Key Takeaways

  • Culture is created by stories, beliefs, and symbols, and it is up to the company to manage its creation and federation. Goodway Group uses the infinity loop approach, where everything the company does for clients benefits employees and vice versa.
  • AI integration in enterprise systems is the future of marketing and digital transformation. Companies need to connect their systems to have full 360 intelligence within the enterprise.
  • Humans need to be involved in the loop when it comes to AI integration and data analytics, and companies need to focus on smart marketing practices before jumping into AI integration.
  • It’s important to have a basic understanding of statistics to ensure a balanced viewpoint when utilizing AI in data analysis.
  • Grouping customer comments into themes and discovering the sentiment around them can help make actionable decisions, but relying solely on customer reviews has it’s own limitations.

Executive Summary

Transforming Digital Media: Jay Friedman’s Journey With The Goodway Group

Greetings, everyone! On The Leader Show With Louis Carter, our guest today is Jay Friedman, the CEO of Goodway Group. Goodway Group delivers a holistic approach to digital media strategy and execution, leveraging sophisticated techniques for data analysis, insights, and customized consulting services.

In this episode, Jay discusses Goodway Group’s journey to getting certified as a Most Loved Worplace® and shares some crucial advice for budding entrepreneurs. He talks about transforming the digital marketplace and the successes that Goodway Group has enjoyed in this segment.

Now, without further ado, let’s jump right in!

Overview Of Goodway Group

Lou initiates the discussion by asking Jay about Goodway Group and his journey as CEO. Jay highlights that Goodway Group is an umbrella company with three ad agency marketing service firms – TUFF Growth, Goodway Group, and Control V Exposed (CVE). 

The company has around 550 employees worldwide- a significant increase in personnel since he joined in 2006, when the team comprised of only 30 individuals. Jay notes that Goodway Group was founded in 1929 and is currently run by the third generation of the family, with him being the first non-family member in the CEO position.

Jay’s Experience as CEO and Managing a Global Team at Goodway Group

When asked about his role as a non-family member CEO, Jay responds by explaining that he focused on building trust by communicating with the founder over a period of 7-10 years, understanding and delivering on the family’s values and promises.

They also discuss the challenge of managing a global team of 550 employees, especially in a fully remote environment since 2010. 

Additionally, Jay highlights that a company’s culture is created through stories, beliefs, and symbols, and it is up to the organization to manage its creation and propagation. He introduced the infinity loop approach, where everything the company does for clients benefits employees and vice versa. 

Lou agrees that this approach considers the entire ecosystem and not just one portion. On that note, Jay suggests that a company must prioritize both clients and employees equally as they both help each other grow and improve.

Balancing CMO’s and CFO’s Objectives

The speakers then discuss the approach of Goodway Group in helping clients achieve their business goals. Jay emphasizes the importance of understanding the CEO’s business goals and the CFO’s focus on return on investment in marketing efforts. According to him, the marketing agency’s job is to support the CMO in demonstrating statistically significant results and the incremental value of their efforts. 

They also talk about the inherent tension between the CMO and CFO and how external consultants and agencies like Goodway Group can help drive a synthesis of the goals between the C-Suite leaders.

The Future of Marketing and Digital Transformation with AI Integration in Enterprise Systems

Lou cites Dharmesh Shah’s work with an AI tool at HubSpot and asks Jay for his insights on how similar tools will transform marketing, both in digital and traditional forms. Jay replies by suggesting that AI integration in enterprise systems is the future of marketing and digital transformation. 

Having AI for the internet corpus might be nice, but integrating AI in the company’s own HubSpot data, customer data platform, inventory systems, and Point of Sales systems is the future. He mentions that companies need to connect their systems to have full 360 degree intelligence within the enterprise. 

On that note, he highlights HubSpot’s efforts in this area but mentions that it will need to connect with other financial systems such as NetSuite

The Importance of Data Strategy and Human Involvement in AI Integration for Digital Transformation

Next, Lou and Jay discuss the importance of data strategy and hygiene in digital transformation. They also emphasize the need for humans to be involved in the loop when it comes to AI integration and data analytics. 

