Matt Zambrio: Enjoy those activities by Moeez. Next up we have Heather Dawson, eCommerce marketing executive and product marketer specializing in brand building and growth strategies for online businesses. She’s going to be presenting on from browsing to buying, using AI to personalize the journey. Hi Heather, how you doing today?

Heather Dawson: Hi, hi Matt, doing great, how are you?

Matt Zambrio: I’m doing well, really excited to have you on, looking forward to your presentation.

Heather Dawson: I’m excited to be here, thank you so much for having me, and thank you to the whole Cloudways team, it’s been such a great event to be a part of. Hope you guys are all having a great time learning a lot, I think there’s a lot of themes here from what I’ve been seeing, and I’m excited to share a little bit about what I’ve come to know throughout my journey and some of the research that I’ve been doing about e-commerce personalization, so let’s dive in.

So first, just a quick introduction, who am I? Thank you for the intro, Matt. I am the founder of Perspective Growth Partners, and I help companies scale through smarter marketing strategy, stronger products, and exceptional customer experiences. I’ve spent the last 20-plus years at some of the world’s largest brands, including the last 15 years at Amazon, which for most of you probably on this call, that’s been a wild ride of growth in and of itself.

I was first an operator leading marketing teams, launching industry-defining products and scaling multi-billion dollar businesses, and then I was a trusted adviser to Amazon’s most senior executives, directing strategic initiatives that influenced products, organizational strategies, and go-to-market strategies across Amazon’s global ads and stores businesses. And this was all really working on behalf of small business customers, both advertisers and sellers on Amazon’s platforms, so my experience really lies in aligning marketing strategy, product innovation, and customer experiences to drive sustainable growth, which I hope resonates with some of you.

Okay, so diving right in, I’m really excited to speak about this topic today because it’s one of the hottest topics in e-commerce. I know you can’t really escape AI in the news these days, and personalization across the customer journey is such a wealth of opportunities for customers, particularly small businesses today. It’s been said many times now and it’s absolutely true, we’re living through such a time of tremendous change in how we work and deliver for customers using this incredible tool, that my aim is really to give you some ideas for how you can think about and maybe start implementing, if you haven’t already, some AI tools across your customer journey to improve discovery, conversion, and retention.

So as part of this today, we’ll level set on some of the current AI capabilities, the benefits of AI-based personalization, evolving consumer expectations and behaviors, and I know you’ve touched on some of these already. Fati spoke about them the other day, there’s just so much to know, but I’ll touch on some of the big ones, and then some of the issues surrounding AI implementations along with some implications to consider for your business.

We’ll dive into, let me get my notes here, I’ll share really a framework to inform your mental model for how you can use this powerful tool, and then some strategies and specific tools to explore. I know folks always want specific examples, there’s so many, and I promise I’ll give you some, but rather than answers, I’m really hoping to inspire you to ask great questions and answer them for yourself, your customers, and your business. And I think we all know you’ve probably used some of these tools even as just a consumer, it’s really about asking questions and tuning your questions to get the most out of these tools.

And so today, my hope is that you walk away with a more informed foundation for thinking about and using AI to personalize your customer’s journey, and that you feel really inspired to continue to learn and develop your skills. This is such an incredible time in history where marketing, technology, and customer experience are converging in really exciting ways, so let’s dive in.

All right, so it’s no secret that AI-enabled commerce is growing rapidly, and that’s kind of a loaded term, basically it’s where AI is assisting commerce. 8.65 billion this year, up to 64 billion by 2034, that’s just a massive hockey stick no matter how you look at it, and it’s touching every facet of e-commerce. The vast majority of companies out there are experimenting with or using AI and plan to increase their spending, so this really indicates a shift from not just testing and pilots but really to full implementation, so if you’re starting your journey, you’re not alone dipping your toe in the water, but dive in, it’s fine.

