In this episode of In-Ear Insights, Katie and Chris talk about the power of brand. What is brand strategy? How do we effectively measure our brand marketing? Listen in to learn the difference between a branded house and a house of brands, how to think about brand strategy, and what the most important brand measurement methodology is for digital marketers.

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Christopher Penn

In this week’s in your insights, we are talking all things brand strategy. It’s one of the upcoming search terms that we identify in our predictive analytics forecasting for stuff that is important to marketers. So, Katie, let’s begin with some basics. In terms of brand, what is brand mean to you? before we can even talk about brand strategy? What does brand mean?

Katie Robbert

we are not, we don’t have a lot of products, per se, or we don’t have companies underneath our company. So, you know, our brand is trust insights. But if you have companies where the past brand is, you know, something that’s not really a service, or a product, something people don’t even really think of, and then the products themselves are the brands such as, you know, a vacuum or a specific kind of shoe or a clothing line, that’s, you know, a house of brands instead of a branded house. And so it can be a bunch of different things. So first, you need to figure out, you know, what is your, you know, what is your offering, or your products, your brands? Or is your company name your brand? So that’s sort of the first thing, you know, so again, for trust insights, our company name is our brand, we don’t have you know, the, we have services, but it’s not the trust insights, predictive analytics product. So predictive analytics doesn’t become its own thing. That then people then forget that trust insights is the parent brand,

Christopher Penn

people do talk about their Prius, in the absence of the Toyota name, because it’s implied, you know, what the Prius is, you don’t know, the no one else has one. And therefore,

In this episode of In-Ear Insights, Katie and Chris tackle a key, undiscussed problem with influencer marketing. In three states in the United States (California, Washington, and Pennsylvania), companies are prohibited from discriminating against contractors with the same level of protections as employees. When companies choose influencers, how rigorously are they screening against bias and discriminatory practices? Listen to the full episode to learn some different perspectives on influencer selection.

Disclaimer: Neither Katie or Chris are lawyers and this podcast episode is not legal advice. Contact a qualified attorney for legal advice before making any decisions that may expose your company to risk.

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Christopher Penn

Do we need to be thinking about in our in the software we build for it for identifying influencers? Do we need to be thinking about bias, do anything about gender bias, race, spies, etc, things like that? Because there is the very real possibility that will end up with a whole bunch of people who are so this homogenous cluster, we did some research and found that within the United States, at least three of the 50 states require companies to apply the same laws for non discrimination for contractors, as they do for employees, the other 47 states and at the federal level, do not. So Katie, from your perspective, as a business owner, who has to be compliant with the law, what are the best practices for influences? They don’t work for you? They are independen

In this episode of In-Ear Insights, Katie and Chris take you behind the scenes as they examine first quarter marketing data. Listen in as they audit Trust Insights’ own marketing data, identify weak spots, determine a course of action, and look at ways to gather additional data for better marketing insights.

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Christopher Penn

In today’s in your insights, we are turning, I guess, the mirror or the looking glass inward. Katie, you wanted to tackle a problem that I’m sure a lot of other marketers have. But we’re looking at in our own data. So why don’t you set the stage?

Katie Robbert

Yeah. So Chris, I would sort of turn to you. And say, if a client came to you with a question like that, where would you even start them?

Christopher Penn

Do we have the right audience? Are we getting the right people to the website? It’ll be question number one. So we look at the demographics who we want to be targeting. And we’ll look at the demographics based on things like Facebook Audience Insights from our tracking

In this episode, Katie and Chris review the field of customer experience analytics. What are customer experience analytics, and what comprises their components? From simple data points like returning users to the website to Net Promoter Scores, join them on a walk through the customer journey and how to measure it at every step.

