Claus Lauter [00:00:00]:
Welcome to episode 306 of the ecommerce Coffee Break podcast. In this episode, we talk about how attribution can help business leaders and executives make smarter decisions about where to spend their marketing money. Joining me on the show today is David Saxon, CEO at attributionapp.com, so let's dive right into it.
Voice over [00:00:19]:
This is the e commerce coffee Break, a top rated Shopify growth podcast dedicated to shopify merchants and business owners looking to grow their online stores. Learn how to survive in the fast changing e commerce world with your host Lauter. And get marketing advice you can't find on Google. Welcome, welcome to the show.
Claus Lauter [00:00:45]:
Welcome to another episode of the ecommerce Coffee Break podcast. Today we want to dive into attribution and why executives should care about attribution. Now, attribution is quite a bit of a technical topic, but there is a lot of data in there that's very important if you're managing a company, if you run a company, if you're an executive. So let's dive into that. And with me on the show, I have David Saxon. He's the CEO of attribution@attributionapp.com. He has extensive sales, digital and partner development experience with over 20 years in his career. And he's the perfect person today to talk to.
Claus Lauter [00:01:19]:
So let's welcome David to the show. Hi David. How are you today?
David Saxon [00:01:21]:
Doing great. Thanks for having me here, .
Claus Lauter [00:01:24]:
David, how would you explain what attribution is to someone who has just started in e commerce and digital marketing?
David Saxon [00:01:31]:
So attribution is really just taking the money that you spend in acquiring new customers and really attributing it to those activities and what resulted in a sale or the customer or the brand in general. And it's truly just measuring the impact of that. And most people refer to it as return on ad spend and just better understanding what channels attributed the most to that sale or that service that companies have sold?
Claus Lauter [00:02:00]:
I think thats where the secret lies in finding out where your return on ad spend comes from. Your return on investment comes from. Now, theres many, many platforms out there. All, they have some kind of attribution in there. It never matches up. Its a complete mess for most of us marketers. Now running a company, obviously you want a hard fixed, you want to really know what are the numbers? Are we spending money on the right marketing channel or can we even scale? Whats your experience in the landscape right now? Maybe looking in the last three to five years, what has happened? Why is attribute so complicated?
David Saxon [00:02:33]:
Yeah, that's a great question. And you bring up a very good point. There is so many different companies out there that have attribution models. And to a testament to it, like even in the G two reports, some of the companies that are listed very high in the G two reports do have attribution, but it's unfortunately, the attribution is such a broad term that it gets incorporated into a lot of these different products and services companies have. But truly doing attribution is really connecting to all those different ad platforms that companies are using, and most of them are using primarily the likes of Google and Meta, Facebook, Twitter, et cetera, and tying it in with the conversion event with some revenue attribute and really having a better insights of the models and everything altogether collectively on there. So it's challenging across the board. It still continued to be challenging because, number one, I think customers data, there's data challenges and the different systems that customers use. There's challenges and potentially on the platforms that they're built on.
David Saxon [00:03:36]:
And there's also challenges in the resources. I think depending on the marketing people and the level and the competence and what they have done, there's varying degrees of their understanding of data and marketing and how it fills into the whole space, right?
Claus Lauter [00:03:52]:
Mm hmm. Now, looking into attribution from a technical aspect, there is different points where attribution actually can be measured and you need to streamline that. And I know that you have a solution to do so. What's your approach to level out the data that it actually makes sense to compare it with each other so that you compare apples with apples at the end of a day.
David Saxon [00:04:15]:
Our philosophy is in the platform that we support for our customers. It's a click based attribution model. There's definitely value in companies spend a lot to get brand awareness and impression data and everything. But when it comes to really understanding what's working, what's not, we view basically the best way to approach this is to have data that you can audit and it's something that you can present to a CFO or CEO who's asking you. It's like, hey, how is our return on ad spend? And do you have data to back it up? So for us, our true belief in the attribution modeling that we do across for our customers is all based on that auditability of the data and the first party data that we collect for our customers that they can attribute to it. So as it relates to that and connecting all that together and giving the visibility into the people's views and the visits and what they're doing and it can be very complex and consuming to tie all that stuff together, but we bring that into a very structured environment where our customers get the best insights that they want as it relates to better understanding which channels are performing and which channels are maybe underperforming. And ill give you a great example of some of the insights some of our customers have seen. Most of the platforms do have their own reporting capabilities, but why customers come to us and when they choose any type of attribution solution is like hey, we want a single sort of truth or we want to bring all this stuff together.
