Data-Driven Marketing

There is just so much data out there, how do you use it to its maximum potential to target your customers and prospects? In this episode, host Will Francis chats with email marketing expert Karen Talavera about how to get a handle on all this data to flesh out your personas, and essentially understand the people behind the numbers.

(recorded June 2020)

Episode Transcript

Will: Welcome to "Ahead of the Game," a podcast brought to you by the Digital Marketing Institute, giving you insights from industry experts to supercharge your marketing skills. Today, it's the modern mindset, where we explore those soft skills that are so vital to developing your career. And this episode is all about data-driven marketing. I'm Will Francis, and I'll be talking to Karen Talavera, a digital marketing specialist based in South Florida in the United States. Karen runs Synchronicity Marketing, a data-driven digital marketing consultancy, meaning that data is at the heart of how she operates. She's recognized as a global expert in email marketing, digital strategy, and optimization, having worked with some of America's most recognized brands, delivering marketing strategy and performance improvements. Karen, welcome to the podcast.

[00:00:51]

Karen: Hey, thanks Will, great to be here. Thanks for having me on.

[00:00:53]

Will: It's an absolute pleasure. Can't wait to chat to you about this very timely and important topic. You talk about data-driven marketing quite a lot. Can you encapsulate in a nutshell for our listeners what that means to you?

[00:01:08]

Karen: Well, to me, data-driven marketing means understanding what you know about your customers and your target audience; some of them might not be customers, they might be prospects. And using known insights to make decisions about what message to send, what channels to send it in, when to send it, and what will motivate those target audiences to do business with your brand. So, it's not based on personality. It's not personality-driven marketing. It's not mass media impression-based marketing. It is literally targeted, you know, usually behaviorally insight-driven marketing. And I would argue that these days, well, this term data-driven marketing has historically been reserved for what's been called direct response marketing. Every channel is data-driven, because we have more and more data, and because we have more of a basis in technology to be able to make these marketing decisions.

[00:02:21]

Will: So it sounds to me like yeah, it's trying to really make better-informed decisions, and really get to the heart of what it is that motivates people to do the thing that you want them to do to benefit your business, which sounds obvious, but you know, I just wanted to kind of hear you say it really. Okay, so thinking about data, something we talk about a lot in marketing, but how do we differentiate between data for the sake of it and actionable insights?

[00:02:51]

Karen: Well, there's so much data out there. Part of how we do that is—this is where historical data-driven marketing has been really powerful­­—is we try to learn more things about our customers. I'll just use the term customers. But again, it could be prospects, it could be whatever target audience. We try to learn more things about people and households than they may have told us themselves. So, you know, we go to third-party data companies to learn about the gender or the composition of a household, the age of a person, the income level of a household, the education level of a person. Maybe we want to flash out geographic information, you know, like, we know what state they live in: for example, in the U.S., but we don't know the exact Metropolitan center. If we know those things about them, we're going to be able to infer other things about them that can allow us to create better offers and better messaging. So, we have all of this sort of demographic and psychographic data that's floating around that can be upended to databases and modeled and analyzed. So, we get these really specific pictures of people, of who they are, we get these profiles; even better, we get personas, which let us understand, you know, the motivations of why people buy and they create these different portraits of people, so to speak.

[00:04:19]

But then we have response data. And again, in traditional direct response marketing, we looked at how people responded to our efforts, we actually couldn't measure that. And we can certainly do that in all of our digital channels today. We can measure if somebody opened an email, we can measure if somebody clicked on a display ad, we can measure if somebody commented on a social media post, you know, if they bought something in a mobile app. So that response data is extremely telling, while some of the demographic and psychic data can be very effectively predictive. The response data is actual behavior and, you know, a big mantra of data-driven marketing is ‘past behavior predicts future behavior, and is one of the best predictors of future behavior’. So how do we differentiate between data for the sake of it and actionable insights is, we don't just accumulate data without any purpose for using it. We want the data that's going to be predictive. We want to be able to know, for example, how many times a customer purchased from us over the last year. And how much they spent each time and how frequently they did so because we can act on that. We can say, "Hey, I've got somebody who's a frequent buyer, but they never spend more than $50." And what's the insight that I can get from that? I'm gonna make them an offer that gets them into a higher average spend, a higher average sale amount. Or I've got somebody who buys once a year, and it seems to be during the holidays, how am I gonna act on that? I am going to give them compelling offers and reasons to come back throughout the year and make them offers they can't refuse so they become a more frequent buyer.