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Christopher Penn

In this episode of in your insights today we are talking about customer experience analytics, measuring the customer experience in so many different ways. And then what do we do with the information. So Katie customer experience analytics was mentioned heavily in Jay Baer his new book talk triggers which we reviewed a couple months ago. And it came out, it came with a very adorable stuffed alpaca. And some of the KPIs mentioned in this book. Things like Net Promoter Score change, offer redemption, customer growth, customer behavior, but you’ve got a lot of work explaining the customer journey, particularly as it pertains pertains to predictive analytics. Those few big numbers are just the tip of the iceberg. We are talking a little bit about some of the stuff that we always want to look at the stages of that customer journey.

Katie Robbert

So I can’t say that it was cute. Second, yeah, you’re right. There’s a lot more data that’s available to marketers about the customer experience. And I think that, that sort of, like, let’s start there. You know, when we talk about the customer experience, we’re really talking about the buyers journey and the customer journey. And together, those make the full, you know, 360 customer experience. And so, within all of those phases, it’s there’s multiple phases, you have a lot of different touch points and data points to collect about the experience that your customers going through.

So that way that you can continue to refine and improve the experience to create more retention. And I think that that’s ultimately the goal of what marketers are after is what data leads to more customer retention. What experience leads my customers to keep coming back and buying more things from me, and to stay loyal?

Christopher Penn

Katie Robbert

In this episode of In-Ear Insights, Katie and Chris talk about how to work with data and visualize it more effectively. Data visualization is a skill not taught in schools, and it’s equal part art and science. Tune in to hear their tips about what’s the best way to use different charts and graphs, what reports should contain, and much more.

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Christopher Penn

In this week’s in your insights we’re talking about crimes against numbers, visualization of data and data storytelling. We’ll start off by saying I saw this horrendous, horrendous chart in the news. So I’m going to put like five different pie charts next to each other, trying to illustrate some kind of comparison about voting and the end 2020 candidates. And we’re not going to talk about the politics all but the fact that someone tried to tell a story about using five in pie charts, all with different colors is a crime against numbers. And so let’s start off today. Like when we’re talking about communicating intelligently with data. Katie, what is some of the most egregious misuse that you’ve seen other than, like, I’ll start off by saying pies for eating, not for communicating data.

Katie Robbert

can come out of the box with things like Excel, or any of those other types of software programs.

I think people just don’t know how to properly communicate with that type of visualization. And it is tough, it’s not something that people get right right away. I mean, how many times do I go back to you and say, I don’t get it, let’s do it again. Because I think what happens is the data itself gets over complicated. And then when you try to put it into a very simple chart or graph,

I think that that’s where it kind of gets mucked up. And so I think, also, if we go back even a step farther, the difference between a chart and a graph, or a visualization or a pie chart, or bar chart, or a line chart, like I think all of those things, they’re so nuanced. And they each have their own specific use and how they tell the story. But who’s teaching that I remember when I was in grad school, and I wasn’t in grad school, right out of college, I was in grad school in my late 20s. So I had been working for a while. And in my stats class, my professor gave us an assignment. And he was like, and part of the deliverable part of your homework is to create some kind of a chart with this data. Now, I’d never learned how to make charts in excel at that point in my career. And I was in my mid 20s, and I remember I had asked him that question goes, it’s not my job to teach you. You just need to Google it. And so I had like a mini meltdown, because I was like, how did I ge

In this episode of In-Ear Insights, Christopher Penn and Katie Robbert discuss the journey to becoming public speakers, public speaking tips and tricks for new speakers, and what speakers do most wrong.

Interested in bringing a Trust Insights team member to speak at your event? Visit our Speakers page for more information.

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Christopher Penn

In this week’s In-Ear Insights we are talking about public speaking what it takes to become a public speaker. What are some of the best practices? What if things that you wish you’d known before becoming a public speaker and so on and so forth. And today, I want to start actually, Katie, since prior to the founding of trust insights, public speaking was not something that you really entertained as, as something that was going to be a part of your career. But being the CEO of the company, there’s a certain amount of public exposure and things that comes with the job. So share your experiences thus far about becoming a public speaker. Particularly since your first foray was to a sold out room of 1000 people.

