Putting the customer at the heart of everything that you do in all ways, always

Hi everyone, and welcome to today's session. Thank you so much for joining us for this inaugural inbox Expo, it's my absolute pleasure to be here as a speaker. So I'm here today to talk to you about how you can put the customer at the heart of everything that you do. In All ways, always, my name is Kate Barrett, I'm the founder of eFocus Marketing, and the author of the best selling book "E-telligence, email marketing isn't dead, the way you're using it is". Over the last 13 to 14 years, I've been lucky enough to work with a whole range of brands, from the small entrepreneurs just getting started through to big name brands, including Marks and Spencer, Argos, TUI, BT, Nissan, and many, many more. And I've seen the good, the bad, and the ugly of email marketing. And I'm here today to show you how you can use email intelligently, to communicate with your subscribers, your customers, your prospects at a level that is really going to help to engage them and move them forward with your brand. Now, this is nothing new. It's something that we see in real life all the time, my local coffee shop, for example. It's run by the lovely George and his wife, who you can see on your screen now, George gives us that personal one to one service that you get from a local coffee shop. He knows who we are, he knows the name of my son, he knows what our drinks order is without us even having to ask for it. He asks us for our advice on the products that he's selling. He gets us to try new things that he's got in and give us real feedback as to whether or not we think he should order more or order something different. He values us as people in his in his business as individuals. And I don't know about you, but the last time that you went into your coffee shop, did you have the same experience? Did he know or did the owner of the coffee shop, know who you are what you like, and even start making your drink before you walk in the door. This has happened for many, many years. And in the 18th century, good retailers would recognize who their customer was and tailor their pitch and their product, according to what they knew about them, just as George does now. And in this example, there's a story of a company called lock and co hatter's of St. James's street in London. And as the story goes, a trusted customer could arrive outside the shop door on their carriage and shout hat and then leave. And the shop staff would then refer to their records for the details of that customer's hat size, their style preferences, that colors that they liked, before making that hat for them, and then delivering it directly to them at their home. Precision, personalization, bring it into the real life where they are targeting their products specifically to that one person. Now this is all talking about in store about what people can do on that face to face one to one basis. But how about this? How many of you have watched Tom Cruise in minority report when he goes into the gap store. And the artificial intelligence in store asks him how those assorted tank tops work out for you. Now, we're not quite there in store in terms of artificial intelligence and non one to one retailers being able to do this for you like gap and other big retailers like that. But actually, although we're not there in store, we are there online, we can do this right now. We can allow people, the personalization of targeting our messaging, how we communicate with them, when we communicate with them precisely to what they've done before, and what that next best action might be putting them at the heart of our communication strategy. And this is all about customer centricity creating that positive experience before, during and after they've made a purchase. It's the old way of doing things online, where we batch and blasts and the same thing to everyone, versus the new way where we get personalized. We make that engagement that people have with our brands online, and particularly through email marketing, easier, more engaging, more accessible. And we wow them with what we have, we surprise and delight them, we don't just sell to them over and over again, we get innovative and clever and intelligent about how we are communicating that sales message to people, and how we help them in between to build loyalty, to build relationships, and give them what they want. What they want is personalized experiences. People are willing to share their personal data in exchange for personalized offers and discounts, product recommendations, and overall shopping experience is particularly post GDPR, where people are a lot more concerned about their data, or a lot more up to date about how their data may be used. If somebody has given you the opportunity to store and use that data and you don't do it, you are missing the ability to target them in a way that is going to have a much greater chance of helping them through to your desired goal, but also to meet their needs. But of course, there really is that switch between what they want and what they're allowing you to do. And what's creeping, there's that privacy versus personalization debate. On that one hand, customers really desire greater personalization. But they are concerned about that creepy use of data, you have to be smooth, you have to be natural and not creepy. So how many of you have heard the example of targets and their personalization and targeting around different phases of a woman's pregnancy? I don't know if you've heard that story before. But if you haven't, I highly recommend that you Google it, look it up. And it's the perfect example of moving from personalization into creepy, we have to remember the human element of everything that we're doing. And in this example, as a as a quick summary for you, target took a load of data that they had, and they analyzed it. And they found that during specific stages of pregnancy, women were more likely to buy certain products. So they then went ahead and based on that propensity modeling of what they most likely would buy during different stages, based on what they'd already bought. They started to target women with messages for each stage of their pregnancy and different products that would be most related to them. But they weren't overtly obvious about it. They weren't smooth, perhaps they didn't take into consideration that particularly with something like pregnancy. It's a very personal experience. It's something that can change, perhaps if miscarriage happens, or perhaps if there was a false positive on a pregnancy test, or perhaps if somebody is a surrogate for somebody else, and they don't actually end up having the baby themselves. They