[00:06:13]

Will: I see, that's a good way of breaking it down. It’s the initial customer data, which is your kind of sketch, isn't it? It's an initial sketch, as your starting point. And it's only really when you get that behavioral data that it gets more granular and more usable. You touched on personas as well, do you think those are still relevant and very important in digital marketing to create these kinds of fictional personas that typify the key person types that make up your audience?

[00:06:41]

Karen: I do. I think personas are so interesting because profiles are sort of, like, you think of how there are criminal profilers out there and they know these specific attributes about people or characteristics about them. They know, you know, maybe somebody's a certain height or a certain age or a certain hair color. And we also know that about our customers, we know they live here, and you know they have three kids, and they're married or they're this old. But that doesn't tell us anything about their personalities and their motivation. So personas go beyond profiles, and they get us into behaviors and psychology, a little bit more. And when we know that about people, we can make better predictions, because we can know things, like, they are early adopters, for example, of technology. And if I'm going to release, you know, the next smartphone, if I'm Apple, and I've got my annual release date coming up in September, and I have a great persona, segmentation of my buyers, then I know who those people are that every time I release the new phone, they're just gonna jump. They might have just bought the last one the previous year, but they're gonna take it. And you're gonna maybe make a different offer to those folks than the ones who haven't upgraded in five years because maybe they're more like technology resistors. Or they're gonna use their phone until the thing absolutely dies on them. And then they're gonna have to upgrade. So when we know that behavioral level, that kind of psychological level of insight about people, we can make better decisions about who to market to and make our communications more relevant. And then we don't do things like just flood the market with throwaway offers, we don't erode bottom line and we don't batch and blast to people unnecessarily.

[00:08:35]

Will: Yeah, absolutely. I mean, in my work, I advocate personas all the time and tell people about personas all the time. It's amazing how many people in marketing don't use personas, because all the courses and, you know, the books about marketing, talk about the benefits. I'm not quite sure I haven't quite got to the bottom of why that is. I think it's never the most important thing to do today, I think, it takes a bit of time away from the daily grind to actually go and create those. But, you know, I once came across a company here in the UK that they'd actually printed out life-size cutout people and had them in the boardroom so that when they're having a meeting, they'd say, "Yeah, but would Jane like this?" You know, and they'd have Jane there as a cardboard cutout in the meeting room. I think it feels a bit silly to some people. But I think it's really effective because I think it really makes you sense-check just down to a basic, you know, point; like, is this creative, right for that person? Is this something that she really wants in her life? You know, it gets to sense-check the proposition, the creative, the offer, the way that it's talked about, absolutely everything about a campaign or a piece of content but still so underutilized, I think, which is a shame.

[00:09:53]

Karen: I would agree with you. I love that example of the life-size cutouts. That's exactly how brands and marketers need to think about personas, you know, there's a person behind these sort of, you know, caricatures, if you will, or enhanced caricatures of people that we create. And, you know, understanding the person and not just a constellation of characteristics about the person is really key, but you're right, it's an investment. It's gonna take some time. It's probably gonna take some, you know, focus grouping, primary market research, somebody has to talk to the customers to really distill and understand from a motivational standpoint, how they are making decisions. And then we have to look at the journey, we have to be able to map the journey. So, these different, you know, personas will usually have...they will go about their journey very differently. They will have different journeys, some will have very short journeys, some will have longer journeys, some will have very twisty winding road types of journeys. And if we have good measurement systems in place to track engagement, and understand how people are making these customer journeys, we can map the journey, but that in itself is another investment, you know, that a lot of marketers are just starting to really make more and more. But yeah, it's not easy work, you know, it truly is going to take a certain level of sophistication and resource and readiness for brands to do that. Big brands, of course, earlier adopters of all of this are making that investment and shining the light for those that are kind of mid-market or small business.

[00:11:42]

Will: Well, that's true. And I mean, it's like all this stuff like I said, it's kind of, it's something you can only really do when there aren't more urgent things. Now, bigger brands have whole departments, people in agencies, whose brief is to do data analysis. Smaller companies, you know, there's never a right time to take time out and really go and gather the data you've got and make it useful. That takes time. And so I suppose I'd love to hear if you've got any tips on taking the data you've got, and reporting it either up into the organization or to clients, what would be your top tips on doing that?

