Leveraging commercial data to drive your ecommerce business has become the gold standard. Data needs to be at the heart of your ecommerce strategy. Without reliable data, how do you know how well your website – or indeed your whole business – is performing?
At Swanky, commercial data informs every decision we make for our clients’ stores. It allows us to understand the strengths and weaknesses of our clients’ websites, improve performance, and continually measure the outcome of all our work to ensure we produce the best possible results.
In this article, we’ll be looking at why data is important for your business, which metrics should be on your radar, and how our teams here at Swanky use data to drive their decision-making. Along the way, we’ll be sharing insights and advice from Tom Cox, Data and Analytics Manager at Swanky.
Why is data important?
“Data should be at the heart of every decision making process as it removes bias and emotion from key decisions,” describes Tom.
“This is particularly important when making changes to your website. A change may be suggested on an aesthetic or UX basis but if it isn’t tested then you cannot be sure what effect the change will have.
Large sites, such as Google, Amazon & Netflix conduct thousands of tests every year to constantly optimise their performance1. Because they know that small, marginal gains can accumulate into big wins. This is why targeted regular testing is imperative to the long term success of a store.”
The importance of data can be seen across all areas of your business, allowing you to:
- Make more informed decisions – Data ensures you only make changes to your business that will have a positive impact.
- Maximise your ROI – To get the most out of your marketing spend, you need reliable data on the return on investment (ROI) of every campaign.
- Identify and fix problems – Thorough data analysis of your business will allow you to pinpoint where issues may lie, in order to resolve them.
- Understand your audience – Website analytics can help you identify who your current audience actually is – their age range, gender and location. You may be surprised by the results.
- Engage with your customers – Learning from data on customer behaviour will help you spot new trends quickly, so you can respond to user preference and keep customers happy.
- Improve User Experience (UX) – Data-driven ecommerce constantly optimises the customer’s onsite experience. Once you understand why customers are leaving your store without placing an order, you can make changes to reduce or remove these obstacles and see your abandoned cart rate drop.
- Improve processes – By testing every new strategy and analysing performance data, you can constantly optimise your business processes and avoid wasting valuable time or resources on ineffective strategies.
- Manage stakeholders – Commercial data gives you evidence to demonstrate the success of your marketing strategies to stakeholders and secure funding for future campaigns.
- Forecast future sales – Another reason why data is important is for forecasting future sales throughout the year, particularly for key retail periods such as BFCM, to make sure you have the stock you need.
Which metrics to pay attention to
Data-driven ecommerce should look to unpack several key metrics, as Tom lays out below:
“Lots of merchants look at their revenue, conversion rate, or website traffic, but often this is where it stops. While these are a great place to start, merchants need to dig a bit deeper to really use data to its full potential.”
Conversion rate is like the pulse of the site. Various factors influence conversion rate, but if users land on the site and make a purchase then it is safe to assume that you have an effective flow.
However, to understand what is influencing your conversion rate, we have to delve deeper into other metrics.
Firstly, where is your traffic coming from? Break down your acquisition source – organic search, paid social, email, PPC, affiliate links etc. – and look at where they land on your site.
Next, you can start to consider page performance. Is the bounce rate (the percentage of visitors who leave your site after viewing only one page and completing no actions) high? Where are users exiting? How many pages are they viewing and what’s the length of the session?
These are key questions we can ask to try to understand what is bringing our conversion rate down, in order to improve the flow.
Measuring your sales revenue is a great starting point for tracking your performance, but it needs to be taken within the context of other contributing factors. Where possible, it’s preferable to look instead at gross profit – as this paints a more accurate picture of the health of your bottom line.
Focusing solely on your top line can lead to some incorrect interpretation of results. For instance, over a sale period where there is heavy discounting, the conversion rate and overall site revenue often see an uplift. However the overall profit will not see the same improvements. This example is where gross profit can be a more valuable metric to analyse.
Shopify has functionality for merchants to input a “Cost per item” when they’re setting up their inventory. This simple step allows merchants to produce basic profitability reports straight from their Shopify dashboards.
If merchants want to go one step further and apply a decent estimated indirect cost (FTE, marketing etc.), they can understand the overall net margin of their business.
Customer Lifetime Value (CLTV)
Perhaps the most important metrics to fully understand are the CLTV and the cost of acquisition for a customer. This is particularly important as more stores are moving towards a subscription-based model. Using the correct attribution model can be key when answering these questions.
By relying on a last-click attribution model, in which the credit for a conversion is given to the last channel the customer interacted with before converting, you could risk missing the bigger picture. This is because last-click attribution measures only which channel has secured each individual transaction.
So instead, you should consider a first-order attribution model, as it shows which sources are responsible for the highest CLTV. This model puts the focus on which channel brought the customer to your store for their first purchase. After all, the cost of acquiring a new customer is far higher than securing purchases from returning customers. For example, paid advertising has a high acquisition cost. But if it’s the channel that brings in the most new customers, analysis of its ROI should also factor in future purchases made by these customers.