Katie Robbert

so far has been positive. I’m fortunate to be in a company with two really seasoned public speaker. So I’ve been able to learn a lot from both you and john. And the thing that I probably naively misunderstood is how much work actually goes into preparing for talking in public even if it’s something that you know really well and can recite in your sleep. So I think that for me, was the biggest lesson learned was the amount of preparation. So for example, you and john pretty much put me on a regimented schedule, almost like a boot camp to prepare me for speaking at inbound last year, where every Friday at 11am I had to run through it with you and I knew for myself I had to have improved from the week before because otherwise I’m just wasting your time. And I think the other really helpful thing was sort of doing that mock roleplaying Have you guys pretended to be audience members asking questions and throwing me curveballs so that I wouldn’t stumble on stage as I’m trying to think through. Okay, what kinds of answers sound intelligent, so it’s public speaking is really difficult. I think the thing for people to keep in mind is that people make a full time job out of it. And it is a lot of work, it is not easy, even if it comes naturally to you. There’s still a lot of work and practice and preparation that goes into it. And, you know, I guess I would pose this question to you, as someone who’s been doing it for a long time, what is your experience when you started versus now when I started, I was terrible.

Christopher Penn

In this audio recording from the MinneAnalytics MinneFRAMA finance conference, listen as Trust Insights co-founder delivers a technical talk on the applications of AI for marketing.

Watch the talk here.

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Good afternoon, everyone. I appreciate the fact that this is really sort of like the the food coma slash my coffee. Caffeine ran out of my bloodstream an hour ago. slot. So we’ll try and keep this interesting. Before we begin. This has been, by the way, I want to give a big hand please, to Graham and to the mini for analytics community, please do yes. And

I love how it is a blend of technical and business. So out of curiosity, how many of you raise your hands, see yourself as a technical user, meaning you write our Python or data or process data? Okay, a few of you. So when we get to some of the techniques, which I’ll be happy to explain at least a little bit about what’s going on behind the scenes so that you get some technical value out of it for everybody else. Just check your text messages during those points. This session is being recorded, the video will be available on the aptly named Where can I get the slides.com. So in about a day and a half, you’ll you’ll be able to get the full video in the slides. The reason we’re here is because we have been asked by our superiors by our stakeholders to deliver three things better, faster, cheaper, as marketers and marketers were nice people. But we’re not especially good at optimizing processes. We’ve been asked for better and in fact, instead of getting better, we’re getting worse. And the reason for it is that we’re being overwhelmed by data. This year, according to IDC, we’re going to generate about 30 zettabytes of data as a civilization. Now out of curiosity, how many people have an idea of how large zettabytes is okay, nobody, nobody has any idea. Here’s why it’s such a ridiculously large number. How many of you watch Netflix? Okay, cool. So like everybody,

if you look at a Netflix film an hour is a gigabyte, give or take, if you start watching Netflix and binge watch, I mean, no stopping binge watch started 55 million years ago in the EEOC era, you would just get through one zettabytes today, right? That’s how much zettabytes is we’re creating 30 of these fun fact in about five years, we’re going to be creating about hundred 20, just from our devices, all these little things that we’ve got connected to us and wires sticking out of us all over and sensors, we’re gonna be creating a massive amount of data. And the data we’re generating isn’t necessarily good. How many of you have this person in your CRM,

right?

So our data isn’t great. So can we deliver on better? Well, our CMOS say, No, in fact, the number of CMOS, the percentage of CMOS using marketing analytics for decision making has declined to about 35% year over year this is from cmo survey.org By the way, which if you have not tried it out, it’s a fantastic survey of what CMOS think basically the think that we’re full of crap.

Well, think about it, how much are you spending on analytics. And then to find out that two thirds of it basically is thrown o