[00:12:24]

Karen: First, define what people love to call—and I'm fine with this term, you know—KPIs, key performance indicators, right? So, usually, you're going to want to create a dashboard of what really matters to the organization. And that's based on what the goals and objectives are for the business. Is it retaining the customers that the business already has? Is it getting new customers? Is a growing average customer spend, or share of wallet? It's probably a blend of a lot of those different things in different priorities for different businesses. So, you know, if a huge initiative and like, I've got a client right now who's basically launching into an established market, consumer home security systems, there are many established players. Their parent company happens to be a well-known name, you know, in a related business. So, they have some entry point considerations. The whole sector is not new, they're gonna have to take market share away from competitors, but they are clearly in growth mode. And a lot of growth marketers, you know, big metrics for them are going to be just rate of adoption, acquisition of new customers. They're gonna worry about retaining customers and getting renewals and all of that down the road.

[00:13:47]

Whereas for somebody in a very established business, it might be especially, you know, as we're doing this right now, we're a couple of months past the coronavirus pandemic, you know, affecting the world. A lot of people are really worried about retaining the customers they have and they're doubling down, they're tripling down, you know, on how do I ensure the long-term survival of my business? And it's gonna mean, keeping the customers I have so I can stay in business to fuel my engines for getting new customers and continually filling my pipeline down the road. But, you know, priority one is, I have to get people to buy from me now, or I'm gonna go under. And that means looking at things like recency, frequency, and monetary amount of existing customer, purchases of customer inactivation rates, meaning, you know, when's the last time somebody bought? And when are we gonna consider them inactive? And what are we gonna do to reactivate them? So, you know, if we have the piece of data of wow, you know, someone's defecting, it's been 12 months since the purchase and they usually buy once a quarter. Now, we can act on it. And that's kind of stuff that needs to be collected and magnified, you know, escalated up to decision-makers and key leadership in an organization or clients in the case of an agency.

[00:15:19]

Will: Yeah. And, you know, of all the decisions a marketer has to make, whether it be strategic, tactical, creative, budgetary, what sort of marketing decisions do you think are best informed by data?

[00:15:36]

Karen: I think those are the decisions around messaging and offer. Meaning, so let's break down messaging, what channels do I go out in? Whether it's everything from mass media—like, television or billboard or print—to email, social, digital, you know, very microchannels. What do I say in those messages? And then what do I do to get, you know, people to engage with me? To purchase or to download or do whatever that conversion action is. You know, to me, conversion is this word for getting people to complete a call to action. You're inviting them to do something, even if it's just, visit a website, in the first place, and then once they get there, you're inviting them to do something else, which might be, sign up for email, and then you might be inviting them to purchase. So getting them to convert is key. And all the data that we have can be used for so many different things. But, you know, if we just look at how people tend to find us, that allows us to decide what channels we should be investing in and how much, you know. And then if we know the channel mix, we can figure out what messages are gonna work best in which channels. And then if we know where our messaging is leading, you know, is going, and what we're saying in these different channels, then we know where to make offers, and what offers are gonna work best. Because aside from all of that, you could try to make product decisions off of marketing data, you could try to make sales decisions off of marketing data, there's a lot that's possible. But I think what's best informed by data is where to message, what the channel mix is, and what the offers are to get people to convert.

[00:17:36]

Will: What to say and where to say it. And those are the things that you can infinitely test aren’t they? They're the things that you can't...it's not that you can just A/B test them, it's A to Z through many times over again. You know, so you can really get quite...become quite accurate in a very granular and nuanced way about what to say to whom and where. And you're right, I think there's some good gains to be there. It's probably where the biggest gains are, certainly have been in my experience. And so, I hate to put you on the spot but I have to ask you, can you remember an occasion in your career where the right use of data of some sort saved the day?

