EP.147/ TRAJECT DATA
Traject Data: How Clean Data Insights Can Transform Your Ecommerce Business with CEO Rochelle Thielen
Rochelle Thielen is the dynamic CEO of Traject Data, where she champions the vital role of data aggregation in driving transformative advancements in AI, machine learning, and software development. Obtaining clean, granular data is a major challenge for many companies, as data can be outdated, inconsistent, or siloed across different systems. This makes it difficult to make informed business decisions, especially when using AI and machine learning. Traject Data helps clients set up API feeds to get real-time data updates on things like product availability, pricing changes, and where their products are being sold across channels. This enables them to make faster, more accurate decisions. The data Traject provides can be used for a variety of use cases, like preventing fraud and unauthorized reselling, as well as optimizing SEO and marketing strategies as search and shopping behaviors evolve. Maintaining a consistent, high-quality customer experience across all touchpoints is critical for retention. Leveraging the right data can help brands predict customer needs and serve them more relevant content and offers. There is no one-size-fits-all approach, as brands need to balance data-driven personalization with respecting customer privacy. Ongoing testing and adjustment is required as consumer expectations continue to shift.
Episode Timestamps:
2:00 - Rochelle's background and introduction to Traject Data
5:00 - The challenges of working with messy, outdated data
10:00 - Using real-time data to prevent issues like unfulfilled orders
15:00 - Leveraging data to combat fraud and unauthorized reselling
20:00 - How data and AI are changing SEO and marketing strategies
25:00 - Balancing data-driven personalization with customer privacy
30:00 - The importance of clean data for improving the customer journey
EP. 147
ROCHELLE THIELEN
TRANSCRIPT
This transcript was completed by an automated system, please forgive any grammatical errors.
SUMMARY KEYWORDS
people, customers, customer experience, ecommerce podcast, Shopify email marketing, agency, retention, talking, team, ecommerce operations, love, great, community, founders, learn, grew, clients, marketing, ecommerce, support
SPEAKERS
Mariah Parsons, Rochelle Thielan
Mariah Parsons 00:00
Music. Welcome to retention Chronicles, the retention podcast for E commerce marketers. I'm your host and fellow e commerce marketer, Mariah Parsons, tune in as I chat with E comm founders and operators all about customer retention. Think marketing ops, customer success and customer experience. We cover it all and more. So get ready to get real with retention. Here is our newest episode. Hello everyone, and welcome back to retention Chronicles. I am psyched for today's episode. Rochelle, thank you for being here today. I know it's out of a very busy schedule, so I'm always grateful when people make the time to come on, share their expertise and just get to like, know the space better about you know the expertise that you're going to share and really expand my own mind. So thank you for making the time say hello to our audience and give a quick introduction of yourself. Thanks so much for having me. Always will find time for you. Of course, I'm Rochelle Phelan. I'm the CEO of trajecta. My background has been across the board in private equity venture SaaS, automotive, insurance marketplace and now directly in source data. So definitely across the board, but excited to be here today. Yeah, I love it. I'm not even going to try and, like, dive into all of those because I just know they're all encompassing. But I will give context to our listeners about how we met. Um, so we met at Shop Talk fall, which is a very fun conference. Um, they had it for the first time in Chicago for their fall conference, but have a bigger one in Vegas and in Europe. And I'm sure all of our listeners have either heard me talk about it, or have attended themselves. And we just so happened to meet at the happy hour that they had exclusively for women that shop talk puts on. And then we come to find out, you know, our teams are already in discussion about getting you on this podcast, which it was just serious, yeah, so it was fate. You're right.