I love this quote from Alan Watts, by the way, it got a little cut off there, this is from like the 1970s, but still so relevant today and really speaks to the mental model around change more than anything. And so really, at the end of the day, why you should care for your business, personalization really powers profits, that’s a lot of P’s I guess, but it’s really about increased relevance, higher engagement, better conversion rates, and stronger customer loyalty, so that’s the foundation and the why.

So obviously it all starts with the customer, and what’s really exciting about AI right now is that it’s helping us as marketers and leaders meet customers where they are. That’s a phrase that’s been said a lot in the zeitgeist in the last few years, but it’s just so true when it comes to the power of these tools, and consumers really expect that personalized experience, 73% expecting companies to understand their needs. It’s no longer that you see an ad and you think it’s creepy if it says your name or if it has a product you just shopped for, that’s really expected by consumers today, so feel good that you’re going in the right direction, and you as a consumer probably feel this way as well.

I think one of the biggest and most interesting areas of this whole user journey, and we’ll talk more about this in a few slides, is discovery, it’s really undergoing such a massive transformation. Nearly 60% of searches don’t end in a click, this is wild, and I cited HubSpot here, but this has been in the news, lots of sources around this recently. So that means consumers are purchasing faster, not necessarily less considered, but they’re finding the information they need and it really helps accelerate their purchase decisions, 47% faster according to one study done by Rep AI, so it’s helping reduce some of that hesitation, shortening the product discovery phase, and removing friction at checkout.

So all this is great and pointing in the same direction. To kind of level set, we’ve probably got a mixed audience in terms of how knowledgeable, so I want to quickly touch on what agentic AI is and how you can think about that compared to some of the other terms in AI, specifically generative AI. Generative AI, a couple of years ago this was the big buzzword, that’s really around creating new content, whether text or images based on user input, that was the beginnings.

Agentic AI is really independently thinking, planning, and acting by orchestrating multiple agents, and not to get too technical, but it’s using multiple AI models going through sequences that use multiple LLMs as that brain to interact with the tools and systems and execute more complex real-time actions. And there’s four main components of this, this is a non-technical description, very high level, but it’s really about making its own choices, those autonomous decisions based on its understanding of the situation rather than relying solely on predefined rules or human input.

It plans ahead and follows through, anticipating those future scenarios, developing strategies, and executing them without the need for constant oversight or direction from humans. It adapts to what’s happening, so it can dynamically adjust its behavior and decision-making based on changing circumstances, allowing it to respond effectively to evolving situations. And then it works towards those goals without constant direction, working independently to set and pursue its own objectives, taking the initiative to achieve the desired outcomes. So what that all adds up to is really exciting possibilities across this entire space, for both data-driven decision-making and the customer experience.

So all that sounds amazing, and it is, but it’s not perfect yet, and it’s not the proverbial silver bullet here. While AI promises a lot of things, there are some things that are more the reality right now that need to be said and level set. One-to-one marketing at scale is the big promise, being able to treat every customer at every stage of the funnel in a unique way, Heather, I saw you browse these shoes, I think you should come back and buy them, that sort of thing. It’s not a replacement, and probably will never be a replacement frankly, for an ideal customer profile that really taps into all of the insights of your customer and rounds out that persona.

And cohorts, we’ll talk about this in another slide or two, but cohorts are becoming so important for how you show up in agentic search, that it’s something you really should continue to pay attention to. So this is an and, and not an or, as you’re thinking about your customer, it’s not hands off the wheel yet, there are parts that claim to be, but it’s really kind of a partner and not a replacement.

And I think underscoring this, it’s not a replacement for human creativity, passion, critical thinking, oversight, these are things that are inherently human and are not going away anytime soon, in fact a lot of people say they’ll never go away. The future is yet to be written here, but definitely a partner. And then this democratization of data and information, we’re all inundated with so much data every day, and the entire world of data available on an enterprise scale has been massive, big data. I laughed with my husband the other day, machine learning was a thing at Amazon 20 years ago, so this has been actively in the space, but it’s really becoming accessible, and that’s pretty exciting.