obviously are a surrogate and have that baby over. Or if a baby's being handed over for adoption, or one of many reasons why this is a very personal specific area of a person's life. Not a number, not a subscriber, a person. So when they did want this, as the story goes, a gentleman walked into one of the stores in Central America and started complaining and saying Why have you sent pregnancy products recommendations to my teenage daughter. Now, of course, it turns out that target were right, the teenage daughter was pregnant, but she hadn't told her family yet. Now again, this is the point at which it gets creepy that target knew before she had even told her family that she was pregnant. So what they did was they pulled back on the overtly obvious they still use this data because it was extremely valuable to them as a business, but they smoothed it out a little bit, they input other products into emails alongside these recommended products that they knew from their data analysis. People would be most likely to buy at different stages, but they just may less obvious that that's what they were targeting based on. And the results of those emails were that they still saw an uplift in those specific products that were dispersed in with a range of other products. But it is that thin line that you're walking, and really think about it from the person's perspective, as in the example that that we've just kind of noted. Think about it also, in the case of the products that they buy, that they may not want to be retargeted on for various reasons, if they're buying an engagement ring, for example. So if you are searching for an engagement ring online, you live with your partner, you're using the same IP address and a way to connect into the internet as your partner. If you're searching for engagement rings, and then are retargeted, on Facebook, on Google, with messages saying, hey, you've used this ring, you may also like this ring, and your prospective fiancee sees this, that's gonna ruin the surprise for you. So you have to really think about the times at which it's practical, and non creepy, and will actually help people for you to use their data very cleverly. Okay, so 22% of people say that they would look for other brands, if they found a particular company's personalization a little bit creepy. And 9% said that they would write negative reviews on the Internet. So we are walking that thin line, we are a tightrope. And if we consider the people that we're talking to, when we come up with these communication strategies, we're going to be on much firmer ground. But people do want this, they don't want it creepy, but they want personalization. They don't want generic anymore, they want something that's going to talk to them at the moment that they need it. So that desire is really morphing into expectation. And there are whole businesses springing up around that personalization strategy. stylists creating your outfits for you, choosing your shoes, and sending you selections each month based on your personal preferences. 64% of people expect companies to provide an individual experience when they've given them the data to do so. And 83% think that an individualized experience is really important. So in terms of customer centricity, this brings us to three key elements, it brings us to understanding who your customers are and what your customers want and need from you, and when they need it. And when you bring those three elements together, that central point is your customer centricity. And it sounds so easy to do, right. But it's not. There are lots of different data sources, lots of different customer types, perhaps 1000s of products, and we have to learn to speak in our customers voice and preempt their needs. But there are ways in which you can start to do this. Or if you're already doing it, take your strategy to the next level. And when you do, you can start to understand some of the really important questions that we're going to be asking. If we can answer them, will help us to better tailor our programs for our audiences. So what's the customer lifetime value in your business? When a customer is about to churn? How do we identify them? What is that customer most likely to want next, so that we can provide them with the best possible recommendations for their needs? What is the optimal frequency to send my message? What's the best time to send my emails, questions I hear all the time. And what is the customer trying to do? What do they want to achieve? And how do we help them to move from one task to another within our businesses? And the way in which we start to answer these questions and get to those three stages of the customer centricity is to know our audience. Now to know our audience, we have to know our data. Everything that we do, starts with our data, and I like to break it down into a data pyramid. So let's start at the bottom of the pyramid and work our way up. Now in the pyramid, there are five main types of data, each representing certain information that you may be accumulating in your business. And as we move up the pyramid, the data becomes more and more value So, at the bottom, we have known data. This is data that you're collecting directly from subscribers, you're asking them, it's details such as their preferences, such as demographic data, who your buyer is basically, their date of birth, their address, their name, their education level, their interests, their income level, those kind of details, perhaps you're more of a b2b business, and you're collecting more thermographic data. So information that you use to categorize businesses, where they're based geographic, geographically, the number of clients that they have the type of organization, they are the industry that in the size that they are. Then there's psychographic data, which is putting the why behind people do what they do. So that comes into the next stage is when I'm kind of skips between the two of known data in our next stage, which we'll talk about in just a moment. The thing with known data is that in the moment, it is some of the most valuable data that you can have. But in the long term, it's actually some of the most unreliable. So consider this. You're a home improvement company, and someone signs up and you ask them if they're planning on renovating their bathroom in the next six months? And the answer is yes. Now, you could have found that information by process of elimination with some of the other levels of the data pyramid that we're going to talk about in a minute. But by asking them, and then by asking them a timeframe, that timeframe isn't a piece of information that you necessarily could have ascertained anywhere else other