The Data Ecom Stores Ignore (Big Mistake!) — Arv Natarajan | How Analytics Fuel Ecommerce Growth, AI’s Role In Turning Data Into Insights, Tracking Search Terms To Find Customer Intent, Search Vs. Browse Behavior, Null Searches And Missed Revenue (#369)

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In this episode, we continue our three-part miniseries on eCommerce search, focusing on the critical role of analytics and reporting in driving online retail success. 

Host Claus Lauter welcomes back Arv Natarajan, Director of Product at GroupBy, to explore how robust data analysis can help eCommerce retailers make better decisions and improve their customer experience through AI-powered insights.

Topics discussed in this episode:  

• How analytics drive eCommerce success through data-driven decisions. 
• What role AI plays in transforming raw data into actionable insights. 
• Why tracking search terms reveals vital customer intent patterns. 
• How to pick the most important metrics for your online store. 
• Why search vs browse behavior impacts different retail sectors. 
• What null searches reveal about missed revenue opportunities. 
• How GroupBy integrates with Shopify's native data collection. 
• Why anonymous tracking delivers better personalization results. 
• What makes an ideal analytics solution for merchants. 
• How usage-based pricing works for stores of all sizes. 

Find the first episode of the mini series here:  https://ecommercecoffeebreak.com/future-of-ecommerce-search-ai/ 

Links & Resources

Website: https://www.groupbyinc.com/integrations/shopify
Shopify App Store: https://apps.shopify.com/groupby-ai-search-discovery
LinkedIn: https://www.linkedin.com/in/arvnatarajan/
X/Twitter: https://x.com/groupbyinc 

Get access to more free resources by visiting the show notes at
https://tinyurl.com/4wdh98kt 

MORE RESOURCES

Download the Ecommerce Conversion Handbook for store optimization tips at https://tinyurl.com/CRO-ebook

Best Apps to Grow Your eCommerce Store: https://ecommercecoffeebreak.com/best-shopify-marketing-tools-recommendations/

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Transcript

Hey there, this is Claus Lauter and you're listening to the eCommerce Coffee Break Podcast, the show that helps you become a smarter online seller. This episode is the second part of our three part miniseries about eCommerce search. We will discuss the critical role of analytics and reporting in driving eCommerce success.

Joining me again is Arv Natarajan, Director of Product at GroupBy. So let's dive right into it. Welcome to the second episode of our mini series on data driven e commerce and e commerce search. Last time, we talked about e commerce search and how to personalize the paths to purchase with the help of AI.

If you missed that episode, listen to episode 365. And today, Arv Natarajan from groupby and I will discuss the critical role of analytics and reporting in driving e commerce success. So we'll dive into this and explore how Robust Data analytes data. Analysis can help e commerce retailers. So that's what comes after the show.

I have for you today. Hey Claus, thanks for having me again. So let's continue where we, um, left off last time. Can you explain how analytics help to improve AI search for online stores? Yeah, for sure. So last time we spoke about really the first steps that a merchant should take. to start evaluating the performance of their search engine.

So first is, let's do an audit to see how the search performance actually is. Let's test some search results, test the user experience, maybe check with customer satisfaction to see how customers are actually perceiving the website. Now we want to talk about, okay, we've done the preliminary analysis. How do we actually dig a little bit deeper and identify the opportunities?

Some actionable insights, perhaps, which help tell us where we should focus. And that has to be through analytics. I think everybody's heard of data driven decisions. That's a pretty common concept. And really, it's critical in this space as well. We want to make sure that the decisions we take to improve the shopping experience are based on data.

And the main source of data for us should be how our customers interact with our website. We want to know what are they searching for? What are they clicking on? What are they buying? These insights will help tell us, okay, if they're clicking on and searching for specific products, but we don't actually carry them, we'll see that through the data.

We will see a, uh, we won't see any conversions or, or, or orders for a particular type of product or a particular category. Or if we are seeing, even on the flip side, if we're seeing some positive data, that should also tell us maybe we want to double down on that, maybe we want to send an email campaign, it looks like these backpacks are selling quite, quite quickly, and it looks to be quite popular, maybe there's a social media post that's made to go viral.

