SOLVING YOUR ONE TIME BUYER PROBLEM

Key Takeaways:

  1. The first step in new customer acquisition is to learn. It is not enough to just have a database. You need to really dig deep and learn about your customer base.
  2. The second step is targeting. You need to decide the who, what, and how you are are going to target.
  3. When it comes to retention the first statement is, don’t get into the mode that you feel like you are compelled to talk to your buyers all the time. You’re not personalizing. Your personally annoying people.
  4. The second is just because somebody is a recent buyer, don’t bombard them with catalogs and e-mails just because they came back.
  5. Finally, do not train your valuable customers to not open your emails. Less is more when dealing with your most valuable customers.

What follows is a lightly edited transcript of Episode 17 of the Inevitable Success Podcast with Damian Bergamaschi and special guest Stephen H. Yu. (Listen Here)

Transcript

Damian Welcome to the Inevitable Success Podcast sponsored by BuyerGenomics where our goal is to help you, the marketer, make success inevitable. Each episode will discuss the craft of data-driven marketing, helping you uncover new and profitable ideas. You will also learn what works and what doesn’t work from top marketing professionals and thought leaders. I’m your host Damian Bergamaschi, and inevitable success starts here.

So today we’re going to talk a little bit about the one-time-buyer also known as lots of different names. The one-and-done customers that permeate almost every retailer’s database. And you describe it as a major challenge to retailers. So, why don’t you kick it off and tell us a little bit about what it is and how people are addressing this?

Stephen Yu Yes, well first step is to recognize what kind of problem this is. And I say that a lot of people don’t even know how many of their customers are in that category, and that’s a problem. And people talk about clicks, clickies, e-mails… Those are not customers. You are really not tracking on a customer level who’s really coming back and not coming back. So if I ask any retailer, “Do you even know how many people have been active in the past 12 months?” They go like, “Mmmm, about 100,000-ish,” but that’s not even an answer. So you really have to size up the other problem. And then let’s talk about why that is a problem because we all know that acquisition comes with money.

You cannot just open up a store and wait for customers to show up, and hope to God that that’s okay. No matter what kind of a channel you employ, you’re talking about a good sum of money to acquire even one customer. If they just buy once and disappear, you just cannot make money off that guy.

So let’s talk about typical size of this problem, and we’ve been helping out a lot of retailers. And on a good side, I’ve seen one-time-buyer under and around 65 percent of the base. Now, if that’s a good number, that’s a little scary. Then how bad can it be? It can be really bad. I’ve seen upwards of 80+ percentage of the customers are one-and-dones. Now that’s a real problem because that puts pressure on the business because –basically you have to fight the war on two fronts. You have to maintain your customer base so that they don’t leave after purchasing just once.

The second part is that you keep bleeding. It’s like pouring water into a bottomless bucket, basically. Imagine your water goes out 80 percent of the time, and you have to keep pumping that in, and your acquisition costs will just go up.

Damian Right it’s very hard to grow the business…yeah.

Stephen Yu Exactly, just very hard. And, people do desperate things like- let me just blast e-mails. I’ve seen a retailer… this is a real retailer, but I will not name names, but it’s a reputable retailer. They sell teenage apparel in pretty much in all 50 states. These guys blast 14 e-mails per person, per week. Now, you may think that that’s a lot, but not when you’re desperate. (laughs)

Damian Right

Stephen Yu Your click rate is going down. Trying everything, and people are not coming back. And by the way, their retention rate is not bad. It’s over 70 percent that come back. But can you imagine a retailer with more than 80 percent customer not returning? They’re really pumping a lot of money into this acquisition problem, if you will, but with not enough return.

So a lot of symptoms that I hear, are things like “Well if I mail something, I have to break even the first time.” Like hmm, why is that? Because direct mail costs a lot more money than say e-mail. It’s hard to break even. We do it because you want to expand the universe, and then you have another CRM plan to really milk those customers. But statements like that come out of desperation. Like, I have to make money the first time because I know most of these guys don’t come back. But, I’m like, “That’s the wrong way to think about it.”

