032 | Predicting Your Customer’s Needs in Real Time with Bill Odell of Aerospike | Studio CMO
The Episode in 60 Seconds
It’s one thing to think you know your customer. It’s another thing to create a marketing message that grows and changes as your customer does.
In this edition of Studio CMO, we talk about:
- The privacy challenges of data gathering
- Has email marketing run its course?
- What is an MQL in our data-rich world?
- Programatic solutions for marketing messages
- How your understanding of the buyer’s journey changes the data you gather and then is changed by what you gather
Bill Odell is the CMO of Aerospike who strives to build next-generation data systems for their customers. Bill has spent over 25 years in the trenches launching new products, building businesses, and leading high performance marketing organizations. He is passionate about helping educate customers on how to apply new technology solutions that help drive transformative business outcomes. Bill has held executive positions at Cisco, Dell Software and SonicWall as well as multiple category-creating growth stage B2B technology companies.
In 2012, researchers at Harvard said, “Data is the new oil.”
Bill Odell believes that realtime data is truly the new oil.
Email marketing might be running its course because LinkedIn and social media are becoming more of the way that we engage with people. But how do you do it contextually and appropriately? — Bill Odell
Privacy matters surrounding data gathering for companies with an online presence have become more complicated in the last two years. Find out how and when your company needs to comply with GDPR and CCPA with these articles:
There is a standard Marketing Qualified Lead (MQL) methodology. If they do X plus Y plus Z, they’re scored and we make a phone call, send them an email, or perhaps an InMail on LinkedIn. But what if you could also look at their activity off your site? That gives you a better signal. You can truly determine if the lead is worth your time. Because the truth of the matter is the number of MQLs—that should be your best leads that actually convert is still relatively low. So how do we get it to go higher? Use different kinds of data signals to try to figure out when’s the right time to contact. That’s a fundamental sea change in marketing. — Bill Odell
Wouldn’t you rather put your ad in front of the right person at the right time and the right place. But underneath that is an engine that has to be able to deal with massive amounts of data. So as marketeers, as we think about choosing ad platforms, you’ve got to really understand that not all ad platforms are the same and you want to go with the ones that actually know how and can deal with massive amounts of data and can prove that they can target and deliver your ad at the right time at the right price to get the right yield. — Bill Odell
What defines us, isn’t our name and our title and our company, right? What defines us is a whole bunch of information, right? It’s where we spend our time. What do we enjoy? What do we purchase? Where do we purchase things from? You know, the companies that are figuring this out, spend a tremendous amount of time, building a very comprehensive profile store. How well you can build the profile store on a bunch of attributes that go beyond name, title, and company. But how do you keep that contextual? Because we move around, we change, we age, we get married and we have kids. And so in order to do any kind of AI- or ML-driven application, it comes down to the data models and those data models are as good as the amount of data you can feed them and how fast you can refresh the models. — Bill Odell
profile store +
frequency of changes +
= best decision at the moment it matters
Information About the Buyer’s Journey
Understanding Your Customer
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Bill Odell (00:00):
What defines us, isn’t our name and our title and our company, right? What defines us is a whole bunch of information, right? It’s where we spend our time. What do we enjoy? What do we purchase? Where do we purchase things from? You know, the companies that are figuring this out, spend a tremendous amount of time, building a very comprehensive profile store. How well you can build the profile store on a bunch of attributes that go beyond name, title, and company. But how do you keep that contextual? Because we move around, we change, we age, we get married and we have kids. And so in order to do any kind of AI- or ML-driven application, it comes down to the data models and those data models are as good as the amount of data you can feed them and how fast you can refresh the models.
Mark Whitlock (01:10):
Welcome to Studio CMO. You’re listening to the podcast that brings real life conversations about the issues that matter to B2B tech marketing leaders. We are here to talk about the wins and talk about some of the losses and some of the hurdles that we face together and meet some of the most interesting people in this space. And John, today, we’re going to be talking a lot about data and I just, just want to know what was the first statistic that mattered to you, or what’s an important statistic that you’ve kind of hung on to in life.
