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Turning an eCommerce store into a profitable brand requires a consistent framework that transforms site visitors into loyal customers with a set of carefully designed messages reaching potential customers at the right time.

Easier said than done, I know, but in this article, we are going to look at the two eCommerce growth frameworks you can utilize to effectively grow your business (no matter the size).

I am sure you have read a lot about eCommerce marketing and growth before. But since you are reading this piece, I assume that you still have questions about the topic.

So in this article, I’ll show how eCommerce businesses can drive sustainable growth with a resource they already have in plenty — DATA!

There are a bunch of articles and videos showing you the different strategies you can use to grow your eCommerce business with paid ads, SEO, email sequences and so on.

But none talks about what you need to have in place before implementing any of these strategies — the fundamentals of growth.

At Humanlytics, we work with various e-commerce businesses and in our work, we’ve observed that all successful eCommerce businesses have one thing in common; they do more with less.

Here is how:

First, you set and agree to achieve a few simple goals. Sales conversions and returning/loyal customers are often all you’re after, which means all your efforts go to making people happy with the products and spreading the word.

Second, you choose just a few strategies to reach the goals set and implement a proper analytics solution that provides insights needed to optimize and prioritize marketing resources on strategies with the biggest impact on their growth goals.

In eCommerce, while “blind growth” can certainly occur, it’s a bit of a gamble because there’s always something to be improved on your site, product, ad campaign, and blog

But since you always in competition with big brands and new eCommerce stores, you need to be smart about how you spend your resources to avoid working on things or using strategies that don’t generate results.

This can be done in two steps:

• Identifying key areas of biggest impact on your revenue growth goals

• Taking data-informed actions to improve performance in those areas

These steps form the basis of the two frameworks we are looking at today, one to help you pinpoint the areas that can have the biggest impact on the revenue growth goals of any eCommerce business.

The second framework to show you how you can generate and take data-informed actions to achieve your growth goals.

A. Growth-metrics framework

Setting up an online store is not enough. Remember that you are competing against millions of businesses online — many of which are large brands — for the attention of potential customers with limited time and resources.

Therefore, the critical first step is uncovering areas of potential optimization to drive revenue growth.

There are a number of approaches to identifying potential areas of focus and optimization and we will be looking at two, starting with one designed by Salesforce.

Salesforce eCommerce team of experts use the framework below backed by reliable data benchmarks generated from over 2,500 leading eCommerce sites and more than a billion eCommerce shoppers to retailers drive revenue growth:

Source: salesforce.com

From the image above, we can see that there are four KPIs contributing to revenue that eCommerce business can control including traffic, conversion rate, average price per unit and units per order.

And it can be deduced that:

• Traffic volume (number of site visitors) and the site conversion rate (visitor to customer) define the number of successful orders an eCommerce site generates.

• Average price per unit (affected by price reduction offers like discounts) and the number of units per order form the average dollar amount spent each time a customer places an order on the site.

• Revenue is a factor of both the number of orders generated and average order value

With this framework, all eCommerce stores have to do to attain consistent revenue growth is to watch their CAC as they:

• Increase traffic generation

• Improve conversion rates

• Increase the average price per unit and

• Increase the number of units per order

If all marketing efforts and resources employed affect one or more of these four metrics, you are to have an impact on your revenue at the end of the month.

I like this framework because it keeps you focused on what’s really important.

Focused on the metrics that affect your bottom line revenue so that you can eventually realize a return on investment from your marketing operations.

You can do this by analyzing your data to find insights into:

• How you can drive quality traffic at a lower cost?

• How you can drive higher conversion on-site?

• How you can ensure promotional strategies drive positive growth?

• How you can automate improvements to the number of units per order?

One of the key challenges faced by SMBs in this article is Data Interpretation. Knowing which questions to ask and what answers to look for is the easiest way businesses can realize the value in Data.

With the Salesforce framework, you can focus on getting answers/insights to the above questions from your data with more goal-focused analytics solutions like:

The second approach is from Shopify. They created a different KPI hierarchy for businesses that are optimizing for revenue growth but the idea is still the same as the one above.

The only difference is that Shopify introduces a new metric in their eCommerce revenue growth framework, customer lifetime value LTV made up of both the purchase frequency (number of repeated purchases) and average order value.

LTV is basically a measure of retention, perhaps one of the most important metrics to track because it’s one of the best indicators of a business that has successfully created value for its customers.

When a customer is satisfied with your product/service, he will come back and buy more (purchase frequency). The opposite is also true.

The beauty of repeated purchases is that they increase revenue generated at a much lower cost and also increase the likelihood of referral purchases.

For example, if your customer buys their first pair of shoes from your store at $30 with CAC of $50, you are not making money.

But if they simply come back and buy again for $30, you make $10 profit, LTV is the easiest way to turn a profit. LTV and referral.

The cost of doing business is increasing for eCommerce while the profit margin keeps getting lower and lower by the day. Anything you can do to lower your cost per acquisition will leave with more resources to acquire even more customers.