So I would say, in summary, yes. Size up the problem, because you cannot just say oh I have that problem. You’ve got to know how big of a problem that is, which will lead to the next step. Well that means you have to have a really true customer 360 database of sort. If you don’t have that, you don’t even know how many customers are really not coming back.

Damian You just made me think of something. So somebody bought one time…

Stephen Yu Yes.

Damian At what time do you say they’re a one-time-buyer? And hear me out because if somebody just buys today, well I don’t really expect them to have a second purchase just yet, right? I’m grateful I just got a first sale. So how do you think about it when you say, alright this is now a one time buyer?

Stephen Yu That is a really good question. Because the answer is “It depends.”

A lot of people don’t like “It depends.” It depends on a lot of things. So what we look at is the non-one-time buyers. I want to have all of the data decide this for you. Don’t draw some arbitrary line like, oh if they have not done anything in 12 months, they’re one-and-gone. What if you’re selling furniture? What if you’re selling cars? You’re not going to buy a new car every year or even a bedroom set. You’re not going to buy that every year. What if you’re selling some really expensive bed set? You’re not going to buy that every year. If you’re selling children’s apparel, yoga pants, or t-shirts, well, in that case, if you wait 12 months, you’re late.

Damian Right.

Stephen Yu So it depends. How do we measure these things? That’s a good question. One is: we look for the non-one-and-gone people. We look at average days between transactions. That’ll give you some idea. And also we look at number of transactions per customer for different time windows, starting with a life to date by the way. So in one year, maybe the average is like 1.2 or 1.3 for the lifetime of the database. And a lot of folks started doing this not too long ago. Let’s say you have a four year history, and the number could be upwards of 1.6, 1.8, maybe 2._ something. That’s a good number.

Point is, you have to really look at your business and look at the data to determine what is gone, it’s gone. So that buyer life cycle that we talk about, it cannot be just one rule for everybody. It doesn’t work that way. It means that you have to look at your data and look at the intervals on a customer level, not some arbitrary, “Yeah it seems like a lot of clicks in there.” That doesn’t tell you anything about how many transactions per customer, per year, per two year, per 48 months. It doesn’t tell you nothing. So basically that’s what you have to do to determine who’s gone.

Damian We have to have either like a magical way to acquire new customers at a very low price or a magical way to keep your customers so you can monetize them over time. Most businesses probably have some kind of in-between state. When you think about customer acquisition, is there something that you could kind of, –knowing that this is the ability to get repeat customers, is there something we should be thinking about?

Stephen Yu Yeah, customer acquisition is not easy because all these profiles, segments, modeling, all those things- The premise of that kind of acquisition tactic is that I want to mimic who’s a customer, and I’m going to acquire people or send e-mail or mail to people who look very much like my customer base but who are not my customers yet.

 And there are many ways to do that, but I want to further qualify that targeting because just looking like your customer is not good enough. Let’s talk about who are the best model customers in your base. Let’s mimic those guys. Because in your customer base if you look hard enough, you’ll see all kinds of people. There are bargain-seekers. We call them barnacles sometimes. They drive like 20 miles to get like 10% off once, and they will never come back. I mean, it’s kind of written that he’s going to be a “one-and-gone” anyway. And then there are loyal customers. How do you define loyalty? Many times? What if he shows up and buys $10 stuff many times and that’s that. Well, he’s not a high-value customer now. The value should be measured in dollar per customer or lifetime value or total spending so far, whatever you do…

Damian And even net of returns or something like that.

Stephen Yu Exactly, in other words, do you even know the guy is a “heavy returner” for example, right? So when they go after– oh, these are the look-alikes of my customers– I’ll say, “no.” Study your base first. Now, what that means is that to know and size up the one-time-buyer problem, you have to have a 360 degree view of a customer. To know that for the non-one-and-done people, you have to know what is the average days between transactions for multi-buyers, you’ve got to know that. And what are the models it isn’t? Well, then you’ve got to look at the loyalty, frequency, all that kind of stuff, the value, etc.