John Farkas (01:42):
I’ll say in the early stages of my life, I did all I could to avoid anything to do with numbers. So that was certainly something I looked at, but for sure, the statistics that I paid attention to early was the back of baseball cards. I was a major baseball card collector, a huge Cincinnati Reds fan. And I had memorized a good part of, uh, the stats on the back of those Topps baseball cards that I had severely dogeared, well-worn and only saved a few in pristine condition. I was all about looking at them and studying them.
Mark Whitlock (02:23):
Yeah. I played nine years of fantasy baseball with my dad and a bunch of other people from another company that I used to work out. And even in the days before instantaneous stuff, we used to have to get a download from the internet of all the baseball stats from the night before. And I think for numbers for me, I just try to keep up with the age of my kids. It’s sometimes harder to, to keep track of all those birthdays and everything, but we’re going to be talking about data today with a guy who is a data expert. Uh, and as, as I would call him the B2B tech whisper, if you look at his career, he’s got an incredible backdrop of working, um, in the tech space Bill Odell is the CMO of Aerospike and they strive to build next generation data systems for their customers. He’s helped B2B tech companies grow including risk sense, Pricelock and JobVite, Right90 he’s held executive positions at Cisco, Dell and Sonic wall. And that only scratches the surface of a career that has, has stretched across the millennium lines. So bill, we’re so grateful to have you on board with us, welcome to Studio CMO.
Bill Odell (03:29):
Uh, well, it’s a pleasure to be here, thanks for, uh, for inviting me.
Mark Whitlock (03:33):
So give us a little bit of information, tell us what Aerospike does better than everybody else.
Bill Odell (03:39):
Aerospike is really all about real-time data. Um, you know, I think Harvard penned an article awhile back that got a lot of notoriety saying data is the new oil, right? And I think now real time is really the new oil real time data. If you think about just the last seven months of our lives here, right? With the pandemic, all of us are online all the time, transacting in ways and volumes that we’ve never ever considered. Right? Uh, we’re not going to the store. The store is coming to us, you know, is one, one example, right? And the amount of load that that’s put on, uh, systems and data systems is, is overwhelming. And really companies that didn’t figure out that the world is going digital and the world is going online, are now waking up to the fact that they better get upon the business of figuring that out, because we don’t believe at Aerospike that things are going to go back to where they were, that this is a fundamental sea change.
Bill Odell (04:47):
And so data, regardless of your function is just something every executive has to pay attention to. So Aerospike, you know, we build a real-time data platform, um, powers, some of the most innovative category leaders in their sectors. If you think about Wayfair as a e-commerce company, pick one, that’s, uh, taking it to Amazon. I mean, Amazon is the 800 pound gorilla, right? But Wayfair is crushing it, right. And what they self described them as, as a software company, that’s happens to sell sofas online because they built their infrastructure. Understanding that the way we consume things now is online. And if they’re going to compete against Amazon, they have to have a data platform underneath it that will actually allow them to do that. And that happens to be Aerospike. And there are others, whether it’s the Sony PlayStation 4. Millions of users are online all the time. And every one of those users gets a personalized experience based upon who they are that gets served up on data stored in Aerospike. And that’s a massive amount of data that has to be present and delivered in real time. And you can’t do that on legacy data platforms. So that’s what we’re about. And it’s exciting to be a, the CMO here.
John Farkas (06:06):
So it only makes sense that because you’re working with Aerospike right now, but you have a data-centric approach to how you look at marketing. One would hope if you were, if you were in, in giant data, you would be in the wrong place. So I’m glad to hear the consistency. Um, the thing I’m intrigued about talking with you about, because you’re one of the few grizzled veterans of marketing. I mean, people don’t make it as far as you have often. You, you know, you were in the first movement of business to business software as a service and bringing that to market and the very early stages. And so I’m really curious just to get your perspective, like if you were to give us an overview of what you’ve seen, move and change, what the, from/to has been in your world, you know, in marketing, how would you describe that?