Additionally, Jay mentions the potential of AI integration within enterprise systems, such as customer data platforms and inventory systems, and how it can lead to 360 intelligence within an organization. However, he also acknowledges that we are still early in the AI revolution, and companies need to focus on smart marketing practices before jumping into AI integration. 

Lastly, the speakers discuss the importance of embracing AI and how it can help employees evolve their careers.

The Importance of Statistical Knowledge for Balanced Viewpoint in AI-Assisted Data Analysis

Moving on, Mr. Friedman emphasizes the importance of having a basic understanding of statistics to ensure a balanced viewpoint when utilizing AI in data analysis. 

He notes that while AI can be helpful in pulling out insights from large datasets, it’s crucial not to overestimate its capabilities and to acknowledge the limitations of smaller datasets. One comment or anecdote does not constitute data, and it’s important to avoid making assumptions or creating data where it doesn’t exist.

Lastly, the speakers discuss the importance of grouping customer comments into themes and discovering the sentiment around them to make actionable decisions. They highlight the limitations of relying solely on customer reviews, such as Yelp or OpenTable, because negative sentiment may be overemphasized, and customers who are happy may not leave a review.

Lou and Jay go into much greater detail over the course of this conversation. Thank you for listening!


Lou Carter : Hey, everybody. We're here today on the Newsweek Leader Live Show. It's a great show today. We have another Most Loved Workplace, another Newsweek and certified Most Loved Workplace that today it's Goodway Group, and we have the CEO of Goodway Group. Jay Friedman on with us today.

He’s gonna tell us all about Goodway Group, how they became a Most Loved Workplace, also advise to other entrepreneurs, to other businesses about what he's learned, really. In transforming the digital marketplace and what he can and has done inside of his company, the Goodway Group, which has had massive amounts of success. Jay, welcome to our show today.

Jay Friedman : Thank you so much. Pleasure to be here.

LC : Hey, let's start with you Jay and Goodway Group. So people get a level set, number of employees, how much business you do, what business you do, so we can get, sort of set in the reality and facts around it.

The Evolution Of Goodway Group: From A Small Business To A Global Presence (01:32)

JF : Yeah, Goodway Group is really an overarching company for, we have three kind of ad agency marketing services firms, just, to make it very simple. we've got TUFF growth, which is, TUFF Growth. And, they are a growth marketing agency. We've got Goodway Group, which is the namesake, which is just the straight marketing services and an advertising services firm. And then we've got CVE or Control versus Exposed, which is the consulting and marketing operations firm. All total, we're about 550 people around the world. And you know,that's up from when I started in ‘06, which seems longer and longer every time I say it.

But that's up from about 30 people then. And of course, the company was founded in 1929. My partner, Dave, is the third generation, so his grandfather started the company. And, I'm the first non-family member to be in the CEO spot. So no pressure.

LC : So, there's a lot of things to unpack here. Number one being, a non-family member, CEO. That's big because trust is a big issue I’d assume. And how did you gain that trust, really is the first thing. And, number two, 500 people throughout the globe. Wow! So, how do you manage and know everybody around the globe and know what's happening to create this great culture that you've developed?

The Infinity Loop Approach: Prioritizing Clients And Employees (03:01)

JF : Yeah, so in terms of building trust, I think the, you know, of course do what you say you're gonna do. And the integrity component is, you know, do what you would do if no one was looking or if someone's looking, it doesn't matter. And that there, that, but really it was just intense amount of communication, especially over the first, I don't know, 7 to 10 years of understanding what was important to Dave and making sure I could deliver on essentially the family promise and the family values that he brought.

And then creating a culture and creating a workplace where he felt that it lived up to everything that he and his family had grown to represent. So, there's that on that side. And then, yeah, 550 folks around the globe.