Rochelle Thielan 02:00
So, yeah, it's great that we're actually, you know, finding the time to sit down now and aligning our schedules, because I feel like that's the hardest part about a podcast, is just getting the recording time set up. So thank you for being here again, and thank you for giving us that quick summary of your background. I think our listeners will know, you know, you got a lot of expertise in a lot of different areas, and now you're bringing it into, you know, source data, like you said. So give us a little bit of a background on traject data. Tell us what you're doing, like what give us kind of the boiler plate so that we, you know, set the stage, and then we'll dive into the thought leadership. Yeah, yeah, you got it. So the easiest way to think about it is, for retailers and brands, what traject data does is goes out online and captures all the information that otherwise would be either inaccessible or not accessible in a scalable way for them to make strategic decisions, usually around customer journeys, marketing SEO and operational decisions. So broad context, but it is kind of like an all of it type of company, especially with all of these tools like AI, what used to be enough data is never enough data anymore. So we've really found a way to do that in a consistent way, fast enough, and with true, real time data that actually feeds the beast in a certain Yes, yeah. And it's been a conversation that we've been having more frequently on retention chronicles of just AI in general, yes, but then, like, how do you actually train the said, said AI to be efficient, to be what you want it to be, to get the results that you wanted to get. And I know this is something that my own expertise, like, I'm still learning as well. I am by no means an expert in space on just AI and like, making sure that you know you can be as efficient as you possibly can be. So I would love to have you kind of walk through when you're talking about data, like, I feel like just the word itself, it encompasses so much, right? Like, anywhere from like data lakes to just like first party, like it zero party. There's just so many different aspects of data and like it all can seem so I guess,
Mariah Parsons 04:12
overwhelming, right? Yeah, like you're an expert in your field, I think just like the enormity of all of it and how fast it's coming at us and changing makes all of us a little bit uncomfortable.
Rochelle Thielan 04:26
And the interesting thing about AI now, which we were just mentioning, Shop Talk, comes up in almost every speaker's conversation when they're trying to deal with so many different aspects of the business, is like you have to think a level deeper, because all of what AI does is really learn from the data it's fed and how those decisions are made, and it tries to replicate and mimic those things. So when we think about the source data, frankly, when we think about AI, some of the first questions we should have is about the data that's being fed. Into that tool to teach it how to make these decisions. And that's the area that's kind of behind the curtain for most people, where they frankly, don't know where that information is coming from. They just kind of like are in a position where they're given a tool that surfaces this information they're making very important and strategic informational decisions with it, but it's hard for them to ask the right questions to know if that data is actually reliable. How current is it, how clean is it? You know, like, what data has been used or fed into the background, either by my team, my company, or other organizations we're subscribing from. So I completely understand. And was in that boat myself. That's like, one thing coming into actual, you know, source data that even personally, for my career, I've really enjoyed being here, because you're forced into a situation where you have to get behind the curtain and learn about it, yeah, yeah. And it's such a great point. And like, I again, like, I I will share just endlessly on this podcast, like, I know I'm guilty of it as a marketer, where it's like, oh my god. Like our database, I'm like, sometimes, like, Okay, wait, do I fully understand how contacts are being added and kept up to be clean, and like, you know, all of the automations that we have going on. And just like, even AI, I'm like, okay, how am I training my AI? Am I putting in the right resources for, you know, am I just putting in a couple of resources because I'm being lazy, or am I, like, actually diving into our database and, like, you know, making my own, you know, AI agent to then make sure that, okay, that's the, like, best. So, yeah, for me, right? Like, there's so many different things, so I know I'm guilty of it. Everyone will relate to it. Yeah, anxiety right now from people listening to this, like, I can feel it. From past lives of just over literally having teams call things like the data swamp would be referred to, where you would dig in, in a company to go like hope you could maybe rely like enough to make a decision, but it's totally fair, because, like, you were just saying you have limited data. Like, some people aren't lazy. They just that's all they can get access to, and they're forced into a corner where they have to, like, buy one of those dreaded lists online for some 1000s of dollars that you don't know what you're going to get, or how old it is, or how did they get this information? Or, you know, like, maybe go into an area where your your parameters are wider than they should be, so you don't know if you're