Bill Odell (07:04):
Like could be here for a long time talking about that. I mean, the big shifts that I’ve seen is, and I’ll go back to data. Whereas, you know, we used to be as marketeers subjected to very, very limited amount of data, right? I mean, I’m old enough to remember. We were lucky if we had a contact database that stored our most recent prospects in some sort of system that would allow our BDRs to be able to at least stand a chance of getting somebody live on the phone because the information was correct. And then hopefully you could track the conversation. Direct mail was the only thing you had other than conferences that you could go engage. And, you know, in the big challenge with direct mail was, if you remember I’m old enough, right. Where, you know, you had a mail room, can you imagine that mail rooms who has mail rooms anymore?
Bill Odell (07:56):
But I remember a mail room where you would go in and see the little cubby with your name on it, and you’d go in there and reach in. And right next to it was a big trashcan. And most of the stuff that you got was junk mail. And you just, Chuck, Chuck, Chuck, Chuck, Chuck, until you got something that was interesting. And so the game and direct mail was how do you get through the clutter? Right. Right. And that was about it. Right. But how did you track if any of that stuff was yielding any return on your investment? Very difficult to do, right? Yeah. So along comes the internet. Right. Pretty cool. Right along comes CRM. Woo. Right. Can you imagine salesforce.com rocked the world? A number one, they made it easy because Siebel, that kind of started that whole space. It was very hard.
Bill Odell (08:40):
And Mark Benioff came from the same place. Tom Siebel came for him and said, look, you only need 20% of the features, but if I can make it, so it’s really simple for you to get up and going and get what you want. I bet I can build a big company. When’s it’s the last time you heard about Siebel systems, right? But CRM in the internet gave us the access to information. We never had as marketing people. We could actually track things. We could store things, we could measure things. Wow. Right. So all of a sudden you’re doing email, not direct mail. You’re doing campaigns that you can track uniquely. You have dashboards. You can go to your board of directors, scary, Hey, here’s, what’s happening with the money. Here’s the money I’m spending. And here’s what it’s yielding or not yielding. And that’s huge.
Bill Odell (09:31):
And now you enter a world now, which I think is a complete, another tectonic shift where it’s not about just data. That’s housed in simple systems like CRM systems. Everybody has a CRM system. Right. And everybody’s doing email marketing. In fact, I’d argue that email marketing might be running its course because LinkedIn and social media is becoming more of the way that we engage with people. Right. But it’s how do you do it contextually and how do you do it appropriately? Think about GDPR and all of that movement CCPA here in California, data privacy now is, is becoming a big issue for people like me. And it’s it’s yeah. I think it’s an okay thing. How about a world without cookies? Right? How about a world where Google is being challenged? This is a huge deal for all of us, but this is now about real time data, right?
Bill Odell (10:22):
If I can target the right person at the right time with the right information appropriately, so information that would help them along their journey to making the right purchase decision. Now, you’re talking about a world where the consumer and the vendor connect in an appropriate way, and it doesn’t become so much about volume of spray and pray, but about, can you really contextually target? And I think that is a fundamental shift in the way, systems have allowed marketers to be able to engage a market. And I think CMOs did figure out how to do that and understand the systems that are good at doing that are the ones that are going to succeed.
John Farkas (11:06):
Yeah. I couldn’t agree more. I think that, uh, certainly as we look at the ability to track and as we start applying increasingly sophisticated models to the data that we’re able to track and develop the ability to predict, um, that’s where marketing moves from sales strategy or a part of a sales strategy to a fundamental business strategy, because we, we take a different seat. Right. I mean, we, we start being able to have insights that no other part in the organization has the ability to, or the mode of managing. How have you seen that happen in the context of your organization?
Bill Odell (11:49):
Yeah, well, I, I always think the data is the great, you know, I mean the, you know, look at the half-life of a COE, right. Uh, is not very long. Right. Well-documented and you know, I think if I were to characterize myself, I’m probably a B2B marketing survivor. Um,
John Farkas (12:07):
It’s worth noting that Bill’s been at Aerospike for more than two years.