David Saxon [00:05:44]:
So we are bringing in cost data from those platforms but were not going to depend on the conversion data because well track that with our customers on our own. As it relates into that with Shopify we can easily plug into those plug and get someone set up and running fairly quickly who has a Shopify account and running on the Shopify platform. But we can truly see once we have all that connectivity into all those different channels, the ability to understand if people are clicking on the ads and they're coming through and doing some type of event. So it's very eye opening for some of our customers. They find out that some of the ad platforms, it's like nobody's clicking on the ads and coming through, but some of those platforms are telling them they are having all these conversions now with us. You can audit all that and track it through. If you're asking that from some of the platforms, obviously it's a black box and they don't provide that data to you. And again, going back to the impressions and the value of that, there's true value and brand awareness as it up levels to those customers and those companies trying to get their message out there, it's hard to measure it, but it just gives our customers a better understanding of like, hey, what's working, what's not, and if people aren't clicking on the ads, that should give you some insights as a brand to like, maybe there's, the messaging's wrong, maybe we should have different copy, maybe there's something else that we're doing that we can improve to get those clicks to come through to the website to take some action.
Claus Lauter [00:07:12]:
I think a very important thing that you measure, Zed, is that the platforms let it be Google, let it be meta, everyone wants to claim the conversion, whatever the conversion is, because obviously then you're spending more money on their platform. But you're right, most of the time the conversion is coming from somewhere else and they claim it and then you're sort of lost and do not really work. Give me an idea on attribution models or conversions that you can measure. Does not necessarily be always the sale that you measure. There's other points, data points you measure. Give me just an overview what KPI's our executives are looking for.
David Saxon [00:07:48]:
We support three different multi touch and two single touch. So we do first touch or last touch, and then we do position based time decay and linear models in the platform. And the beauty of how we collect and store the data for our customers, you can switch between those different models. Most of our customers typically start out with linear, which gives equal credit to all the different touch points. And then over time, they'll look at this at more of a position base, which is, you know, more of a u shape. They can give like heavier credit to the first touch, heavier credit to the last touch, and equal credit to the touches in between. So it's almost like a journey when people start to kind of like go through that process of like when they start to really get into the attribution, really looking at linear, then eventually switching to position based. But all those different models could be we cover and aggregate altogether.
David Saxon [00:08:40]:
And the beautiful thing about it is, as companies are using our platform over time, they can go back historically, after we've collected this data for them and look at all the different models and see what seems to be working. They can look at the different channels to see what's better with the first touch or last touch or multi touch, and they can make their decisions based upon that. It's really providing them with this much clarity and transparency of whats working and whats not and where to best invest.
Claus Lauter [00:09:07]:
I want to dive a little bit into the day to day life of a marketeer, of someone who runs an e commerce business. As we are on a podcast, it was difficult to see whats actually in front of you. Can you talk me through the dashboard? What will I have in front of me? If Im working on your platform, theres.
David Saxon [00:09:23]:
Definitely charts and reports that we do cover. I would say most of the stuff is just aggregating a single point of seeing where my return on how much Im spending in the channels that we're measuring and what's my click through or conversions and what's my return on ad spend as a whole and then clicking through into that. People can break it down and go into the individual details. And we do support ABM models as well. So we can aggregate and roll up all the different users into one specific company. For companies that are b two b but on the b two C side. You can see all those conversions in the journey path individually, what that is. But like most analytics platforms or the tools that are out there, people come and take a high level and then they can start digging into maybe they just launched a new Facebook campaign and they wanted to drill in to see how that's comparing.
