Name: Turn Your Data Into Sales with Mailchimp Analytics
Uploaded: 2026-02-26T17:30:53.312Z
Duration: 24 min 40 s
Description: Turn Your Data Into Sales with Mailchimp Analytics

Transcript for "Turn Your Data Into Sales with Mailchimp Analytics": Nicole Jane. She's our senior staff product manager for analytics. Nicole, I've only been on the team a short while, but I know I've seen so much change in this suite, and I know you've been here quite a long time. Before we get into the details, I'd love for the audience to hear from you. Tell me, what is it about building these reporting tools that you find most rewarding? Well, obviously, I love Excel, and I love charts and data. But truly, the fun part has been taking raw data and turning it into tools that people can use every day, like our subject line generator, send time optimization, and behavioral prediction. So that data isn't just something you look at. It's something that works on your behalf. I'm really thinking about our subject line generator, where we mined millions and billions of subject lines that have been sent through Mailchimp to find the best practices that really drive open rates. And we baked all of those learnings into the AI's instructions. The win is how rewarding it is to see a marketer realize they don't have to be a data person to get an edge from data. I really wanna make the data work for marketers so they can stay focused on building their brand and not spend cycles on the manual work of reporting. I love that. So you're the data person that helps people who aren't data people. That's. exactly what I've seen here too. As I mentioned, I'm newer to the team, and I've been looking at the the tools with a fresh set of eyes, which I think is always a a good perspective to have. It seems like there are so many businesses that really have a lot of robust data but aren't quite sure how to move from a report to a sale, and I think it's actually pretty common. Many businesses are growing so quickly, they're just scratching the surface, and some haven't even had a time to set up some of the foundational elements that that we believe in, like a basic welcome automation or even other automations that actually can do a lot of the heavy lifting and work to engage customers in the background and drive revenue so you can focus on other tasks. So that's really why we came together today to put this session together. We think there's a massive opportunity to turn those foundations into consistent revenue. Exactly. People think they need to do something incredibly complex to see a return. They're gonna triangulate 95 reports across three years and come up with a magical answer, but it's really about unification. When you bring your email, your SMS, and your store data together from places like Shopify or Wix into one single view, the easy wins just start to jump right out. Yeah. And I really noticed that with the predictive tools as I came on board. It's not about necessarily doing all the math yourself. It's about the fact that all of this data is feeding into one simple output. So it tells you where to focus and why, whether that's identifying customers ready to replenish, those who need a win back offer so you can spend your time where it actually moves the needle. So before we jump in, we're gonna demo some products and just talk about some of the context in reporting and analytics. I wanted to do a quick temperature check with a poll. So for the audience, which of these best describes your current data relationship status? A, data. I just check my open rates and hope for the best. B, I have some data, but I'm not sure how to turn it into an email or sale. C, I'm using automations, but I wanna see what else I can be doing. Or d, I'm a data pro, just looking for new shortcuts. So throw your answer in there. We'll give folks a few minutes. While this is going live, I also just wanted to go over a few housekeeping items. First, please submit questions in the q and a q and a box at any time. Some of them may be answered in the chat. Nicole and I will be back at the end for a live q and a, and we'll make sure we address some of those as well. Second, there's gonna be a survey at the end, so we'd love to hear your feedback so that we can keep improving our sessions and the content that we bring to you. And finally, just to note that this session is being recorded. So looking at the poll results, it looks like many of you are in that ARB camp, which is great. That's exactly why we're here and we structured this session, so we're gonna show you how to bridge that gap. A few days ago, Nicole and I met to record this session, so we're gonna roll the recording, and then we'll see you shortly for our live q and a. Marketing today is complex and challenging, and most marketers are doing a lot of things right. You're running email, SMS, and automations. You're tracking performance, but managing all these pieces can feel cumbersome and leaving you having to prioritize where to spend your time. Additionally, the challenge isn't a lack of data. It's connecting, interpreting it, and having the time to do so. This can lead to missed opportunities and lost revenue. For example, e email performance may live in one report and SMS performance in another, making