than asking them. And that is massively massively valuable information in the moment that you wouldn't have otherwise have known. So once that timeframe has passed, or they've completed their renovation, if you're still sending them emails about taps, or the best bots or design ideas for their bathroom, you're quickly going to have a message that's out of date, and are going to become unwanted and most likely annoying. But within that six months period, that they've told you that they are most likely to be renovating their bathroom, it is extremely valuable information to think about if somebody moves house, or if somebody gets married, and their address or their name details change, unless you update that known data, it quickly becomes out of date. So you have to think about how you're collecting it either at the point of sign up through an email polls to gather preference information or interest information through preference centers, where you ask people what they'd like to receive from you when they'd like to receive it. How are you going to ask people what they need from you, and make sure that that's up to date, to make sure that you're doing that on a regular basis and giving people the opportunity to update that information. So moving on up the pyramid after known data, we have cultural data. So this is where the psychographic information that I mentioned earlier splits between the two, between known data and cultural data. So this is the personality and emotions based on the behaviour of your subscribers, and is linked to their choices, including attitudes, lifestyle, hobbies, and risk aversion that they have that personality magazines, they read all of those things that are telling you why your subscriber might be interacting or purchasing. and cultural data generally relates to the differences in cultural norms and surrounds your wider information. So it connects products together, for example, by category by type, relevancy, or knowing what type of products and services are most relevant to people in different areas of the country or around the world. So supermarket supermarkets use this a lot. For example, the products that a supermarket would advertise to people in Scotland versus people in London, will be slightly different depending on that specific regions, tastes and trends. So it does change for people, those cultural differences. And then as we move up the pyramid and we get more and more specific, we've got contextual data. So this includes information about what's happening for the subscriber right now, such as where they are geographically what device they're using to open their emails on current weather conditions, and this can change in real time. So changing sections of your email such as countdown timers, weather forecasts, maps, delivery trackers, social media feeds, depending on what's happening for them right now. So a high street retailer might use a live maps in their emails that change depending on where you are, geographically, when you open that email, whether you're in Scotland or whether you're in London, your map to your local store will change. And then we have behavioral data. So this is tracking subscriber behavior on your website with a drop pics or cookie tracking, and giving you that wealth of information about what's going on right now. products, they browse categories, subcategories, blog posts, they read videos, they've watched, any actions that they've taken. So on the website, in your emails, and your social media, through other marketing channels, any behavioral data that you can pull together. So for example, if somebody is on your website, and they're browsing your frequently asked questions, they're telling you what that behavior that they're looking for more help. If they are browsing multiple products of the same type, they're trying to choose what's right for them. If they're browsing multiple categories, perhaps they're looking for inspiration. So this can tell you a lot about what customers need right now. So linking back to our known data example of the bathroom renovation, if somebody is browsing borrow from products you can denote from that data, that they might be looking to update their bathroom, but you don't know within what time period. So that's where the known data would come into it. And then further up the pyramid at the top, we have purchase data. So everything about what they've done with you in terms of that conversion. So what they've purchased, when how many times when the last time was, what the products were specifically, and any other information relating to that purchase. Now, depending on what your business is, that purchase may mean different things to you as that end conversion, of course. Then we have artificial intelligence. Now, this could be artificial intelligence through machines. It could also be intelligence created through data teams that you have, and the analysis that they do of all of those pieces of data, and linking it together to create other pieces of data to create propensity models of what people might be likely to do next, what they might be likely to want next, and helping you really to ascertain the next best action, and how you can best serve your customers. So it's the analysis side of things. Now, what we haven't looked at in this data pyramid is the qualitative side of your data. So we've got the quantitative and the qualitative. So you've got the numbers base, and then you've got the opinion based. So coming from a variety of sources, such as focus groups, such as user experience, studies, surveys, your net promoter score, listening to what people are saying, on social media, or from your customer services teams, and bringing all of these pieces of data together quantitative and qualitative, and really helping you to walk in those customers shoes, find their voice, understand what they want, when they want it, and how you can best deliver it to them. So conversations that they're having. And I'm really listening to that data. And if you don't know, then ask them what they want come back to that known data. But you've got to think about how you collect that data, whether you ask for it, whether you track it, or whether you analyze it. Doing a data audit is a great way to start getting a handle on what data you have in your business now, and what data you might like so that you can better understand your customer. And we need to bring in our own human voice, our own perspective on what may or may not be damaging for people. So we have the target example earlier around the pregnancy. Now that's not something that a machine unless you plug it into the machine is going to be able to know that's a human feeling a human emotion, and