You know, and we've been remote since 2010, like pretty fully remote since 2010. And I often get a, you know, a question or ask the question, “how do you create a culture when you're fully remote?” The answer is the culture forms, whether you're remote or in person. Culture is a set of stories, beliefs, and symbols. And so it is up to the company to manage the creation and the federation of those stories, beliefs, and symbols. Otherwise, your employees will do it for you.

And so what we use, and I'd say the foundation of our culture and our approach is what we call the infinity loop, which is I find a lot of folks saying, “you know, we're a client first organization”, or “we're an employee first organization.” I think that's a little bit like saying, you know, “If I had to prioritize my heart or my brain, I would prioritize…..” Well, you can't, you, you need them both.

And so the infinity loop is everything we do for our clients has to benefit our employees and everything we do for our employees has to better for our clients. And as long as we follow along with that, we're in really good shape.

LC : I like that looking at the system as a whole rather than as one. Because when, you know, some may say that employees, you know, go put plays first and customers will be helped the most, right? Customer service goes up, plays go first. You're saying the whole ecosystem has to be well, very well attained, well attributed, strong.

JF : Yeah, we have to feed both. We have to feed both with excellence, because they really do help each other. When we do great work for our clients, our employees learn and grow their skills. When we do great things for our employees, our clients benefit from grown-employees and improving employees in the market.

LC : So, going back to the family, because this is interesting. We said about the values, you know, I liked how you said that because that most likely had a big influence on how you lead, how your customers are treated, how your employees are work-within, right? And so how everybody, what are they like? Tell me about the Goodway Group values from the family themselves.

Understanding Dysfunctional Helpfulness: Goodway Group Family Values (6:10)

JF : Yeah, and so I want to be clear that it's the “family’s” with an ‘s values as opposed to family values, which are, you know, it'd be great if workplaces could be families, but they are communities and companies and we have to go with that. But, the family’s values, you know, we did the exercise and we sat around and we thought through the values and everything, but ultimately what we did was we issued values in favor of behaviors.

And so we have 22 behaviors or so. And, because values, you know, I think the way I look at it is how many driving laws are there? There's a lot of driving laws. You can't recite them all from scratch or you know, by heart, but you generally know them. And if the only driving laws were, ‘drive friendly’, ‘be considerate’, ‘share the road’, it'd be really hard for the police to pull you over and say, you know, I don't think you were driving friendly.

And so there are very specific rules like turn on your signal before you switch lanes. And so we have very specific behaviors, with descriptions, and “here's what it looks like when you do it well”, and “here's what it looks like when you don't do it well.” You know, so for example, stay on the right side of helpful. It's very specific. It's important for people to be helpful to their coworkers, but there are times where you could maybe take over your coworkers job, and start doing the work for them. And that's not on the right side of helpful, but to just say teamwork isn't enough.

LC : One of those things that's interesting is there's a big difference between help and support. Right?

JF : That's great. Yeah.

LC : Because that's the other side of helpful, isn't it? Going too far, you know, and it's, you know, doing too much support rather than just giving what they need, the resources, whatever it may be. So there is a dysfunctional or disabled element of helpful. That's what you're, teaching and helping people to realize.

JF : Yeah, all good has the potential to bleed into not good. And, I think that is one of the things that I see really across anything. Is when something like that, for example, gets twisted to say, “but I was being helpful”, but in reality, someone knows they really weren't being helpful. Like the intent was not there.

And so, but that's another one of our behaviors is assume positive intent. It's easy in a remote workplace, you're behind a screen. We all know what happens when people get behind a screen and go on social media, nothing good. You're behind a screen and it's easy to read into text and say, “geez, I don't, you know, I think they were coming at me there”, or whatever it is.

But if you assume positive intent and assume that it was said in the best possible way, then you can be deductive from there. And, if there's a reason to believe otherwise, then go for it. But….

LC : Yeah, it's funny, like an intention is such an interesting concept because you can have good intention, yet still make, be on the other side of any of those behaviors, at all times. And the other….