really making data specific to your industry, or starting to creep into other things that are completely different than what they were before, so totally understandable, and that's like, where we've had to learn so much is we end up being the coaches in that scenario. And a lot of this stuff, you have to sit right next to your engineering and product teams and understand from an engineering mindset, like, how are you actually setting up and querying for the data to know which most people aren't gonna do, because they've got the rest of their company relying on much higher level decision making. Yeah, so we'll tell our audience, like, we know it's stressful, take a deep breath, and then Rochelle, I'm gonna have you explain. Like, how do we even get to the point where, like, okay, data is messy, data is dirty, data needs to be optimized. Data needs to be better, just overall better, because it is a great point that, like, you can't have aI run on bad data. So if someone's sitting in our audience and is like, well, that's definitely me. I'm raising my hand admittedly,
Mariah Parsons 08:36
tell us about, like, Why do you think just our systems even get to that point when we're, like, sitting at such a precipice of, like, technology is so great, but we still have these problems of like, you know, like the of data just being messy, or data just being so all encompassing that it's that it's hard and you have to dedicate efforts of, like, cleaning it out so that you can create other technology, like AI to do a better job. Yeah. So some of those things we just kind of talk through the one I think that's critical to this audience, and that I've seen more and more of is there's usually in companies, this kind of unintended gap in between the business side of the company and the data or technology or engineering teams. So to bring those two things together and really solve that problem, you have to, as a business person, be working with someone as a strategic partner who truly understands what you're trying to get that AI to do to the level you do on the business side, and then have that partner, whether it's inside your organization or With a company similar to ours, walk through meticulously, how we can outline and ask for the information that you need in a localized, granular way, so that it's a continuous feed, rather than some type of cashed old information with somebody who basically took a ticket of okay, we think they want.
Rochelle Thielan 10:00
Leads for this company and gave it their best shot to do it. So, long story short is it's hard, it's meticulous work, and we have to have the patience to do a little bit more than we used to. Yeah. So, so you're, yeah, you're exactly right. Like, I think it is. It takes dedication to change right? Like, for anything that's outside of, you know, what we're specifically talking about here and so, and I know I've done that right, where it's like, clean out our database and just like, dedicate time to it like that. That is what, whether it's, you know, working with a team like yours, whether it's just like, chipping away at something, or just like, even beginning to understand a database that you inherited from, you know, another set of hands, or someone who is a previous leader at your company. What is it, you know, what is even? What is sourcing granular like good data, quote, unquote and good. How can that kind of be used for emerging technologies, and what does that look like for a brand? Yeah, exactly. Great question. So there's a couple different examples here. So let me. Let me just start by giving you a real life example of a marketplace that we work with that is huge in the US and Europe, and was losing literally millions of dollars over the holidays, because they're one of those marketplaces that has people, contractors, going out, picking up products, you know, in the moment, and delivering them. And during the holidays, like we all know, hours are all over the place. They're changing, literally, day by day, especially if they're smaller retailers that maybe just like posting updates within the last 24 hours. So the way they were losing millions of dollars is they were having to pay for unfulfilled orders and refund people, which obviously isn't good for retention or anything else, and they were having to pay these contractors to go and pick up stuff when there was nothing there to pick up and at scale, huge problem. So this was because the data that they had was old and not good, right? So to put that into the context of the question you just asked of like, how do we move that into a granular, clean data source, you need to. So basically, they we worked with them to set up an API feed into their organization, where every couple of hours, they were literally going on and pulling or scraping the information from all of these partners that they had. So if those hours changed within the last 60 minutes or so, they now have real time information. So those customers are aren't able to order in the moment. And if you think about it, even up until the last few years, we would have felt like real time is real time, even if it was a week old data, if it was 30 day old data, you can take this same application when you're looking at customer journeys and this omni channel experience that all of us are leaning into, and translate that over of if you're a direct to consumer brand, or, you know, basically any type of brand that's concerned about how your products are represented across all these channels, this stuff is happening literally Minute by Minute. Your