Damian I like that, the “model citizen.” It’s almost like a play on words there.

Stephen Yu Well, anyways, so to know who the best guys are, we’re all going back to the fact that you have to define who your customers are. To do that, you cannot do it with some kind of email-based platform. You cannot do this based on just an order fulfillment database. You cannot do this with some kind of email tracking report. You just cannot do it that way. You really have to build what we used to call a “customer database.” People call it a “CRM database,” or “customer database,” or popular terms: a “single view of a customer” or “360 view of a customer.” However you want to call it, it’s all the same thing, but basically you have to do that. Otherwise, you will not even know who to mimic.

Stephen Yu I mean that’s the first step. Once you do that, you should define, OK so I know my buyer’s lifecycle. Maybe I’ll allow he should have done something in the past two years because you sell expensive items, or it could be one year because you sell small-price tchotchke items. And the value should be top echelon of your customer base. What is a study you can only do with a customer database? I’m gonna say, what does the top 10 percent, top 15 percent, top 20 percent spending level look like? Instead of just creating an arbitrary number like, “people who spend more than a thousand dollars.” Well, what if you only have like .1% of your customer base has spent more than a thousand dollars in a 12 month period? You have to do this on a data-based form.

Now, once you know that by the way, there are a lot of ways to acquire new customers. You can create a sample like that, just like that. People who bought more than twice in a past period, or spent the top 10-15 percentile of the spending level, or somebody who had done something recently, whatever it is, now you can share such good customer lists with any acquisition vendor, third party data vendor, could be Facebook, whoever you use to mimic and get more new customers, say you’ve got to really understand what you’re dealing with. You cannot just say, you know, “I’ll just give you a random sample of my customer base, and why don’t you go at it?” Well, guess what? You’re going to attract a lot of barnacles in it too.

Damian You know, when you give it to something like Facebook, Facebook is going to, if you use their look-alike, they’re going to have a little bit of a black box, and they’re going to make their own look-alike. Now, if you could make your ideal, let’s say, what you are looking for. If you were making your model, what are all the degrees in that 360 degree view that are important to you?

Stephen Yu That is a really good question. For example- I think I wrote a column about that too: define what’s best for you. I’ll give you a very simple example like airlines, for example. What is a frequent flyer? It depends. You shouldn’t define frequent fly out of the general population. Not many people even fly once a year. But if you have to define frequent fly in, say, the airline customer file, there are a lot of people who fly every other week. So the definition of “best” changes, and how do you define the best of the best of the best? I’ll say, you know what? When you are in the business of mimicking the potential customers, go after all of it because sometimes the spending level and the frequency of the person coming back are inversely related anyway.

I say go after both because you’re just mimicking the model citizen anyway. Again, modeling through the modeling. And it could be a black box by the way. But there are things you can control. Because, what is modeling? Modeling is nothing but mathematical similarity from group A to group B. You can control what group A looks like. Group B you don’t know because you just gave it to a third party data vendor or- They may be kind enough to show you all the model variables, but do you really care at that point? Or guys like Facebook will not share anything. I mean I’ve seen variables that Facebook normally uses. They list like 98 variables.

Damian Yep.

Stephen Yu And by the way, just for the record, that number looks surprised low because I’ve seen databases with like a thousand variables.

Damian I think they have a lot of inferred data too.

Stephen Yu I think so too. But what’s so amazing though is that you’re talking about every facet of a human behavior: what they are, what do they look like, what they do, what they like, what they click, what they subscribe to, what they bought. I mean they have all those things. So they can blackbox or not. They can build good models. Let’s just assume that. And all the recent Facebook scandal proves the point that it really worked. If it didn’t work, nobody would care. So it works. What you can control is what you give to these guys. It’s like, we want to give just one target? What if that target is wrong? Then you’re done. I’ll say, different enough, but multiple targets, meaning that if you create a target based on value- that’s distinct, right? -if you create a value on recency, that’s distinct, because not all recent buyers become good customers, but you know that they’re in the market for something. So therefore, you’ve got to look at it from a multifaceted way.