Improving the frequency of purchase can greatly lower your CAC and improve your LTV in the process.

With this framework, all eCommerce stores have to do to attain consistent revenue growth is to watch their CAC as they consistently:

• Increase traffic generation

• Improve conversion rates

• Increase the average price per unit

• Number of units per order and

• Increase purchase frequency

These are the areas of highest impact on eCommerce revenue and an improvement in any will directly lead to growth in revenue, consistent growth in any will lead to consistent revenue growth of your business.

Ideally, that should be the case, but in the real world, we work with limited time, budgets, skills and still have to compete for customers with big brands that have it all like freakin’ AMAZON.

The question then is how do you prioritize your limited resources to generate the highest impact on revenue?

How do you choose the best area of focus to attain revenue growth at any one time?

• Will you focus on traffic generation with paid and SEO?

• Will you put all energy and resources to improve conversion rates with new designs, discounts, email sign-ups, and pop-ups?

• Will you focus on purchase frequency will email sequences and retargeting ads?

There are a number of ways you can go about choosing what you want to focus on for revenue growth and the most common one is the ICE score method.

Growth teams use this method (coined by Sean Ellis) to prioritize growth experiments/strategies of interest, based on perceived impact, confidence and ease of implementation.

With this method, you assign varying weights to different strategies in all three categories (impact, confidence, and ease) based on what you think and as effective as this method is, it’s still subject to personal/team opinion.

Not exactly as data-driven as we need to be if you are going to be efficient about how we utilize limited resources at any one time.

Which brings us to the last framework today, where we will be relying entirely on our data to show us where to focus resources if we are to meet our set revenue growth goals with a specified time.

 See how fast-growing eCommerce businesses like William Painter are using data analytics to grow even faster. Download here.

B. Data-informed growth framework.

Ecommerce businesses collect huge volumes of data from their daily operations about their marketing strategies, site visitors, leads, and customers.

If we are smart about how we use all this data, it can show us the best way we can reach more customers and generate more revenue.

This is a proven framework that is being used by fast-growing eCommerce companies like Quzi Health, William Painter, RealEats, NaturallClub, and others to consistently meet their revenue growth goals.

With this framework, these companies are able to:

• Identify areas of highest impact on their revenue along their metric customer journey

• Set revenue growth goals and generate insights about how they can achieve the set goal

• Turn insights generated into a set of actions they can take to achieve set goals within a specific period of time

• Track actions taken to ensure that they meet their growth goals.

Before you can start generating any results with this framework, there are a few steps to follow:

1. Deep Data Integration

Running an eCommerce business today you need multiple marketing channels, services, and tools to effectively reach potential customers at the right time before your competitors provide them with an alternative offer.

These channels and tools collect all kinds of data which in itself is a problem because businesses are often confronted with a never-ending flood of incoming data that is difficult to keep up with and organize to realize it’s value.

Deep integration is about connecting your data sources and making them talk to each other so that they are truly connected and can report all aspects of the data collected.

With deep data integrations, valuable eCommerce data can be automatically recorded and organized in real-time without the need to create custom fields or tags to represent specific aspects of the data.

Deep integration is different from segregated data integrations because it digs a little deeper (as the name suggests) than basic data like name, email, or titles.

To communicate data like total revenue each customer generates for your business, the total number of products customers buy, what is the journey of a customer as they made the purchase, how many different sites did they visit, what were their experiences on those sites.

Essentially, the Deep Data Integrations helps you know your customers more intimately.

And also allows you to combine data from a variety of sources, including your website, social media, mobile campaigns, offline databases, CRM systems, and more into one dashboard — A single source of Truth with a 360 view.

This is data you can then analyze since it represents the complete picture of your business, it’s operations and customers.

But before any analysis can be performed on this data, it has to be standardized into a single format that is commonly understood in your business.

2. Data Standardization

As you can imagine, you have customers making purchases from Google Ads, email sequences and Facebook Ads all at different stages in their customer journey.

Even if you are able to bring all this data into one platform, it will not be in the same format because Google, Facebook, and your CRM all use different incomparable data formats.

Data is most valuable when you have something to compare it to, something that's impossible to do if your data is not in a similar format.

Easy to compare, right?

It’s nice to know that your Facebook Ads generated 150 purchases this week, but that doesn’t tell you what you should do next year.

But if it’s a 50% decrease from last week (oops…), clearly you have some changes to make. If this is a 50% increase, though, you know that you’re on the right track!

Now, what if you are running Ads on multiple platforms, will you compare metrics from Facebook Ads performance to Google Ads performance in silos?

How will that help you in creating a unified customer experience across all channels?

Standardization harmonizes your data across channels so that metrics of interest can make sense when comparing them.

3. Current performance analysis — Customer journey analysis

This is an analysis that can only be done with A.I. Yes, we are currently at that stage where we need Artificial Intelligence to analyze our data.