For merchants with a subscription model, churn is another key metric essential for measuring performance. Churn describes the proportion of customers that are cancelling their subscriptions and it goes hand in hand with CLTV. If you can reduce churn, you are getting more value out of your marketing spend by retaining customers for longer.
Swanky partners with ReCharge, whose integration allows merchants to offer a flexible and adaptive subscription prospect. For instance, ReCharge captures cancellation reasons and offers a relevant incentive for the customer to keep their subscription. This type of integration is invaluable in reducing churn.
Average Order Value (AOV)
Certain merchants choose to specifically target AOV to reduce the burden of fulfilment costs and improve the bottom line. For these merchants, this means optimising their site to bundle products (like our client The Recycled Candle Company), or cross-sell through complementary product recommendations.
Other merchants have more of a focus on upselling. For example, one Swanky client sells handmade, luxury items. As a result of their unique product range, their primary focus is to increase AOV instead of increasing sales, which they are doing so by selling higher value items. With this in mind, their target is to optimise the store to direct customers towards their premium range.
How does Swanky use data?
At Swanky, we value the importance of data in every area of our work. Client data informs all of our decision making, from UX choices during the design process, to developing conversion rate optimisation (CRO) campaigns that increase revenue and improve conversion rates. Our data analysts process and interpret data from our merchants’ stores, to enable our clients to see where their site can be improved.
Below, Tom breaks down some of the key aspects of Swanky’s data-driven ecommerce approach:
Data-led website design and migration
At the start of any new website project, Swanky implements a discovery process to gain insight into the client’s current store. We assess which areas of their site are performing well, the make up of their traffic (channel, demographics), and product performance (product views, quantity purchased).
Using tools such as Hotjar, we can gain insight into customer behaviour by studying heatmaps and survey responses.
In addition, we look at page metrics to understand whether the current sitemap is suitable or whether it needs to be changed.
This information then informs how we structure the new site to improve performance. Some clients are surprised by the performance of certain aspects of their site.
“During our analysis of one client’s site, we found that their blog entries generated lots of organic traffic and that users spent considerable time on each page. However, we simultaneously found that the majority of users were bouncing from the blog, rather than accessing the rest of the site, and therefore not converting. So from this knowledge, we were able to implement changes such as introducing product recommendations on the blog posts, to ensure more users converted into customers.”
A full audit of data analytics
For new clients joining our Growth Accelerator program, we begin by doing a full audit of their Shopify and analytical tech stack. We want to check that everything is configured properly and is producing the information we need – so we know we’re starting with reliable data.
We set up Shopify analytics so that it’s measuring how many users view a product, add it to basket and actually make it to checkout, so that we can pinpoint which parts of the website customers may be exiting from.
“A typical problem we encounter is when a large number of sessions drop out at the checkout stage,” explains Tom.
“We can therefore track specifically at which stage users are dropping out of the checkout funnel (contact, shipping, payment etc.). If there is a high dropout at shipping, we can then hypothesise. Could this be because customers are surprised by shipping costs, or unable to select the shipping option they want?”
Using data to drive improvements
Swanky’s team of digital strategists and digital marketers have dashboards that we use to closely monitor the performance of each client. They use this information to drive improvements that will have the biggest uplift on KPIs.
We also provide an additional service where we create vibrant, interactive dashboards for clients to better understand their data, which comes with analytical commentary from our team. By presenting data that is easily digestible, we aim to help our customers understand why data is important and the impact it can have on their bottom line.
We use data to understand how users navigate through a website, which pages perform well and which don’t. We want to know where users are coming from and where they are landing. It’s also important to measure how different products perform – which products users are viewing, which they are adding to their baskets and so on.
When it comes to CRO, we first look at the data and make observations about user behaviour. This information is used to produce a proposal of which tests to implement on the site. The test proposal is prioritised by how complex each change is compared to how big an impact it may have on revenue.
We also analyse all marketing campaigns using data from Klaviyo, Facebook and Google Ads to compare open rate, impressions, conversion rate and so on. This helps the teams really focus on what is effective, and try and understand why, or learn what we could do better for future campaigns.
Swanky can help merchants to analyse how profitable their business is by pulling profitability reports from the data on their Shopify store. By inputting the costs of their tech stack, product costs and assumed salary costs, we help merchants to build a picture of their gross profit line, so that merchants can make more informed decisions. Without a solid understanding of your commercial data, you have no way of knowing your real return on investment, and whether you are making enough profit.
Do you need help understanding your commercial data?
At Swanky, our team of ecommerce experts can help leverage your commercial data to grow your business to its full potential. With our data-led approach, you’ll see measurable improvements that have a direct impact on your bottom line.
To find out more about our data-driven ecommerce solutions, get in touch with our team today – we’d love to hear from you!