[00:18:20]

Karen: Yeah (coughs), I can think of this more in a general than a very specific example. But I saw this with a consumer beauty brand business, multiple brands under one umbrella. They had huge customer bases, international. Certainly very strong in the U.S. where I'm based, both retail and direct-to-consumer so they had retail distribution, and you could buy off the websites. What happens, you know, for a lot of brands that are in that kind of space, there's tons of them, is that they start eroding margin by doing too many discounts. They start doing heavy promotional discounts off the website, or these get communicated through email or I mean, some of them even still have catalogs or in-store or direct mail. And it will be, you know, 15% off, 20% off for friends and family sales. And so they're giving away margin through the discounts, but they're getting a lot more people to buy. And yet, you still have to look at the bottom line, how much revenue is coming in, because there's a tradeoff between a lower average order value that you're gonna get through discounting and an increase in the sheer number of sales. And, you know, if you're only getting more buyers then when you're giving away margin and you have to keep giving away margin to keep getting them to buy, you actually get to a point of diminishing returns over time. So, I've seen certain brands, I'm trying to think of some off the top of my head. I know there was one that was like a child's furniture retailer that never do price discounts or price promotions. You know, they will promote, they will do things like, you know, seasonal sale, they'll put all kinds of different theming and wrapping around a promotion, or they'll promote a particular product category, but they won't discount.

[00:20:33]

Will: Why, what do you think drives that? Do you think there's a database decision behind that?

[00:20:36]

Karen: Well, they...Yeah, they do what's called, and this is classic, you know, B2C marketing, and RFM analysis. So, RFM stands for recency, frequency, and monetary amount of a sale. So, a customer base will be looked at in terms of their purchase behavior. And they'll get segmented into literally—you've got three variables, right, the recency, how recently someone bought, the frequency with which they buy, and how much they spend. And that data will be looked at over, let's say, a 12, or 24 month period. And you can make nine different quadrants with all of that, you know, just to simplify it, you could have like: high recency, low frequency, you know, high monetary, low frequency, what have you. So, if you really map all of that out, you can see that, you know, you might be running into a situation where you can get people to buy more frequently, but again, only at lower price points. And then you condition them to waiting for a sale and eventually erode the revenue coming into the business to the point where your revenue isn't growing. You know, your customers might be buying more often, maybe you're even getting more customers, but you're just conditioning them to be sale shoppers, and now you have an uphill battle to try to grow revenue. So, the solution to that, you know, is that you don't constantly price discount, or you reserve that tactic for the people that really deserve it; who are the people that really deserve it? Either your best customers, or, you know, you're gonna reward them from time-to-time, or the folks that hardly ever buy, or there's a holiday coming up and it's worth pushing them. You know, it's worth testing to see if you can get them over the threshold.

[00:22:23]

Will: Yeah, I get that. There are brands that three-emails-in with offers, and I will just never buy from them at full price again. You know, only takes about two or three emails with offers and you go, "Okay, these guys just always have a sale on, I'm never gonna need to buy this stuff at full price."

[00:22:39]

Karen: Yeah.

[00:22:40]

Will: And I'm thinking of a brand in particular that sends me emails at the moment and I don't think they know that. Or, you know, I don't know, they seem to be giving all their margin away. It's a good point.

[00:22:50]

Will: Hello, a quick reminder for me that if you're enjoying our podcast series, why not become a member of the DMI, so that you can enjoy loads more content from webinars and case studies, the toolkit and more real-life insights from the world of digital marketing? Head to digitalmarketinginstitute.com/aheadofthegame, sign up for free. And now back to the podcast.

[00:23:14]

You've clearly got a data-driven approach to marketing. Where does that leave creativity and intuition in the mix of creating campaigns?

[00:23:25]

Karen: Data can be a great asset in informing creative. So back to profiles and personas, you know, now I'm imagining, you know, a client's or I'm imagining a brand's customers as cardboard cutouts, you know, these different people, these different personas. Well, you know, we need to move away from the one-size-fits-all creative strategy. And most of our digital channels allow us to dynamically version and dynamically customize different creative treatments for these different audience segments or personas. Even if we can't get segmentation down to a level of persona, we can do simple geographic segmentation on everything from display advertising to social media ads, to email, we could probably segment on gender. So, you know, are you going to serve the same display ad to everybody in a retargeting situation who visited the website, if you know something about them that lets you customize it? Hopefully, you're gonna customize. This happens in email all the time. And there are some really great tech enablement platforms that allow marketers to establish a content library. Let's say it's an airline, right? And promote different routes or different vacation packages to people that live in different places at different times of the year. And to dynamically assemble content into, you know, an email campaign that gets sent out and looks very different for you, Will, you know, in Ireland than me living near Miami. Because maybe you wanna come to Miami, but I'm already here and I don't wanna go to Orlando either. I wanna go to Europe, I wanna go to California, I wanna go somewhere else. So, now, we can actually dynamically version our creative based on data that we know about people. That's pretty cool.