prices can change. Who's selling your product can change how it's represented, where it is on the digital shelf is being adjusted, and it's very uncomfortable for people who work so hard to get this stuff under control. So if you're only getting a report that has the last you know, 30 day old data, or even a week old data, there's no way for you to stay on top of things changing at the pace they are now. So I guess, in summary, when you're asking me about what is this granular like critical data set that we're moving toward, it's really getting away from these off the shelf type solutions that are delivering you these reports and moving into a world where even in in as simple as Excel or these common reporting tools like Tableau or Looker, you're able to set up a feed and get that information literally. Now if you want to see that and be notified of those changes, yeah, it's so interesting and like, really ties back into ops. And just like making sure that you're running your business sufficiently. And I loved what you said around, you know, the the example that you gave of, if there's a brand that, or there's, you know, someone who a marketplace who has no, you know, doesn't have inventory from this one partner, and then you have all these stores, or you have all these, these orders that are placed, and then the customers, you know, you have to be refunded, even though they were excited about getting their order. And then it's like a nightmare for customer retention,
Mariah Parsons 14:48
because you are sitting at like, Okay, now they they wanted to place an order, which is, like, huge, because we're gonna miss out on that order now, and then the whole whammy of okay, and now they already have. Without even a product in hand to, like, maybe rectify the bad customer experience. They don't even have a product, and they already, you know, have a bad interaction with our brand. Exactly. It just, it really, it is something that I think is like an it's nightmare fuel for, you know, people out there. Yeah, can I give you actually, I want to give you one more examples do? Yeah, this was so interesting. We're talking about emerging technology. Even like the people who typically reach out to us are emerging technologies. Like they can't get what they want. They're trying to do things even faster. And this company I met with there is actually, we all know fraud is this huge issue, right? And one of the things that unfortunately happens is people are reselling products on other places for higher prices, right? This is no nothing new. It's just kind of like that cat and mouse game of like they're trying to stay ahead. Brands are trying to stop it from happening. So this, this company is basically trying to use our data, and will end up using our data so that at the moment of the transaction, like, let's just say, you know, it's the it's the New Age Air Jordan that comes out and drops, and I'm going to go and buy that, and I'm, you know, a bad actor reseller. When I buy this bulk quantity of shoes, they're instantly going on sources like Amazon and eBay to check and see if I the bad actor, have already re I'm already attempting to resell this stuff at a unacceptable price level. And if that happens within the couple of minutes before, say, Nike would ship these shoes, they're able to stop that order now, because they're able to identify that this is happening when you think about, like, when we're talking about granular, localized, like, real data, for them to be able to go and do that source within a couple of minutes and stop something like that happening. It's just like, incredible that that's even an option these days. You know? Yeah, no, it's, it's kind of like other worldly to think about of like, Whoa, how, how are we, like, at that point where you can, like, really, really get that finite and, like, every race, yeah, exactly. And it's like, whoa, wait. It's like, should I be scared? Should I be excited? I don't know. Should I be all of them. Um, and like, this is something I'm gonna even bring it out of E commerce for a quick tangent. Um, this is, like, something that even resellers with, like Ticketmaster, right? Like, I always have been wondering, and this is sparked because, obviously, the air is tore, um, because everyone who listens to this will probably know that I'm a Swifty. Um, not a huge surprise, but I was trying to get tickets, and it's just crazy impossible, especially for the US, right? So I just, I love that use case of, like, if you're finding someone who's trying to gamify some type of system and, like, make a profit off of it, using that data to be like, Nope, you're flagged. Like, orders canceled, you you're gonna, you know, like, and then that information is is out there for maybe other brands to even know, or like, XYZ you know benefit to just you're caught, you know, like it's, it's, it's a cool application to see
Rochelle Thielan 18:06
again, millions of dollars that are lost. Plus, when we're talking about retention, is like you're saying as a Swifty, but like other retailers can relate to is like when they have these hot products go, they don't want to sell it to another reseller who's going to ruin that experience for people. They want to sell it to consumers. So these technologies are really enabling that. But again, that's an that's a great example of this is impossible for brands to do themselves without outsourcing it to a partner that just lives in this data space, because it is hard to get that kind of data that fast and be reliable doing it, it's really hard.