it difficult to compare how each channel contributes to engagement or conversion as you look across an entire campaign. Without a unified view, it's hard to answer practical questions like which channel performs the best at different stages of the funnel and how should that influence strategy. Analytics needs to help not just by showing metrics, but by helping interpret what they mean and what to do next. This is why modern analytics supports a full decision making journey. Reporting establishes a baseline, how your funnel performs, where customers engage, and where they drop off, but just understanding past performance isn't enough. Prediction helps you look forward, identifying who is most likely to take action, when timing matters, and where risks or opportunities exist. Action is where insight becomes impact, whether that is optimizing strategy, setting up automations that drive ongoing revenue, or personalizing engagement based on what the data is telling you. Today, we are going to walk through this progression from reporting to prediction to action. So let's start at the foundation, reporting. Before you can predict or personalize, you need a clear view of your funnel and engagement across channels, email, SMS, and automations in one place. That means connecting marketing activity to outcomes from your online store. With integrations across Shopify, Wix, and WooCommerce, ecommerce data becomes part of the picture. So engagement, conversions, and revenue can all be analyzed together. For example, seeing how email supports early engagement while SMS performs closer to checkout can directly inform how you sequence campaigns and design your fund. Nicole will now show you the marketing dashboard and how it brings everything together. Alright. Let's set some context here. The marketing dashboard gives you a unified view of engagement, conversions, and revenue across email, SMS, and automations. Instead of reviewing separate reports, you can easily compare how different channels and campaigns contribute to conversion. Plus, since Mailchimp is the delivery engine, the data is fresher and more actionable than a third party business intelligence tool. The dashboard also services insights that highlight patterns, helping you understand where to double down, where to adjust, and how to evolve strategy. Let's jump in and see an example. Alright. Here we are on the marketing dashboard. We should have had an outstanding month. I've really ramped up the volume of campaigns, but it's not translating to marketing attributed revenue. Let's see which campaigns are not pulling their weight. Okay. I can see that how to emails are driving the most orders, but they're not getting a great open rate. I wonder how the funnel compares for these campaigns. Alright. So when I come down to the funnel, I can see that these campaigns have a strong conversion rate, but they aren't landing with the right customers at the right time to get seen. Maybe instead of blasting my entire customer base with this how to content, let me try targeting it to window shoppers. I could even try dialing in the timeliness of Outreach with something like a browse abandon automation. I'd really love to send fewer big time intensive campaigns. I mean, we can all afford to work smarter, not harder. Am I right? What's next, Jonathan? Once you understand your baseline performance, the next opportunity is unlocking incremental revenue, not by doing more, but by being more precise and intentional. Predictive insights help surface where revenue is most likely to come from next and where it may be at risk. They help identify which customers are most likely to purchase again, which customers may be drifting away, and where timing matters most. That enables you to know exactly where to spend your next marketing dollar. And that's powerful because it shifts marketing from broad outreach to focused action. Instead of sending the same message to everyone, you can prioritize the customers most likely to convert or churn and engage them with personalized messages designed for that moment. In practice, predictive insights help you both protect revenue you might otherwise lose and capture revenue you might otherwise miss. You do this identifying which customers to prioritize and then enabling targeted follow ups, such as a replenishment reminder, a win back message, or an automated recommendation, and the moment it's most likely to make an impact. Alright. In the conversion insights dashboard, predictive signals like likelihood to purchase, predicted next order timing, and churn risk help you prioritize outreach to the right customers at the right time. We're using all that rich history, what email content they've engaged with, what they've browsed in your store, and what they've bought to illuminate future buying behavior before it happens. Let's take a look. Here, we are looking at the predictions for our lighting brand that sells online. I can see that I have a healthy population of first time buyers ready to convert. This is a great group to target content that goes from our broad brand introduction into maybe our category bestsellers, and I can target a campaign directly to them with a segment. And I've got an outlook into who is ready to repurchase and