David Saxon [00:10:14]:
And you can drill all the way down into the different levels and the granularity. As an example in Google, we can go down to the campaign level, then to the keyword level and you can look at all how those campaigns are performing across the board on a day to day basis.
Claus Lauter [00:10:31]:
Hey , here, just a quick one. If you like the content of this episode, subscribe to the weekly newsletter at newsletter dot e commercecoffeebreak.com I score and create 50 news sources so you don't have to saving your hours of research. Grow your revenue with ecommerce news, marketing strategies, tools, podcast interviews and more, all in a quick three minute read. So head over to newsletter Dot e commercecoffeebreak.com to subscribe as said, 100% free. Also you will find the link in the show notes. And now back to the show. Can you give an example of one of your clients, what kind of results they saw after they implemented your solution?
David Saxon [00:11:04]:
Yeah, I think the biggest of results that people see from a macro sense, and I'll give a couple examples to some specific companies, but the macro sense is just not most companies that are measuring are just really dependent on the ad platforms telling them what's working and what's not. So I think it gives them better clarity and understanding. Exactly. Okay, I have a true model or I have true traffic that I know people are coming in through these channels to the website and they're converting and I'm able to kind of like get everything into one platform and take a look at it. And I think from that most people are really started seem to be very eye opening of just like the fact that it's like, oh, some people didn't even know that, you know, they didn't have any click through conversions on certain platforms or certain keywords and really starting to understand the level of how can I start spending money more wisely or where can I shift money to spend money in different channels? Or more importantly, it's like, hey, let's run an ab campaigns on certain areas where it seems like things are a little bit not performing or underperforming or other channels that I want to invest in. So at the end of the day, it really just provides more higher a deeper level of clarity for companies to really dig into things.
Claus Lauter [00:12:24]:
Tell me a little bit about the implementation, the onboarding process. Do I need to do any kind of homework? What are the different steps before I can get up and running?
David Saxon [00:12:34]:
Well, the great thing with Shopify customers, it's very simple to get up and running. Literally could be as much as clicking through, connecting to the Shopify plus account. And it's just going in and authenticating the channels. So if you're doing Facebook or Google or whatever channels that you're using, going with your credentials, authenticating, and then you're up and running. So it's pretty straightforward. And even for the customers that don't have Shopify and more custom connectors that we got to connect with, typically at the most, it could take anywhere from like seven to 14 days to get up and running, where we can really start to do some analysis and look into the attribution. But Shopify is probably the easiest. That gets people up and running fairly quickly.
Claus Lauter [00:13:20]:
Okay, that's good news. Are there any kind of myths out there right now about attribution? Because there's a lot of things going on with third party cookies going away and a lot of, I think, false information is floating around. What's the thing that you hear the most, which is probably not true?
David Saxon [00:13:36]:
Well, it's interesting. Like we get often asked about third party cookies, and to us, we've been a first party data system since our inception, so it really doesn't affect us. It's definitely going to affect some other technologies and platforms out there. And I think, you know, surprisingly, in the last several months, we haven't heard a lot of people bringing it up. I think most people are getting ahead of it already or anticipating it's going to happen. Your guess is as good as mine. It's going to happen this year. Uh, you know, we wouldn't be surprised if it doesn't happen at all in the near future, but for the most part, it really doesnt affect us.
David Saxon [00:14:10]:
The other point really, which goes back to the impression data, I think there still is a lot of companies out there and maybe you see this a little bit more so in larger companies where the impression data is definitely key. And its very important to any organization in getting their brand and message out there as well. But its surprising to see how theres a lot of marketers that still really want to measure the impact and show the value of this. And its a very tough thing to do unless you have a ton of traffic and a lot of data. Theres a huge amount of numbers that you can pour into it to really show kind of like, hey, this is definitely having a meaningful impact, but for most companies, because we support anywhere from like SMBs all the way up to the mid market and stuff. But unless you're an enterprise in the top 10% of the enterprise companies, you're not going to have that level of traffic or data to really have a meaningful understanding of what's working with impressions or not. So I think most of this is our journey has been, it's just helping people make that transition. It's like you have to be more data driven.
