that you're unable to get back. If you make decisions on interviews with four customers that you won or lost deals and the deals are $2,000 a year ARR, I don't know if you want to make decisions based on four interviews.

Can you feel comfortable doing that? That takes some guts.

You probably want to have more 40 or 50 interviews before you can start to detect a pattern. And that's what you can get at with Flex interviews because it's easy for the customer and it's easy for us to collect that data in that form factor, and it's just a whole level above what you get from a quantitative survey.

I love it, this has been a great conversation, super helpful, super awesome. You've done this multiple times before, like you mentioned earlier, Craig, you're one of the people that we've worked with at Clozd that I would say is on the front bleeding edge of adopting win-loss technologies and programs and driving value from it. So it's been a pleasure for us to work with you.

Let's say I'm you five years ago or seven years ago when you're first getting exposed to win-loss, what advice would you give somebody who's stepping into this for the first time? And what are some of the things to make sure you do and what are some of the things to maybe make sure you don't do if you're doing win-loss for the first time?

Such a great question. 2017 me, what would I say? First thing I would say is, you probably have some hunches around your go-to-market effort. You're probably suspicious about something and you are wondering if you should make a change. So that's where win-loss can be brought to bear so effectively to back your change with data.

And sometimes it's intimidating to get started with something like that, so if somebody asked me like you just did, I would say, start super small. Pick some hunch that you have, do a very small number of interviews, and I'm here to tell you, as soon as you read the first one or the rest of your management team reads the first one or your head of compete reads the first one, you will want more data like that because it's just so insightful, it's just a world that is not available to you until you do third party win-loss.

That's awesome, and you just get started. What would you tell yourself not to do? What are some of the mistakes that you've seen or things you've run into in the past that where you'd give watch-outs to somebody that's doing win-loss?

Another great question. With great power, comes great responsibility.

I love it.

If you have a data-driven insight that almost inevitably this is going to call out some department or some other executive leader, it's going to be like the CRO. What are you doing over there? Or the product leader, just do your best, whoever you are within the organization to make sure that whatever you glean from win-loss is not used to forward some kind of agenda.

You just need to make it just this dispassionate thing that's looking at your business and sharing insights for all of us to come to the same conclusions. But don't use it to advance some kind of agenda internally, it's not what it's for. Win-loss is at its best when it's data that's served up to a bunch of smart people and they all come to the same conclusion because they have the same data.

I love it. I've never heard it stated that way, and I love it. Win-loss information can be super powerful if people look at it through a objective, humble, we're all messed up, we all make mistakes, we all screw up in our jobs and we're just trying to figure out how to advance the ball, and we're all on one team trying to get better. When it's looked through that way, great. When it is weaponized and politicized, watch out. And I don't think anybody wants to work in an organization that does that because it's definitely not healthy, but it's super important too, I love that feedback or that guidance, it's super helpful.

It can bring teams together to solve problems, that's the power of it.

I love it. Craig, this has been awesome, thank you so much, I appreciate you taking the time, everyone else, I appreciate you joining in. If you're interested in seeing more sessions, they're all up there, go jump on and we'll talk to you all later, thank you.

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