[00:25:30]

Will: But do you think there's a danger? I suppose what I'm getting at is do you think there's a danger that we can, you know, be informed by the data? And rightly so because, obviously, that's one of the main bonuses of being in digital marketing, that we have access to all this data. But that we can maybe not allow intuition or not allow creative risk into the process, which I would argue is what has led to, you know, the best ad advertising campaigns of all time, all have a really healthy dose of art as well as being informed by the science?

[00:26:06]

Karen: I think we can get overly analytical. So, data is a great signal to have. And some of it can directly inform, especially in testing situations, which offer or which headline or which subject line is going to perform better, but we can't lose our humanity. We can't lose that insight into the marketplace that a lot of agency work and a lot of, you know, the branding side of marketing is very good at. It's tapping into the hearts and minds of the customer, the essence of what they really want. We can't rely solely on data, on let's say website behavior, you know, or purchase behavior to tell us what's in the hearts and minds of people. That data is gonna tell us what they do on the website, what they tend to buy, but we also have to go beyond that and get into the why: why do they do what they do? And a lot of times when we know the why, that's what fuels those great creative campaigns, you know, or the personality of a brand. Whether it's a new, you know, a Disney thing that's happening, you know, tapping into maybe they've identified like a need for people to connect as a family. And that's gonna be, you know, the underlying motivation around the marketing and it's going to inform some of the creative, but then tactically how they execute that might rely a little bit more on some of the data we've been talking about.

[00:27:41]

Will: Yeah, no, absolutely. Okay, so I have to ask you, what apps, sites or services are in your kind of go-to toolbox, when it comes to gathering, manipulating, and utilizing data in your marketing work?

[00:27:58]

Karen: Well, anything that enables data science for the layperson, I'm definitely a big fan of. So, who are mere civilians out there in marketing. You know, they are people like marketing coordinators, managers, product managers, channel managers, channel specialists. They could have titles like digital marketing specialist, email marketing manager, CRM person, you know, what have you. That they're very good at understanding their channel. They have a specific responsibility and function they need to fulfill. But they're classic marketers, they didn't come up in like, from a stats background, or an analytics background or an IT background where they might actually understand how to manipulate data and do various statistical analysis or types of modeling on data. So, now, thank goodness, we have a lot of tools and platforms that allow the sort of civilian, you know, the classic marketer who has to work with data these days to not have to rely on the IT department or not have to hire a data scientist to actually get some stuff done. And some of those are the CDP platforms out there. Customer Data Platforms, like everything from AgilOne to Tealium, to the big marketing clouds, all have one, Oracle, IBMs, Salesforce. They've got a lot of built-in, enabled, you know, features and functions for somebody once data is in the platform to be able to run different types of analyses without knowing how to do that, say, off of raw data in an Excel spreadsheet, or in another platform.

[00:29:52]

Other ones that come to mind for me are...they can be CDPs in their own right or they can just layer on top of a CDP. Or they're good for smaller businesses that are basically just data analysis software, like, QuickPivot is the name that works worldwide with smaller and larger retailers, mostly. And, you know, we're talking about retailers a lot, because they have a lot of data, they have a lot of purchase data, but it could be the travel sector. It could be growth marketers like mobile app companies, QuickPivot, RedPoint Global, those are a couple that are out there. And then sometimes even the marketing execution platforms themselves like different, you know, email marketing platforms or omnichannel marketing platforms have some built-in stuff.

[00:30:39]

Will: Yeah, absolutely. Okay, so, if someone's listening to this, and they're starting to think, right, you know, Karen knows an awful lot about data and I need to really up my game in this respect, you know, and become far more data-driven as a marketer. What can they do immediately after listening to this podcast, when the credits roll, in practical terms to do just that to go and really up their game in data-driven marketing?

[00:31:12]

Karen: Well, it's a bit of a tricky question, because they're all gonna be starting from different...they're all gonna be beginning from different start points. And so, you know, I could recommend something that might be great for enterprise marketers who already have a CDP where the smaller business is gonna say, "Oh, my, gosh, what are you talking about," or, "I can never invest in that." So, to make it a little more universal, I guess my recommendation would be the number one thing that could be done if it isn't already being done is to connect purchase data to any marketing data you have, and even sales data. And what do I mean by marketing and sales data? That's the stuff like, "How did my last email campaign perform?" That's coming out of an email services provider, the platform where you send your email. That's "how did my last social campaign perform. Who responded? Who opened? Who clicked? Sales data", maybe the Salesforce is actually using a platform like Salesforce to manage all their leads and prospects and customers. And you can see the record of the last time somebody was called or the last time, you know, there was an outreach by the salesperson. But purchase data is again that, you know, recency, frequency, monetary, what did somebody buy? How often? What's the last time? How much did they spend? Often for manufacturers or retailers down to the physical product level—the skew level, as they'll call it—so we got to get that purchase data, that core purchase data, connected to marketing data.