Bill Odell (12:11):
Yes, that’s true. Yeah. Don’t change. But I think data is the great neutralizer, meaning, you know, there’s the common thing in B2B companies is, you know, marketing and sales, right? Th th the contention that you can have, you know, sales, ah, where am I leads? And marketing’s like, how come you’re not following up on my leads and all that who are right. If you can present good data that talks about, well, what are the things that are working? What are the things that aren’t working and have an honest discussion about that you sort of get all of the ambiguity out of the conversation. And I come into companies and I first say, let’s figure out a way to start building the systems and the models to be able to track things so that we can start to have a conversation about performance, because no, one’s going to debate the fact that we all want to be performing at an optimal level. Data is the way that you, and how you can analyze data and look at data and look at it. Contextually continuously is the way that you kind of get all the ambiguity and finger-pointing out of the, out of the room because nobody wants to do that. You know, but without having data that you can sit down and look at it as a team, it doesn’t sort of, doesn’t matter.
John Farkas (13:27):
Certainly if we look at, you know, the typical framework that leads us through the funnel and in the user journey, we’re pretty well versed today in understanding how to manage and track and watch that. The thing that’s different. The thing that I think is the horizon right now, and the thing that the smart forward-looking marketing leaders are looking at are the predictive potential of the tools and things. We have talked to us about how you’re looking at that and how you’re making use of some of those opportunities.
Bill Odell (13:58):
So about a year ago at Aerospike, we started to use an intense data system that would allow us to use keywords and combinations of keywords and phrases through this tool that would give us an indication of companies based upon their search. What they’re searching for online were they actually in market for our type of solution. And we took that data and we really refined all of our keywords and everything that we could imagine that might be an indication that people were in a buyer’s journey. And we integrated that data into Salesforce so that our reps, if they were trying to get into, let’s say 3M company, they could not only see how many people had downloaded a white paper. How many people were an MQL they could see right there in Salesforce are these companies by the, by the search activity, starting to surge on topics that would indicate they might in fact be ready for a conversation.
Bill Odell (15:04):
If you contrast that with just the standard marketing qualified lead, which is just basically a model to say, if they do this plus this plus that they’re scored to a point where we should maybe make them a phone call or send them an email, right. Or an InMail on LinkedIn. Now you can time that to say, well, that was interesting, but wow, look at all the other activity that they’re doing off of my site, outside of me, that gives us a better signal, in my opinion, to really say, is it worth our time? Because the truth of the matter is the number of MQLs—that should be your best leads that actually convert is still relatively low. So how do we get it to go higher? And I would suggest it’s not by just brute force, it’s by using different kinds of data signals to try to figure out when’s the right time to time that, and I think from the customer’s point of view, it’s more natural for them to have somebody reach out to them at the moment of time when they really are seriously now starting to take a look at something then as opposed to just, I’m just poking around. And I think that’s a fundamental sea change.
John Farkas (16:12):
We’re not asking them to take a left turn, you’re joining them in their stream and that’s maybe a surprise less. So these days, I think people are getting a little bit used to these intuitive movements, but what’s really interesting is
Bill Odell (16:27):
Systems. Now that we’re starting to use that we’ll take that intent signal, match it to accounts that we think we have a good fit for match it to their activity, coming to my website, match it to display ads that I am targeting those companies and put that all in a bucket and give that account a score. Okay. Based on a number of data signals and yeah, you still look at your waterfall model to you. Don’t give it up. And now you put that all into a model and say, well, what are those accounts that we should spend more money on, spend more time on what are the ones we might take a backseat on that just, I think gets us more efficient as marketers and gets us again in a more natural conversation with a potential client and not just keep beating them and saying, I’m here, I’m here to talk to me. So I think these predictive systems are the wave of the future, and we’re certainly investing in those
John Farkas (17:29):
Well. You’ve been looking at that pretty intensely for the last year. What kind of results what’s changed? How are you seeing that take root and have effect?
Bill Odell (17:38):
We are now much more focused on accounts that we think are ready for us. Um, it’s still early days, to be honest with you, we’ve seen through these systems and how we target these companies that seem to be in a buyer’s journey. We see five, seven fold, more of those coming to my website than prior. I mean, you can say 30 days prior. I know how many times somebody, anybody from that company in those company, my website now, how many are coming? 30 days later, five to seven times more people are coming to visit us. They’re coming to visit us on the pages. We want them to come to visit because we know kind of who they are and what content we think that they would be interested in. So, so, you know, those are early signals that this is working, but you know, a lot of these things are pretty new. I mean, some of these systems are not that old, so we’re still figuring it out, but the early indicators are good.