I’ll look at it from past behavior like recency and monetary and frequency and all that stuff– and expressed in terms of days between transaction, how many times per customer, all that or dollar per customer, all those behavioral targeting. The other will be regional. Do you have any regional skus? Or do you have any specific target you want to go after? Then that’s regional.

Damian You mean like geography?

Stephen Yu Yeah, geography. In other words, obviously, yeah that they were looking at a lot of new acquisition plans for a New York-based apparel retailers. Well obviously, they have a store in New York and L.A. Guess what? You’re going to have a further sku towards it. So you have to really divide different targets for New York and L.A. where the store presence is real versus all the online-only kind of regions in the country. Now, if you go outside the country, forget it. You’ve got to have a different strategy anyway. The regional target is important. Then there’s a demographic targeting. What if you are bases like ritual people?

And by the way, a lot of customers will say, “Oh, I thought that my customers are younger.” Well, we say to them, you know what? This is what your data tells us. What? Is the old people money not good for you? No. But if you have some desire to get into new market, that means you’re now past the point where you just want to mimic your old customers. You’re getting to new territory. That means, for Facebook or other third party vendors, you are giving them a new universe to play with. In that case, it’s the demographic targeting. So geo, demo, everything really.

So, my idea is to really expand your imagination and just go at it, but don’t overlap too much because at the end of the day if you target like three-times-buyer or four-times-buyer, it may sound different on paper, it’s going to yield very similar results anyway. So don’t get too close, but be more imaginative and expand your horizon in terms of creating those target segments. Again, one more thing is: work with multiple partners because if you just use one method, you’re going to dry that well really soon.

Damian You know, I actually think I first heard this term from you a few years ago. So you made me think about it when you started telling the story about the airline customer.

Stephen Yu Sure.

Damian And the word was, or words that you used was “dual universe.”

Stephen Yu Yes.

Damian So you made me think about- alright, so part of this seems like there’s an order of operations to it. You have a customer database. Now, determine who qualifies as a one-time-buyer versus not. And then after that, it’s like OK, now how can I understand them? And there’s all these degrees that you have that you look about them, but then there’s this other component which is don’t mix universes that aren’t really the same. And, for example, you have a business traveler and somebody that has a family. If you put that universe together, there may be some averaging that kind of cancels out the signal.

Stephen Yu Absolutely.

Damian And I remember you were talking about it…

Stephen Yu I used to call it a phantom target. It’s a very different or distinct, two different segments if you combine them by accident, the average of those two is like nobody. There’s no such thing as average targeting anyway, and that by the way is an airline example if anybody can understand that, but it happens in the apparel business too. For example, there are people who come very infrequently, but when she shows up, she buys a lot. And by the way, I’m one of those guys.

But then there are habitual visitors who just love to shop, admire things in your store, but rarely buy anything. Now, is she a bad customer? No because one day, she’ll buy something because her foot traffic tells us so. That’s why, by the way, people care so much about clicks and browsing history and all that because we hope that such behavior will lead to a purchase one day. But is that a slam dunk? No way. This is why even a basic understanding of how many different and distinct universes you have in your base is the first step, and you cannot do that without a decent buyer-centric database.

Damian A story comes to mind. I don’t know if you remember this or not but I remember you were looking at a database, and the client had sent over all their files. And we were like, “Wow, some people here are really really really valuable, and you kind of isolated it down, and then I think what ended up happening is, we sent over a list of them, and then all the sudden the client was like, “Oh yeah, yeah, those are designers that buy all the time.” And they were like “Oh yeah yeah.” They didn’t think about that, but it came out in the data.