Let's maybe double down on that type of product to get more attention focused on it and and help our customers again with a more relevant, personalized, richer shopping experience. So analytics should be really a core part of what we do every day or every week, something we look at to understand how our site is behaving.

Um, I think analytics is something that a lot of merchants online sellers, they're really underestimate. Obviously. Yes. Data driven decisions. It's all over the place. Everyone knows that's the thing to do. I really wonder how many people are actually doing this now. AI helps a lot with that. Um, how does AI substitute the data that you've got in the past?

I don't think it substitutes the data. I think it helps. Use that data and generate actionable insights. So it's not, we're not using AI to replace the data that we're capturing. We're using it to take that data and then perform the analysis and help tell us or guide us on the decisions we like we should be making.

So an example might be like I've called out where the AI might be able to identify the products that we put into an email. Um, or the, and I think actually one of the things I really like about how far we've come from an AI and analytics perspective is how broad we can apply the insight. So it's not just also improving our.

Shopping experience, but it could also improve some of the side parts of our technology stack when we consider the e commerce shopping experience. So we talked about email merchandising, so that's a different form of merchandising, but maybe there's also some buying decisions that we can make if we know through these actual insights.

generated based on the data that we've collected that a product is running out of stock, for example, and, and, and that means then we need to make a buying decision to go purchase more inventory for that particular product. If the AI can help us with that, now we've not just improved the shopping experience.

It's specifically the shopping experience or the search experience, but it's our e commerce site in general. It's a bit more of a broader view into how the site is performing, um, and can help us in many areas apart from just the core search experience itself. Talk me through the day to day experience on your platform, what people are using, which kind of tools and features that they should use on a day to day.

Yeah, to me, I think analytics should be a core part of every merchant's day. I think it should be one of the first things that we look at. It is what happened in the last 24 hours, maybe what's happened in the last week or in the last month. There are various time periods they can look like, which will tell you different things.

If you're looking at it in the last 24 hours, this is more of a real time check into how your site is actually performing right now. But what you may miss in that is the forest for the trees, where if you look at it in something that's a bit more of a longer time frame, you can see how we're performing this month compared to the last month.

And you're looking at more general trends, which may tell you some other things. So one of the first things that I recommend every merchant to do is go into the analytics platform on Shopify. I believe there are some default analytics that are provided, but certainly look at what else is available on the marketplace to help you understand how your site is performing.

You want to be able to identify what are your top searches? What are your problem areas? Do you have any situations where your customers have abandoned their cart for whatever reason? And then you can dig a little bit deeper into why that's the case. But at first you want to understand these higher level key metrics.

that help you get a good picture of how your site is performing. And from there, you can dig a little bit deeper. And the first thing to do in fact, is before you even look at the data is to understand what are the metrics that you care about? Is it revenue? Is it conversion rate? Is it your bounce rate?

What are the different metrics? And there are so many out there. You shouldn't pick every single one of them. Pick three or four that are the most important ones for your business. And again, there are a lot of best practice guides out there and people you can talk to, which will help guide you in identifying the right metrics for your business.

I think one of the main metrics, and I think that should be a very simple one, is search terms, what people are searching for. What would you read out of these results? This, this is a very easy metric to gauge how your site search experience is performing and, and what your customers care about. If you see in that list of top search terms for the last 24 hours, or for the last week, for the last month, what your customers are searching for, you can draw from that some insights on whether or not they are, you are providing the right experience for them.

If you, if you sell apparel and you see a lot of search terms in therefore. categories outside of apparel, let's say food products or something else, then you know that there's a mismatch. Somehow you've got some customers that are on your website searching for the wrong kinds of products that you don't actually carry.

So what can you do in this situation? Maybe you can start buying some of those products to serve those customers, or you can guide them to a different shopping experience to cross sell and perhaps sell something related to what they're searching for. If, for example, they're looking for Recipes or something like that.

You can maybe have some kind of content on your website that guides them to the right path instead of the products that they're looking for, which you don't carry. There are many actions you can take based on that. But first is generating the insight, which is these customers are looking for things that I don't carry.

What do I do with that? So the, the top search terms on your website will help generate some of these insights. Mm hmm. Now, AI needs data, um, and depending on how much traffic you have on your store, data will build up faster or slower. What kind of priorities would you give, um, looking into understanding data on these different levels?