John Farkas (18:31):
If you were to identify and you, you talked about some of this a little earlier, but if you were to identify some key tools that you’re making use of, if you were to kind of identify important elements of the stack that you’re employing, that are helping you do some of this stuff, unpack that for us a little bit,
Bill Odell (18:50):
The most recent ones are a Bombora, which we use for intent to pretty popular system out there. A lot of my peers use it. We’re using an ABM platform called Demandbase, been around for a long time. Interestingly enough, they happen to be a customer of ours. One of the things that Demandbase does well, and they just bought engage you or choose an account-based marketing platform. So we think that the integration of account-based marketing the way Engagio looked at it, and Demandbase is a good combination, you know, engage. You was founded by the founder of Marquetto, which is probably arguably one of the most successful marketing automation systems. So we use Marketo Salesforce. Uh, we’re using Demandbase now. Um, we’ve been using Bombora. Demandbase has its own intent engine. We might run them in parallel just to see how they do, but Demandbase has a DSP.
Bill Odell (19:40):
So DSP is an programmatic ad platform. So what that means is I can say here’s a list of accounts that are, are, seem like they’re in a buyer’s journey, target them specifically with an ad. And those ads then would drive them back to my website. And I have one pane of glass to see how all of that’s working. I can see which companies are surging. So I know when to time the ad, I can track that, add to activity back to the website and my S and they integrate with Salesforce. So my BDRs and AEs can say, here are the ones that you ought to be reaching out to. Now that is really powerful because I fundamentally believe that account-based marketing is real. And it’s the way B2B companies, particularly ours. Cause we sell a pretty heavy lift that you need to be thinking about the account level, not the individual level, if you have any buyers committee involved and not just, we’re not B to C, we’re not transacting on the website. There’s multiple people that get involved in that decision. You want to know how are all those people sort of with what you’re doing? And so those platforms are super, super interesting for us.
John Farkas (20:54):
I think what you’re saying is exactly right. The understanding of the sophisticated and certainly Aerospike is on the sophisticated multi-systemic framework that every, the lots of cooperation has to have to employ, which is really true. I mean, if you look at health tech solutions, if you look at, um, FinTech solutions, you’re dealing with these systemic frameworks that need lots of buy-in and you might have one hook in the water and you need seven. Yep. You know, you need seven solid hooks. If you’ve got one hook in the water, trying to get more of the folks in the flow is a really important move in that cycle. That if you’ve got one solid lead, that’s going to take a pretty systemic movement to adopt. That’s where account-based just makes so much sense. And the having the tools to be able to spread that influence is really critical.
Bill Odell (21:48):
So one of the really important developments over the last 10 years, but really coming to fruition in the last five years is this notion of programmatic advertising. What that means is let’s take Google as an example, and I spend money on Google, right? I buy Google ads. I do Google display network. I’m basically throwing out a really large net, hoping I’m going to catch a few fish. Programmatic is different. It actually says, tell me who you’re trying to get hold of. And they will build a profile of those types of people at those types of companies and help you build a campaign that targets them with the right ad at the right time, in the right place. And the really good programmatic vendors understand that you have to do it in real time because they’re bidding against a lot of people for that piece of real estate.
Bill Odell (22:49):
And if you want to be able to, I mean, as the Trade Desk, they want to make money. They want that ad to get in front of the right person. That’s going to click before the theater competitor does. And because that market has gotten to be very sophisticated and very successful, they are the way that advertising is going trade desk, customer virus, customer advisory board kind of looked at my CEO and said, I’ve got a better idea for you than billboard ads. Wouldn’t you rather put your ad in front of the right person at the right time and the right place. But underneath that is an engine that has to be able to deal with massive amounts of data. So as marketeers, as we think about choosing ad platforms, you’ve got to really understand that not all ad platforms are the same and you want to go with the ones that actually know how and can deal with massive amounts of data and can prove that they can target and deliver your ad at the right time at the right price to get the right yield. And that’s, that’s hugely important. And we have sort of an inside track cause we actually, our database powers those platforms. We kind of know which ones are good, but that’s, that’s what we invest in because you know, digital is the future for marketing and you know, you want to make sure you’re getting the right ad in front of the right person at the right time at the right price. Okay.