JF : Absolutely

LC : Your intention may happen. Yeah. Because your intention may be completely different than what the other person may want. Now what happens, and we have examples I'm sure of what that is, the other side of good.

Understanding Incrementality and Other Important Metrics in Marketing (09:28)

JF : Yeah, that's it. And so I think, you know, and I mean you can look to the law, right? Like intent is important, um, but it's not the end all. And, so intent I think is pretty foundational, to things. And then actions and results are really what carry the intent into the full delivery of good, per se.

LC : It is. That's interesting. because I like how you're using the word “Good-way”. And there is that Goodway. And you, right? That's really what you're talking about. It's a behavior, it's a value. You've chosen values over behaviors. So our values drive those actions and behaviors. And I see how you're saying that around laws as well. Do you have a legal background, it sounds like, because [laugh].

JF : No..

LC : it's as interesting how you applied it because it is. There are laws of, of living, of communicating and being, how does it go with your clients too? Because you have a lot of specific branding work, transformation work, analytics work. I've seen that. It's impressive what you do.

And so I wanted to get into that. So yeah, some of the work you do and perhaps even the brands that you work with and how that plays out with the brands and companies. Because I saw you work with a lot of franchises, a lot of larger global brands that require a lot of translation and work across the globe. And what does that look like and how do you get involved at that level with you?

JF : I think, you know, this is where it comes down to whether you're in marketing or you're in HR or you're in operations. I think folks and many companies that are specialties, in those areas or in any area tend to think about their function and how they then contribute. And they want metrics, which is great.

But at the end of the day, the CEO has business goals, and the CFO is trying to make sure that every dollar that is spent contributes toward reaching those goals and returns a greater amount than was spent. And, so I think that when again, whether it's marketing agencies, which we see all the time, but there's of course folks in HR or logistics or whatever it is, they say, “well, what's my budget?” But that's the wrong question. it's, “what's our growth target?”

What are we trying to achieve? What is the revenue target we're trying to achieve? And then, how can I spend as little money as possible to contribute my portion? And, that's just not how most folks look at it. But as marketers, I think that's the best way to look at it. Because as marketers, it's important., you know, there's always this inherent tension between the Chief Marketing Officer and the Chief Financial Officer.

Chief Financial Officer says, I don't know how, what marketing's delivering. I don't know whether it's, you know, how to measure it. And I think, it is the marketing agency's job to support that CMO to say, here's how, you know, here's statistically significant reasons you can be confident in the results, and here is the incrementality value of things, right?

Because, it's easy for you know, as I always say you know, if the last person to touch a customer always gets credit, then the Walmart greeter made every sale Walmart's ever seen. And, that's clearly not the case. And so yeah, it’s I think, it's on external consultants and agencies like us and to support their main clients' drive to meet CEO and CFO goals.

LC : That's interesting. So you really do help CFOs, CMOs to drive to get to their goals with a different kind of slant to it. You're saying, I wanna reduce your costs, it's not about budget.

JF : Yes.

LC : I want to get to your numbers. And that means that we have these levers that we choose that you should be most mindful of in digital marketing, digital transformation, right? In media that you have to press. And these are the best levers because they have the greatest chances of success and give better conservative estimates.

The Need for Marketers to Embrace the Scientific Transformation of Marketing through Big Data, Analytics, and AI [13:30]

JF : I think what sometimes marketers are, specifically marketing agencies don't always recognize is that, you know, if the budget is, you know, $50 million. Let's say, well that last million to a CFO could be spent on R&D, it could be spent on a new factory, it could be spent on better insurance. There's, it's completely fungible to the CFO, and it is on the marketer and the marketer's agency to make the case, why that's needed, not valuable because all money spent, I'm sure in every function is valuable, but why it's needed to contribute to the goals. And so that's where incrementality comes in and a lot of other important metrics.

But I think the other thing that, the other big trend in marketing that is happening right now, and I don't even know how often people stop and think about it, but is, every industry undergoes a scientific transformation.