when, making them ideal targets for automated replenishment reminders. Let's set them up with an automation that reaches out to them thirty days before their expected date of next purchase. Alright. But I've got a bit of a leak at the bottom of my retention funnel with this group who's showing signs of disengagement. They are who I should narrowly focus a win back message before it's too late. Now I've uncovered these new strategies to drive sales and identified exactly who needs to hear from us next. But identifying the opportunity is only half the battle. The real magic happens when you stop looking at the data and start acting on it. Jonathan, how do we take these specific groups I found and actually get them moving through the funnel? That's the perfect hand off, Nicole. This is where prediction naturally turns into execution. Once you know which customers are most likely to act or those most at risk, you don't have to wait. You can immediately take action by creating targeted segments or triggering the automations that we just identified. For example, a high likelihood to purchase segment might prompt an automated follow-up with personalized product recommendations while while a high churn risk group might trigger a reengagement flow. At this stage, analytics is already driving action by helping you focus your marketing where it where it has the highest likelihood for impact. As analytics becomes more advanced, another challenge emerges, balancing time requirements and data complex Even when the right signals are available, uncovering deeper insights, connecting patterns across campaigns, or exploring new strategies can require significant effort and expertise. Instead of manual reporting and analysis, imagine an AI powered chat experience that helps summarize insights, answer questions, and guide you towards deeper opportunities, such as refining strategy or setting up more sophisticated automations. More specifically, it can clearly explain what happened, why it happened, what that means, and what to do next. This can help you quickly diagnose impact, anomalies when things don't go right, and connect insights directly to action, such as creating segments, running AB tests, and launching campaigns that can immediately improve performance. Okay. What we're about to show you is the analytics agent. Okay. What we're about to show you is the analytics agent, which is something we're actively testing in alpha with a small group of customers today. We're letting you behind the curtain here. This information is intended to outline our general product direction but represents no obligation. It's not a promise of future functionality and should not be relied on in making any purchase decisions. But rather it's a look at how we're exploring ways to help marketers act on data faster. Imagine you could talk to your data. This is gonna take intelligence that turns that fragmented data into insights, which saves you on manual work. Look at how the AI is able to take the last 93 campaigns and after some thinking, deliver key insights and uncover new opportunities with data backed recommendations. You can see how the output includes both immediate actions to improve campaign performance plus long term things to incorporate into your strategy. The goal here is obviously to reduce time to insight and support more strategic decision making, not replace human judgment. Now to Jonathan to wrap it up. When reporting, prediction, and action work together, analytics becomes part of the strategy, not just an exercise in reporting. It helps marketers decide where to invest, how to personalize engagement, and how to build programs that drive ongoing revenue rather than one off wins. This is how analytics can support smarter strategy, drive stronger customer relationships, and build meaningful business impact over time. To summarize things, we wanna leave you with the three key takeaways from today's session. One, move beyond basic reporting. Stop looking at clicks in a vacuum. Use a unified view to see exactly how your cross channel exit engagement from email to SMS is driving ecommerce revenue. Two, prioritize high value opportunities. Use predictive signals like likelihood to purchase to focus your time and budget where the data shows the most immediate potential for ROI. And three, turn insight into automated action. Don't let your data sit on a shelf. Trigger targeted automations like replenishment and win back flows we discussed so you're capturing revenue twenty four seven without the manual lift. And we are back live. So I hope those demos made the transition from data to action feel a lot more attainable. And seeing how an analytics agent can summarize dozens of campaign into a clear strategy is a huge time saver and such an exciting opportunity. The team is only early in exploring. So before we jump into your questions, just a reminder, when you submit a question, your name will be visible to everyone participating today, and you are providing this consent. So, Nicole, let's start with a question for you, as I assume most actually will be for you as the expert. For a business owner who's worried about data overload, how often should they realistically be checking their dashboards to stay on track? Yeah. That is such a