John Farkas (24:14):
So which ones are good?
Bill Odell (24:15):
Well, there’s a lot, but the trade desk, you can look them up. I mean, they’re now doing things on streaming TV. They’re, they’re making a big bet that that’s going to be the future of programmatic, um, app nexus, um, bought by at and T um, you know, there’s a lot of them, but, uh, just go to the magic quadrant and look at, look at the ones and, you know, Aerospike power is probably eight out of 10 of them. Um, but, uh, choose your DSP, uh, wisely because you want to make sure that you are getting the right yield out of those investments.
Mark Whitlock (24:48):
Uh, I’m seeing our CMOs who listened to our podcast, pounding on their steering wheels a little bit right now. And, and remembering back to the I’ll think about, we had Nicholas Holland on the podcast, Nicholas leads the marketing hub portion for HubSpot, and they did some massive research and discovered that personalization was one of the greatest driving factors for conversion. And yet when he would talk to marketing executives, they would kind of shrug and go, well, you know, other than, you know, the first name and an email, I don’t know if we’ve really ever been able to deploy any of that. So we’ve got a couple things here. One, we used to have a cup that we wanted to get a couple of raindrops of data in as marketers. And now we have this massive ocean of data that we have to interpret and beyond that. So if I’m trying to get into the instantaneous predictive world and I want to invest in Bombora or Demandbase and, and use that portion of, of what they’re doing, where should I start? What’s, what’s the first step I should take to make sure that we’re doing it right. Making, making that investment and making it work.
Bill Odell (25:59):
Yeah, I think a lot in terms of the buyer’s journey, if you haven’t figured out the buyer’s journey and let, let’s take personas as a grant, if you don’t know your personas, you got to have that, but you really need to understand what does a buyer’s journey look like because before you start investing in all of that, if you don’t really know how they start to investigate the category of product you’re in, and then what is the pieces of information that they need along the journey to help them along the way it’s sort of this basis systems that you, any system you get, isn’t going to do you any good at all? So we spent a lot of time in the last year that we hired a firm to go out and literally talk to customers and ask them, how do you acquire a product like ours?
Bill Odell (26:48):
And so when you have that, then you can start to think about putting in systems that can help you try to predict where are they in that buyer’s journey, you know, have they actually taken the steps along the way to, to satisfy that you think, you know, because the predictive model has to be based upon what you think is some condition that would predict that that is actually the condition that is in front of you and you have to. So I think as a marketer about the buyer’s journey and you know, how well do we understand the personas too, but, you know, personas is something we should all, all already have in place. I think
Mark Whitlock (27:25):
That’s one of the core tenants of Studio CMO. If you’ve been listening to our podcast for any length of time, you’ve heard us talk about understanding your buyer’s needs, talking to them from an empathetic understanding. You’ve also heard us talk about our buyer matrix. So in the S in the also heard us talk about our buyer matrix proprietary process of understanding your customer better. I’m going to put information in the show notes about the buyer matrix about the buyer’s journey. We have several great articles on that. Um, that’s an incredible place to start, uh, for sure, bill,
Bill Odell (27:56):
What defines us, isn’t our name and our title and our company, right? What defines us is a whole bunch of information, right? It’s where we spend our time. What do we enjoy? What do we purchase? Where do we purchase things from? You know, the companies that are figuring this out, spend a tremendous amount of time, building a very comprehensive profile store on all of us. So if any of us on this don’t believe that our information is out there and that there are companies out there that have built these profiles stores. We’re not playing in the real world, but how well you can not only build the profile store on a bunch of attributes that go beyond name, title, and company, but where are you hanging out? What do you purchase? What are your interests, where you travel becomes super, super important, but how do you keep that fresh?