And so, I would encourage really anybody in any function to think about this. If you think about farming, you know in the late 1800s, you know, there was someone who would, you know, they'd take a bite of the wheat and say, yeah, I think it's about right [laugh]. And, now today it's all 100% scientifically controlled and grown. And, it underwent this scientific transformation. You know, if you think about medicine in the late 1800s, it was, here's some honey and here's some whiskey, you'll be fine.

And, you know, that underwent a scientific transformation. Even tires on your car, you know, I mean, now you need like a PhD in chemistry to, you know, innovate what's next in tires. Marketing and really I think all of the ‘softer areas’ of business are undergoing a scientific transformation into using big data, statistics, analytics, and now certainly AI to transform how businesses are looked at.

And I think that the sooner that folks, especially in marketing embrace the need to understand the science, the sooner that they will help succeed and contribute toward those CFO goals.

Transforming Marketing, Sales, and Customer Service with AI (15:47)

LC : And it's relearning the science, relearning it again. You know, because we have to think of things in such different ways. It's not just chatGPT, it's these incredible amounts of AIs that can predict amazing information by the information it gives us, and we give it. So we can actually train now, AI to think better than we can.

JF : Correct. And chatGPT for example, I kind of call it the HTML of AI

LC : [laugh]. Yeah, it's like an PHP

JF : Yeah, it's the first major leap forward that's gonna be a foundation for a lot of other things, but it's not the end game. and chatGPT is amazing because it has the corpus of the internet, from which to pull more valuable, far more valuable to firms going forward, though will be using a chatGPT style software service that is able to pour through its own data, through the company's own data and through think about, through inventory, through logistics, through manufacturing, through people in HR, and really help the enterprise optimize in much faster and smarter fashions.

LC : I just look at like what Dharmesh Shah is doing at HubSpot, the AI tool there, and, you know, tell us about, how you foresee those kinds of tools, you know, coming into play and how they're transforming, how we think about marketing digital traditional transformation

Exploring the Potential of AI Integration in Enterprise Systems and its Implications for Digital Transformation [17:14]

JF : That plays right into kind of where I was going with the AI revolution that's happening is that it's nice to have AI on the, you know, for the corpus of the internet, but to have AI on your own HubSpot data to have AI on your own, within your own customer data platform, within your own inventory systems, within your own Point Of Sales Systems, that is where the magic is going to happen.

And so the companies that are looking to help take advantage of that. And ultimately what I think HubSpot's doing is awesome, but it's also gonna have to connect to a NetSuite or other financial systems, etc. Because it is about that full 360 intelligence within internet enterprise.

LC : That's interesting. You said full 360 intelligence, because what the AI tools will do is integrate into those other intelligence areas, right? And, you know, finance, marketing, sales, like the whole suite and even customer service. And it has implications for healthcare, for retail, for all service areas and product areas.

So, what does that look like for you at Goodway Group? Are you, is that part of your suite of services where you help companies to transform in that way, finding the best technologies or even providing those technologies, so people can be on top of it and really learn how to do that? Is that some of the things you're talking about with transformation of digital?

Balancing Excitement for AI with Current Smart Marketing Practices (18:36)

JF : Yes. I mean, I think we're exceptionally early and, you know, I think anybody who says that they have it all figured out with AI and marketing, I'd be wary. But yeah, it's thinking about how to get ready for it. Because I think there are a lot of people who want to jump into it and then they realize their data isn't in a place where it can even be discerned and joined. And so, just digital transformation typically begins with smart data strategy and data hygiene and so we've helped a number of different clients in those areas. And, so yeah, I do think that, yes, it's a love affair with AI right now and it's exciting for everyone to be looking forward into the future on this. But that doesn't prevent us from needing to just do smart marketing, as it exists today.

LC : I agree. I totally agree. Because you know, we're looking at a new generation, it's sort of like, what do we do when people haven't been brushing their teeth for 20 years. [laugh]

And we have a new technology to brush your teeth, right? [laugh], it's like, oh, you haven't brushed your teeth. I first have to work for a little bit of time, perhaps get you new teeth, work in the platter, you know, so then we can work onto this new technology.