So conversion rates, revenue, customer satisfaction, do you look into every metric every day or Do you sort of schedule that over the months? I think you definitely want to pick three or four that are important to you that you look at all the time. So to me, if I was a merchant, it would be revenue would be number one.

I mean, I'm in the business to sell, and so I should be checking revenue. That is my number one metric. Now, if I'm looking at gauging the efficacy of various parts of my website, I might drill a little bit deeper. Am I looking at search revenue? So revenue generated from the search experience? Or is it revenue generated from the browsing experience?

Or is it revenue generated from email traffic? There are various ways that you can slice the data to give you a bit more of a targeted view into what is important to your business. So revenue, for me, always has to be one of the top metrics that I look at. Another one that I like looking at, I mean, I think retailers are familiar with conversion rate.

It, again, has to be looked at in a certain lens. It is not a one size fits all metric. So for me, for example, when I'm looking at a search conversion rate, I'm now measuring how effective is the search engine. And for every search that's performed, how many times do shoppers actually convert? That, to me, helps me understand, are we having a good, search experience that helps users find the right products that they're looking for.

And it's not necessary that if you have a poor conversion rate that the search engine is back. There might be other reasons why users are not converting. And then looking at this metric will help you identify, okay, this is a problem area. Let's drill a little bit deeper and find out what is actually causing the issue.

Because it could be the search engine. It could be inventory issues. It could be the fact that your, the front end experience of your website is broken and users, the links to your products are actually not working. And that's not a search engine problem. It's not an inventory problem. It's a website problem.

So there are very, there are many ways that this could be caused, uh, like a poor conversion rate could be caused. And so you need to find out why that's the actual case. Um, but for me, revenue is a top metric. Conversion rate's another one. If you, if you're in the business where your customers should be buying multiple products upon checkout, it's not just the, I'm looking for this one pair of jeans and that's all I'm buying.

But if they're actually looking to complete their set. Or if there's a way to sell more as part of your business and that's one of your key objectives, then average order value might be something that's important to you. Or number of units in a basket might be something that's important to you. So, um, the first thing is understanding what is important to your business and then finding those metrics that help you identify if your business is performing well.

You mentioned, um, revenue by search and revenue by browsing. So I think that's a very interesting metric because as far as I remember is that somebody who searches usually is a better customer. They usually have a higher conversion rate, sometimes a higher revenue. Do you have some examples from maybe different industries on how that looks in real life?

So is there industries where there's more searches going on than browsing? Yeah, I would, I would say it does vary from industry to industry. What we find is that typically. There are more browse events or browse instances than search instances. So if you can draw the analogy to going into a, an actual physical store, when you walk into the store, you may have an idea of what you're looking to buy, or you may just be browsing for something that you're interested in.

You may walk down. The isle that contains the shoes and so now you might be looking at shoes. You're browsing for shoes. You don't know what if you're actually going to buy a pair of shoes or if you don't even know what kind of shoes you might want to see, but if you spot it, you might actually want to want to maybe try them on and then buy them.

The same thing I think is equivalent on the, in the online experience where if you're performing a search, it's probably true that you're looking for a very specific type of product. I'm looking for. Uh, uh, a Keurig coffee maker that has these kinds of pots and maybe that that's what you're already going to going to be buying or if you're looking for just coffee makers and generally might browse to the coffee makers page because you're not sure if you want an espresso or a Keurig or something else, maybe you want a, um, a filter coffee machine or you want some other type of coffee machine.

You're not really sure what you're looking for, but you know, it's in that category. And so you're trying to drill down to the right product we're looking for. Um, so I think Yeah. Understanding the segment of the shopping experience that you're looking at is key also when considering metrics because it's not a one size fits all for the metrics.

Um, so I think in, in terms of what I've seen in, in, in the industry, typically there's more browse than search because there's more people kind of trying to find the right product they're looking for rather than they have the exact. Um, they may also have in the past struggled with a poor search engine that's been unable to identify the intent of what they're looking for.