[00:33:04]

Will: I know you're saying because we can split that audience those nine ways is that what you're talking about and putting people on a nine-block matrix?

[00 :33:11]

Karen: That's part of it, but also so we can do attribution, which is figuring out which marketing channels are actually driving sales and which ones should get the credit. Because the ones that get the credit and attributions, you know, that's a sticky wicket as well. Or, you know, it's a tangled web, you could say, because most companies trying to do good marketing channel attribution, find that there isn't a simple model that can give credit just to one channel. Usually, multiple channels are working in cohesion and are getting, in reality, partial credit for creating a sale. You know, as an example, somebody might have seen a display ad, visited the website, downloaded a white paper connected on social media, and then got an email, which finally prompted them to purchase or set up a sales appointment, you know, whether it's B2C or B2B. So, do you give all the credit to the email that pushed the person over the line to conversion? Not necessarily, but at least if you know that all of those marketing channels you're using are driving some kind of action and you could connect it ultimately to a purchase, you are not operating in the dark.

[00:34:20]

Will: That's a very good point, actually. And you did touch on that before. It's all these consumer buying journeys are messy and I do come across the attitude in digital marketing sometimes that, you know, it's all very neat. And you know, people see an ad they go and buy something that's kind of the end of the story. And that would be lovely if that was the reality and I can see why some people are attracted to that as a story. But the reality is that people can take, even for small purchases, I'm talking $20 purchases, people can take a year to think about that because they're switching over from a moisturizer, you know, that perfectly happy with. But they've heard that this other one's really good. And, you know, it takes time for them to read a blog post here, see some PR there, see some outdoor there or social posts and email. I mean, it could be ten different touchpoints before they actually go and purchase and I think that's a far more realistic picture. So, the point about attribution is really important. I think that's maybe the next step, isn't it, for anybody going away from this is to kind of really think about attribution. Think about the credit that you're given to your different channels. And then how you don't just give the credit for each person to one channel. I mean, I have to throw that on to you because I'm not sure what is the best approach for doing that? You know, let's say I'm seeing email drive 80% of my actual purchases, but I know or I intuitively feel that my other channels are working quite hard and getting quite a lot of exposure and engagement too. So, how do I measure ROI in that way?

[00:36:01]

Karen: Yeah, that's a challenge of understanding the partial weight of the different channels. So a lot of very effective and successful attribution models are partial weight models. And some of them are even weight where all the channels get equal credit. Some of them are, you know, the first touch channel of the first touchpoint gets the most credit or, you know, they call first click last click or the last channel. So, unless you're a DTC marketer, direct-to-consumer only using one channel, there will always be influencing channels and, you know, more direct sales channels. One of the only ways to figure out really, you know, how much weight each of those should get is, do a suppression test, you know. So, let's say you're running display ads, you're on social, you're doing email. You know, you are a consumer brand, people are mostly buying online. You know, take a percentage of your audience or of your list and stop hitting them with display ads, you know, and just let the rest of your efforts carry the day and then see, did they purchase less?

[00:37:20]

Will: That's a great idea.

[00:37:21]

Karen: You know, see what their buying behavior looks like compared to people that got all the treatments. So that is what happens, you know, a lot in the real world is, you know, we've had this big upward trajectory of growth in digital channels, new digital channels being introduced all the way from, you know, 2004 or 2005 to the present day. There's always some new platform, everybody was just hopping on board, hopping on board and saying, "I cannot be there. I can't be absent from some of these. I need to have a presence because, you know, my absence means a loss of...you know, my absence will be noticed, first of all, and loss of market share against competition and all of that." So, I think there's a lot of FOMO, there was a lot of I just have to get on board and do everything. So, my absence will not impact me.