David Saxon [00:15:21]:
You have to look at the true conversions. And, you know, these people are coming through and theyre clicking on this, doing some type of conversion impressions are important. You should be very well aware with that. But over time, I think were looking to get marketers to a point where theyre going to be a little bit more data driven and in tune with what reality is, as opposed to just taking the guess of whats happening out there in the impression side of the business.
Claus Lauter [00:15:47]:
Yeah, I think data marketers need to become a little bit more data scientists than they were in the past because it's all about data. You need to really know your numbers. Who's your perfect customer? Are there specific industries or niche that you work more with?
David Saxon [00:16:01]:
B two B or b two c? It's a very big mix between SaaS companies, e commerce companies, brands that are selling things online, small companies that are doing that. And I think it's key for us. It's just when the ideal customer for us is a customer, Sue's at least spending in a couple of channels, say Google, Facebook, starting to spend upwards of thousands of dollars a month and really starting to want to expand and grow their business, but dont really have a clarity of, hey, whats working better in one channel versus the other. And maybe theyre starting to invest in other things such as podcast or email campaigns or anything else outside of that where its starting to get a little bit more complex. And as theyre growing, they need to have something thats going to have a better central system thats really going to help them better understand whats going out there. So hopefully that gives a little bit more of a clarity. I know I was a little bit all over the place, but our ICP could be any kind of company thats looking at those levels.
Claus Lauter [00:17:04]:
How does your pricing structure work?
David Saxon [00:17:06]:
We are on the Shopify marketplace, so were Shopify customers. You can actually get started with a free plan if you wanted to. And it ranges upwards. If you wanted to have more of the features and benefits, it grows up into like $500 a month plus the percentage of ad spend. So theres three different levels that we have out there and the biggest thing is just like getting started is one thing, just to have some further clarity and were always a big fan of like hey lets crawl, walk, run first. Before you get into it, just start with understanding even whats going on within your Google or Facebook campaigns, right. Bringing that into one central focal point and seeing if people are clicking through and converting and what that means to you. So many ways to get started and we just looking to provide more transparency for people who are spending money out there in those different channels.
Claus Lauter [00:17:57]:
Absolutely. Before we get to the end of our coffee break today, David, is there anything that you want to share with our listeners that we haven't covered yet?
David Saxon [00:18:04]:
Yeah, I think there's more that's going to be coming maybe by the time this podcast gets posted. We do have a second app in the Shopify store that's a connector to CDP's and the first one is going to be with a segment CDP. So we're excited about that. That's going through the approval process right now. Very close and anticipating it's going to get released this week. But by the time this podcast comes out, we're probably going to have that app available as well for a company to get all of that data into their cdp if they're a segment customer as well.
Claus Lauter [00:18:39]:
Excellent. That's good news. Where can people find out more about you guys?
David Saxon [00:18:43]:
Come to visit our LinkedIn page as well as the website attributionapp.com dot. Feel free to connect directly with me. We'd love to have conversations. There's plenty of people that can come. If you want to sign up for a demo and a conversation to see if we can help, please come and visit the website and the doors open.
Claus Lauter [00:19:01]:
Okay, I will put the links in the show notes as always, and you're just one click away. I think starting with the free plan or even having a demo directly with you makes absolutely sense. If you want to find out where you're losing money in your marketing strategy and how you can optimize that with a better attribution model in the back. David, thanks so much for your time. I think that was a good entry into attribution and I hope a lot of people will follow up on that and make their business better.
David Saxon [00:19:25]:
Great, thank you, .
Claus Lauter [00:19:28]:
Hey here. Thanks for joining me on another episode of the ecommerce Coffee Break podcast. Before you go. I like to ask two things from you. First, please help me with the algorithm so I can bring more impactful guests on the show. It will make it also easier for others to discover the podcast, simply like comment and subscribe in the app you're using to listen to the podcast. And even better if you could leave a rating. Thanks again and I'll catch you in the next episode.
Claus Lauter [00:19:50]:
Have a good one.