And so then they realize, you know what, when I keep typing in the search box, I'm not finding the right products. Maybe let's go through the categories for the, for the shop and see if I can find the right categories that I know my product is going to be in. And so that way it's, it's a little bit easier sometimes for the shopper as well.

So, um, it does vary from industry to industry. I would say apparel. Maybe is, is more browsing search. Again, if you think about it, going to a store, you're going down the aisle for shoes, you're going down the aisle for clothes, you, you, uh, it's more of a browsing experience. Whereas if you're more in a big box store, if you, if you know the exact kind of product you're looking for, maybe it's a search.

Maybe you're looking for a 65 inch TV. That's a Samsung and it's got smart technology. So then, you know, you type that into the search box, you find just those products. And now you're able to find or more quickly find the product that you're looking for. So, um, I think it does vary from industry to industry.

It's, it's worth looking at on your website, what your customers are doing. It's very easy to track this. You can track how many times the person is in the search box and typing something versus how many times they just navigate to the browse page. So. It's very easy to track this data and you should look at it for your website.

In the past, obviously, I had to go to many different platforms to draw and pull the data from there. Um, your solution group by, um, helps with that. Talk me through, through the dashboard. What kind of numbers can I see and how does that look like? Yeah. So once you install the app, uh, we start collecting all the data that Shopify collects.

So Shopify actually collects all of this data as well. They have in the default setup, A way to understand the interactions that are happening on your site and to capture that data. Now, what data is captured is also interesting. It's not necessary that they capture everything. They could, for example, uh, not capture a lot of the PI information.

And in fact, I would suggest that you check and see what is being captured because This person will be personally identifiable information. I don't think is important in a lot of these metrics that you're looking at. And we don't care that it's John Smith or Jane Smith who's making that interaction, just for that person has done that, that behavior.

And so, um, in our app, for example, we don't capture any PI information. We only care about the specific events that are happening on your website, regardless of who was performing them. And, and when we look at personalization, for example, we know that individual one No matter who that person is, has then done these behaviors.

So we can also drive personalization that way. Um, but we capture all this data through the default Shopify, uh, setup. And then we're able to then drive a lot of the dashboards that we have in our platform. And those dashboards generate a lot of these actual insights that I've been talking about. So it helps you understand how your shoppers are behaving on your website.

What are they searching for? What are they clicking on? Do you have any problem areas where You've got a high instance of a metric that is actually a negative metric like null searches where you actually don't have any products shown to the customer because you don't carry that product. You don't have any inventory.

There might be many reasons why you end up in a situation where your customers do not see any products after doing a search. And that's not a great shopping experience. So then if that's the case, what do you, what is the insight you can take away from that? Well, maybe we want to show some other products that are similar to what they were looking for or in products that maybe they were maybe interested in that are trending in on your website.

You might have some some viral marketing campaigns that are going live that you may want to show your customers to help funnel traffic to those pages. Um, so there are many ways of taking advantage of the analytics. But we, we go with the default analytics that Shopify is able to capture without any additional work needed by the merchant.

And then we take that and try and generate some actionable insights. I think you just mentioned a bit of a hidden golden nuggets there. The non searches. I had the experience in my store years ago that people were searching for a very specific bag, which I didn't have. And with that, I started product development and took a while, but then we had this product.

So, and That was a massive revenue winner at the end of the day, just by looking into what people were searching for. And it shows you how important that is and how valuable this is. From your app, um, do you also still use Google Analytics and other tools or are you completely relying on your app? So we can really rely on our own analytics.

I would say there is absolutely a time and a place for something like a Google Analytics or Adobe or Telium. There's many platforms out there that look at analytics in a broad sense. I would say that how we differentiate from those kinds of platforms is we are very much e commerce focused. For the moment, we're actually looking at broadening scope as well.

But when you look at what is most important to a merchant from a, uh, e commerce point of view, there are very specific insights that you need to generate. And so that's where we focus is how do we help retailers basically sell more that that's what our analytics are geared towards. So, um, but, but Google analytics or Adobe or some of these other platforms may tell you some other things that may help the rest of your business.

Um, they may give you a broader view into some other parts of your, of the. Of the site and how it's performing. Um, whereas our analytics are more targeted towards e commerce. Absolutely. On that, tell me about your perfect customer. Yeah, I think our perfect customer is someone who recognizes they have a poor shopping experience from a search or browse point of view.