we have to make sure that our strategies aren't just data LED, but they're human led as well. So this is an example from Cath Kidston that I received in the last few weeks actually asking people if they want to opt out of Mother's Day emails. It's not a problem, click here. They'll take you out of that specific communication types. Because Mother's Day, Father's Day Valentine's Day can be really emotional time. For people, and they may not want to be receiving these types of messages. So think about how you can have that human focus, as well as your data driven marketing. Personalisation is challenging, accessing the right data, getting that senior level buy in scaling up, but the value of personalisation is there. And although it can be hard to determine, one thing that you can do is really to show what happens when you do and don't have personalisation in place. Show them how you're currently communicating with people, and how it's not serving the customer. First, test it test on a small basis, find those positive returns, and then look at how you can scale that up and deliver that personalisation. So let's break down these three elements in a little bit more detail just to go through and give you some examples. The first is to look at who you're talking to figuring out who that one person is, who that individual customer is that you're talking to. So some of you may have customer personas, where you're targeting people based on segmenting them into groups of the type of people that they are. So HubSpot did this and that's example you can see on your screen, so they had marketing Mary, owner Ollie, enterprise Erin, and there were differences between those types of people. But when they could visualize who they were, and bring those similarities together to create segments based on personas, they could better talk to them in the tone of voice, with the right imagery that connected with them. And this really helps them to increase their click through rates. Think about pizza companies, most people like pizza, and it's the same product. But when you look at the TV advertising, for example, you'll see different types of ads, you'll see imagery of a group of friends together on a Friday night, having fun laughing together sharing those experiences, versus a family on a Saturday night where mom and dad don't have to worry about cooking, they don't have to worry about doing the washing up. And the family can spend that quality time together, same product, different tone, different imagery. That is how personas come into play in your segmentation strategy to target the who RFM analysis, for example, really bringing together that purchase data to work out who your best customers are, and who at the other end might be at risk of lapsing and everyone in between. So you can change your messaging strategy, depending on whether or not they're your champions who are most loyal, and are going to keep coming back to you regardless, or the ones that need a little bit more of a push, and slightly different messaging, different offers to move them through that process, and help to really understand how to communicate with them better. All of those different groups, different segments come from your data, and understanding who they are and what they need from you. And that's the next point is what your customers need. And how do you work that out. We know they want relevant offers to be remembered to feel listened to and understood and to be in control. And we know that that works to increase our results. So we can use our traditional artificial intelligence to work out the next best action, the best product. So for example, if you have been tasked with maximising your product margins to meet company objectives, you would serve up not only the most relevant products based on previous purchases based on behavioural data and what they've been browsing, but also those within those categories with the highest margins. To set the best messaging that we can in terms of tone sentiment, in your copy in your subject lines, in terms of the imagery that you use. There's lots of different ways that we can use that learning to pull from our data and change our messaging so that it changes our content based on what consumers want. 80% like it when emails they receive from retailers recommend products to them based on previous purchases. For example, we've got an example on the screen from Netflix where they're giving recommendations on what you might like to watch based on what you've watched before. Price alerts where something in your basket has changed price and you're helping the customer by telling them the price has gone down. Perhaps by personalising in your imagery, personalising with when you send your emails with birthday emails and specific offers related to That time in a person's life, telling people what's been happening in their account, and encouraging them to come back and interact more. But be careful, because like with the target example, personalisation can sometimes go wrong. And there's an example here from Uber, where they are pulling in how many minutes you've ridden with them, or how many rides you've taken. Now, what should have happened is, if it was under a certain number of minutes, under a certain number of rides, that that message should have changed to encourage that subscriber to come back and ride again, in this example, with a live store map to the local store, but unfortunately, in this case, the customer's local store was over three hours away from their home address. So again, there should have been some locality metric put into place where if it was over a certain number of miles or time that that changed when on store, call to action to on that, that change to an on site call to action, for them to come back through and buy online, we have to understand who we're talking to, again, bring that human element in. That goes for not just how you personalize your messages, but for your design as well, and how you make it accessible for everybody. So by designing for someone with a permanent disability, or someone with a situational limitation, so for example, if somebody is a new parent, and they're holding a baby, and they can't move around and have that dexterity anymore, if they perhaps got a temporary arm injury, or perhaps they are disabled and have a disability, that they are missing one of their limbs, where it's a permanent disability. In each of those different areas, we need to consider how we're building our marketing strategies, and specifically, in this case, our email marketing strategy. So there's a great breakdown here from the wonderful taxi for email that I've stolen, and it breaks it down into those four key