Stephen Yu Exactly. And you’re describing what we call natural course of revelation when you look at the data is that sometimes it’s a confirmation of what you knew already. Sometimes it will reveal something that you never knew. Like, “Oh gee, I didn’t know that I was dealing with triple universes here.” That changes everything from an acquisition point of view as well as a customer care point of view that, you know, if it’s really like a whale who comes in once in a while, and maybe there’s a pattern to it, don’t sendthem seven emails per week. It’s not going to work anyway.

So knowing what you’re dealing with is the first step. So again, dual universe, triple universe, whatever it is, that’s what we call segmentation. And the way we should look at it is, here’s a database, and you’ve got to have that kind of commitment. You’ve got to build a database, and we can help you with that too. Build a database and learn as much as possible. Say what are we dealing with here in terms of their behavior, in terms of every variable that we have, all the recency, monetary, and all that? How many distinct universities do we have? You’ll be quite surprised that you have really multiple people. Sometimes the new customers and the recent customers are similar but could be different. Dormant customers are always the same as tenured customers. For example– Yeah?

Damian I just want to clarify because the nuance of recent and new customers sometimes I feel like confuses people. So, why don’t you just differentiate those two?

Stephen Yu Oh, sure. Recent customers are some people who just did something recently. It could be his fourth purchase.

Damian Right.

Stephen Yu New customer means that they’re really new.

Damian Yeah it’s one of those after you hear it, you’re like, “Oh duh.”

Stephen Yu Yes, but if he uses only one variable called last transaction date and calculates some count of days from last transaction, those two groups will get treated the same way.

Damian Yeah, and that’s such a common thing. I can see it every time.

Stephen Yu Oh, yeah. So look at it multidimensionally, meaning that if you also know the first transaction date, and you know the lifetime purchase amount for that guy, and number of transactions you’ve been counting, you’d know that the guy is a multibuyer, and don’t treat him the same way just because he did something recently. I mean, for example, I know for a fact sometimes I go to my favorite guitar shop and buy some stuff that I don’t really need. Immediately, they look at my recency regardless of what kind of things that I bought in the past.

They start sending me all these catalogues and e-mails and bombard me with all these things. Why? Because my recency flag just went up. And I go like, none of these are customized or catered to what I am looking for if you look at my past history no matter how long ago. Then you would not do this to me. But guess what? They just use one variable. I guess what we’re trying to say is this: you’ve got to really learn the base. That’s the step number one. Two is, –and we talked about some examples of what kind of a segmentation we can do even for a simple acquisition exercise. I didn’t even get into the statistical modeling yet– but the second part is targeting.

It’s like, okay, now I learned about my base. What are we going to target? What do we look like? What channel are we going to use? Are you going to use Facebook? For example, in that case, how many different segments am I going to provide to Facebook? Or if I’m using the third party vendor or co-op database, Co-op databases never build just one model to cover their credibility as well. Because, what if they build one model, and it doesn’t work? They’ll be fired. So they want to build multiple models anyway. So all this segmentation targeting is the step right after the learning part. So learn, target, and guess what?

Now you have to execute. Execution is not easy because now you’re talking about multichannel marketing. You can be deploying all kinds of campaigns through Facebook or social media, or it could be mailing a catalog, postcard, you name it. And e-mail, the most abused channel of all, well just because it’s easy doesn’t mean they could just freely blast things away like those guys that I used as an example. Fourteen times a week per person, I mean that’s just insane. But, you know why they do it? It’s because they didn’t look at the database, and they say- They only looked at one thing though. “Oh my god, my clickthrough rate is going down. So how many more e-mails should I send out to match the old clickthrough count?” Not even a clickthrough rate, all the desperate moves that’s not going to work. But at the end of the day, that’s where the rubber meets the road is when you actually send something a customer can actually see and feel. So that’s the third step.