great question, and it's exactly why we built a quick snapshot of your entire program right into the Mailchimp home screen so that every time you log in, you can quickly scan and monitor for what's changed. We've even got little red and green indicators so it will draw your eye to exactly what needs attention. I think that's enough to to really, like, do your quick pulse check. But I would really like to see marketers spending, you know, time with with their program analytics in the marketing dashboard weekly, it's important to see those week over week trends so that you can adjust strategy, before the month closes out. That gives you enough time to ramp up a campaign, change an approach, try a different, content strategy, all of those things you need to do to drive sales. So about weekly is when you want that, like, high level view. That makes sense, and that's how great you can make it really easy to find the insights and really easy to react quickly to change within the month and really drive impact. One other one for you. For those who might not even have a welcome flow or automation set up, where what is the first report they should look at tomorrow morning to find a quick win? Oh, yeah, definitely. So every automation has a dedicated report page. And that's where you're gonna go to see the number of contacts that are entering the automation and completing it. So that's that's your first stop. The automation report, is this thing even working and reaching my audience? And that's where you're also going to get the high level engagement and attributed revenue. After an automation has been running for a bit, again, is your week over week check, You you should be thinking about how it performs in context of your entire program. So when you are on the marketing dashboard, you can see how that automation is contributing to conversions amongst everything else you're doing. So that's your second stop. First, automation report. Second, marketing dashboard. Awesome. And if a customer or if someone's worried about over messaging their list, what dashboard should they use to show if email and SMS campaigns are either working together or maybe cannibalizing each other? Yeah. Again, that's exactly why we built marketing dashboard is to see all of your channels in one place. And it's a really good way to compare. We have that funnel experience so that that you can you can contrast how a different channel moves your audience from sends to to opens to clicks to conversions. And you can look at how the two channels work together to drive conversions, you know, in our charts. So you can kinda set what you wanna consider in your report, look at it all together. When we think about over messaging, I definitely want you to be looking at the mix of I'm thinking about engagement here. So which channels are driving let's just start with clicks. Clicks and conversions are gonna be your, like, positive signal, and then you wanna contrast that with the negative signal of unsubscribes. And so all of that is right there on the marketing dashboard organized by channel, super easy to get a quick pulse. Awesome. Maybe we have time for one more, so we'll let you really lean into your your data nerd side of yourself and the predictive insights, which I think are so exciting. So for likelihood to purchase and churn risk signals, how much data does Mailchimp actually need before those predictions become reliable? Well, that's that's the great thing about our new modern approach to modeling and all of the amazing things that AI is doing for us. Thank you so much. Our AI scientists have set the minimum threshold as having sent one email to your audience. With that and the connection to your store, we need both. The connection to your store gives us an incredible amount of history, even if it's a brand new store. We can still see all of the browsing activity going on. Are they at are customers adding to cart? Are they starting checkout? Like, those are super rich signals. And with that one email that you've sent, we know who is open and who is clicked, who is starting to warm up. That is really enough to set a pretty reliable propensity score. And that's what we use to power likelihood to purchase and churn risk signals. So it it works pretty well for a for a new a new user and a new store. That's great to hear. Immediate value. That's what we wanna hear. Yeah. I think that's the the all the time we have and are gonna be our last question for today. But if you didn't get a chance to ask yours or you really wanna go deeper in anything that we covered, feel free to reach out. We're always happy to talk through your specific use cases. So a big thank you, Nicole. You were fantastic today. Thanks to everyone who joined us. And, again, if you want more tailored guidance, the best next step is to connect with our digital sales team for a demo or a quick conversation. Our team is all always ready to help you bridge the gap between data and sales, so that's whether you're looking to recover revenue at risk or automate your next replenishment cycle. We'll show you how Mailchimp Analytics can help turn that data into your most powerful sales tool. So thanks again for spending part of your day with us, and have a great rest of the afternoon. Bye.