[00:38:17]

Well, now that we've been out there for a while the real question is, "Do I really have to be on everything?" You know, where is my audience? What if it's on Pinterest and not on Instagram? What if it's on Instagram and not on Facebook? So, marketers are getting a lot smarter about testing and being less fearful of not participating in a certain channel, especially when it comes to social. You know, email has been around since the beginning. It was the first digital marketing channel. It's very direct. It's extremely one to one. It's private and that way it's very different from social. It has long been the workhorse of data-driven marketing. It is the evolution of historic, you know, offline analog direct response marketing, which was also usually data-driven. So that's probably gonna work forever. You know, I wouldn't recommend a brand not doing email marketing, but they might want to take a look at their overall investment in search, display, you know, paid search particular and social as well as maybe mobile to see do they need absolutely everything? Do they need to be everywhere? And if they need to be there, then what should they be doing? Like, what really makes sense? Is it just engaging people with the brand in fun and interesting ways and more of a dialogue and a discussion versus a sales conversation?

[00:39:43]

Will: Yeah, that's good to hear. Because I think that you know, a common frustration I come across particularly from people who are social media managers is that they get a lot of flack, I think, internally or they are challenged internally by their, you know, seniors, that social isn't driving enough sales. Or they might be managers of another channel as well like search, for instance, it's just not driving sales. But that's because on paper from a very blunt reading of the numbers that no, it's not. But I think we need to find new ways of showing and proving that, like, you talked about influencing channels, I think that's really important. It's just a really important part of the conversation to be had, you know, that you can't... I think it was perhaps a fallacy in the early days of social, particularly, that it was this free marketing channel and had some sort of magic touch you could just convert people. But, you know, much like investing in your store, having nice windows and furniture, you can't attribute sales to that either, but of course it's all part of what influences people to go and make that sale. So it's interesting to hear you talk about that.

[00:40:58]

Karen: I couldn't agree with you more. I think there was an early fallacy that social would be a free lunch, you know, as far as revenue. You know what they say about free lunches, right? There aren't any. However, I am a huge advocate of organic social, so I do think a lot of brands need to be there so they can collaborate and build community with their customers. And we're talking non-paid social, you know, so they need to be listening, and they probably need to be speaking, and their customers are there and maybe do wanna talk to them. So they might wanna talk to them, but they might not wanna buy from them in that context. So, certainly, in my point of view, social is not and never was meant to be a sales channel. It can be, it's not a primary sales channel. You know, when I watch anything on YouTube these days and, you know, I'll freely admit, I don't have a paid subscription so I know I can get rid of all the ads and all that if I did. I mean, it's become a huge ad channel. Incredible. You know, and there's kind of a nuisance factor to that. But I know my focus group of one when I'm watching something on YouTube, I am usually not in a buying context at all. I'm not looking for anything, I'm not watching a video that's gonna help me make a buying decision. I'm kind of irritated. And yet, you know, I still, if the targeting is good, I might actually, you know, I might watch an ad I might click through to something, but it's probably 1 out of 20 at best.

[00:42:43]

So we kind of adjust our own expectations, and our own mindset about some of these channels. And still yeah, be there organically, to listen and to speak and to build community on social. But I would not advise brands to expect it to be a sales channel. And if there, you know, if those marketers responsible are getting pressure from management, then sometimes they have the responsibility of pushing back and educating. Or saying, "Yeah, we can sell more, but it's gonna take this much investment in content," you know, generation, or creating videos or, you know, content creation, even for like Instagram, Pinterest, you know, what about Snapchat? We haven't talked about that. What about TikTok? Who is gonna create all of this content that needs to be there for those channels to be effective? It's gonna cost money.

[00:43:44]

Will: Indeed, it is. Well, thanks, Karen. That's been a very insightful conversation. I feel like I've learned a lot. And there's lots of good tips in there for people who do want to become more data-driven and smarter and more efficient in the way that they direct their marketing efforts. So, thanks for that. Just tell our listeners where they can find you online.

[00:44:07]

Karen: Oh, thanks, Will. I'm at synchronicitymarketing.com. So, head there or follow me on social, I'm most active on Twitter, LinkedIn, and Facebook.

[00:44:18]

Will: Great stuff. Thank you so much, Karen.

[00:44:21]

Karen: Thanks, Will, it's been great. Have a good one.

[00:44:23]

Will: See you

[00:44:24]

Karen: Thanks.

[00:44:25]

Will: If you enjoyed this episode, subscribe wherever you get your podcasts. And for more information about transforming your marketing career through certified online training, head to digitalmarketinginstitute.com. Thanks for listening.