The fourth step now is, OK, now we did all these things. Let’s figure out what worked. You could call it a backend analysis or post campaign analysis. Some people use fancy terms like attribution, but the definition of attribution could vary quite widely. But the point is, this is what old timers used to call “closed loop marketing.” You do learn, target, execute, and then you see what worked. And then do it again. You’d learn again, basically. That’s closed loop. Now I may scare a lot of retailers who are listening to this. They say, “Oh my God. I don’t even know where to start here.” I’ll say start with learn. We just gave you the steps. Let’s not be too scared about the complexity of this thing and not do anything, because there are steps to this.

Damian Yeah, you know, one of the things that I love the most about doing that first step is, I think, it brings some of the creativity back to the marketer. I think it’s empowering because once you start thinking,- to go back to that airline example, even to the message, the offers, the creatives that you show to that specific universe in your target will be different. The business flyer: you’re not going to show him pictures of Disneyland with families going on vacation. That’s not why he’s buying.

Stephen Yu Learning is fun. One time I was helping out this hotel chain in Europe, and those guys did not capture a lot of things that they should have captured. But the thing about data mining– this is why it’s so fun– like you said, you have to use your imagination too. What if you didn’t catch if that trip was for business or leisure or a little bit of both? I said, you know what? Give us the following: give me the booking time, an actual travel date, and day of the week of the check-in date. Is that weekend or week day, for example? And by the way, the longer the booking period, the leading time is, it’s more likely to be a leisure travel. Business travelers sometimes have to go to London with a week notice. You have to buy your ticket.

Damian Yep. That’s true.

Stephen Yu And party size. Yeah party size or– I mean, if you have to go, you have to go, but you’re not going to do that with your own money, unless you’re filthy rich.

So all these indicators, I’m not saying that we know for sure who is a leisure traveler or not, but this is a game–

Damian It’s probabilistic.

Stephen Yu  Exactly. It’s a game of percentages. If you think somebody is more likely to be a really high-powered sales guy who travels the world by looking at the frequency and the days between trips, the leading time that he has for himself to book something, you can analyze all these things. And what we want to bring, as a marketer, to the table is the imagination. So what? You find out that somebody is a leisure traveler. Do you even have a way to personalize it, the message? Or are you just going to send the same thing all over the place? In that case, why don’t we just not bother with any of these things and just keep sending the same thing, and see what happens, because it’s not going to improve. So that’s the learn part. So we talked about a lot of things–

Damian Yeah, we did.

Stephen Yu –But I want to dial back in terms of retention as well because we only talked about acquisition, but this one-time-buyer problem or whatever you call it, ultimately leads to buyer lifecycle as well. And you asked a question about, well how often is often enough? Or until when do we call somebody active? Or it depends, and that’s the learning part by knowing the average transaction date interval and all that kind of stuff. When it comes to retention though, and I guess the first statement is that, please don’t get into the mode that you feel like you are compelled to talk to them all the time. You’re not personalizing. Your personally annoying people.

Damian And nobody likes that guy either.

Stephen Yu Nobody likes that guy. It’s like, “I heard about this product twice this week. So why are you doing this to me?” and like, “Are you trying to coerce me to buy this thing?” It’s not going to work. So please don’t do that. So that means, you have to be smart about two things. One is even among your customer target, you have to look at least two dimensions. One is: what kind of people are they? So create that profile that you have created for the purpose of acquisition. Do it on your own internally as well. Hey, after all your house file names are free anyway. So just be smart about it. Less is more in this case. Fourteen emails per person per week? Please!

Second dimension is: the timing of it. Just because somebody is recent, don’t bombard them with all these catalogs and e-mails just because he came back. “Oh yeah, we missed you. I’m going to share everything that I have.” Now that is such old marketing by the way. Old sales guy shows absolutely everything that he has in his bag and says, “You know, I’m going to show you everything, so stop me when it’s interesting to you.” Well guess what? Those days are over. I mean, modern buyers are so savvy, and they get bored within .2 seconds. We’re talking about a really impatient bunch of people. We are actually, all of us as consumers. Don’t do that, please.