But it's not quite there yet. So a lot of what you do probably in this hygiene moments are, let's look at the data, put them in the right cells, determine what are the right information that you need to know and what you want to work with, right? Yeah. Versus what you don't want to work with.

Embracing AI in the Digital Age and the Importance of Human Input in AI and Data Analytics (20:15)

JF : Yeah. So that’s I think that's a huge part of it. I think it's also, you know, back to the Most Loved Workplaces, kind of component is helping people understand how to embrace AI and weave it into how they evolve their career. And you know, I saw a great quote somewhere that I've conveyed to our employees, which is, “you won't be replaced by AI but you might be replaced by someone who learns how to and embraces using AI better than you.”

And so, from that perspective, I think it's really important for employees to, and we have, you know, one of our digital transformation divisions, CVE is already embracing and just testing everything they possibly can with AI to see where it's better. Because if it's better, why bother doing the longer human thing? If you can just get AI to do it for you in a faster time? It will be that human and machine push and pull, and being in sync will enable the best results, really.

LC : And I think that's where a lot of people go wrong is saying they don't think there needs to be a human in a loop. So they’re reduce funding, they will just pay for AI, no human in a loop. And that's not true, yet. [laugh] You know, for now,, what we have done too. We do sentiment, we've created our own sentiment analysis, emotion analysis and thematic analysis that goes through thousands of points of data, of employee comments and play, and then discovering what's the core themes? What are the core emotions? Because we're a Most Loved Workplace, we need to know about love and what is the general positive sentiment.

Now, that requires that we take lots of data and lots of surveys and constructs and put a human in the loop is, we have to know first what are our labels?

We have to label our data. It's boring at first, but someone's gotta do it. Someone's gotta be an annotator, a labeler, the boring person in the data room who's gonna talk the boring. Sorry, nope. There are no boring people. The boring job [laugh] which by the way, there's people who love it too. So I'm not disrespecting anybody who've done that, I'm saying is actually, I love you guys.

What you've done is awesome. So, you have to appreciate that, that human part of it, and then we can create the AI part of it, and then the human has to keep going and expressing if it's right or wrong or not, because people get really angry when things are wrong, period. We lost Jay, which is okay, [laugh], it's been every time we lose Jay, Jay's at the airport.

And when I was talking about with Jay is, and you guys can see this too, if you look up, just go to, you'll check out what we've been doing with thematic analysis, sentiment analysis and emotion analysis. If we take your level of workplace data or any data or comments that you've been doing, and we make them, and we actually look at the core emotions that are inside of these comments, see, it's hard to do.

Think of like hundreds of thousands of comments that you've gotten before. If you're anyone in HR right now and you've tried to put lots of comments in, or somebody in marketing, you know, you have too many comments in there and you can't figure out the themes associated with them. But we've done, workplacely, Most Loved workplace, if you go to, you'll see, you could take that information and see what the core themes are as well as what the general sentiment, positive, negative, neutral of those comments are, and emotion.

So, think about the possibilities with this kind of technology. It's extraordinary. So you're gonna now be able to not just by hand learn what those themes are and what you have to do every single time, Now you're going to be able to do much more than that. You're gonna be able to know the themes, give recommendations much more quickly than you ever had before.

Jay, welcome back. Talking about transformation of the digital age, and also of metrics, and measurement, and how that works really within the digital transformation culture and within also, HR learning. How that impacts, how we view employee data, and what we can do with that employee data in new and different ways. So as not to just serve employees, but serve customers.

Weighing Data Points: The Human Element in AI (24:42)

JF : A crucial component to that is really, I don't think we need to be statisticians or data scientists, but we need to have a basic understanding of statistics because it's really easy for an enterprise of 40 people, to do a survey and then think that AI is gonna pull out all of the best analysis. but the reality is when there's only 40 people, there's only so much statistical confidence that can be gained and one comment, what is it? The plural of anecdote is not data, you know? And so it's really important for people to just take a balanced viewpoint of all of this, now and going forward because it's not the answer to everything. It can't create data where it didn't exist.