areas. So hearing, when you're using video in your emails, provide subtitles and captions. If you're using visual elements in your emails, code for screen readers and designed for visual impairment, I've got some examples of that for you in just a moment. Dexterity makes sure your emails are easy to interact with and tab through. cognitive considerations make sure that easy to understand and to read. So in terms of the colour and contrast making sure that there's enough contrast between your colours. And there's a great tool on the screen there that you can go and have a look at to see what your contrast ratio is. So that there is enough difference between your colours between, for example, text on a background colour that you can read what's on it, making sure you don't use animated images that flash at certain rates because of photosensitive seizures, making sure that you're designing with screen readers in mind. Also don't forget that this is the perfect example of a permanent and a situational disability. So for example, screen readers for those who are blind, but also perhaps using Alexa or Siri to read out your emails to you, perhaps if you're driving, or you're trying to multitask and do different things at once. This is how technology is progressing. And making sure that our emails are designed for accessibility is where we need to be to move forward and make sure that everyone can be included in our messaging, how you code your emails using semantic elements so that screen readers can easily scan through the emails using your P tags and your H tags using role equals presentation on your presentational table so that again, screen readers can understand the difference between a table and elements and how they read through that for what's content. Also design. Using alt tags on your images so that if the images are disabled, there's still a description of what that image is that can be read out, making sure that your font size is large enough that it's spaced out that it's easy to read and not too condensed in terms of the font that you choose. Making sure that your call to action design is optimized for different people. So making sure that it's easily clickable, that it's easily tappable that you're using bullet proof buttons that are still there and can actually be actioned even when images are turned off. Don't use click here use descriptive words of what's going to happen next benefit driven and this helps people in all situations and it helps people across multiple different devices and with permanent and situational disabilities. So again, to bring that human element into your marketing He's so important in every sense. And then making sure that we're sending messages when they need to be communicated. So there's going to be time of day and day of week. But I want you to go deeper and think about the customer journey. Where are they in their journey with you? Are they moving from those beginning stages when they just find out about you, and sign up for your emails and welcome them in to research and consideration where you deliver the content that they need to move forward and decide to make a purchase from you sign up to your your software to buy that product? What do they need to know to move them through? So abandoned basket emails, abandoned form emails, abandoned, browse emails, your standard newsletters, your sales emails, will all fall into the research and consideration phase. And then how do we make the purchase and follow up experience stage as amazing as possible, so that people want to come back to you. So in these examples, the brands are using video to show how to better use those products. If we can build loyalty now, and give them that wow experience, thrill them delight them, we're going to make that next stage when they're in loyalty and repeat purchase so much easier. Now, I'm sure some of you have seen these kind of emails where you use data to make people feel special. And EasyJet did that by reiterating data back to people, Fitbit, do it, loads of different brands do this TripAdvisor to help you to understand how you're helping other people, or how that brand has helped you what your personal stats are, it's almost gamification of the process, telling that personalized story. And then of course, bringing it all together at the end in terms of how you reengage people with buying from you, with your marketing with your email marketing, and bring them back round. So understanding the data that tells you how people are identified at each of these stages, what messaging they need, at each of these stages, and then how you deliver that, at that right time is absolutely critical to how you pull the human element in and put the customer at the heart of your messaging. And don't forget, your customers aren't just your subscribers, this goes beyond email into that holistic view of your marketing strategy. Your omni channel strategy, pulling those channels together with email at the heart of your personalization. So I just want to leave you with my five steps as a summary of what we've talked about today to create a truly personalized experience. One, create unified profiles to understand who your customers are sending your messages to the right person, create tailored messages for each of those people. Either it is segmentation group level, or if you can add a one to one personalization, product recommendation article recommendation level, you can use AI driven technology to help you to do that at the more advanced stages, that's sending the right message to that person, automate delivery of messages, work out what data tells you is the right time to send those emails to send out those marketing communications and choose that right channel to deliver those messages at the right time. And then analyze, test, optimize, and repeat so that you can send the right person the right message at the right time through the right channel. and optimize how you're talking to customers based on their own data and their needs. So don't forget intelligence, putting the cost customer putting the customer at the heart of everything that you do, in all ways. Always. Thank you so much for listening today. I hope you found that useful and inspirational. Please do get in touch with me. If you would like more information about how we can help you to implement intelligent email in your business. Grab a copy of my book on Amazon, or check out my new website, email design guru for inspiration from around different industries on how you can make amazing email marketing that really meets the needs of your customers. So I'm going to throw it open to any questions that anyone might have. I'm here to answer them for you. Thanks, everyone.