Someone who says, who has identified that their customers are not finding the products they're looking for. That means they know that they have a problem that they need to solve. I mean, of course, we can help customers identify this problem. So. Uh, we're able to help do an audit and things like that as well.

But if you know that you can improve your shopping experience, you know that your customers are not finding the right product, then I suggest that the first step should be, well, how do I improve the search experience? How do I improve the browser experience? To me, the easiest way is to try an app like route by which is able to just replace the search technology on your website on your Shopify site and Use our search engine and test it It's very once a one click installation process it takes a couple of hours to upload your catalog to our engine and then you're off and running and you can test and See if the search experience is better or not And again, if you have those analytics in place You can start measuring and seeing the difference of performance if you don't have the analytics in place we can help you with that as well, but Um, really it's, it's a customer that knows that they have a search problem and they want to fix it.

That to me is, is someone who is aware that of the problem and wants to look, there's looking to solve it. Um, we can, we can help with awareness. We can help with the technology. We can help with analytics. Um, but for me, the ideal customer knows they have a problem and, and would like to solve. Sometimes you don't know what you don't know.

So you don't know that you have a problem. So you might still go and check it out and you might be surprised what kind of results come out of it. Exactly. So tell me a little bit about the pricing structure. Yeah. So we actually, um, have pricing based on queries that are used. So if you think of a query as a search, basically.

So every time a search is performed, then. That counts towards your query limit and you have a query limit for your for the month, you might be a site that has, let's say, low traffic. So you're in the maybe thousands of searches a month or something like that, or less. And then you might be kind of looking, pushing the mid market to a larger scale business where you have hundreds of thousands of searches a month.

A lot of our core customer base has hundreds of thousands or millions of searches a month. They're quite large stores. And so, uh, we're able to serve a customer of any scale and the pricing is based on that. So it's, it's really driven by the amount of usage of the search engine, uh, which will dictate the costs that you might see.

And we want to make sure that you're not paying for any more than you're using. So if you're, if you are in that smaller scale of a business, then you'll only pay for what you use. And we also try and take the approach, which we think is different to some of our competitors, where the cost that you pay is, is on, is very much, you're aware of everything that you're paying for.

There is no additional charges or fees that come in. You don't have to pay extra for analytics. You don't have to pay extra for data ingestion. You don't have to pay extra for any, anything else that you might sometimes have to pay extra for in some of these other platforms. So, it's a, it's a, everything is included in the cost that you see on the website.

And on or on the app site and it is primarily driven by the users that you have. That makes absolutely sense. And I think data driven e commerce and was that data driven marketing is so important. And as you just said, if you have a bigger store, if you have a lot of traffic, a lot of numbers going back and forth in there, then you need the right tool to analyze and really to come to conclusions and results.

What's your next step is before our coffee break comes to an end today. Is there anything you want to share with our listeners that we haven't covered yet? I mean, I think I want to reiterate what we've talked about today. To me, analytics is such a core and critical part of what every merchant should be considering on a daily basis.

Please don't ignore this space. Please, if you don't have an analytics tool, try and see what's out there in the market that can help you. Something that's low effort, easy to use, that does most of the work for you. That's a great starting point. You don't need to be fully involved to set up the analytics tool and, and set up the dashboards and things like that.

There are a lot of tools out there that that do it for you. So please don't, um, sleep on this. Let's say like, let's please move forward on, on choosing an analytics tool. That's right for you and, and start looking at some of that, that data and seeing where you should be focusing on. Absolutely. Yeah.

Couldn't agree more. Um, I'm relying on data driven tools and it makes my life so much easier because a data scientist has done their heartlifting. Exactly. I just need to read the results from it. Where can people go and find out more about you guys? So on the Shopify app store, you'll be able to search for group buy and find our app.

Or you can go to groupbuyinc. com, we'll have some links in the show notes and you'll find us there. Excellent. I will put the links in the show notes as always. You will be just one click away. I'll catch you in the last episode of our mini series and then we continue our chat there. Thanks so much for your time today.

Thanks, Thijs. Appreciate it.