Simply because we are dealing with huge volumes of data, and with A.I, you are able to automatically extract meaningful patterns from large datasets for decision making.

Ecommerce businesses are currently using A.I to know what customers are going to buy before they go anywhere near the checkout, thanks to Artificial intelligence, predictive analytics and tons of customer data.

A.I is useful when trying to find interesting patterns in the data, patterns that would have been impossible for your Data/marketing analyst to uncover and also provide a data-backed explanation for those patterns.

Let’s take an example of a Footwear store that has just recorded a decrease in revenue and a corresponding decrease in site traffic.

In reaction to the decrease, the marketing manager tries to grow traffic volume with the assumption that the decrease in revenue is due to a decrease in traffic.

Sure, a decrease in traffic can reduce revenue but what if the major cause of the reduction in revenue is a decrease in the frequency of purchase?

That would mean, you have spent time and resources growing traffic as a way of increasing your revenue when a simple email sequence to your previous customers pushing for repeated purchases could have done the trick.

It’s from these patterns and their respective data-backed explanations that we can make informed decisions on and what qualifies as - Actionable insights.

The analysis at this stage basically to identify possible strengths and weaknesses in your entire customer journey so that you know what you need to be working on in order to attain your growth goal.

4. Goal setting

This is probably the most important step here. Goals.

Goals give you a sense of direction and help you focus on what’s important within a given period of time.

For eCommerce, goals can range from traffic generation targets to email subscribers, Facebook followers, SEO rankings, number of returned orders.

Chances are, if you ask any management-level person in eCommerce or any other type of business, anywhere in the world, “what is your top priority?” they would answer — revenue growth, or simply growth.

Which is quite obvious after all, if you’re not growing, you’re stagnating. And you can only stagnate so long before you cease to have the means to compete effectively or, really, do anything at all.

As such, in this framework, we focus on eCommerce revenue growth, any other targets are subsidiary achievements.

The analysis carried above provides you with insights into the strengths and weaknesses of your customer journey.

It is from these strengths and weaknesses that we can set goals of specific aspects about the customer journey that we can work on to reach our revenue growth target.

For example, if one of the noted weaknesses, is lower conversions at the checkout point, a goal can be set to improve checkout conversion by a given percentage within a specific period of time.

With A.I, this customer journey goal setting can be fully automated, where we match your current weaknesses with specific goals, deliver actionable insights into how you can achieve your set goal and track execution of actions taken.

Learn more here: A.I powered customer journey analysis.

5. Insights to actions

This is where insights generated by A.I are transformed into a set of actions your business can take in order to achieve the set goal. From the patterns and explanations generated from your customer and marketing data, a set of actions and strategies you can take can be deduced.

These are actions/ strategies, based on your current performance will have the highest impact on your revenue goal.

Using our previous footwear example, with deep data integration between the CRM and Google analytics into one A.I powered platform, patterns between revenue, site traffic, repeated purchases, and aspects would have been uncovered.

Correlating explanations to the decrease in revenue provided and the best courses of action deduced, in this case, retention nurturing emails or any other strategy to generate repeated purchases from returning customers.

In many cases, this is as far as we go, but it’s always good to keep an eye out to see if what you’re doing is working or not.

6. Action tracking

A crucial step in this framework is monitoring the actions taken to ensure that you are on track to achieve your set goals.

This is the part that can’t be fully automated because it requires a human element to hold your team accountable for achieving a specific goal given the actions taken.

Because at the end of the day, it’s about the actions you take and failure can just be a failure to act.

That is why for this framework, you need an analytics solution that not only analyzes your data to inform of the actions you should take but also holds you accountable to ensure that you achieve your goal.

Humanlytics does a great job here by holding performance meeting with their clients to ensure that the actions are taken to achieve set goals and use A.I to review performance on a weekly basis.

Still using our Footwear example, if the email sequence is not generating expected results, we can switch to retargeting ads or combine the two depending on the resources available.

And that concludes the entire data-informed framework you can use to grow your eCommerce business and as you’ve seen it a lot more than a quick fix but at the end of the day it puts you on a path of consistent data-driven revenue growth.

In the next article, we shall look at how to choose the right tools, software, and services that can automate all this for you.

“Look more closely at the data you already have to uncover ways of growing your revenue”

Sustainable growth can be drastically be enhanced through effective learning to leverage and utilize the data available to any eCommerce business.

Learning to harness the data at your disposal can be a bit intimidating.

However, effectively learning to do so provides your business with the necessary information for revenue growth as well as gaining a leg up on competitors who fail to utilize this digital gold.

At Humanlytics, we provide marketing analytics services for eCommerce businesses.

We currently support deep integrations with Google Analytics, Facebook Ads, and Google Ads, and e-commerce platforms like Shopify.

With DataSlinger engine, we are able to analyze your data and provide you with actionable insights for your business growth. If interested, don’t hesitate to reach us at bill@humanlytics.co.

If you have any challenges with analytics or just want to know how you can use marketing data for your business growth.
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