However, and this is a big however, and it will always be forever and always true, your outputs are really still only as good as your inputs. So making sure that you have clean, structured, labeled data going into these models that you’re using is just so important to getting the results you want. And another personal anecdote, my last job at Amazon, I mentioned I was advising senior leaders, and our role was really to gather data, talk with customers, evaluate solutions, but what did they really want from us? They wanted the critical thinking, the perspective, the so-what, what-now.

And so that’s a very human way of thinking about amassing all of these inputs and really thinking about what does that mean for your business, and I would argue this type of critical thinking is really not going to come from machines and from a chatbot, those are partners to help you in your critical thinking. But the innovation, the risk-taking, the looking around corners, that’s what humans are good at, and I would encourage you to think of AI as an extension of you and your team. AI is a tool that you need to learn how to use, just like you needed to learn how to drive a car back in the days of horse and buggy when the car was invented, you got to learn to drive, but it’s a very powerful tool.

Okay, so like most changes, and this is a really big one that we’re living through, pretty exciting but also not without its challenges, it’s kind of lumpy. I think hopefully this resonates with some of you who have tried these tools in the past, but there are some real challenges here, and it’s important to think about these and make sure you’re thinking about your organization and how you’re approaching this in light of these challenges. Small and medium-sized businesses, I’ve classically spent a lot of my career studying SMBs at this point, limited bandwidth constantly comes up, often wearing many hats, lacking time and resources, this is a real thing and despite good intentions can be a hurdle for a lot of companies.

Maybe previous attempts at using some of these tools fell short and people are feeling skeptical or hesitant to invest further, that’s real, that’s definitely true. Marketers today and business leaders generally, incredible pressure to deliver ROI, and the good news is the promise of AI is that you will find more ROI, but this idea that you need to deliver today is a lot of pressure and maybe causes people not to spend some time diving in where they could. And then finally, foundational tech or data issues, data organization and access, fragmented data sources, poor organization can really hinder effective implementation, so those fundamentals are very very important.

And then this slide got a little munched, but really personal hurdles are something you can’t ignore either, for leaders of teams, and maybe for yourself as well. Feeling a little uncertain, negative, worried about job security, behind, not sure where to start, feelings of inertia. I love this image of this cat, he’s feeling very sluggish, but it’s a lightweight way to say these are real feelings your employees might be feeling, you might be feeling, and it’s okay, we’re all learning together, you’ve got to go into the learning pit and accept that you’re going to come out the other side better.

And so overcoming these challenges really requires a strategic approach, that’s what we’ll go through next, that balances the potential and what’s possible with some of these practical realities and limited resources. The great news is the tools are getting better all the time, and this is such an incredible time of year to be thinking about how you leverage one of the highest volumes to start thinking of things you may have only dreamed of, but can you test small and on a large scale because of the time period, quickly to get some data and inform your strategy going into next year? And I see the comment from Curtis there, solopreneur, I understand, it’s real.

So let’s dive into building a strategy. This is a really simple slide, don’t confuse simple with easy, never do that. Building the right strategy, how do you stitch together the right mix of solutions, and when you think about these solutions you can think about them in a range, from in-tool solutions, maybe you’re using tools today that have launched AI capabilities, that’s fantastic, start there, and I think that’s where a lot of small businesses have started according to some of the data I’ve been seeing. And then there’s full custom implementations that leverage your data with open-source models, or fully private models, and everything in between.

I’ve focused more on the DTC and a little bit of the marketplace experiences, but this is such a wide range of solutions right now, I actually just saw another solution yesterday that was pretty exciting, got a $25 million seed round, it’s pretty hard to even map all the solutions right now. So this is not an exhaustive list or all the answers, this is a starting place, but what I would say is, I’d be remiss spending so much time at Amazon not to say start with the customer, that’s probably pretty obvious but so important. So what are your customers’ problems, what are they trying to do, and how can you solve those problems, getting really crisp on that is the foundation and the starting place, and if you do that well, everything else follows.