Mariah Parsons 18:06
Yeah, no, it's, it's so it's right. That's why it's like, I that's why I like doing this podcast. Is like, if this can make it a little bit easier for someone out there, of like, Oh, I didn't even think about, you know, third party resellers or something. And it's like, okay, maybe now you have a new use case to worry about. But if you can, like, get ahead of it, right? Or just, be like, even just have a little bit more understanding of all the potential ways that data can help or hinder your life. Of like, well, it's gonna potentially open up a new, you know, fraud, fraud instance that you weren't prepared. Yeah, yeah, I'd rather, I think we'd all rather know exactly it's, like, short term worry, but like, long term, it'll pay off, so then you can start dealing with it, right? Or you can at least, like, know it's there and decide when you want to prioritize dealing with it, but it's not happening behind your back. Yes, yeah, exactly. And so, like, I think that's something that is so and I appreciate you sharing the use cases, because I know it makes it the context so much easier for people to like, I guess, apply to their apply to their own operations, and like their own use cases like, I think everyone knows, obviously there's use cases are going to be specific to each company, but I know it's always like comfort. To hear, okay, like, even these big, you know, big marketplaces, or big, big emerging tech, they don't have it figured out, you know. So it's like, even if you're a smaller, you know, smaller company, and like, figuring it out, it's, it's still comforting, very confident, yeah, it's like, that's one of the great things when you're at a company behind the curtain, like we are, where, in a lot of cases, you know, you just don't have access to it. Like nobody's on stage raising their hands saying, Oh yeah, we have that problem too. We actually don't know where our brands are placed, and can't see omni channel. But I can tell you, 100% just from my meetings at Shop Talk, that my my chin even hit the floor at some of these, like nationwide brands, where they're telling me, in 2025 this is on our roadmap. We know we need to do it, but we don't know how to even get there. This is so common. So whether you're, you know, small, medium business, or you're in that position where you're like, wow, we're way too big, and we really shouldn't have this problem. Now, rest assured, like seen it done, it been there. Like you're not alone. This is a problem for everybody, because they all know they need to, but that step from like, I know I need to, to how do I do it is a huge one, and it's one of my favorite conversations to have with people, because it just gives you the confidence that okay, even from we don't have to hire a huge data analytics team. We don't have to go out and spend tons of money on these really expensive platforms to do this. We can actually do this in house, by just getting a partner, getting a basic stream of data and starting with, let's watch our prices. Let's watch who's selling our products, and do that through again, like Excel Tableau, Looker at these very like, basic solutions. And then when you're ready and you're hungry and you're like, getting this confidence level, go out and spend the money now that you can justify this as an organization, it's like baby steps. Sometimes can have huge payoffs without having to feel like you have to go big or go home. Yeah, for sure, Michelle, you're so, you're so, right. That's so true of just like little, little things along the way can be a lot more tolerable in terms of, you know, life doesn't stop, like, other obligations don't stop, but rolling something out into the strategy that can be helpful, it really does a lot. And I want to dive into because we've been talking obviously, about, like, the with the case studies that you've given more about, like ops and thinking about like logistics and fulfillment, and like fraud and reselling. And I want to tap into the marketing side as well, because I think, like I've heard as a marketer, and I used to be sitting in this camp where, like, say, SEO is just a a little bit of a black box, right? Like, there's whole technologies, of course, centered around SEO strategies and making sure that, you know, you can, you're best optimized for search engines. But I would love to hear your take on, you know, making that that good, granular data, and how it also can help with SEO strategy, or just like any marketing strategy in general, absolutely, this is a great angle that we should go into, also a hot topic at shop talk and just in everyday conversations the so I want to start with a case study again, because sometimes it's hard to, just like, get your mind around real World application. So like, one of the best examples I've heard coming in from brand, from brand partner is a really big nationwide brand talking about, and these guys are in the beauty industry, about how SEO used to be really about owning keywords, right? Like you would do your very, best to like nail down those words. Well now, with things like Google's AIO and just all this AI coming into place, you no longer can just think about words. You have to think about so say, I'm out there selling sunscreen, right? So instead of me owning all these terms around