2. Vital e-commerce metrics for analyzing marketing data<\/a><\/p>\n 3. Synder Business Insights – your ultimate e-commerce analytics tool<\/a><\/p>\n\n\n\n <\/p>\n\n\n\n And now we\u2019ll look at the primary types of e-commerce analytics and business benefits.<\/p>\n\n\n\n Perhaps the most important data in e-commerce analytics is the shopping audience of your online store. This data analytics will help you build a better picture of who<\/em> your customer is, so you can tailor your promotions and interfaces to improve engagement.<\/p>\n\n\n\n Data available includes things like:<\/p>\n\n\n\n Another valuable aspect of this analysis is looking at the customer data that shows how your audience uses your services\u2013do they shop on a mobile device or laptop? How many visitors log in from an Android device? When you fine-tune your customer persona based on data analytics, you can hugely improve your targeted marketing and determine the pain points you need to address. <\/p>\n\n\n\n The next step is to use e-commerce analytics to uncover insights into acquisitions\u2013how do customers find you? Tracking acquisition data is incredibly relevant because it tells you which online channels are worth investing in or which types of product promotions attract the most visitors to your store. This analysis process delivers data that feeds into a successful marketing strategy, such as:<\/p>\n\n\n\n If you have the relevant data about which channels are most profitable, you can allocate your budget to the areas where you can be confident it\u2019ll drive traffic your site so that it has the biggest impact on revenue.<\/p>\n\n\n\n We\u2019ve mentioned conversions, but this area of data analytics deserves a separate slot because your conversion rates mean everything to your bottom line. It\u2019s great to have high visitor numbers on your site, but if only a tiny fraction converts into paid-up customers, something isn\u2019t working.<\/p>\n\n\n\n In e-commerce, a conversion assessment will draw on data to tell you:<\/p>\n\n\n\n You can get as in-depth as you need, getting the data quantifying how consumers behave, why they abandon a shopping cart, and how many return as repeat shoppers. E-commerce businesses also use conversion analysis to look at financials and assess how much revenue they make per conversion\u2013and whether there are opportunities to improve that figure. <\/p>\n\n\n\n Finally, let\u2019s talk about consumer behavior data \u2013 what does your average customer do when they land on your home page? The data here ensures you understand how a customer perceives each element of your app, website, or store.<\/p>\n\n\n\n For example, you might use your analytics to identify:<\/p>\n\n\n\n It can be impossible to assess your e-commerce retail impartially. Shopping behavior analytics show you what your customers really<\/em> think so that you can respond accordingly.<\/p>\n\n\n\n Data is the key factor in business, whether you\u2019re updating your marketing plan or need to know what to include in a business report.<\/p>\n\n\n\n First, we\u2019ll look at the most important marketing points e-commerce businesses need to analyze. We\u2019ll explore the key performance indicators (KPIs) that businesses should be continually tracking when they sell their goods or services. Want to know more about KPI reporting? Check out our article \u2018<\/em>What Is a KPI Report: A Simple Explainer of KPI Reporting<\/em><\/a>\u2019.<\/em><\/p>\n\n\n\n Average Order Value, or AOV, is one of the most important e-commerce metrics which measures the average total of every order customers place with a business over a definite period of time. It\u2019s crucial for online stores to keep track of this metric as it impacts major business decisions such as advertising or pricing strategies.<\/p>\n\n\n\n In order to calculate it, use the following formula:<\/p>\n\n\n\n As the name suggests, CAC is the total cost of acquiring a customer. This is another important marketing analytics metric for e-commerce businesses which typically includes all data on marketing and other related expenses like advertising costs, salary for marketing people, etc.<\/p>\n\n\n\n The customer acquisition cost formula is as follows:<\/p>\n\n\n\n In e-commerce analytics, customer conversion rate (CRR) is a customer data metric that equals the percentage of potential customers who take a specific desired action on the website or landing page, for instance make a purchase or sign up for your services. <\/p>\n\n\n\n The conversion rate formula:<\/p>\n\n\n\n Customer lifetime value (CLV) is a measure which equals the total amount of money a customer spends during their entire relationship with your company. <\/p>\n\n\n\n To calculate customer lifetime value, use the following formula:<\/p>\n\n\n\n Return on ad spend, or ROAS, is an e-commerce metric used to evaluate the efficiency of digital advertising campaigns and see if the marketing strategy the business has chosen really works well.