Ecommerce Attribution Modeling Simplified

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jakaria
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Joined: Tue Jan 25, 2022 4:26 am

Ecommerce Attribution Modeling Simplified

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So here's the thing: your e-commerce attribution modeling strategy is probably costing you sales. Why? Chances are you're misreading your Google Analytics and Tag Manager data, which can lead to incorrect assumptions and counter-strategies that will ultimately significantly harm your e-commerce business. Relying on the default Google Analytics settings - the last time a user visited your site - means you're not looking at the big picture, leading to decisions based on misinformation. Misinformation that could cause you to pause campaigns that you think are n't working, when in fact they are. Tip for beginners: If you have just launched your store or are about to start your online business and you are new to analytics, you can check out this beginner's guide first: Google Analytics for e-commerce. This is where e-commerce attribution modeling strategies come in. Attribution modeling is how you assign value to conversions through your PPC campaigns, email marketing, SEO, referrals, etc., to determine the impact each channel has on each of your conversions . Think of Analytics as the platform where you can examine buyer behavior and attribution as the indicator of each channel's effectiveness in driving that behavior. A perfect symbiotic relationship to enhance e-commerce success. Given the variety of marketing channels we use today and the wide reach of your sales funnels, it's no wonder that tracking the efficiency and effectiveness of each to increase sales may seem overwhelming. Add that to the increase in attribution modeling strategies; it is difficult for the most experienced marketers to navigate. Take this e-commerce traffic scenario as an example Web browser Pam is looking for tips on buying the best yoga leggings. She stumbles across your popular blog post, “How to Choose the Right Yoga Leggings,” but after reading, leaves your store. In the next few days, thanks to your Facebook remarketing campaign strategy, Pam sees an offer of yoga leggings on your store in her newsfeed. She clicks on it, looks at your offer, but goes no further. After a week, Pam is ready to buy her yoga leggings. So she Googles “buy yoga leggings online” and sees your paid search ad, which she clicks on, then completes the purchase. Using this scenario, let's look at three attribution strategies. The last interaction The last interaction is the default attribution model used by Google.

This will only show the last time a visitor explored or interacted with your online store and through which channel they arrived there before converting. So in our scenario above, this would show Pam's last interaction with your store before she bought the yoga leggings and assign it as a conversion channel/medium - which would be a Google search ad. The first interaction However, Pam's first interaction with your store was when she discovered your e-commerce blog. So the first interaction attribution here would show you that the conversion was driven from organic search. In short, the first interaction is where Google attributes the original way a shopper first found your store as a source of conversion. The linear approach Linear attribution will track all of the Latest Mailing Database channels Pam used on her shopping journey through your store. This will include everything from when she first discovered your blog post to when she finally clicked "pay" when you checked out. In this scenario, that would include the organic, Facebook, and Google channels she went through. And that's just the tip of the e-commerce attribution modeling iceberg with a variety of attribution modeling tactics to consider. What does it mean? As you can see in this example, if you had only looked at the default last interaction, you would have missed the importance of your blog content. Or, if you had only looked at the first interaction, you would have missed the importance of your Google campaign. Both of these could have led you to make some misguided marketing decisions. And with so many options and sources, it can become very difficult to navigate. Despite all this, up to 55% of advertisers still only use one-touch attribution models, and 28.4% use none at all! This is where we come in… In this article, we'll walk you through 6 steps to help you re-evaluate or effectively implement the best e-commerce attribution modeling strategy for your business. Tactics that will help you get a more complete picture of your paid and free cross-platform strategies to make more accurate marketing choices that drive sales. Before you start Ideally, you'll eventually want to aim for a custom model that suits your specific business,

but you'll need to develop your data collection and customer insights first. Finding the best attribution model strategy will require you to continuously track your data and customer behavior while closely monitoring your goals and changing the customer journey on the path to conversions, regardless of how far along they are. To achieve this, you want to continuously assess your:Main conversion paths Channels that contribute the most to conversions Customer research and buying behavior Step 1: Be very intimate with your data Now let's get to the heart of e-commerce attribution modeling: your data. If you want to increase sales, you need to win at eCommerce marketing. And to win in eCommerce marketing, your attribution modeling needs to be on point. This is not possible without a deep understanding of your data, at all times, and using it to guide your decisions. Going into attribution modeling blindly is essentially wasting money. In short, if you devote time, money or energy to it, you absolutely must collect data on it. The more data you have, the more accurate your marketing and sales choices will be. More importantly, it will help you better understand the conversion paths your buyers take, which you can then improve or expand on, instead of just focusing on the total sales counter. Pro tip: don't underestimate your LTVs! The lifetime value of each of your buyers and your return rate have an important role to play in optimizing conversion paths. These buyers return repeatedly, and understanding their return journey is important to leverage return business. We all know it's cheaper to convert existing customers than to find new buyers; recognizing how you bring them back to the store will help you create marketing guidelines to improve your return rates and retain customers.
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