sunscreen and facial care and all these things, I have to think about things like terms, like going on vacation that people are going to be searching for, and try to, like, get my head around and get the right data sources. So when people are talking as as you do with these AI solutions in more of a conversational way, and aren't any more, you know, typing in the search, I have to be able to predict, like, where my marketing spend is best placed, and that requires, again, going out there and capturing information from things like Google's AIO, Tiktok shops, search capabilities, even Amazon is doing this. It's something we've invested in heavily over the last year, because that's where everything is headed, right? And it's like, essentially what AI does, and it tries to make the decision for us of what we really mean to ask even like we don't know, and we need help doing that. It's taking away all.
Rochelle Thielan 25:00
Ability for us to function as human beings and like making those decisions. So you as marketers now, and we as marketers have to make the double step of interpretation of a conversation and what they're really trying to ask for that fits our product set. Yeah, and it's so interesting, and I'd love to hear if this is like crossed your mind, or been something that's also on your horizon, of like social search engines, of like Tiktok, of right? Like, how does that operate differently than Google? Of people going into Tiktok and searching like best bridesmaids dresses or something, right? Like, it also, how does data applied there and like your social or sorry, SEO strategy applied there. Like, what are the similarities? What are the differences? How do you combine them? How do, like, all of that, it just gets so much more intricate. Does? It does? And, you know, some of the stuff goes back to the simplicity of having real time, accurate flows of information where all of these things are coming up. So if you're going to stay ahead in Google, for instance, even with AIO, things like Tiktok that you're mentioning, everyone kind of already understands that. A lot of times, like influencers and the things that people are talking about and having conversations about tend to be the forefront, right, like that's the beach head of how everything's going to follow. So we have to, as a data provider, provide those solutions that are going to give context to that along with so you can see how that flow is happening and react and adjust to it later on in things like Google in a consistent way. So again, when I talked about at the beginning how organizations either don't have this information accessible or don't internally, have the resources to do it, that's where companies like ours have to step up and set up entire teams that are basically adrenaline junkies, because this stuff shifts constantly all over the place of where this information is coming from, and all they do all day long, is try to stay ahead of the infrastructure where those data points are, and make sure that those feeds coming into our marketing partners have data flow at a quantity they can trust, and don't go blank. It's one of the the probably only places in data that data going blank, frankly, is a huge problem, because we're pulling this information. It's not through a standard API, because those APIs are too limited to really give marketers what they need. That's so interesting. Yeah, it's it, literally, I feel like we could have, you know, a whole podcast season on all like these topics, because they just, they, they're all encompassing. And that's where it's like, you all are the experts. I am very much not. And it's, it is just so fascinating, because I always am learning something new on this episode. And I want to circle back to kind of, like, customer retention, and talking about when we're talking about good data, because it's not just right. It's not just about like, enabling your team to work better, to work faster, to work with better data insights. It's also about like, it benefiting the customer and so that you can better retain them, better have that so that they can have a better customer experience. So I'd love to hear kind of your take, given that obviously here we're all about customer retention, and kind of see where the two like intersect. Yeah, yeah. Great, great way to pull this together. So I think one of the easiest ways to do this is when we talk about customer journeys, because frankly, we work in this industry, but we're in it as consumers as well, and can really connect to our exhaustion and our fatigue the same way our customers experience this. When we're served up all sorts of data. That's wrong, right? They think we want to buy these certain products, so they're pushing it at us, or when we go on Google that we're really looking for this information we're not, and all this information shoved at us, and everyone feels the sense of fatigue. So if we aren't doing all the things we've been talking about, and we have the best, most optimized way of making those guesses, right, retention is right there, right? What's going to happen when we're exhausted from going to a site and we're just continuously served up this one kind of something because we looked for it once for a friend of ours, or whatever else, we're going to stop going because it's