Bill Odell (28:52):
How do you keep that up to date? How do you keep that contextual? Because we move around, we change, we age, we get married, we have kids, things change in our own characteristics. And so in order to do any kind of AI or ML driven application, which is what all of this comes down to, it comes down to the data models and those data models are as good as the amount of data you can feed them and how fast you can refresh the models. So if you look at the Trade Desk or you look at PayPal and another customer of ours, or any of those guys, they’re all about profiles. Stores have a lot of information on us. They build AI models and they refresh those models with data on a continuous basis to make those models better and better and better at predicting things, predicting what might be something we might be interested in today in PayPal’s case, it’s like predicting whether or not something we’re trying to buy is actually fraudulent or not right.
Bill Odell (29:57):
Is a big deal. But yeah, I mean, predictive is really down to the data, the profile store, how, how frequent you can, you can keep that up-to-date so you can feed an AI model to make the best decision, you know, at the moment that it matters. So I think that’s where predictive comes in. You know, we talked a lot about predictive, predictive analytics. Isn’t new guys around for a while. What we think about is real-time decisioning, almost real-time analytics, making those decisions. Computer makes that decisions in the moment it matters. And as marketing people, we won’t, you want that don’t you want your campaign to be delivered in the moment that matters to the person who’s ready to, to engage in your,
John Farkas (30:41):
Yeah. I mean, that’s clearly where the future’s going. It’s certainly technology. That’s being applied in a lot of different customer engagement Mo you know, frameworks in the AI world. And so why not in the context of marketing, because the technology exists to understand where people are going and what they’re into, what their next step is, so that you can meet them there. The minute you can do that, it’s just creates a nice backroom right into where you want folks to go.
Bill Odell (31:10):
Exactly. If you think about just our day-to-day experience, right. We buy more and more stuff online. Right. Right. You know, Amazon is probably the model we think about a lot. In fact, I think the thing that the advantage Amazon has is they’ve created a user experience. That is a competitive differentiation. That’s probably less, so anything other than we’re just so used to buying something that if we want to return it, you know, click here, click here, click here, you get a return label. You walk down and, you know, nowadays we’ll come pick it up at your doorstep. Right? Yeah. Very difficult for people to replicate that. Right. But if you, if you think about that experience, right, this is a fact 30% of the Amazon’s revenue comes from purchases that are made after they’ve already filled up their shopping cart. That’s a need to do it because they know based on your profile, that if you’re buying this, you might also be interested in that 30% of their revenue.
Bill Odell (32:06):
So if you’re a marketing person and you’re dealing in an e-commerce type of a market, you want to make sure that the underlying capability of the e-commerce engine for your product is actually going to be capable to serve up the next product that you might think that the person was going to want to buy. And so that in Wayfair does that, they use us to do that. That’s a huge advantage to you because you’re increasing your shopping cart size, and that’s just more revenue. And you know, another thing is, is if you can serve it up quickly, um, you’ll have less cart abandoned rates. E-commerce is all about shopping carts, right? And you want to make sure people don’t abandon, but you want to make sure they fill up the shopping cart. So if you’re a marketing person playing and has an application playing in that space, you want to make sure that you understand that there is an underlying model there that’s predicting who we are, what we like. And hopefully if it delivers on time, you’re going to see more, more revenue.
Mark Whitlock (33:13):
So we’re all very familiar with the Amazon model and we’ve seen the Wayfair model and we’ve ordered from both in our household, for sure. But take that to a B2B context. Where, where does that level of, of abandoned cart? I mean, we use an abandoned cart, um, plugin here, uh, where does that apply in B2B best from your vantage point?
Bill Odell (33:39):
I’ll give you a one that you may not be obvious, but if you think about how we move money now, right. When’s the last time you went into a branch, right? Right. Exactly. I deposit my check. I transfer my money. I pay my bills. I do it all online. Right. Right. The banks that have figured out that once they have you online, they’re going to start to offer things to you. That’s B to C. Right. But go to it, a payment system that deals with money between banks, you know, banks, loan money to each other all the time. Right. And so if you can’t deliver the right experience to a bank, who’s looking to get money from another bank. Cause they all have overnight issues where they need more capital today to be able to meet some, you know, some need that I have because I, you know, I’m overextended or whatever banks do.