Considering the full journey, but really thinking about where you can prioritize the largest areas of opportunity for your customers and business. Maybe you have a large repeat customer base, I worked with a customer that had 40% repeat customers, but they didn’t know who their highest value customers were and weren’t doing anything to stimulate that, that’s a very basic example, but analyzing and thinking about your customer needs and then how can you address that as a business and where your pain points layer together is the way to go.

And then thinking about AI as a tool to deliver on your promise. This sounds really simple, the flip side is, oh, there’s a shiny new tool, I want to go use that, that sounds cool. Well, yes, stay curious and stay excited about the space, but really, how does that fit in your strategy, is that solving a customer problem that’s worth solving for your business, so coming back to this as a touchstone.

So where can AI help? This is not the journey map, it’s a diagram to lay out some of the areas where AI is pushing into, and it’s most areas in e-commerce right now. AI really enhances e-commerce personalization by using machine learning to analyze real-time customer data for tailored product recommendations, content, improved support through AI-powered chatbots and experiences, and more. Key applications right now include recommendation engines, predictive analytics for anticipating those needs, anticipating customer needs more holistically, smart search functions that understand intent, visual search is layered into that, which is a really exciting area.

I’ll plug Amazon here one more time, Amazon’s been using this, I use it all the time, Google has a great solution for this as well, so that’s becoming more available to small and medium-sized businesses. Personalized content and marketing of course, I think this is the one I naturally think of first, that one-to-one experience versus broad targeting. Chatbots, maybe one that you’ve experienced or implemented, this is where a lot of companies started, trying to shore up their support, available 24/7, such a big game-changer and meeting customers where they expect to be met with answers.

And then finally, I mentioned this one, dynamic pricing, I don’t go into it in depth, and I would say be careful, it’s been in the news recently, some really large CPG companies in not so nice of a light, and in probably a customer-trust-eroding way, have been dynamically adjusting prices. Customers don’t like that very much if it’s fully transparent, so be careful if you go down this road, but AI can analyze market data, customer behavior, and adjust prices dynamically, which can help optimize revenue and profits, which is important, if your company’s not in business you can’t help your customers, is the bottom line there.

So thinking about all of these areas, I wanted to simplify this a bit, that’s a very wide range of things, how do you find those high-impact use cases? Really the world of possibilities broken down into three stages is how I’ve structured the rest of this, discovery, conversion, and retention and loyalty. Every business’s growth path is going to be unique, my challenge to you is to think critically about your business, what are your customers’ biggest issues, what repetitive processes exist that can be automated, and start there and build the muscle required to adopt AI solutions across the full journey, you don’t have to do it all at once.

So the following slides have a few guided prompts and then some ideas in terms of strategies and implementation you can consider, and after that I’ll go through some specific examples for each of these journey stages that I personally like. So diving into discovery, we talked earlier about changing consumer behavior when it comes to product discovery, and while full shopping agents are definitely emerging, we saw on Tuesday with Shopify’s announcement, that agentic generative engine answer is rapidly replacing traditional search. So thinking about how you can use the data you have to develop segments, cohorts, and then use that to feed your content engine for these agentic experiences.

So AEO, GEO are some of the acronyms being used right now, but basically the answer that’s popping up in ChatGPT and the others when a customer asks a question. What questions are being asked, and I could spend a whole session on this, and I’ll also say anyone who says they know exactly how this works, you should be very suspicious of, because it’s evolving very rapidly, there’s a lot of black-box sort of inputs and calculations behind the scenes in terms of what is actually being shown and how it’s being crawled, it’s a new space. The good news is it seems the basics of SEO still apply here, but the implementation is a little bit tweaked.