exhausting, and it's like you can find this anywhere else, right? There's tons of competition out there. So I think just people are talking about the right thing, which is consumer journey. It's like, what do I experience no matter what site I go to for your brands? And how can we, first of all, measure what we can then manage by pulling that data together in a way and then consuming it? In that control tower methodology, where it isn't overwhelming anymore, it's now calling my attention to the areas I need to address so I'm not wasting all this time trying to manage what isn't manageable, so that at the end of that whole piece, what the customer really sees and what's placed forefront for them is accurate, and our best ability to put our best foot forward every single time. And I think that's a lot easier to talk about than it is to do, and it's changing so much right now. Even when we have it figured out yesterday, it's hard to decide what we're going to do tomorrow, because it's shifting under our feet,
Mariah Parsons 30:43
and it's really, you know, whether it's this podcast or working with partners that you trust, surrounding yourself with this council of people from all these different angles, be it data or retention or, you know, tons of other places and operations. That's how I think will be the most successful with retention is like taking all these pieces together and using it to again, like consistently evaluate and make those changes in our organization that feel like the next, and the data proves are the next right step. Yeah, yeah, for sure. So with the customer journey, because that's, that's it. You're so right. You're so right in that it is so intricate and so exhaustive. When you're searching as a consumer, when you're searching, you know, for one thing, and maybe it's even for a gift, and you went, you know, you went and bought it already and then still being served to you, you know, months later or something, you're like, Oh my God. I'm just excited and exhausted, and now I'm getting tired of seeing this brand or this product or whatever, or like similar products. And so I want to ask when you're talking about, like, serving and using data, really smart data, clean data to serve, really intentional, but not over exhaust someone, I feel like a lot of consumers, especially those who maybe aren't in marketing or in the tech world, they like, you know, you're you're talking to your friend about a product, and then the next minute, it's like, your phone has that product, right? So I think, right, you're like, it's like, even type this in. How is this awesome, exactly? So I'd love to get your opinion on this, because I think it's such a delicate balance of, like, using smart data, but not like scaring someone, not scaring a consumer. Of like, wait a minute, that's like, too good now, because there's like, such a big um hurdle for the consumer, I think to be like, Whoa. Like, a hold up and like, like, that's creepy now and then it also, like, it turns them away from, you know, shopping with a shopping with a brand, or shopping with a technology, or some something, something so, talk us, talk us through. How you kind of like, I guess, do that dance.
Rochelle Thielan 32:54
I would love to have the answer for you so many other people. I think the reality is this is a personal decision for a brand, right? Depending on who your own ideal customer profile is, lots of things with demographics probably to come into play too, with how comfortable people are and used to having and really what feels like, in certain cases, an intrusion of privacy just be part of their life now or not. So there isn't, at least from my perspective, any one answer for that. I think what, what I really view our role to be is to be providing the best data we can across the sources that we have. And that's really where our role stops. We aren't there to make those decisions for brands. We're happy to be part of conversations. I love talking about these things too, and I think one of the things having a good partner should be used for are asking them, the smartest people go to partners like us and say, What's everybody else doing? What do you see out there? What's changing right now? What new shifts are people making? And use that right to get ideas of their own for things that work or don't. But as far as, like, a one size fits all, oh no, yeah, there never is right, like, I wish, yeah, yeah. I think it's a good point of trying to just have all the options on the table, and then the brand can decide if, like, okay, maybe, you know, our demographic is XYZ, so they're not going to respond well to this versus okay. Maybe this demographic is more used to,
Mariah Parsons 34:30
you know, life being so interconnected across devices and across different platforms. And,
Rochelle Thielan 34:36
yeah, we think now. I mean, imagine kids who are in middle school and high school now, they're probably gonna have the opposite reaction of, like, how could they not be telling me this while I'm just, like, thinking of it as a thought and not even saying anything? So Exactly, yeah, the world keeps shifting. And I think that's the thing is you gotta, like, keep talking to people, talking to your customers. And using the data that's available to be changing along with that for sure.