Bill Odell (34:37):
I was a banker. So I know that the banking system is a huge system that happens without any of us, seeing it. And banks are lending money back and forth to each other and chance to party all the time. You know, if my experience is such that I can’t do, I don’t understand where I can get that money. And I know that that money’s going to be available and there might be something else I need, besides that, just the money from that bank, I’m going to go elsewhere. Right. It’s happening in B2B too, that B2B companies are transacting online. Just like, like we are transacting online and they’re moving goods and services between each other online, even in, COVID just think about people couldn’t find PPE. Right. They couldn’t find where it was. And countries were left with trying to figure out, Hey, do you have any masks?
Bill Odell (35:19):
Do you have any ventilators, imagine a marketplace where they could figure out where that inventory was. And they said, yeah, you know, I only have ventilators, but I’ve got a bunch of masks. And imagine that you could do that. I mean, that’s kind of something that hasn’t been built yet, but we’re living in an right now where there are, you know, hospitals are in need of S of goods and other frontline workers that are in need of goods. And how do you, and there’s a supply chain there. And that supply chain is online. And how do you make sure that people know where they can get things? And if you can offer them one thing, offer them something else they might be in need of, but they weren’t originally looking for, I think there’s a lot of opportunity for B2B in that same experience.
John Farkas (36:01):
I feel like we’ve just opened the hatch on the rabbit hole here. Um, because the reality is if you start looking at predictive and then take it to the next step and look at real time ability to create a vacuum that pulls people into your stream, that is where we’re going. And it’s where we are in a lot of ways. But I think that the realization of that, and as the AI gets continuing more sophisticated and these models get better and better trained the ability to do this in, in remarkably intuitive ways is just going to increase and bill, thanks for opening the hatch to the rabbit hole today. I think it’s a, it’s a super important topic. I think it’s something we want. We’ll want to come back and, and dive a little deeper with you if you’ll indulge us. Um, but it’s, it’s essential. This is not a click to buy transaction. This is an involved conversation that needs the sophisticated approach of building a relationship. And that takes tools and time and in, uh, when we’re, when we’re dealing with a sales cycle, that’s increasingly self-serve. I think having those tools in place that allow you to support that is essential. So thanks for, uh, bringing us along in that. And, uh, I’m excited to see where, where Aerospike moves, because you’re obviously taking a smarter approach to engagement. That’s going to yield great results.
Bill Odell (37:22):
Thanks for having me.
Mark Whitlock (37:23):
So when you come to Studiocmo.com and click on the Aerospike interview here with Bill Odell, we’ve got lots of information for you. I’m sure you’re wanting to do research and to predictive and into real-time predictive. Uh, we’ll we’re going to link out to Bombora and Demandbase and of course, Aerospike. So you can take a look at everything that they’re doing. They’ve got a host of case studies on their site. We’ll link directly to that page on their site, where you can look at some of what they’re doing with many of the customers that bill talked about today. He brought up the privacy issues with GDPR and CCPA. We know many of you are growing into a level you’ve thought about it. You’ve, you’ve done some things to bring your company and your website into enough compliance. We have articles that are helpful for you for GDPR and CCPA that we’d love to have you connect into as well. And then as we talked about earlier in the podcast, if you’re wanting to dive into your buyer’s journey, more understand who your buyer is, more so that you can make better decisions. When you get into predictive analytics, we have articles, uh, about our buyer matrix process and about the buyer’s journey that we’ll link out from studiocmo.com and then search for the Aerospike interview. Look forward to having you come visit. And while you’re there, do us a favor, subscribe to this podcast. The fastest way you can get the latest information from Studio CMO is by subscribing on your device. You can scroll down to the bottom of any page on our website and you’ll find the podcast app you prefer most click on it, subscribe. And that way, when bill comes back and we talk, uh, in a, at a deeper level about these issues, you’ll be one of the first to know when his episode is back with Studio CMO. So John, as we close out today, we’ll just remind our listeners that we want to care about our buyer’s needs and our buyer’s concerns and our buyers problems. We want to lead out of that empathetic understanding.
John Farkas (39:15):
And as always, you want to work really hard to make your buyer the hero.
Mark Whitlock (39:20):
We’ll see you next time on Studio CMO.