So the real point is thinking about your audience and what you know, and using that as the input into some of these newer experiences and your content. All of these experiences, all this data, is a gold mine to make both those one-on-one interactions and your segmentation better. I would also encourage you, if you haven’t already, to dive into how is your brand showing up in the conversation, in AEO, GEO, in search, in your product titles and descriptions, this is probably already part of what you’re doing to optimize your listings if you work on platforms like Amazon and Walmart.

And this is probably pretty obvious and simple, maybe not in execution, but is your message personalized? How much of your outbound across your paid and owned channels or email is personalized, maybe that’s a place to start. One of the most exciting things of recent years is that there are AI-based solutions offered by pretty much all of the major ad players, Google, Meta, TikTok, and Amazon being some of them, offering some pretty cool things that are AI-optimized. Now, they have their downsides, but they can be a huge time-saver.

And last but not least, what is your test budget? A lot of times companies are like, oh yeah, we’re testing some things, is it off the side of your desk or a structured test plan? 10 to 20% is that best-practice range, and you should be thinking about this in terms of time and money. I actually hired a woman at my last company whose job at a small business was really this, I thought that was pretty unique, but so important, this really has to become part of the rhythm of your business.

All right, moving on to conversion. Similar to discovery, personalization with AI can really boost conversion across most touch points. I’ll hit on a couple of solutions in a bit that are looking at the full journey, so it’s not just conversion on your product detail page to cart, but really thinking about how you’re amplifying all of those conversions with real-time data analytics and decision-making that agentic AI allows. So starting with your data and analytics, getting really curious, this is an area where AI can accelerate and amplify your capabilities as a small team, democratizing some of those deeper analytics that only large companies had at their disposal in the past.

Some of the most basic low-hanging fruit, and honestly this was an area where we brought ideas to Amazon to implement on behalf of customers, abandoned cart, was something the ads team actually wasn’t allowing anyone to target for the longest time. It’s just such a great way to follow up and gain additional conversions with consumers who maybe just forgot, we’re all so busy, if you do one thing, set up an abandoned cart flow, and that can be done with SMS or email. And then, what do you know about your customers that can feed a more personalized content experience, is it a low-funnel page, a great bundle offer, these are great ways for cross-sell, upsell, lots of strategies around holidays.

And then the action items, tools and strategies, data audit for outdated data, inconsistent structure, labeled data, so important. A lot of times businesses as they’re growing and trying to move fast, this becomes a really big debt in the future, so thinking about that as you’re scaling is important. And then finally, last but certainly not least, I think this is one of the most exciting spaces, I’m not a retention and loyalty expert, and maybe that’s why this is so exciting, that there’s such a democratization of these tools for a small business use case.

Most of you are probably generalists with a lot on your plate, this can really simplify what is pretty sophisticated marketing, large teams at enterprises handle this type of work in my experience, and you can get access to it with very slick and easy-to-use tools now that leverage AI. So the goal is improving customer retention and loyalty, but that incorporates satisfaction, support, repeat purchase, recommendation, and other social proof, and this is one of the largest levers to improve your lifetime value to customer acquisition cost ratio.

And if you’re like, what is that, it’s just going to reduce your cost to acquire customers, you don’t have to acquire as many, you’ll probably still want to acquire some, but retaining them is a lot better and less costly. So who are your highest value customers, do you know who they are, are you using targeted campaigns and content, do you have a loyalty program, these are things AI can now help you do. You want to feed those owned and operated communities and loyalty programs and consider the short and long-term priorities, these are strategic large initiatives that might take months, so start small, don’t try to do everything at once, and take advantage of that holiday volume to experiment, learn, and adjust.

And so I know we’re running a little short on time, so I did want to share a few of the solutions I think are really interesting, and these are more of that mid-market, but a lot of these can be scaled up and down. The first, I’d be remiss not to talk about Amazon, and a lot of these, without oversimplifying, I’m probably leaving out great solutions for any individual category, but these are the ones I’ve seen and think are pretty cool. So Amazon Creative Studio, this one is near and dear to my heart, we worked on this with the business team that launched it, it just got announced last month at Amazon Accelerate at the selling partner conference and it’s in beta, so very new.