Mariah Parsons 35:05
So one more question about the customer journey aspect of it. Do you see, obviously, my experiences in the post purchase side of things, it's where I've, you know, focused as a marketer with Malomo. And so do you see, like, a difference in, I guess, the importance of data for pre purchase and post purchase, or is it like across the board, across all the customer journey? It's across the board, and it even starts at customer acquisition, like before people are even buying it like you're talking about SEO is a great example of pre customer purchase, as well as like lead sourcing for businesses, if they're going out there, and even how they're distributing products, which is like a different form of customer journey. But
Rochelle Thielan 35:51
a lot of these tactics are being applied in multiple different ways, but really kind of have the same general ideas and flow behind them. Yeah, okay, amazing. Thank you for fielding all of my questions. Yeah, and so great. Rochelle, thank you for making the time. Like, I know I just, I always it's a tough to, like, balance myself of I'm like, Okay, I want to just have, like, these episodes be so long and like, five hours and just continue talking. But that is just not realistic, right? So thank you for making the time. It is. I'm going to wrap us up because this was just, it is fantastic. And I know there's a lot for people to dive into in this space, and I know there's just like, we only are scratching the surface with this episode, but I know it's, it'll be a great one for our audience. So thank you. Yeah, well, if anyone ever wants to spend another 1520 minutes? This is how I learned so much, too. So I am all in for the conversation at any point and anytime.
Mariah Parsons 36:55
Hello, everyone. It's Mariah again. I am just popping in to say thank you for listening to today's episode, and I am so so so grateful that I have been able to be on this journey for the past couple of years with this podcast, it's been phenomenal to grow and see our community of 1000s of listeners. See what you guys are up to, what you're learning, what you want to hear about next. So if you haven't already, please like and subscribe to the show so we can continue doing this. Leave us a review. Let us know your thoughts. Follow us on our new social media channels and check out our newly launched website. If you or someone you know would be a great guest for the show, please do not be shy. Fill out the form that we have on there, because those are some of my favorite interviews, and I will make sure that our new website is linked in the bio. It's retention Chronicles, podcast.com and as always, let's give a warm shout out to our day one sponsor, Malomo. As you already know, Malomo is an order tracking platform that enables Shopify brands to take control of their transactional email and SMS through branded order tracking. What does that mean? That means you ditch those boring carrier tracking pages, the all white pages that have nothing on them but a tracking number, and update on the date of your estimated arrival, and swap those with pages that actually match your brand and can help you convert on some of your goals, customers like you and I obsessively check that tracking page when we're looking for our order at our doorstep an average of 4.6 times. If you can believe it, yes, customers are going to that page 4.6 times. So don't waste out on all that customer engagement and instead send them to a page that converts in the way that you want it to. I am talking dealing with shipping issues, having cross sells and upsells, having your social media on there, your loyalty programs, anything, anything that you can imagine. So if you want to learn more about how to do that, go to go malomo.com that's G O M, a, l o m, o.com and if you didn't get that, don't worry. That website link for our sponsor, as well as our podcast website are linked in our episode description. So with that, I will sign off and see you all next time you.