The timing of it is that you can look at it multiple ways. One is: gentle nudge for the recent buyers or when the golden opportunity– that may vary from customer to customer depending on your business model– when that is about to run out, just send him a reminder and give him a reason to sign back on, or if somebody is really high value, don’t just send the same e-mail. Give him some special offers or an exclusive invitation or something. I mean, make them feel more important. In terms of both, what kind of a segment the guy belongs to and when you do these things. It’s certainly not the day after you sold some $400 item.

Well, he’s not going to do it again soon no matter how desperate YOU are. They don’t care. Then if you know the life cycle of, okay, they are new, and they are going into a fading mode, and if somebody is really “gone”– I call it a “gonner” or a “dormant customer” unless they could be one year or two year depending on your business, then you’ve got to have a totally different approach. If somebody is “fading,” maybe you should bribe them to come back. But if they are totally gone, then you may have certain information about the guy, but he’s a “gonner.” Treat him as if he’s a new customer. Like a new prospect almost, but what you’ve got on your side is that you know what he did, say four years ago. Oh, at least he did something nice four years ago, and treat him differently.

So that doesn’t mean that, Oh because my clock says so, I’m going to just contact everybody in my customer base, and guess what? If you look at your customer base, depending on how you look at it, but about a third or even more will be classified as dormant customers. That’s just normal because you know why? We’re talking about the world where 80% don’t come back anyway. Even if you do come back, well it’s a long time.

So therefore, you shouldn’t be surprised by the size of what we call the one customers. And what do you do? Do everything you can to select of the best of the best and have a plan accordingly using all data, as well as some third party data that could be commonly available. It’s just a way to slug them about the retention strategy as well.

Damian And I guess to kind of close the loop on that, one of the things that I hear a lot is, Well, I’m emailing this guy fourteen times anyway. So the person you’re talking about is getting the message, and what I think I hear from you is, yeah, but that’s the person who actually is driving the revenue that really matters. And you might not be sending them the best message or possibly even turning them off.

Stephen Yu Actually, that could be the next episode.

Damian Yeah.

Stephen Yu  We can talkabout what is relevant in the age where we have to all compete for people’s attention. I read a stat somewhere that– this is an old stat too– that the average human being looks at about six to seven different kinds of screens a day. Now, billboard, TV screen, your mobile screen, every screen that you can think of, in the future even thin air will be a billboard personalized for you by the way.

I saw that in the movies, and I don’t think that future is far ahead. Now, having said that, you cannot just show the same thing to people. Why do people look at certain things? Because it’s relevant to them. So you’ve got to think more in terms of that. And by the way, fourteen e-mails per person per week is not always bad if you’re really going after brand recognition that you want to be remembered. Actually, fourteen times is too much, but still, people remember after the third or fourth time.

Damian I think it depends on the goal that you’ve got.

Stephen Yu But one thing to remember: do not train your valuable customer base, do not train them to not open your emails. They say, “Oh, I got an e-mail from XYZ retailer.” Guess what? They’ll highlight-all, delete. That’s what’s going to happen. So don’t train them to ignore your message cuz you’re spending too much effort to it. Less is more. And if you can personalize as much as we can, and well, I guess that’s the next week’s topic but…

Damian Sounds good.

Stephen Yu Exactly. We’re going to continue this conversation. It was really fun.

Damian It was great. Thanks so much Stephen.

Stephen Yu Thank you.

Damian If you enjoyed today’s episode, we ask that you please leave a rating and write a review. Or better yet share it with another marketer. Be sure to subscribe to the podcast for new episodes. Also check out the show description for complete show notes and links to all resources covered in today’s episode. If you’d like to speak to someone about any topics covered in today’s episode, please visit BuyerGenomics.com and start a chat with the BG team today.

2018-11-02T21:05:28+00:00