This is a game-changer if you use Amazon ads and struggle with keeping up with creative or spending a lot on agencies, I know there may be some agency folks in the audience, but this can help you too. This is a simplified tool to create both display and video content from a single product image or from your website, a big step forward. Consistently in all the work we did around ads, creative and generating ROI were the two king and queen problems, so constantly trying to help businesses with this, I think this is a huge step forward.

The other solutions here are Performance Max and Advantage Plus, these are what I was mentioning before, those AI-based solutions. Performance Max is one all-in-one goal-based campaign you can set up, it’s got seven ad formats based on one set of creative assets, and you can run those ads across search, YouTube, Gmail, display, across all of Google’s network. The promise is hands-off, I already cautioned you on hands off the wheel, so it’s a trust-but-verify situation, but they do promise higher conversion, ROAS, return on ad spend, and they’re using AI for bidding, budget allocation, creative, cross-channel placements.

Meta has a very similar product, not going to dive too deep in the interest of time, but it’s that automated audience targeting, creative testing, budget allocation similar to Performance Max. On the conversion front, this ramps up and gets interesting as you go from the ad space into some of the more website-based and checkout-based experiences. Vermont is one that has been coming up, it’s a unique solution, I haven’t seen anything quite like it, it offers full-funnel customization, everything from an ad click to a product detail page to a bundle to offers and carts, and you can generate, test, and refine different experiences without dev work or touching your main site, which is a game-changer for folks who have dev teams who are equally strapped.

Microsoft Clarity Copilot, this is a free tool, so for those very small businesses out there, some really cool analytics here, can’t hurt to check out, very cool to see predictive heat maps, forecasting, click patterns. Shopify Magic, another Shopify solution, you’ve probably seen this, it’s getting better and better from what we’ve seen in my testing, one of the coolest new things it can do is convert chats to checkout, so something you might want to check out, no pun intended.

And then lastly on loyalty, again probably the coolest space because it takes so much data and information and makes it so accessible, Attentive, this is an SMS-first solution, so if you don’t have an SMS program or you’re curious, that might be a nice layer onto some of the things you’re doing, really slick segmentation, purchase prediction algorithms. I think I’m getting yanked off the stage, thank you Matt, Klaviyo and Retention X, those are my final recos. So I could talk for hours on this topic, thank you so much for having me. I wanted to just say in closing four thoughts, just get in there, experiment, and learn fast, don’t lose sight of your fundamentals and get distracted by shiny objects, and humans, we’re still important.

Matt Zambrio: No, thank you so much. Yeah, we do not have the Oscar music here to play, but this is fantastic, and we have so many questions that have come through in the Q&A. We unfortunately don’t have time for them right now, but we do just want to ask, as some closing remarks, what are your thoughts about Prepathon and your experience as a guest speaker with us today?

Heather Dawson: Yeah, thank you, this has been a lot of fun. I have to say I spent the last 15 years writing chock-a-block documents, which probably comes through in presentations, so it’s been really fun to get out and share the work we’re doing at Perspective Growth Partners with you guys. This is such a great way for us to come together ahead of such a huge holiday time period, everyone here has a time period of rapid experimentation at their fingertips because of the volume that’s likely to come through, so just really use this as an opportunity and get excited, get curious, I think it’s just the tip of the iceberg in terms of what these solutions can do, so hopefully you’re inspired to walk away and begin testing.

Matt Zambrio: Well, Heather, thank you, we really appreciate you coming, really enjoyed having you here today.

Heather Dawson: Thank you so much.

Matt Zambrio: All right, so next up we have Moeez back again for Two Truths and a Lie, the e-commerce edition, very excited to see what he has in store for us, we’ll be back in a couple minutes.