LC : Exactly. Yeah. So, what Jay was just talking about is one play comment won't give you that much more information. What we're saying is taking a group of comments, right? And grouping those in, looking at the themes, then in discovering the sentiment around that, and then giving you an ability to make a decision on it. You get all these customer information and data from Glassdoor, from Indeed, from all the various, Yelp reviews, but you can't do anything with that and you don't know what is right or wrong after a long time.

So, if you get true clear information that you can begin to place into categories and now you know what to do with that info and you can make an actual action, have a more of a data-centric approach to taking action.

The Limitations Of Relying Solely On Customer Reviews For Business Insights (26:14)

JF : That's a really good point on like a Yelp or an OpenTable. It would be really interesting to see how reviews or, you know, review sentiment does or does not correlate with availability and how much booking that a restaurant gets. Because clearly there's a lot of people who just, they only review when they wanna complain. And so, you know, you may overweight or over view negative sentiment but if the restaurant's booked solid for a year, then something's going right, actually.

And so I think that's where we need humans to understand how to weight and value data. And again, go back to the business goals as opposed to, you know, when the metric becomes the target, it's become an invalid metric.

LC : That's the beauty of AI, is that human in the loop can weigh those data points and essentially those reviews that you're seeing. You're right, there can be massive amounts of traffic in a restaurant, but yet you only get all the negative reviews, all of a sudden they start coming, right? Coming in the restaurant and the reviews start going up and up and up because we start weighing them differently. Because we're, we're realizing that sentiment is specific. It can be be weighted more with positive review if the emotion is understood.

So, we're looking at things like optimism, right? We're looking at things like, like happiness, like optimism, like hate, anger, frustration. These all weigh differently as emotions than sentiment. Sentiment is positive, negative, neutral than you have emotions underlying it. Those emotions actually trigger and change sentiment. And this, you're only asking for sentiment now, right? And we're saying one through five, it is like, nah, it's different.

The Importance Of A Smart Data Strategy In Digital Transformation (28:11)

JF : Yeah. well and people self-disclosing their own sentiment is generally not very accurate and that's where as marketers, I think we have to and that's where the scientific transformation of marketing can really help marketers and enterprises start to parse through. Because again, you may, you know, whether it's an internal employee survey, or it's a Yelp or something like that, well, someone may have negative sentiment, but if you look at all 23 of their reviews they've posted and they're all negative, well then you have to take that with a grain of salt, whereas if you have someone who's got a very nice distribution of one through five stars and it matches the universe and they say something negative, then you should probably…..

LC : A hundred percent. And it’s such a help I'm sure to your clients worldwide, is that they can now understand how best to work those, not just reviews, but how to enable the flow by understanding how customers really do think.

JF : Yes, exactly and it's same internally with employees I think. You know, there's, I forget what the common thing is, but there's always 10 to 20% of, you know, employees who lead, they're change makers, you know, there's 10% who always wanna stay behind, and then there's the middle. And so, you know, an employee survey you can really start to look at the very positive or the very negative comments and be swayed and I think being able to have either questions or ways to, kind of like the Olympic diving thing, remove the high and the low, take the average of the rest.

LC : [laugh]. It's right, the median, what we're looking at too is methodology is very important. So meaning if the methodology is “do well’ with what people do well and what you could do better, you've now shifted the conversation from being a person that is, or in any way, a person that is thinking of what you did wrong. So, that's negative immediately to how can I help you become even better to serve me best.

Hey everybody, we're down on the 12:30 mark. We've been here with Jay Friedman, CEO of Goodway Group is on his way now to the airport. And it's been great seeing you Jay.

JF : Thank you.

LC : You're Welcome, on the leader show so we can hear you a little bit. But Jay, all the best to you. See you soon. Bye everybody.

JF : Thank you. Bye.