<\/p>\n\n\n\n It\u2019s easy to calculate it using the following formula:<\/p>\n\n\n\n Read more about ROAS in our article \u2018<\/em>Optimizing Return on Ad Spend: How to get 6x ROAS and more sales<\/em><\/a>\u2019.<\/em><\/em><\/p>\n\n\n\n As is clear from the name, this index is all about the income an e-commerce company receives from selling its products or providing its services.<\/p>\n\n\n\n The sales revenue formula is:<\/p>\n\n\n\n Now that we\u2019ve learnt what important KPIs you need to keep track of, you might wonder how to calculate those metrics accurately and fast. Let\u2019s look at how to streamline the process of calculating and analyzing this marketing data. <\/p>\n\n\n\n Big data analytics<\/a> for e-commerce businesses can be daunting, so why not resort to modern technology? A well-known solution here is Google analytics. But luckily, there are some alternatives. <\/p>\n\n\n\n Your perfect choice would be Synder Business Insights<\/a>. This tool was created by YCombinator alumni with 7+ years of experience in solving accounting issues and is aimed at helping marketing agencies, e-commerce and SaaS businesses and accountants make informed business decisions and drive better sales. <\/p>\n\n\n\n With 25+ integrations available, Synder Business Insights lets you capture data from multiple sales channels and payment platforms in use and package it into clear, useful reports accessible on one single dashboard. No more spreadsheets, apps and mistakes made while trying to gather data from all channels in operation!<\/p>\n\n\n\n Real numbers don\u2019t lie and Synder transforms them into actionable insights that highlight where a business performs well, and what areas need improvement. Questions like How much time does an average customer spend with my e-commerce business? Do I have more new or returning customers? How much money does an average order bring? How much did I make last month from all channels\/a particular channel? What\u2019s my bes\/least performing item?<\/em> get answered in seconds!<\/p>\n\n\n\n Just a few clicks and Synder Business Insights will give you actual data on the crucial e-commerce KPIs concerning:<\/p>\n\n\n\n Upon subscription, Synder Business Insights e-commerce analytics tool will become your single source of truth for e-commerce business data and provide you with insights into how to improve your performance. And the best part is, Synder does it all automatically so that you have more time to think about your growth strategy. <\/p>\n\n\n\n Thirsty to get more data about how Synder can work magic for you? Sign up for a free trial<\/a> or book a demo<\/a> with one of our specialists to get a guided tour of the tool.<\/p>\n\n\n\n <\/p>\n\n\n\n\t
Different types of e-commerce analytics<\/strong><\/span><\/h2>\n\n\n\n
1. E-Commerce audience analytics<\/strong><\/h3>\n\n\n\n
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2. Retail customer acquisition data analysis<\/strong><\/strong><\/h3>\n\n\n\n
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3. Analytics of conversion data for an online store<\/strong><\/h3>\n\n\n\n
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4. Online behavior data analytics<\/strong><\/h3>\n\n\n\n
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Vital e-commerce metrics for analyzing marketing data<\/strong><\/strong><\/span><\/h2>\n\n\n\n
Average order value<\/strong><\/span><\/h3>\n\n\n\n
Revenue \u00f7 Number of orders = AOV<\/strong><\/h4>\n\n\n\n
Customer acquisition cost<\/strong><\/span><\/h3>\n\n\n\n
Money spent on sales and marketing <\/strong>\u00f7 Number of customers =<\/strong> <\/strong>CAC<\/strong><\/h4>\n\n\n\n
Customer conversion rate<\/strong><\/span><\/h3>\n\n\n\n
Conversions<\/strong> <\/strong>\u00f7 Total clicks or visits \u00d7 100 =<\/strong> <\/strong>CCR<\/strong> <\/strong><\/h3>\n\n\n\n
Customer lifetime value<\/strong><\/span><\/h3>\n\n\n\n
Average purchase value of a customer
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Number of purchases per year
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Average length of relationship of a customer with your in years
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LTV<\/h4>\n\n\n\nReturn on ad spend<\/strong><\/span><\/h3>\n\n\n\n
Gross Revenue from Ad campaign <\/strong>\u00f7 Cost of Ad Campaign = ROAS <\/strong><\/h4>\n\n\n\n
Sales revenue<\/strong><\/span><\/h3>\n\n\n\n
The number of units sold <\/strong>\u00d7 The average price per unit = Sales revenue<\/strong><\/h4>\n\n\n\n
Synder Business Insights: analyze your data with this ultimate e-commerce analytics tool<\/strong><\/strong><\/span><\/h2>\n\n\n\n
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